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Kilkenny M, Churilov L, Cadilhac DA. Risk‐adjusted hospital mortality rates for stroke: evidence from the Australian Stroke Clinical Registry (AuSCR). Med J Aust 2017; 207:315-316. [DOI: 10.5694/mja17.00493] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Accepted: 06/13/2017] [Indexed: 11/17/2022]
Affiliation(s)
- Monique Kilkenny
- Monash University, Melbourne, VIC
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | - Leonid Churilov
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | - Dominique A Cadilhac
- Monash University, Melbourne, VIC
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
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52
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Reeves MJ, Fonarow GC, Xu H, Matsouaka RA, Xian Y, Saver J, Schwamm L, Smith EE. Is Risk-Standardized In-Hospital Stroke Mortality an Adequate Proxy for Risk-Standardized 30-Day Stroke Mortality Data? Circ Cardiovasc Qual Outcomes 2017; 10:CIRCOUTCOMES.117.003748. [DOI: 10.1161/circoutcomes.117.003748] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 09/07/2017] [Indexed: 11/16/2022]
Affiliation(s)
- Mathew J. Reeves
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Gregg C. Fonarow
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Haolin Xu
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Roland A. Matsouaka
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Ying Xian
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Jeffrey Saver
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Lee Schwamm
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
| | - Eric E. Smith
- From the Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.); Division of Cardiology (G.C.F.), and Department of Neurology (J.S.), Geffen School of Medicine, University of California, Los Angeles; Duke Clinical Research Institute, Durham, NC (H.X., R.A.M., Y.X.); Department of Biostatistics and Bioinformatics, Duke University, Durham, NC (R.A.M.); Department of Neurology, Duke University Medical Center, Durham, NC (Y.X.); Massachusetts General Hospital,
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Wang J, Xie Y, Zhao S, Zhang J, Chai Y, Li Y, Liao X. Dengzhanxixin injection for cerebral infarction: A systematic review and meta-analysis of randomized controlled trials. Medicine (Baltimore) 2017; 96:e7674. [PMID: 28796050 PMCID: PMC5556216 DOI: 10.1097/md.0000000000007674] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND No systematic review has been published in English of Dengzhanxixin (DZXX) injection for cerebral infarction. The aim of this systematic review was to assess the effects and safety of DZXX injection for cerebral infarction. METHODS Eight databases were searched from their inception. Randomized controlled trials (RCTs) related to DZXX for cerebral infarction in English or Chinese without restrictions on the publication status were included. Neurological deficit, quality of life, and response rates were analyzed. Adverse events were also investigated. RESULTS Twenty-three randomized controlled trials (RCTs) with 2291 participants were included. Meta-analysis showed that DZXX injection plus routine western therapy was better than routine western therapy alone for reducing neurologic deficit (MD -2.86, 95% CI -3.87 to -1.86), for improving quality of life (MD 9.48, 95% CI 8.34-10.63), and for improving response rates (RR 1.20, 95% CI 1.15-1.25). No serious adverse drug events (ADE) were reported. CONCLUSIONS DZXX injection may have a potential therapeutic effect for cerebral infarction in reducing neurologic deficit, improving life quality and response rates. However, we could not draw any definitive conclusions due to the insufficient evidences. More high-quality trials are needed to provide more strong evidence and to assess the safety of DZXX injection.
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Affiliation(s)
- Jia Wang
- Institute of Basic Research in Clinical Medicine
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences
| | - Yanming Xie
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences
| | | | - Jiangsong Zhang
- Zhejiang University of Traditional Chinese Medicine, Zhejiang, China
| | - Yan Chai
- Department of Epidemiology, University of California-Los Angeles, CA
| | - Yuanyuan Li
- Institute of Basic Research in Clinical Medicine
| | - Xing Liao
- Institute of Basic Research in Clinical Medicine
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54
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Katzan IL, Thompson NR, Lapin B, Uchino K. Added Value of Patient-Reported Outcome Measures in Stroke Clinical Practice. J Am Heart Assoc 2017; 6:JAHA.116.005356. [PMID: 28733434 PMCID: PMC5586276 DOI: 10.1161/jaha.116.005356] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background There is uncertainty regarding the clinical utility of the data obtained from patient‐reported outcome measures (PROMs) for patient care. We evaluated the incremental information obtained by PROMs compared to the clinician‐reported modified Rankin Scale (mRS). Methods and Results This was an observational study of 3283 ischemic stroke patients seen in a cerebrovascular clinic from September 14, 2012 to June 16, 2015 who completed the routinely collected PROMs: Stroke Impact Scale‐16 (SIS‐16), EQ‐5D, Patient Health Questionnaire‐9, PROMIS Physical Function, and PROMIS fatigue. The amount of variation in the PROMs explained by mRS was determined using r2 after adjustment for age and level of stroke impairment. The proportion with meaningful change was calculated for patients with ≥2 visits. Concordance with change in the other scales and the ability to discriminate changes in health state as measured by c‐statistic was evaluated for mRS versus SIS‐16. Correlation between PROMs and mRS was highest for SIS‐16 (r=−0.64, P<0.01). The r2 ranged from 0.11 (PROMIS fatigue) to 0.56 (SIS‐16). Change in scores occurred in 51% with mRS and 35% with SIS‐16. There was lower agreement and less ability to discriminate change in mRS than in SIS‐16 with change in the other measures. Conclusions PROMs provide additional valuable information compared to the mRS alone in stroke patients seen in the ambulatory setting. SIS‐16 may have a better ability to identify change than mRS in health status of relevance to the patient. PROMs may be a useful addition to mRS in the assessment of health status in clinical practice.
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Affiliation(s)
- Irene L Katzan
- Neurological Institute Center for Outcomes Research & Evaluation Cleveland Clinic, Cleveland, OH .,Cerebrovascular Center, Cleveland Clinic, Cleveland, OH
| | - Nicolas R Thompson
- Neurological Institute Center for Outcomes Research & Evaluation Cleveland Clinic, Cleveland, OH
| | - Brittany Lapin
- Neurological Institute Center for Outcomes Research & Evaluation Cleveland Clinic, Cleveland, OH
| | - Ken Uchino
- Cerebrovascular Center, Cleveland Clinic, Cleveland, OH
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55
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Hankey GJ. Assessing the outcome of stroke in Australia. Med J Aust 2017; 206:343-344. [PMID: 28446115 DOI: 10.5694/mja16.01383] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Accepted: 01/13/2017] [Indexed: 11/17/2022]
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56
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Cadilhac DA, Kilkenny MF, Levi CR, Lannin NA, Thrift AG, Kim J, Grabsch B, Churilov L, Dewey HM, Hill K, Faux SG, Grimley R, Castley H, Hand PJ, Wong A, Herkes GK, Gill M, Crompton D, Middleton S, Donnan GA, Anderson CS. Risk‐adjusted hospital mortality rates for stroke: evidence from the Australian Stroke Clinical Registry (AuSCR). Med J Aust 2017; 206:345-350. [DOI: 10.5694/mja16.00525] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
Affiliation(s)
- Dominique A Cadilhac
- Monash University, Melbourne, VIC
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | - Monique F Kilkenny
- Monash University, Melbourne, VIC
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | | | | | | | - Joosup Kim
- Monash University, Melbourne, VIC
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | - Brenda Grabsch
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | - Leonid Churilov
- Florey Institute of Neuroscience and Mental Health, Melbourne, VIC
| | - Helen M Dewey
- Eastern Health Clinical School, Monash University, Melbourne, VIC
| | | | - Steven G Faux
- St Vincent's Hospital, Sydney, NSW
- Sunshine Coast Clinical School, University of Queensland, Birtinya, QLD
| | - Rohan Grimley
- Sunshine Coast Clinical School, University of Queensland, Birtinya, QLD
| | | | | | - Andrew Wong
- Royal Brisbane and Women's Hospital, Brisbane, QLD
- University of Queensland, Brisbane, QLD
| | | | - Melissa Gill
- Armidale Rural Referral Hospital, Hunter New England Local Health District, Armidale, NSW
| | | | - Sandy Middleton
- St Vincent's Health Australia (Sydney), Sydney, NSW
- Australian Catholic University, Sydney, NSW
| | | | - Craig S Anderson
- The George Institute for Global Health, Sydney, NSW
- Royal Prince Alfred Hospital, Sydney, NSW
- The George Institute China at Peking University Health Science Center, Beijing, China
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57
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Maguire JM, Bevan S, Stanne TM, Lorenzen E, Fernandez-Cadenas I, Hankey GJ, Jimenez-Conde J, Jood K, Lee JM, Lemmens R, Levi C, Norrving B, Rannikmae K, Rost N, Rosand J, Rothwell PM, Scott R, Strbian D, Sturm J, Sudlow C, Traylor M, Thijs V, Tatlisumak T, Wieloch T, Woo D, Worrall BB, Jern C, Lindgren A. GISCOME - Genetics of Ischaemic Stroke Functional Outcome network: A protocol for an international multicentre genetic association study. Eur Stroke J 2017; 2:229-237. [PMID: 31008316 DOI: 10.1177/2396987317704547] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 03/17/2017] [Indexed: 01/12/2023] Open
Abstract
Introduction Genome-wide association studies have identified several novel genetic loci associated with stroke risk, but how genetic factors influence stroke outcome is less studied. The Genetics of Ischaemic Stroke Functional outcome network aims at performing genetic studies of stroke outcome. We here describe the study protocol and methods basis of Genetics of Ischaemic Stroke Functional outcome. Methods The Genetics of Ischaemic Stroke Functional outcome network has assembled patients from 12 ischaemic stroke projects with genome-wide genotypic and outcome data from the International Stroke Genetics Consortium and the National Institute of Neurological Diseases Stroke Genetics Network initiatives. We have assessed the availability of baseline variables, outcome metrics and time-points for collection of outcome data. Results We have collected 8831 ischaemic stroke cases with genotypic and outcome data. Modified Rankin score was the outcome metric most readily available. We detected heterogeneity between cohorts for age and initial stroke severity (according to the NIH Stroke Scale), and will take this into account in analyses. We intend to conduct a first phase genome-wide association outcome study on ischaemic stroke cases with data on initial stroke severity and modified Rankin score within 60-190 days. To date, we have assembled 5762 such cases and are currently seeking additional cases meeting these criteria for second phase analyses. Conclusion Genetics of Ischaemic Stroke Functional outcome is a unique collection of ischaemic stroke cases with detailed genetic and outcome data providing an opportunity for discovery of genetic loci influencing functional outcome. Genetics of Ischaemic Stroke Functional outcome will serve as an exploratory study where the results as well as the methodological observations will provide a basis for future studies on functional outcome. Genetics of Ischaemic Stroke Functional outcome can also be used for candidate gene replication or assessing stroke outcome non-genetic association hypotheses.
