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Joundi RA, Hill MD, Stang J, Nicol D, Yu AYX, Kapral MK, King JA, Halabi ML, Smith EE. Association Between Time to Treatment With Endovascular Thrombectomy and Home-Time After Acute Ischemic Stroke. Neurology 2024; 102:e209454. [PMID: 38848515 DOI: 10.1212/wnl.0000000000209454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Home-time is a patient-prioritized stroke outcome that can be derived from administrative data linkages. The effect of faster time-to-treatment with endovascular thrombectomy (EVT) on home-time after acute stroke is unknown. METHODS We used the Quality Improvement and Clinical Research registry to identify a cohort of patients who received EVT for acute ischemic stroke between 2015 and 2022 in Alberta, Canada. We calculated days at home in the first 90 days after stroke. We used ordinal regression across 6 ordered categories of home-time to evaluate the association between onset-to-arterial puncture and higher home-time, adjusting for age, sex, rural residence, NIH Stroke Scale, comorbidities, intravenous thrombolysis, and year of treatment. We used restricted cubic splines to assess the nonlinear relationship between continuous variation in time metrics and higher home-time, and also reported the adjusted odds ratios within time categories. We additionally evaluated door-to-puncture and reperfusion times. Finally, we analyzed home-time with zero-inflated models to determine the minutes of earlier treatment required to gain 1 day of home-time. RESULTS We had 1,885 individuals in our final analytic sample. There was a nonlinear increase in home-time with faster treatment when EVT was within 4 hours of stroke onset or 2 hours of hospital arrival. There was a higher odds of achieving more days at home when onset-to-puncture time was <2 hours (adjusted odds ratio 2.36, 95% CI 1.77-3.16) and 2 to <4 hours (1.37, 95% CI 1.11-1.71) compared with ≥6 hours, and when door-to-puncture time was <1 hour (aOR 2.25, 95% CI 1.74-2.90), 1 to <1.5 hours (aOR 1.89, 95% CI 1.47-2.41), and 1.5 to <2 hours (1.35, 95% CI 1.04-1.76) compared with ≥2 hours. Results were consistent for reperfusion times. For every hour of faster treatment within 6 hours of stroke onset, there was an estimated increase in home-time of 4.7 days, meaning that approximately 1 day of home-time was gained for each 12.8 minutes of faster treatment. DISCUSSION Faster time-to-treatment with EVT for acute stroke was associated with greater home-time, particularly within 4 hours of onset-to-puncture and 2 hours of door-to-puncture time. Within 6 hours of stroke onset, each 13 minutes of faster treatment is associated with a gain of 1 day of home-time.
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Affiliation(s)
- Raed A Joundi
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Michael D Hill
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Jillian Stang
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Dana Nicol
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Amy Ying Xin Yu
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Moira K Kapral
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - James A King
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Mary-Lou Halabi
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
| | - Eric E Smith
- From the Division of Neurology (R.A.J.), Hamilton Health Sciences, McMaster University & Population Health Research Institute, Ontario; Departments of Clinical Neurosciences (M.D.H., E.E.S.) and Community Health Sciences (E.E.S.), Cumming School of Medicine, University of Calgary; Data and Analytics (DnA) (J.S., D.N.) and Cardiovascular Health and Stroke Strategic Clinical Network (M.-L.H.), Alberta Health Services; ICES (A.Y.X.Y., M.K.K.), Toronto; Department of Medicine (Neurology) (A.Y.X.Y.), University of Toronto; Sunnybrook Health Sciences Centre (A.Y.X.Y.), Ontario; Department of Medicine (A.Y.X.Y.), Division of Neurology, University of Toronto; Department of Medicine (General Internal Medicine) (M.K.K.), University of Toronto-University Health Network, Ontario; Alberta Strategy for Patient Oriented Research Support Unit Data Platform (J.A.K.); and Provincial Research Data Services (J.A.K.), Alberta Health Services, Canada
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Sico JJ, Hu X, Myers LJ, Levine D, Bravata DM, Arling GW. Real-world analysis of two ischaemic stroke and TIA systolic blood pressure goals on 12-month mortality and recurrent vascular events. Stroke Vasc Neurol 2024:svn-2023-002759. [PMID: 38191185 DOI: 10.1136/svn-2023-002759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 12/12/2023] [Indexed: 01/10/2024] Open