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Affiliation(s)
- Jane M Maguire
- Faculty of Health, University of Technology, Australia.,Hunter Medical Research Institute, University of Newcastle, Australia.,Priority Research Centre for Stroke and Traumatic Brain Injury, University of Newcastle, Australia
| | - Steve Bevan
- School of Life Sciences, University of Lincoln, UK
| | - Tara M Stanne
- Institute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, Sweden
| | - Erik Lorenzen
- Institute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, Sweden
| | - Israel Fernandez-Cadenas
- Stroke Pharmacogenomics and Genetics, Fundació Docència I Recerca Mutuaterrassa, Mutua de Terrassa Hospital, Spain.,Neurovascular Research Laboratory and Neurovascular Unit, Neurology and Medicine Departments - Universitat Autònoma de Barcelona, Vall d'Hebrón Hospital, Spain
| | - Graeme J Hankey
- School of Medicine and Pharmacology, The University of Western Australia, Australia
| | - Jordi Jimenez-Conde
- Department of Neurology, Institut Hospital del Mar d'Investigació Mèdica (IMIM), Spain.,Department of Neurology, Hospital del Mar; Neurovascular Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques); Universitat Autònoma de Barcelona/DCEXS
| | - Katarina Jood
- Institute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, Sweden
| | - Jin-Moo Lee
- Department of Neurology, Washington University School of Medicine, USA
| | - Robin Lemmens
- Department of Neurosciences, Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND), KU Leuven - University of Leuven, Belgium.,Laboratory of Neurobiology, VIB, Vesalius Research Center, Belgium.,Department of Neurology, University Hospitals Leuven, Belgium
| | - Christopher Levi
- Hunter Medical Research Institute, University of Newcastle, Australia.,Priority Research Centre for Stroke and Traumatic Brain Injury, University of Newcastle, Australia.,Faculty of Health and Medicine, University of Newcastle, Australia
| | - Bo Norrving
- Department of Clinical Sciences Lund, Neurology, Lund University, Sweden.,Department of Neurology and Rehabilitation Medicine, Skane University Hospital, Sweden
| | | | - Natalia Rost
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, USA
| | - Jonathan Rosand
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, USA.,Center for Human Genetic Research, Massachusetts General Hospital, USA
| | - Peter M Rothwell
- Stroke Prevention Research Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Rodney Scott
- Faculty of Health, University of Technology, Australia.,Hunter Medical Research Institute, University of Newcastle, Australia
| | - Daniel Strbian
- Department of Neurology, Helsinki University Hospital, Finland
| | - Jonathan Sturm
- Faculty of Health and Medicine, University of Newcastle, Australia
| | - Cathie Sudlow
- Centre for Clinical Brain Sciences, University of Edinburgh, UK
| | - Matthew Traylor
- Department of Clinical Neurosciences, University of Cambridge, UK
| | - Vincent Thijs
- Department of Neurology, Austin Health, Heidelberg, Australia.,Florey Institute for Neuroscience and Mental Health, University of Melbourne, Australia
| | - Turgut Tatlisumak
- Institute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, Sweden.,Department of Neurology, Helsinki University Hospital, Finland
| | - Tadeusz Wieloch
- Department of Clinical Sciences Lund, Neurology, Lund University, Sweden
| | - Daniel Woo
- Department of Neurology and Rehabilitation, University of Cincinnati, College of Medicine, USA
| | - Bradford B Worrall
- Department of Neurology, University of Virginia, USA.,Department of Health Evaluation Sciences, University of Virginia, USA
| | - Christina Jern
- Institute of Biomedicine, Sahlgrenska Academy at the University of Gothenburg, Sweden
| | - Arne Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, Sweden.,Department of Neurology and Rehabilitation Medicine, Skane University Hospital, Sweden
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Bettger JP, Thomas L, Liang L, Xian Y, Bushnell CD, Saver JL, Fonarow GC, Peterson ED. Hospital Variation in Functional Recovery After Stroke. Circ Cardiovasc Qual Outcomes 2017; 10:CIRCOUTCOMES.115.002391. [DOI: 10.1161/circoutcomes.115.002391] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Accepted: 11/30/2016] [Indexed: 11/16/2022]
Abstract
Background—
Functional status is a key patient-centric outcome, but there are little data on whether functional recovery post-stroke varies among hospitals. This study examined the distribution of functional status 3 months after stroke, determined whether these outcomes vary among hospitals, and identified hospital characteristics associated with better (or worse) functional outcomes.
Methods and Results—
Observational analysis of the AVAIL study (Adherence Evaluation After Ischemic Stroke-Longitudinal) included 2083 ischemic stroke patients enrolled from 82 US hospitals participating in Get With The Guidelines-Stroke and AVAIL. The primary outcome was dependence or death at 3 months (modified Rankin Scale [mRS] score of 3–6). Secondary outcomes included functional dependence (mRS score of 3–5), disabled (mRS score of 2–5), and mRS evaluated as a continuous score. By 3 months post-discharge, 36.5% of patients were functionally dependent or dead. Rates of dependence or death varied widely by discharging hospitals (range: 0%–67%). After risk adjustment, patients had lower rates of 3-month dependence or death when treated at teaching hospitals (odds ratio, 0.72; 95% confidence interval, 0.54–0.96) and certified primary stroke centers (odds ratio, 0.69; 95% confidence interval, 0.53–0.91). In contrast, a composite measure of hospital-level adherence to acute stroke care performance metrics, stroke volume, and bed size was not associated with downstream patient functional status. Findings were robust across mRS end points and sensitivity analyses.
Conclusions—
One third of acute ischemic stroke patients were functionally dependent or dead 3 months postacute stroke; functional recovery rates varied considerably among hospitals, supporting the need to better determine which care processes can maximize functional outcomes.
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Affiliation(s)
- Janet Prvu Bettger
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Laine Thomas
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Li Liang
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Ying Xian
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Cheryl D. Bushnell
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Jeffrey L. Saver
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Gregg C. Fonarow
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
| | - Eric D. Peterson
- From the Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.P.B., L.T., L.L., Y.X., E.D.P.); Wake Forest Baptist Medical Center, Winston-Salem, NC (C.D.B.); and University of California at Los Angeles (J.L.S., G.C.F.)