Abstract
INTRODUCTION Whether obtaining the more intensive goal systolic blood pressure (SBP) of <130 mm Hg, rather than a less intensive SBP goal of <140 mm Hg poststroke/transient ischaemic attack (TIA) is associated with incremental mortality and recurrent vascular event benefit is largely unexplored using real-world data. Lowering SBP excessively may result in poorer outcomes. METHODS This is a retrospective cohort study of 26 368 Veterans presenting to a Veterans Administration Medical Center (VAMC) with a stroke/TIA between October 2015 and July 2018. Patients were excluded from the study if they had missing or extreme BP values, receiving dialysis or palliative care, left against medical advice had a cancer diagnosis, were cared for in a VAMC enrolled in a stroke/TIA quality improvement initiative, died or had a cerebrovascular or cardiovascular event within 90 days after their index stroke/TIA. The analytical sample included 12 337 patients. Average SBP during 90 days after discharge was assessed in categories (≤105 mm Hg, 106-115 mm Hg, 116-130 mm Hg, 131-140 mm Hg and >140 mm Hg). Separate multivariable Cox proportional hazard regressions were used to examine the relationship between average SBP groups and time to: (1) mortality and (2) any recurrent vascular event, from 90 days to up to 365 days after discharge from the index emergency department visit or inpatient admission. RESULTS Compared with those with SBP>140 mm Hg, patients with SBP between 116 and 130 mm Hg had a significantly lower risk of recurrent stroke/TIA (HR 0.77, 95% CI 0.60 to 0.99) but not cardiovascular events. Patients with SBP lower than 105 mm Hg, compared with those with >140 mm Hg demonstrated a statistically significant higher risk of death (HR 2.07, 95% CI 1.43 to 3.00), but no statistical differences were found in other SBP groups. DISCUSSION Data support a more intensive SBP goal to prevent recurrent cerebrovascular events among stroke/TIA patients by 90 days poststroke/TIA compared with less intensive goal. Very low SBPs were associated with increased mortality risk.
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Affiliation(s)
- Jason J Sico
- Internal Medicine and Neurology, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Neurology, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Xin Hu
- Yale School of Public Health, New Haven, Connecticut, USA
| | - Laura J Myers
- VA Health Services Research and Development (HSR&D) Center for Healthcare Informatics and Communication and the HSR&D Stroke Quality Enhancement Research Initiative (QUERI), Indianapolis, Indiana, USA
- Richard L. Roudebush VA Medical Center, Indianapolis, Indiana, USA
| | - Deborah Levine
- Departments of Medicine and Neurology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Dawn M Bravata
- Health Services Research and Development (HSR&D) Center for Healthcare Informatics and Communication and the HSR&D Stroke Quality Enhancement Research Initiative (QUERI); Richard L. Roudebush VA Medical Center, Indianapolis, Indiana, USA
| | - Greg W Arling
- Department of Veterans Affairs (VA), Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, Indiana, USA
- Department of Nursing, Purdue University, West Lafayette, Indiana, USA
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Duan C, Wang S, Xiong Y, Gu HQ, Yang K, Zhao XQ, Meng X, Wang Y. Short- and long-term outcomes of patients with minor stroke and nonvalvular atrial fibrillation. BMC Neurol 2023; 23:410. [PMID: 37986056 PMCID: PMC10658860 DOI: 10.1186/s12883-023-03457-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/07/2023] [Indexed: 11/22/2023] Open
Abstract
BACKGROUND AND PURPOSE Nonvalvular atrial fibrillation (NVAF) is a risk factor for stroke. This study was undertaken to determine the influence of NVAF on the mortality and recurrent stroke after a minor stroke event. METHODS Data were derived from the Third China National Stroke Registry (CNSR-III) which enrolled 15,166 subjects during August 2015 through March 2018 in China. Patients with minor stroke (NIHSS ≤ 5) within 24 h after onset were included. Clinical outcomes including all-cause mortality, cardiovascular death, recurrent ischemic stroke, and recurrent hemorrhagic stroke were collected. The Cox proportional hazards models were used to determine the association between NVAF and clinical outcomes. RESULTS A total of 4,753 patients were included in our study. Of them, 