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Choi EY, Kim SH, Ock M, Lee HJ, Son WS, Jo MW, Lee SI. Evaluation of the Validity of Risk-Adjustment Model of Acute Stroke Mortality for Comparing Hospital Performance. HEALTH POLICY AND MANAGEMENT 2016. [DOI: 10.4332/kjhpa.2016.26.4.359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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60
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Adelman EE, Lisabeth LD, Smith MA, Baek J, Case EC, Sánchez BN, Burke JF, Skolarus LE, Zahuranec DB, Meurer WJ, Brown DL, Kerber KA, Levine DA, Garcia NM, Campbell MS, Morgenstern LB. Stroke Performance Measures Do Not Predict Functional Outcome. Neurohospitalist 2016. [PMID: 28634500 DOI: 10.1177/1941874416675797] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND AND PURPOSE Poststroke functional outcome is critical to stroke survivors. We sought to determine whether adherence to current stroke performance measures is associated with better functional outcome 90 days after an ischemic stroke. METHODS Utilizing the Brain Attack Surveillance in Corpus Christi cohort, we examined adherence to 7 ischemic stroke performance measures from February 2009 to June 2012. Adherence to the measures was analyzed in aggregate using a binary defect-free score and an opportunity score, representing the proportion of eligible measures met. The opportunity score ranges from 0 to 1, with values closer to 1 implying better adherence. Functional outcome, defined by an activities of daily living and instrumental activities of daily living (ADL/IADL) score (range 1-4, higher scores worse), was ascertained at 90 days poststroke. Tobit regression models were fitted to examine the associations between the performance measures and functional outcome, adjusting for demographic and clinical characteristics, including stroke severity. RESULTS There were 565 patients with ischemic stroke included in the analysis. The median ADL/IADL score was 2.32 (interquartile range [IQR]: 1.41-3.41). The median opportunity score was 1 (IQR: 0.8-1), and 58.4% of the patients received defect-free care. After adjustment, the opportunity score (P = .67) and defect-free care (P = .92) were not associated with functional outcome. CONCLUSION In this population, adherence to a composite of current stroke performance measures was not associated with poststroke functional outcome after adjustment for other factors. Performance measures that are associated with improved functional outcome should be developed and incorporated into stroke quality measures.
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Affiliation(s)
- Eric E Adelman
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Lynda D Lisabeth
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Melinda A Smith
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Jonggyu Baek
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Erin C Case
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Brisa N Sánchez
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - James F Burke
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Veterans Affairs Health Services Research and Development Center of Excellence, Ann Arbor, MI, USA
| | - Lesli E Skolarus
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Darin B Zahuranec
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - William J Meurer
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Devin L Brown
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Kevin A Kerber
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Deborah A Levine
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Veterans Affairs Health Services Research and Development Center of Excellence, Ann Arbor, MI, USA.,Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Nelda M Garcia
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | | | - Lewis B Morgenstern
- Stroke Program, Department of Neurology, University of Michigan, Ann Arbor, MI, USA.,Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.,Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, USA
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Hung LC, Sung SF, Hsieh CY, Hu YH, Lin HJ, Chen YW, Yang YHK, Lin SJ. Validation of a novel claims-based stroke severity index in patients with intracerebral hemorrhage. J Epidemiol 2016; 27:24-29. [PMID: 28135194 PMCID: PMC5328736 DOI: 10.1016/j.je.2016.08.003] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Stroke severity is an important outcome predictor for intracerebral hemorrhage (ICH) but is typically unavailable in administrative claims data. We validated a claims-based stroke severity index (SSI) in patients with ICH in Taiwan. METHODS Consecutive ICH patients from hospital-based stroke registries were linked with a nationwide claims database. Stroke severity, assessed using the National Institutes of Health Stroke Scale (NIHSS), and functional outcomes, assessed using the modified Rankin Scale (mRS), were obtained from the registries. The SSI was calculated based on billing codes in each patient's claims. We assessed two types of criterion-related validity (concurrent validity and predictive validity) by correlating the SSI with the NIHSS and the mRS. Logistic regression models with or without stroke severity as a continuous covariate were fitted to predict mortality at 3, 6, and 12 months. RESULTS The concurrent validity of the SSI was established by its significant correlation with the admission NIHSS (r = 0.731; 95% confidence interval [CI], 0.705-0.755), and the predictive validity was verified by its significant correlations with the 3-month (r = 0.696; 95% CI, 0.665-0.724), 6-month (r = 0.685; 95% CI, 0.653-0.715) and 1-year (r = 0.664; 95% CI, 0.622-0.702) mRS. Mortality models with NIHSS had the highest area under the receiver operating characteristic curve, followed by models with SSI and models without any marker of stroke severity. CONCLUSIONS The SSI appears to be a valid proxy for the NIHSS and an effective adjustment for stroke severity in studies of ICH outcome with administrative claims data.
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Affiliation(s)
- Ling-Chien Hung
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, Chiayi City, Taiwan
| | - Sheng-Feng Sung
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, Chiayi City, Taiwan
| | - Cheng-Yang Hsieh
- Department of Neurology, Tainan Sin Lau Hospital, Tainan, Taiwan.
| | - Ya-Han Hu
- Department of Information Management and Institute of Healthcare Information Management, National Chung Cheng University, Chiayi County, Taiwan
| | - Huey-Juan Lin
- Department of Neurology, Chi Mei Medical Center, Tainan, Taiwan
| | - Yu-Wei Chen
- Department of Neurology, Landseed Hospital, Tao-Yuan County, Taiwan; Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Yea-Huei Kao Yang
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Sue-Jane Lin
- Department of Pharmacy Systems, Outcomes & Policy, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA
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Li Z, Wang C, Zhao X, Liu L, Wang C, Li H, Shen H, Liang L, Bettger J, Yang Q, Wang D, Wang A, Pan Y, Jiang Y, Yang X, Zhang C, Fonarow GC, Schwamm LH, Hu B, Peterson ED, Xian Y, Wang Y, Wang Y. Substantial Progress Yet Significant Opportunity for Improvement in Stroke Care in China. Stroke 2016; 47:2843-2849. [PMID: 27758941 DOI: 10.1161/strokeaha.116.014143] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 09/12/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Stroke is a leading cause of death in China. Yet the adherence to guideline-recommended ischemic stroke performance metrics in the past decade has been previously shown to be suboptimal. Since then, several nationwide stroke quality management initiatives have been conducted in China. We sought to determine whether adherence had improved since then. METHODS Data were obtained from the 2 phases of China National Stroke Registries, which included 131 hospitals (12 173 patients with acute ischemic stroke) in China National Stroke Registries phase 1 from 2007 to 2008 versus 219 hospitals (19 604 patients) in China National Stroke Registries phase 2 from 2012 to 2013. Multiple regression models were developed to evaluate the difference in adherence to performance measure between the 2 study periods. RESULTS The overall quality of care has improved over time, as reflected by the higher composite score of 0.76 in 2012 to 2013 versus 0.63 in 2007 to 2008. Nine of 13 individual performance metrics improved. However, there were no significant improvements in the rates of intravenous thrombolytic therapy and anticoagulation for atrial fibrillation. After multivariate analysis, there remained a significant 1.17-fold (95% confidence interval, 1.14-1.21) increase in the odds of delivering evidence-based performance metrics in the more recent time periods versus older data. The performance metrics with the most significantly increased odds included stroke education, dysphagia screening, smoking cessation, and antithrombotics at discharge. CONCLUSIONS Adherence to stroke performance metrics has increased over time, but significant opportunities remain for further improvement. Continuous stroke quality improvement program should be developed as a national priority in China.
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Affiliation(s)
- Zixiao Li
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Chunjuan Wang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Xingquan Zhao
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Liping Liu
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Chunxue Wang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Hao Li
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Haipeng Shen
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Li Liang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Janet Bettger
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Qing Yang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - David Wang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Anxin Wang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Yuesong Pan
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Yong Jiang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Xiaomeng Yang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Changqing Zhang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Gregg C Fonarow
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Lee H Schwamm
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Bo Hu
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Eric D Peterson
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Ying Xian
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.)
| | - Yilong Wang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.).
| | - Yongjun Wang
- From the Division of Vascular Neurology, Department of Neurology (Z.L., X.Z., C.Z., Yongjun Wang), Tiantan Clinical Trial and Research Center for Stroke, Department of Neurology (Z.L., Chunjuan Wang, H.L., A.W., Y.P., Y.J., X.Y., Yilong Wang), Neurointensive Care Unit, Department of Neurology (L.L.), and Department of Neuropsychiatry and Behavioral Neurology and Clinical Psychology (Chunxue Wang), Beijing TianTan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, Beijing (Yilong Wang, Yongjun Wang); Center of Stroke, Beijing Institute for Brain Disorders, China (Z.L., X.Z.); Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, China (Chunjuan Wang); Department of Statistics and Operations Research, University of North Carolina at Chapel Hill (H.S.); Duke Clinical Research Institute (J.B., E.D.P., Y.X.) and Duke University School of Nursing (J.B., Q.Y.), Duke University, Durham, NC; INI Stroke Network, OSF Healthcare System, University of Illinois College of Medicine, Peoria (D.W.); Ahmanson-UCLA Cardiomyopathy Center, Ronald Reagan-UCLA Medical Center (G.C.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (L.H.S.); and Department of Quantitative Health Sciences, Cleveland Clinic, OH (B.H.).