222 patients had NVAF (4.7%) (mean age, 71.1 years) and 4,531 patients were without AF (95.3%) (mean age, 61.4 years). NVAF was associated with 12-month cardiovascular mortality in both univariate (hazards ratio [HR], 4.13; 95% confidence interval [CI], 1.84 to 9.31; P < 0.001) and multivariate analyses (HR, 4.66; 95% CI, 1.79 to 12.15; P = 0.001). There was no difference in the in-hospital ischemic stroke recurrence rate between the two groups (HR, 0.45 [95% CI, 0.19 to 1.05] P = 0.07 at discharge). However, patients with NVAF had a lower rate of recurrent ischemic stroke at medium- (3 months and 6 months) and long-term (12 months) follow-up (HR, 0.33 [95% CI, 0.16 to 0.68] P = 0.003 at 3 months; 0.49 [95% CI, 0.27 to 0.89] P = 0.02 at 6 months; 0.55 [95% CI, 0.32 to 0.94] P = 0.03 at 12 months, respectively) compared with those without. There was no difference in all-cause mortality and hemorrhagic stroke between the two groups during follow-up. CONCLUSIONS Minor stroke patients with NVAF were at higher risk of cardiovascular death but had a lower rate of recurrent ischemic stroke compared to those without during the subsequent year after stroke event. A more accurate stroke risk prediction model for NVAF is warranted for optimal patient care strategies.
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Affiliation(s)
- Chunmiao Duan
- Vascular Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Department of Neurology, Beijing Daxing Teaching Hospital, Capital Medical University, Beijing, China
| | - Shang Wang
- Neurocardiology Center, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yunyun Xiong
- Vascular Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Hong Qiu Gu
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- National Center for Healthcare Quality Management in Neurological Diseases, Beijing, China
| | - Kaixuan Yang
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- National Center for Healthcare Quality Management in Neurological Diseases, Beijing, China
| | - Xing-Quan Zhao
- Vascular Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xia Meng
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yongjun Wang
- Vascular Neurology, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, China.
- National Center for Healthcare Quality Management in Neurological Diseases, Beijing, China.
- Center for Stroke, Beijing Institute for Brain Disorders, Beijing, China.
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Arling G, Miech EJ, Myers LJ, Sexson A, Bravata DM. The impact of the COVID-19 pandemic on blood pressure control after a stroke or transient ischemic attack among patients at VA medical centers. J Stroke Cerebrovasc Dis 2023; 32:107140. [PMID: 37084497 PMCID: PMC10103761 DOI: 10.1016/j.jstrokecerebrovasdis.2023.107140] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 04/23/2023] Open
Abstract
OBJECTIVE To study factors associated with systolic blood pressure(SBP) control for patients post-discharge from an ischemic stroke or transient ischemic attack(TIA) during the early months of the COVID-19 pandemic compared to pre-pandemic periods within the Veterans Health Administration(VHA). MATERIALS AND METHODS We analyzed retrospective data from patients discharged from Emergency Departments or inpatient admissions after an ischemic stroke or TIA. Cohorts consisted of 2,816 patients during March-September 2020 and 11,900 during the same months in 2017-2019. Outcomes included primary care or neurology clinic visits, recorded blood pressure readings and average blood pressure control in the 90-days post-discharge. Random effect logit models were used to compare clinical characteristics of the cohorts and relationships between patient characteristics and outcomes. RESULTS The majority (73%) of patients with recorded readings during the COVID-19 period had a mean post-discharge SBP within goal (<140 mmHg); this was slightly lower than the pre-COVID-19 period (78%; p=0.001). Only 38% of the COVID-19 cohort had a recorded SBP in the 90-days post-discharge compared with 83% of patients during the pre-pandemic period (p=0.001). During the pandemic period, 29% did not have follow-up primary care or neurologist visits, and 33% had a phone or video visit without a recorded SBP reading. CONCLUSIONS Patients with an acute cerebrovascular event during the initial COVID-19 period were less likely to have outpatient visits or blood pressure measurements than during the pre-pandemic period; patients with uncontrolled SBP should be targeted for follow-up hypertension management.
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Affiliation(s)
- Greg Arling
- Purdue University School of Nursing, West Lafayette, IN, USA.
| | - Edward J Miech
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Expanding Expertise Through E-health Network Development (EXTEND) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA; Regenstrief Institute, Indianapolis, IN, USA; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Expanding Expertise Through E-health Network Development (EXTEND) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA; VA HSR&D Center for Health Information and Communication (CHIC); Richard L. Roudebush VA Medical Center; Indianapolis, IN, USA; Regenstrief Institute, Indianapolis, IN, USA; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ali Sexson
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Expanding Expertise Through E-health Network Development (EXTEND) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA; VA HSR&D Center for Health Information and Communication (CHIC); Richard L. Roudebush VA Medical Center; Indianapolis, IN, USA
| | - Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Expanding Expertise Through E-health Network Development (EXTEND) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA; VA HSR&D Center for Health Information and Communication (CHIC); Richard L. Roudebush VA Medical Center; Indianapolis, IN, USA; Regenstrief Institute, Indianapolis, IN, USA; Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA; Medicine Service, Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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Bhatia K, Ladd LM, Carr KH, Di Napoli M, Saver JL, McCullough LD, Hosseini Farahabadi M, Alsbrook DL, Hinduja A, Ortiz Garcia JG, Sabbagh SY, Jafarli A, Divani AA. Contemporary Antiplatelet and Anticoagulant Therapies for Secondary Stroke Prevention: A Narrative Review of Current Literature and Guidelines. Curr Neurol Neurosci Rep 2023; 23:235-262. [PMID: 37037980 DOI: 10.1007/s11910-023-01266-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/10/2023] [Indexed: 04/12/2023]
Abstract
PURPOSE OF REVIEW Stroke is a leading cause of death and disability worldwide. The annual incidence of new or recurrent stroke is approximately 795,000 cases per year in the United States, of which 87% are ischemic in nature. In addition to the management of modifiable high-risk factors to reduce the risk of recurrent stroke, antithrombotic agents (antiplatelets and anticoagulants) play an important role in secondary stroke prevention. This review will discuss the published literature on the use of antiplatelets and anticoagulants in secondary prevention of acute ischemic stroke and transient ischemic attack (TIA), including their pharmacology, efficacy, and adverse effects. We will also highlight the role of dual antiplatelet therapy (DAPT) in secondary stroke prevention, along with supporting literature. RECENT FINDINGS Single antiplatelet therapy (SAPT) with aspirin or clopidogrel reduces the risk of recurrent ischemic stroke in patients with non-cardioembolic ischemic stroke or TIA. However, as shown in recent trials, short-term DAPT with aspirin and clopidogrel or ticagrelor for 21-30 days is more effective than SAPT in patients with minor acute non-cardioembolic stroke or high-risk TIA. Although short-term DAPT is highly effective in preventing recurrent stroke, a more prolonged course can increase bleeding risks without additional benefit. DAPT for 90 days, followed by aspirin monotherapy for patients with large vessel intracranial atherosclerotic disease, is suitable for secondary stroke prevention. However, patients need to be monitored for both minor (e.g., bruising) and major (e.g., intracranial) bleeding complications. Conversely, oral warfarin and newer direct oral anticoagulant (DOACs) such as dabigatran, rivaroxaban, apixaban, and edoxaban are the agents of choice for secondary stroke prevention in patients with non-valvular cardioembolic strokes. DOACs may be preferred over warfarin due to decreased bleeding risks, including ICH, lack of need for international normalized ratio monitoring, no dietary restrictions, and limited drug-drug interactions. The choice between different antiplatelets and anticoagulants for prevention of ischemic stroke depends on the underlying stroke mechanism, cytochrome P450 2C19 polymorphisms, bleeding risk profile, compliance, drug tolerance, and drug resistance. Physicians must carefully weigh each patient's relative benefits and bleeding risks before initiating an antiplatelet/anticoagulant treatment regimen. Further studies are warranted to study the optimal duration of DAPT in symptomatic intracranial atherosclerosis since the benefit is most pronounced in the short term while the bleeding risk remains high during the extended duration of therapy.