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Sung SF, Hsieh CY, Lin HJ, Chen YW, Chen CH, Kao Yang YH, Hu YH. Validity of a stroke severity index for administrative claims data research: a retrospective cohort study. BMC Health Serv Res 2016; 16:509. [PMID: 27660046 PMCID: PMC5034530 DOI: 10.1186/s12913-016-1769-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2016] [Accepted: 09/16/2016] [Indexed: 11/10/2022] Open
Abstract
Background Ascertaining stroke severity in claims data-based studies is difficult because clinical information is unavailable. We assessed the predictive validity of a claims-based stroke severity index (SSI) and determined whether it improves case-mix adjustment. Methods We analyzed patients with acute ischemic stroke (AIS) from hospital-based stroke registries linked with a nationwide claims database. We estimated the SSI according to patient claims data. Actual stroke severity measured with the National Institutes of Health Stroke Scale (NIHSS) and functional outcomes measured with the modified Rankin Scale (mRS) were retrieved from stroke registries. Predictive validity was tested by correlating SSI with mRS. Logistic regression models were used to predict mortality. Results The SSI correlated with mRS at 3 months (Spearman rho = 0.578; 95 % confidence interval [CI], 0.556–0.600), 6 months (rho = 0.551; 95 % CI, 0.528–0.574), and 1 year (rho = 0.532; 95 % CI 0.504–0.560). Mortality models with the SSI demonstrated superior discrimination to those without. The AUCs of models including the SSI and models with the NIHSS did not differ significantly. Conclusions The SSI correlated with functional outcomes after AIS and improved the case-mix adjustment of mortality models. It can act as a valid proxy for stroke severity in claims data-based studies. Electronic supplementary material The online version of this article (doi:10.1186/s12913-016-1769-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sheng-Feng Sung
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, 539 Zhongxiao Road, East District, Chiayi City, 60002, Taiwan
| | - Cheng-Yang Hsieh
- Department of Neurology, Tainan Sin Lau Hospital, 57, Section 1, Dongmen Road, East District, Tainan, 70142, Taiwan
| | - Huey-Juan Lin
- Department of Neurology, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan, 710, Taiwan
| | - Yu-Wei Chen
- Department of Neurology, Landseed Hospital, 77 Guangtai Road, Pingjhen District, Taoyuan, Taiwan.,Department of Neurology, National Taiwan University Hospital, 7 Zhongshan South Road, Zhongzheng District, Taipei, 10002, Taiwan
| | - Chih-Hung Chen
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, 1 University Road, East District, Tainan, 701, Taiwan
| | - Yea-Huei Kao Yang
- School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, 1 University Road, East District, Tainan, 701, Taiwan
| | - Ya-Han Hu
- Department of Information Management and Institute of Healthcare Information Management, National Chung Cheng University, 168 University Road, Min-Hsiung, Chiayi County, 62102, Taiwan.
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64
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Bembenek JP, Niewada M, Karlinski M, Czlonkowska A. Effect of prestroke antiplatelets use on first-ever ischaemic stroke severity and early outcome. Int J Clin Pract 2016; 70:477-81. [PMID: 27040605 DOI: 10.1111/ijcp.12804] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES We aimed to investigate whether prior use of antiplatelet agents (AP) may be associated with lower severity and improved short-term outcome of the first-ever acute ischaemic stroke. METHODS This was a retrospective, case-control study based on a prospective hospital stroke registry covering consecutive acute stroke patients admitted to a single stroke centre in highly urbanised area (Warsaw, Poland) between 1995 and 2013. Patients receiving oral anticoagulants were excluded from the analysis. Statistical analysis included multiple regression and logistic regression adjusted for age, sex, hypertension, atrial fibrillation, congestive heart failure, diabetes, coronary heart disease and history of myocardial infarction. RESULTS During the study period, there were 3036 eligible patients, of whom 879 (29%) received AP before stroke onset. Patients from the AP group were older and more often burdened with stroke risk factors. There were no differences in baseline stroke severity, hospital mortality and proportion of patients alive and independent at discharge. However, AP turned out to be independently associated with lower NIHSS score on admission (β = -0.045, p = 0.008) and increased odds for being alive and independent at discharge (odds ratio 1.36, 95% CI: 1.13-1.67) and decreased odds for in-hospital mortality (odds ratio 0.77, 95% CI: 0.59-0.99). CONCLUSIONS Our findings provide further evidence supporting modest benefit of AP therapy on the course and outcome of first-ever ischaemic stroke. Further large studies are needed to confirm this effect.
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Affiliation(s)
- J P Bembenek
- 2nd Department of Neurology, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - M Niewada
- Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Warsaw, Poland
| | - M Karlinski
- 2nd Department of Neurology, Institute of Psychiatry and Neurology, Warsaw, Poland
| | - A Czlonkowska
- 2nd Department of Neurology, Institute of Psychiatry and Neurology, Warsaw, Poland
- Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Warsaw, Poland
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Chang TE, Lichtman JH, Goldstein LB, George MG. Accuracy of ICD-9-CM Codes by Hospital Characteristics and Stroke Severity: Paul Coverdell National Acute Stroke Program. J Am Heart Assoc 2016; 5:e003056. [PMID: 27247334 PMCID: PMC4937256 DOI: 10.1161/jaha.115.003056] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 04/18/2016] [Indexed: 12/01/2022]
Abstract
BACKGROUND Epidemiological and health services research often use International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify patients with clinical conditions in administrative databases. We determined whether there are systematic variations between stroke patient clinical diagnoses and ICD-9-CM codes, stratified by hospital characteristics and stroke severity. METHODS AND RESULTS We used the records of patients discharged from hospitals participating in the Paul Coverdell National Acute Stroke Program in 2013. Within this stroke-enriched cohort, we compared agreement between the attending physician's clinical diagnosis and principal ICD-9-CM code and determined whether disagreements varied by hospital characteristics (presence of a stroke unit, stroke team, number of hospital beds, and hospital location). For patients with a documented National Institutes of Health Stroke Scale score at admission, we assessed whether diagnostic agreement varied by stroke severity. Agreement was generally high (>89%); differences between the physician diagnosis and ICD-9-CM codes were primarily attributed to discordance between ischemic stroke and transient ischemic attack (TIA), and subarachnoid and intracerebral hemorrhage. Agreement was higher for patients in metropolitan hospitals with stroke units, stroke teams, and >200 beds (all P<0.001). Agreement was lowest (60.3%) for rural hospitals with ≤200 beds and without stroke units or teams. Agreement was also lower for milder (94.9%) versus more-severe (96.4%) ischemic strokes (P<0.001). CONCLUSIONS We identified disagreements in stroke/TIA coding by hospital characteristics and stroke severity, particularly for milder ischemic strokes. Such systematic variations in ICD-9-CM coding practices can affect stroke case identification in epidemiological studies and may have implications for hospital-level quality metrics.
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Affiliation(s)
- Tiffany E Chang
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT
| | - Judith H Lichtman
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT
| | - Larry B Goldstein
- Department of Neurology, Kentucky Neuroscience Institute, University of Kentucky, Lexington, KY
| | - Mary G George
- Division for Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, GA
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Thompson MP, Luo Z, Gardiner J, Burke JF, Nickles A, Reeves MJ. Quantifying Selection Bias in National Institute of Health Stroke Scale Data Documented in an Acute Stroke Registry. Circ Cardiovasc Qual Outcomes 2016; 9:286-93. [PMID: 27166201 DOI: 10.1161/circoutcomes.115.002352] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Accepted: 03/23/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND As a measure of stroke severity, the National Institutes of Health Stroke Scale (NIHSS) is an important predictor of patient- and hospital-level outcomes, yet is often undocumented. The purpose of this study is to quantify and correct for potential selection bias in observed NIHSS data. METHODS AND RESULTS Data were obtained from the Michigan Stroke Registry and included 10 262 patients with ischemic stroke aged ≥65 years discharged from 23 hospitals from 2009 to 2012, of which 74.6% of patients had documented NIHSS. We estimated models predicting NIHSS documentation and NIHSS score and used the Heckman selection model to estimate a correlation coefficient (ρ) between the 2 model error terms, which quantifies the degree of selection bias in the documentation of NIHSS. The Heckman model found modest, but significant, selection bias (ρ=0.19; 95% confidence interval: 0.09, 0.29; P<0.001), indicating that because NIHSS score increased (ie, strokes were more severe), the probability of documentation also increased. We also estimated a selection bias-corrected population mean NIHSS score of 4.8, which was substantially lower than the observed mean NIHSS score of 7.4. Evidence of selection bias was also identified using hospital-level analysis, where increased NIHSS documentation was correlated with lower mean NIHSS scores (r=-0.39; P<0.001). CONCLUSIONS We demonstrate modest, but important, selection bias in documented NIHSS data, which are missing more often in patients with less severe stroke. The population mean NIHSS score was overestimated by >2 points, which could significantly alter the risk profile of hospitals treating patients with ischemic stroke and subsequent hospital risk-adjusted outcomes.
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Affiliation(s)
- Michael P Thompson
- From the Department of Epidemiology and Biostatistics, Michigan State University, Lansing (M.P.T., Z.L., J.G., M.J.R.); Department of Neurology, University of Michigan, Ann Arbor (J.M.B.); and Chronic Disease Epidemiology Section, Michigan Department of Health and Human Services, Lansing (A.N.).
| | - Zhehui Luo
- From the Department of Epidemiology and Biostatistics, Michigan State University, Lansing (M.P.T., Z.L., J.G., M.J.R.); Department of Neurology, University of Michigan, Ann Arbor (J.M.B.); and Chronic Disease Epidemiology Section, Michigan Department of Health and Human Services, Lansing (A.N.)
| | - Joseph Gardiner
- From the Department of Epidemiology and Biostatistics, Michigan State University, Lansing (M.P.T., Z.L., J.G., M.J.R.); Department of Neurology, University of Michigan, Ann Arbor (J.M.B.); and Chronic Disease Epidemiology Section, Michigan Department of Health and Human Services, Lansing (A.N.)
| | - James F Burke
- From the Department of Epidemiology and Biostatistics, Michigan State University, Lansing (M.P.T., Z.L., J.G., M.J.R.); Department of Neurology, University of Michigan, Ann Arbor (J.M.B.); and Chronic Disease Epidemiology Section, Michigan Department of Health and Human Services, Lansing (A.N.)
| | - Adrienne Nickles
- From the Department of Epidemiology and Biostatistics, Michigan State University, Lansing (M.P.T., Z.L., J.G., M.J.R.); Department of Neurology, University of Michigan, Ann Arbor (J.M.B.); and Chronic Disease Epidemiology Section, Michigan Department of Health and Human Services, Lansing (A.N.)
| | - Mathew J Reeves
- From the Department of Epidemiology and Biostatistics, Michigan State University, Lansing (M.P.T., Z.L., J.G., M.J.R.); Department of Neurology, University of Michigan, Ann Arbor (J.M.B.); and Chronic Disease Epidemiology Section, Michigan Department of Health and Human Services, Lansing (A.N.)
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Katzan IL, Fan Y, Uchino K, Griffith SD. The PROMIS physical function scale: A promising scale for use in patients with ischemic stroke. Neurology 2016; 86:1801-7. [PMID: 27164715 DOI: 10.1212/wnl.0000000000002652] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Accepted: 01/29/2016] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate the performance of the Patient Reported Outcomes Measurement Information System (PROMIS) physical function (PF) scale compared to the validated Stroke Impact Scale-16 (SIS-16) in ischemic stroke patients seen in an ambulatory cerebrovascular clinic. METHODS This was a retrospective cohort study. PROMIS PF (computer adaptive testing version) and SIS-16 measures were electronically collected on 1,946 ischemic stroke patients seen in a cerebrovascular clinic using an electronic platform from September 12, 2012, to June 16, 2015. Distribution of scores was compared to assess ceiling and floor effects. Correlations with other commonly used functional status scales were performed to assess convergent validity. RESULTS The SIS-16 and PROMIS PF had a 19.6% and <1% ceiling effect, respectively. Patients completed 16 SIS-16 items and a median of 4 (interquartile range 4-4) PROMIS PF items. Internal consistency of both SIS-16 and PROMIS PF was excellent. The SIS-16 had slightly but significantly higher correlations with the other functional scales than PROMIS PF. CONCLUSIONS The use of PROMIS to obtain electronic patient-reported functional status in an ambulatory setting is feasible. PROMIS PF is an option for measurement of physical function in ischemic stroke patients. It had similar test characteristics as the SIS-16 but with lower patient burden and minimal ceiling effect.
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Affiliation(s)
| | - Youran Fan
- From the Neurological Institute, Cleveland Clinic, OH
| | - Ken Uchino
- From the Neurological Institute, Cleveland Clinic, OH
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Nickles AV, Roberts S, Shell E, Mitchell M, Hussain S, Lyon-Callo S, Reeves MJ. Characteristics and Outcomes of Stroke Patients Transferred to Hospitals Participating in the Michigan Coverdell Acute Stroke Registry. Circ Cardiovasc Qual Outcomes 2016; 9:265-74. [PMID: 27072678 DOI: 10.1161/circoutcomes.115.002388] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 02/18/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND Interhospital transfer of acute stroke patients is becoming increasingly important as regional stroke systems of care continue to evolve. We describe the characteristics and outcomes of stroke cases transferred to hospitals participating in the Michigan Coverdell Stroke Registry. METHODS AND RESULTS Thirty-six hospitals participated in the Michigan registry during 2009 to 2011. Transfer patients were transferred from another hospital either acutely or after admission. Multivariable logistic regression was used to determine predictors of transfer and the independent association between transfer and in-hospital mortality and complications. Of 16 202 acute stroke admissions, 19.1% were transferred. Independent predictors of being transferred included younger age, hemorrhagic stroke, and higher stroke severity, but having a past history of stroke decreased the likelihood of being transferred. Transferred cases had higher in-hospital mortality (12.0% versus 6.4%; P<0.001) compared with regular admissions and were more likely to suffer complications (18.4% versus 12.8%; P<0.001). These differences remained after adjustment for confounding variables (adjusted odds ratio for mortality =1.32, 95% confidence interval 1.12, 1.56; adjusted odds ratio for complications =1.39, 95% confidence interval 1.22, 1.58). Among ischemic stroke, elevated odds of poor outcomes among transferred patients remained after adjustment for stroke severity. CONCLUSIONS Transferred patients represent a complex admixture of patient characteristics that result in higher risks of poor outcomes. Our results suggest that it is prudent to account for patient transfer status when comparing hospital outcomes and that stroke registries need to expand their data collection capacity to provide a better understanding of the relative benefits and risks of transferring patients.
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Affiliation(s)
- Adrienne V Nickles
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.)
| | - Stacey Roberts
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.)
| | - Erin Shell
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.)
| | - Marylou Mitchell
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.)
| | - Syed Hussain
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.)
| | - Sarah Lyon-Callo
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.)
| | - Mathew J Reeves
- From the Michigan Department of Community Health, Lansing (A.V.N., S.R., S.L.-C.); Department of Neurology and Ophthalmology, Michigan State University, East Lansing (E.S., S.H.); Stroke Service, Sparrow Hospital, Lansing, MI (M.M., S.H.); and Department of Epidemiology and Biostatistics, Michigan State University, East Lansing (M.J.R.).
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The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register. PLoS One 2016; 11:e0153082. [PMID: 27054326 PMCID: PMC4824466 DOI: 10.1371/journal.pone.0153082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Accepted: 03/23/2016] [Indexed: 11/19/2022] Open
Abstract
Background When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke) to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance. Methods The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008–2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method. Results Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252) and high specificity (0.991). There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence. Conclusions The study emphasizes the importance of combining clinical relevance and level of statistical confidence when profiling hospital performance. To guide the decision process a web-based tool that gives ROC-curves for different scenarios is provided.