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Affiliation(s)
- Kunal Bhatia
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Lindsey M Ladd
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kelsey H Carr
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Mario Di Napoli
- Neurological Service, SS Annunziata Hospital, Sulmona, L'Aquila, Italy
| | - Jeffrey L Saver
- Department of Neurology, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA
| | - Louise D McCullough
- Department of Neurology, McGovern Medical School, University of Texas Health Sciences Center, Houston, TX, USA
| | | | - Diana L Alsbrook
- Department of Neurology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Archana Hinduja
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Jorge G Ortiz Garcia
- Department of Neurology, the University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Sara Y Sabbagh
- Department of Neurology, University of New Mexico, Albuquerque, NM, USA
| | - Alibay Jafarli
- Department of Neurology, Tufts Medical Center, Boston, MA, USA
| | - Afshin A Divani
- Department of Neurology, University of New Mexico, Albuquerque, NM, USA.
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Amin HP, Madsen TE, Bravata DM, Wira CR, Johnston SC, Ashcraft S, Burrus TM, Panagos PD, Wintermark M, Esenwa C. Diagnosis, Workup, Risk Reduction of Transient Ischemic Attack in the Emergency Department Setting: A Scientific Statement From the American Heart Association. Stroke 2023; 54:e109-e121. [PMID: 36655570 DOI: 10.1161/str.0000000000000418] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
At least 240 000 individuals experience a transient ischemic attack each year in the United States. Transient ischemic attack is a strong predictor of subsequent stroke. The 90-day stroke risk after transient ischemic attack can be as high as 17.8%, with almost half occurring within 2 days of the index event. Diagnosing transient ischemic attack can also be challenging given the transitory nature of symptoms, often reassuring neurological examination at the time of evaluation, and lack of confirmatory testing. Limited resources, such as imaging availability and access to specialists, can further exacerbate this challenge. This scientific statement focuses on the correct clinical diagnosis, risk assessment, and management decisions of patients with suspected transient ischemic attack. Identification of high-risk patients can be achieved through use of comprehensive protocols incorporating acute phase imaging of both the brain and cerebral vasculature, thoughtful use of risk stratification scales, and ancillary testing with the ultimate goal of determining who can be safely discharged home from the emergency department versus admitted to the hospital. We discuss various methods for rapid yet comprehensive evaluations, keeping resource-limited sites in mind. In addition, we discuss strategies for secondary prevention of future cerebrovascular events using maximal medical therapy and patient education.