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Ghith N, Wagner P, Frølich A, Merlo J. Short Term Survival after Admission for Heart Failure in Sweden: Applying Multilevel Analyses of Discriminatory Accuracy to Evaluate Institutional Performance. PLoS One 2016; 11:e0148187. [PMID: 26840122 PMCID: PMC4739586 DOI: 10.1371/journal.pone.0148187] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Accepted: 01/14/2016] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Hospital performance is frequently evaluated by analyzing differences between hospital averages in some quality indicators. The results are often expressed as quality charts of hospital variance (e.g., league tables, funnel plots). However, those analyses seldom consider patients heterogeneity around averages, which is of fundamental relevance for a correct evaluation. Therefore, we apply an innovative methodology based on measures of components of variance and discriminatory accuracy to analyze 30-day mortality after hospital discharge with a diagnosis of Heart Failure (HF) in Sweden. METHODS We analyzed 36,943 patients aged 45-80 treated in 565 wards at 71 hospitals during 2007-2009. We applied single and multilevel logistic regression analyses to calculate the odds ratios and the area under the receiver-operating characteristic (AUC). We evaluated general hospital and ward effects by quantifying the intra-class correlation coefficient (ICC) and the increment in the AUC obtained by adding random effects in a multilevel regression analysis (MLRA). Finally, the Odds Ratios (ORs) for specific ward and hospital characteristics were interpreted jointly with the proportional change in variance (PCV) and the proportion of ORs in the opposite direction (POOR). FINDINGS Overall, the average 30-day mortality was 9%. Using only patient information on age and previous hospitalizations for different diseases we obtained an AUC = 0.727. This value was almost unchanged when adding sex, country of birth as well as hospitals and wards levels. Average mortality was higher in small wards and municipal hospitals but the POOR values were 15% and 16% respectively. CONCLUSIONS Swedish wards and hospitals in general performed homogeneously well, resulting in a low 30-day mortality rate after HF. In our study, knowledge on a patient's previous hospitalizations was the best predictor of 30-day mortality, and this information did not improve by knowing the sex and country of birth of the patient or where the patient was treated.
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Affiliation(s)
- Nermin Ghith
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Research Unit of Chronic Conditions, Bispebjerg University Hospital, Copenhagen, Denmark
| | - Philippe Wagner
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Centre for Clinical Research, Västmanland, Uppsala University, Västerås, Sweden
| | - Anne Frølich
- Research Unit of Chronic Conditions, Bispebjerg University Hospital, Copenhagen, Denmark
| | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
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Phan TG, Clissold B, Ly J, Ma H, Moran C, Srikanth V. Stroke Severity and Comorbidity Index for Prediction of Mortality after Ischemic Stroke from the Virtual International Stroke Trials Archive-Acute Collaboration. J Stroke Cerebrovasc Dis 2016; 25:835-42. [PMID: 26796056 DOI: 10.1016/j.jstrokecerebrovasdis.2015.12.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2015] [Revised: 10/23/2015] [Accepted: 12/09/2015] [Indexed: 10/22/2022] Open
Abstract
BACKGROUND There is increasing interest in the use of administrative data (incorporating comorbidity index) and stroke severity score to predict ischemic stroke mortality. The aim of this study was to determine the optimal timing for the collection of stroke severity data and the minimum clinical dataset to be included in models of stroke mortality. To address these issues, we chose the Virtual International Stroke Trials Archive (VISTA), which contains National Institutes of Health Stroke Scale (NIHSS) on admission and at 24 hours, as well as outcome at 90 days. METHODS VISTA was searched for patients who had baseline and 24-hour NIHSS. Improvement in regression models was performed by the net reclassification improvement (NRI) method. RESULTS The clinical data among 5206 patients were mean age, 69 ± 13; comorbidity index, 3.3 ± .9; median NIHSS at baseline, 12 (interquartile range [IQR] 8-17); NIHSS at 24 hours, 9 (IQR 8-15); and death at 90 days in 15%. The baseline model consists of age, gender, and comorbidity index. Adding the baseline NIHSS to model 1 improved the NRI by 0.671 (95% confidence interval [CI] 0.595-0.747) [or 67.1% correct reclassification between model 1 and model 2]. Adding the 24 hour NIHSS term to model 1 (model 3) improved the NRI by 0.929 (95% CI 0.857-1.000) for model 3 versus model 1. Adding the variable thrombolysis to model 3 (model 4) improve NRI by 0.1 (95% CI 0.023-0.178) [model 4 versus model 3]. CONCLUSION The optimal model for the prediction of mortality was achieved by adding the 24-hour NIHSS and thrombolysis to the baseline model.
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Affiliation(s)
- Thanh G Phan
- Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, Australia.
| | - Benjamin Clissold
- Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, Australia
| | - John Ly
- Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, Australia
| | - Henry Ma
- Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, Australia
| | - Chris Moran
- Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, Australia
| | - Velandai Srikanth
- Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, Australia
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72
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Reeves MJ, Smith EE, Fonarow GC, Zhao X, Thompson M, Peterson ED, Schwamm LH, Olson D. Variation and Trends in the Documentation of National Institutes of Health Stroke Scale in GWTG-Stroke Hospitals. Circ Cardiovasc Qual Outcomes 2015; 8:S90-8. [DOI: 10.1161/circoutcomes.115.001775] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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73
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Polymorphismus des „brain derived neurotrophic factor“ und Erholung nach Schlaganfall. DER NERVENARZT 2015; 86:1255-60. [DOI: 10.1007/s00115-015-4325-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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74
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Shah SV, Corado C, Bergman D, Curran Y, Bernstein RA, Naidech AM, Prabhakaran S. Impact of Poststroke Medical Complications on 30-Day Readmission Rate. J Stroke Cerebrovasc Dis 2015; 24:1969-77. [DOI: 10.1016/j.jstrokecerebrovasdis.2015.04.037] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2014] [Revised: 03/18/2015] [Accepted: 04/05/2015] [Indexed: 10/23/2022] Open
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75
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Lorente L, Martín MM, Abreu-González P, Ramos L, Argueso M, Solé-Violán J, Riaño-Ruiz M, Jiménez A. Serum malondialdehyde levels in patients with malignant middle cerebral artery infarction are associated with mortality. PLoS One 2015; 10:e0125893. [PMID: 25933254 PMCID: PMC4416778 DOI: 10.1371/journal.pone.0125893] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 03/24/2015] [Indexed: 01/20/2023] Open
Abstract
Objective Malondialdehyde (MDA) is an end-product formed during lipid peroxidation, due to degradation of cellular membrane phospholipids. MDA is released into extracellular space and finally into the blood; it has been used as an effective biomarker of lipid oxidation. High circulating levels of MDA have been previously described in patients with ischemic stoke than in controls, and an association between circulating MDA levels and neurological functional outcome in patients with ischemic stoke. However, an association between serum MDA levels and mortality in patients with ischemic stroke has not been previously reported, and that was the objective of this study. Methods Observational, prospective and multicenter study performed in six Intensive Care Units. We included patients with severe malignant middle cerebral artery infarction (MMCAI) defined as Glasgow Coma Scale (GCS) lower than 9. We measured serum MDA levels in 50 patients with severe MMCAI at the time of diagnosis and in 100 healthy subjects. Mortality at 30 days was the end point of the study. Results We found that patients with severe MMCAI showed higher serum MDA levels than healthy subjects (p<0.001). We found higher serum MDA levels (p<0.001) in non-surviving MMCAI patients (n=26) than in survivors (n=24). The area under the curve for prediction of 30-day mortality for serum MDA levels was 0.77 (95% CI = 0.63-0.88; p<0.001). Serum MDA levels >2.27 nmol/mL were associated with 30-day mortality (OR=7.23; 95% CI=1.84-28.73; p=0.005) controlling for GCS and age on multiple binomial logistic regression analysis. Conclusions To our knowledge, this is the first study showing that serum malondialdehyde levels in patients with MMCAI are associated with early mortality.
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Affiliation(s)
- Leonardo Lorente
- Intensive Care Unit, Hospital Universitario de Canarias, Santa Cruz de Tenerife, Spain
- * E-mail:
| | - María M. Martín
- Intensive Care Unit, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Pedro Abreu-González
- Deparment of Phisiology, Faculty of Medicine, University of the La Laguna, La Laguna. Santa Cruz de Tenerife, Spain
| | - Luis Ramos
- Intensive Care Unit, Hospital General La Palma, Breña Alta, La Palma, Spain
| | - Mónica Argueso
- Intensive Care Unit, Hospital Clínico Universitario de Valencia, Valencia, Spain
| | - Jordi Solé-Violán
- Intensive Care Unit, Hospital Universitario Dr. Negrín, CIBERES, Las Palmas de Gran Canaria, Spain
| | - Marta Riaño-Ruiz
- Servicio de Bioquímica Clínica, Complejo Hospitalario Universitario Insular Materno-Infantil, Las Palmas de Gran Canaria, Spain
| | - Alejandro Jiménez
- Research Unit, Hospital Universitario de Canarias, La Laguna, Santa Cruz de Tenerife, Spain
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Turner M, Barber M, Dodds H, Murphy D, Dennis M, Langhorne P, Macleod MJ. Implementing a Simple Care Bundle Is Associated With Improved Outcomes in a National Cohort of Patients With Ischemic Stroke. Stroke 2015; 46:1065-70. [DOI: 10.1161/strokeaha.114.007608] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Melanie Turner
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
| | - Mark Barber
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
| | - Hazel Dodds
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
| | - David Murphy
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
| | - Martin Dennis
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
| | - Peter Langhorne
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
| | - Mary-Joan Macleod
- From the Division of Applied Medicine, University of Aberdeen, Aberdeen, United Kingdom (M.T., M.-J.M.); Stroke Unit, Monklands Hospital, Lanarkshire, United Kingdom (M.B.); Information Services Division, National Services Scotland, Edinburgh, United Kingdom (H.D., D.M.); Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom (M.D.); and Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (P.L.)
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Asplund K, Sukhova M, Wester P, Stegmayr B. Diagnostic procedures, treatments, and outcomes in stroke patients admitted to different types of hospitals. Stroke 2015; 46:806-12. [PMID: 25657174 DOI: 10.1161/strokeaha.114.007212] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE In many countries, including Sweden, initiatives have been taken to reduce between-hospital differences in the quality of stroke services. We have explored to what extent hospital type (university, specialized nonuniversity, or community hospital) influences hospital performance. METHODS Riksstroke collects clinical data during hospital stay (national coverage 94%). Follow-up data at 3 months were collected using administrative registers and a questionnaire completed by surviving patients (response rate 88%). Structural data were collected from a questionnaire completed by hospital staff (response rate 100%). Multivariate analyses with adjustment for clustering were used to test differences between types of hospitals. RESULTS The proportion of patients admitted directly to a stroke unit was highest in community hospitals and lowest in university hospitals. Magnetic resonance, carotid imaging, and thrombectomy were more frequently performed in university hospitals, and the door-to-needle time for thrombolysis was shorter. Secondary prevention with antihypertensive drugs was used less often, and outpatient follow-up was less frequent in university hospitals. Fewer patients in community hospitals were dissatisfied with their rehabilitation. After adjusting for possible confounders, poor outcome (dead or activities of daily living dependency 3 months after stroke) was not significantly different between the 3 types of hospital. CONCLUSIONS In a setting with national stroke guidelines, stroke units in all hospitals, and measurement of hospital performance and benchmarking, outcome (after case-mix adjustment) is similar in university, specialized nonuniversity, and community hospitals. There seems to be fewer barriers to organizing well-functioning stroke services in community hospitals compared with university hospitals.
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Affiliation(s)
- Kjell Asplund
- From the Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University, Sweden.
| | - Maria Sukhova
- From the Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University, Sweden
| | - Per Wester
- From the Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University, Sweden
| | - Birgitta Stegmayr
- From the Riksstroke, Medicine, Department of Public Health and Clinical Medicine, Umeå University, Sweden
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Developing a stroke severity index based on administrative data was feasible using data mining techniques. J Clin Epidemiol 2015; 68:1292-300. [PMID: 25700940 DOI: 10.1016/j.jclinepi.2015.01.009] [Citation(s) in RCA: 83] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Revised: 12/16/2014] [Accepted: 01/16/2015] [Indexed: 01/04/2023]
Abstract
OBJECTIVES Case-mix adjustment is difficult for stroke outcome studies using administrative data. However, relevant prescription, laboratory, procedure, and service claims might be surrogates for stroke severity. This study proposes a method for developing a stroke severity index (SSI) by using administrative data. STUDY DESIGN AND SETTING We identified 3,577 patients with acute ischemic stroke from a hospital-based registry and analyzed claims data with plenty of features. Stroke severity was measured using the National Institutes of Health Stroke Scale (NIHSS). We used two data mining methods and conventional multiple linear regression (MLR) to develop prediction models, comparing the model performance according to the Pearson correlation coefficient between the SSI and the NIHSS. We validated these models in four independent cohorts by using hospital-based registry data linked to a nationwide administrative database. RESULTS We identified seven predictive features and developed three models. The k-nearest neighbor model (correlation coefficient, 0.743; 95% confidence interval: 0.737, 0.749) performed slightly better than the MLR model (0.742; 0.736, 0.747), followed by the regression tree model (0.737; 0.731, 0.742). In the validation cohorts, the correlation coefficients were between 0.677 and 0.725 for all three models. CONCLUSION The claims-based SSI enables adjusting for disease severity in stroke studies using administrative data.
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Lichtman JH, Leifheit-Limson EC, Goldstein LB. Centers for medicare and medicaid services medicare data and stroke research: goldmine or landmine? Stroke 2015; 46:598-604. [PMID: 25593137 DOI: 10.1161/strokeaha.114.003255] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Judith H Lichtman
- From the Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT (J.H.L., E.C.L.-L.); and Department of Neurology, Duke Stroke Center, Duke University and Durham VAMC, Durham, NC (L.B.G.).
| | - Erica C Leifheit-Limson
- From the Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT (J.H.L., E.C.L.-L.); and Department of Neurology, Duke Stroke Center, Duke University and Durham VAMC, Durham, NC (L.B.G.)
| | - Larry B Goldstein
- From the Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT (J.H.L., E.C.L.-L.); and Department of Neurology, Duke Stroke Center, Duke University and Durham VAMC, Durham, NC (L.B.G.)
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Xian Y, Holloway RG, Smith EE, Schwamm LH, Reeves MJ, Bhatt DL, Schulte PJ, Cox M, Olson DM, Hernandez AF, Lytle BL, Anstrom KJ, Fonarow GC, Peterson ED. Racial/Ethnic differences in process of care and outcomes among patients hospitalized with intracerebral hemorrhage. Stroke 2014; 45:3243-50. [PMID: 25213344 DOI: 10.1161/strokeaha.114.005620] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Although racial/ethnic differences in care are pervasive in many areas of medicine, little is known whether intracerebral hemorrhage (ICH) care processes or outcomes differ by race/ethnicity. METHODS We analyzed 123 623 patients with ICH (83 216 white, 22 147 black, 10 519 Hispanic, and 7741 Asian) hospitalized at 1199 Get With The Guidelines-Stroke hospitals between 2003 and 2012. Multivariable logistic regression with generalized estimating equation was used to evaluate the association among race, stroke performance measures, and in-hospital outcomes. RESULTS Relative to white patients, black, Hispanic, and Asian patients were significantly younger, but more frequently had more severe stroke (median National Institutes of Health Stroke Scale, 9, 10, 10, and 11, respectively; P<0.001). After adjustment for both patient and hospital-level characteristics, black patients were more likely to receive deep venous thrombosis prophylaxis, rehabilitation assessment, dysphagia screening, and stroke education, but less likely to have door to computed tomographic time ≤25 minutes and smoking cessation counseling than whites. Both Hispanic and Asian patients had higher odds of dysphagia screening but lower odds of smoking cessation counseling. In-hospital all-cause mortality was lower for blacks (23.0%), Hispanics (22.8%), and Asians (25.3%) than for white patients (27.6%). After risk adjustment, all minority groups had lower odds of death, of receiving comfort measures only or of being discharged to hospice. In contrast, they were more likely to exceed the median length of stay when compared with white patients. CONCLUSIONS Although individual quality indicators in ICH varied by race/ethnicity, black, Hispanic, and Asian patients with ICH had lower risk-adjusted in-hospital mortality than white patients with ICH.
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Affiliation(s)
- Ying Xian
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.).
| | - Robert G Holloway
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Eric E Smith
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Lee H Schwamm
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Mathew J Reeves
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Deepak L Bhatt
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Phillip J Schulte
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Margueritte Cox
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - DaiWai M Olson
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Adrian F Hernandez
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Barbara L Lytle
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Kevin J Anstrom
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Gregg C Fonarow
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
| | - Eric D Peterson
- From the Duke Clinical Research Institute, Durham, NC (Y.X., P.J.S., M.C., A.F.H., B.L.L., E.D.P.); Department of Neurology, University of Rochester Medical Center, NY (R.G.H.); Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada (E.E.S.); Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.); Department of Epidemiology, Michigan State University, East Lansing (M.J.R.); Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (D.L.B.); Neurology & Neurotherapeutics, Neurological Surgery, University of Texas Southwestern Medical Center, Dallas (D.M.O.); and Division of Cardiology, University of California, Los Angeles (G.C.F.)
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82
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Howard G, Voeks JH, Meschia JF, Howard VJ, Brott TG. Picking the good apples: statistics versus good judgment in choosing stent operators for a multicenter clinical trial. Stroke 2014; 45:3325-9. [PMID: 25213339 DOI: 10.1161/strokeaha.114.006807] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE The Carotid Revascularization Endarterectomy Versus Stenting Trial was completed with a low stroke and death rate. A lead-in series of patients receiving carotid artery stenting was used to select the physician-operators for the study, where performance was evaluated by complication rates and by peer review of cases. Herein, we assess the potential contribution of statistical evaluation of complication rates. METHODS The ability to discriminate between stent operators who can successfully meet the published guideline of <3% combined rate of stroke and death is calculated under the binomial distribution, based on a small consecutive case series (n=24 patients). RESULTS A criterion of ≤2 stroke or death events among the 24 patients (<8% event rate) was required of operators. Setting such a high criterion, however, ensures an inability to exclude operators who cannot meet the criteria. In fact, if a good operator is defined as having a 2% event rate and a poor operator as a 6% event rate, even a series of 240 patients would (on average) still exclude 5.4% of the good operators and include 4.6% of the poor operators. CONCLUSIONS The low periprocedural event rates in the trial suggest success in separating skillful operators from less skillful. However, it seems unlikely that statistical assessment of event rates in the lead-in contributed to successful selection, but rather successful selection was more likely because of peer review of subjective and other factors including patient volume and technical approaches. CLINICAL TRIAL REGISTRATION URL http://www.clinicaltrials.gov. Unique identifier: NCT00004732.
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Affiliation(s)
- George Howard
- From the Departments of Biostatistics (G.H.) and Epidemiology (V.J.H.), University of Alabama at Birmingham, School of Public Health; Department of Neurology, Medical University of South Carolina, Charleston (J.H.V.); and Department of Neurology, Mayo Clinic Jacksonville, FL (J.F.M., T.G.B.)
| | - Jenifer H Voeks
- From the Departments of Biostatistics (G.H.) and Epidemiology (V.J.H.), University of Alabama at Birmingham, School of Public Health; Department of Neurology, Medical University of South Carolina, Charleston (J.H.V.); and Department of Neurology, Mayo Clinic Jacksonville, FL (J.F.M., T.G.B.)
| | - James F Meschia
- From the Departments of Biostatistics (G.H.) and Epidemiology (V.J.H.), University of Alabama at Birmingham, School of Public Health; Department of Neurology, Medical University of South Carolina, Charleston (J.H.V.); and Department of Neurology, Mayo Clinic Jacksonville, FL (J.F.M., T.G.B.)
| | - Virginia J Howard
- From the Departments of Biostatistics (G.H.) and Epidemiology (V.J.H.), University of Alabama at Birmingham, School of Public Health; Department of Neurology, Medical University of South Carolina, Charleston (J.H.V.); and Department of Neurology, Mayo Clinic Jacksonville, FL (J.F.M., T.G.B.)
| | - Thomas G Brott
- From the Departments of Biostatistics (G.H.) and Epidemiology (V.J.H.), University of Alabama at Birmingham, School of Public Health; Department of Neurology, Medical University of South Carolina, Charleston (J.H.V.); and Department of Neurology, Mayo Clinic Jacksonville, FL (J.F.M., T.G.B.).
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Strowd RE, Wise SM, Umesi UN, Bishop L, Craig J, Lefkowitz D, Reynolds PS, Tegeler C, Arnan M, Duncan PW, Bushnell CD. Predictors of 30-day hospital readmission following ischemic and hemorrhagic stroke. Am J Med Qual 2014; 30:441-6. [PMID: 24919597 DOI: 10.1177/1062860614535838] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Stroke patients have a high rate of 30-day readmission. Understanding the characteristics of patients at high risk of readmission is critical. A retrospective case-control study was designed to determine factors associated with 30-day readmission after stroke. A total of 79 cases with acute ischemic or hemorrhagic strokes readmitted to the same hospital within 30 days were compared with 86 frequency-matched controls. Readmitted patients were more likely to have had ≥2 hospitalizations in the year prior to stroke (21.5% vs 2.3% in controls, P < .001), and in the multivariate model, admission National Institutes of Health Stroke Score (NIHSS; odds ratio [OR] = 1.072; 95% confidence interval [CI] = 1.021-1.126 per 1 point increase; P = .005), prior hospitalizations (OR = 2.205; 95% CI = 1.426-3.412 per admission; P < .001), and absence of hyperlipidemia (OR = 0.444; 95% CI = 0.221-0.894; P = .023) were independently associated with readmission. The research team concludes that admission NIHSS and frequent prior hospitalizations are associated with 30-day readmission after stroke. If validated, these characteristics identify high-risk patients and focus efforts to reduce readmission.
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Affiliation(s)
- Roy E Strowd
- Wake Forest School of Medicine, Winston Salem, NC
| | | | | | - Laura Bishop
- Wake Forest School of Medicine, Winston Salem, NC
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84
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Broderick JP, Jauch EC, Derdeyn CP. Organizational update: American Heart Association Stroke Council. Stroke 2014; 45:e104-5. [PMID: 24876266 DOI: 10.1161/strokeaha.114.004936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Joseph P Broderick
- From the Department of Neurology and Rehabilitation Medicine, University of Cincinnati Neuroscience Institute, OH (J.P.B.); Department of Emergency Medicine, Medical University of South Carolina, Charleston (E.C.J.); Mallinckrodt Institute of Radiology, St. Louis, MO (C.P.D.); and the Departments of Neurology and Neurological Surgery, Washington University School of Medicine, St. Louis, MO (C.P.D.).
| | - Edward C Jauch
- From the Department of Neurology and Rehabilitation Medicine, University of Cincinnati Neuroscience Institute, OH (J.P.B.); Department of Emergency Medicine, Medical University of South Carolina, Charleston (E.C.J.); Mallinckrodt Institute of Radiology, St. Louis, MO (C.P.D.); and the Departments of Neurology and Neurological Surgery, Washington University School of Medicine, St. Louis, MO (C.P.D.)
| | - Colin P Derdeyn
- From the Department of Neurology and Rehabilitation Medicine, University of Cincinnati Neuroscience Institute, OH (J.P.B.); Department of Emergency Medicine, Medical University of South Carolina, Charleston (E.C.J.); Mallinckrodt Institute of Radiology, St. Louis, MO (C.P.D.); and the Departments of Neurology and Neurological Surgery, Washington University School of Medicine, St. Louis, MO (C.P.D.)
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85
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Fonarow GC, Alberts MJ, Broderick JP, Jauch EC, Kleindorfer DO, Saver JL, Solis P, Suter R, Schwamm LH. Stroke outcomes measures must be appropriately risk adjusted to ensure quality care of patients: a presidential advisory from the American Heart Association/American Stroke Association. Stroke 2014; 45:1589-601. [PMID: 24523036 DOI: 10.1161/str.0000000000000014] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Because stroke is among the leading causes of death, disability, hospitalizations, and healthcare expenditures in the United States, there is interest in reporting outcomes for patients hospitalized with acute ischemic stroke. The American Heart Association/American Stroke Association, as part of its commitment to promote high-quality, evidence-based care for cardiovascular and stroke patients, fully supports the development of properly risk-adjusted outcome measures for stroke. To accurately assess and report hospital-level outcomes, adequate risk adjustment for case mix is essential. During the development of the Centers for Medicare & Medicaid Services 30-day stroke mortality and 30-day stroke readmission measures, concerns were expressed that these measures were not adequately designed because they do not include a valid initial stroke severity measure, such as the National Institutes of Health Stroke Scale. These outcome measures, as currently constructed, may be prone to mischaracterizing the quality of stroke care being delivered by hospitals and may ultimately harm acute ischemic stroke patients. This article details (1) why the Centers for Medicare & Medicaid Services acute ischemic stroke outcome measures in their present form may not provide adequate risk adjustment, (2) why the measures as currently designed may lead to inaccurate representation of hospital performance and have the potential for serious unintended consequences, (3) what activities the American Heart Association/American Stroke Association has engaged in to highlight these concerns to the Centers for Medicare & Medicaid Services and other interested parties, and (4) alternative approaches and opportunities that should be considered for more accurately risk-adjusting 30-day outcomes measures in patients with ischemic stroke.
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