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Lin J, Jiang M, Liu J, Yao L. The efficacy of transitional care services in patients with transient ischemic attack: A retrospective cohort study. Medicine (Baltimore) 2022; 101:e30872. [PMID: 36181073 PMCID: PMC9524928 DOI: 10.1097/md.0000000000030872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Transient ischemic attack (TIA) carries a particularly high short-term risk of stroke, which is associated with brain dysfunction caused by a regional reduction in blood flow. Transitional care services present benefits in improving ischemic neurological function and decreasing the recurrence in patients with TIA. The purpose of this study was to investigate the effects of transitional care on clinical outcomes in patients hospitalized for TIA. We retrospectively collected data about 1288 patients with TIA from May 2017 to June 2019. Patients were divided into mild (n = 438), moderate (n = 420) and severe group (n = 430) accessed by age, blood pressure, type of TIA, and duration (ABCD2) score. Participants were patients hospitalized due to TIA, assigned to transitional care (n = 643) or usual care (n = 645), and followed up for 24 months. Physical function of patients was evaluated using the 6-minute walk test. We evaluated patient reach, implementation using hospital quality measures, hospital-level sustainability physical function, ischemic neurological score, composite quality indicator score, and recurrence of TIA between transitional care or usual care group. TIA patients in transitional care group had better physical function and quality indicator score, lower ischemic neurological score and recurrence of TIA, and shorter hospital stay than patients in usual care group. Results demonstrated that transitional care significantly improved the patients' satisfaction compared to usual care. Patients in mild, moderate, and severe group presented more benefits than usual care clinical outcomes in patients hospitalized for TIA. Transitional care is associated with better functional status for patients with TIA.
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Affiliation(s)
- Jing Lin
- Second Department of Neurology, Department of Oncology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang 157001, China
| | - Meiling Jiang
- Second Department of Neurology, Department of Oncology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang 157001, China
| | - Jinmiao Liu
- Second Department of Neurology, Department of Oncology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang 157001, China
| | - Lan Yao
- Second Department of Neurology, Department of Oncology, Hongqi Hospital Affiliated to Mudanjiang Medical University, Mudanjiang 157001, China
- *Correspondence: Lan Yao, No. 5, Tongxiang Road, Aimin District, Mudanjiang City, Heilongjiang Province 157001, China (e-mail )
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Bravata DM, Miech EJ, Myers LJ, Perkins AJ, Zhang Y, Rattray NA, Baird SA, Penney LS, Austin C, Damush TM. The Perils of a "My Work Here is Done" perspective: a mixed methods evaluation of sustainment of an evidence-based intervention for transient ischemic attack. BMC Health Serv Res 2022; 22:857. [PMID: 35787273 PMCID: PMC9254423 DOI: 10.1186/s12913-022-08207-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/16/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND To evaluate quality improvement sustainment for Transient Ischemic Attack (TIA) and identify factors influencing sustainment, which is a challenge for Learning Healthcare Systems. METHODS Mixed methods were used to assess changes in care quality across periods (baseline, implementation, sustainment) and identify factors promoting or hindering sustainment of care quality. PREVENT was a stepped-wedge trial at six US Department of Veterans Affairs implementation sites and 36 control sites (August 2015-September 2019). Quality of care was measured by the without-fail rate: proportion of TIA patients who received all of the care for which they were eligible among brain imaging, carotid artery imaging, neurology consultation, hypertension control, anticoagulation for atrial fibrillation, antithrombotics, and high/moderate potency statins. Key informant interviews were used to identify factors associated with sustainment. RESULTS The without-fail rate at PREVENT sites improved from 36.7% (baseline, 58/158) to 54.0% (implementation, 95/176) and settled at 48.3% (sustainment, 56/116). At control sites, the without-fail rate improved from 38.6% (baseline, 345/893) to 41.8% (implementation, 363/869) and remained at 43.0% (sustainment, 293/681). After adjustment, no statistically significant difference in sustainment quality between intervention and control sites was identified. Among PREVENT facilities, the without-fail rate improved ≥2% at 3 sites, declined ≥2% at two sites, and remained unchanged at one site during sustainment. Factors promoting sustainment were planning, motivation to sustain, integration of processes into routine practice, leadership engagement, and establishing systems for reflecting and evaluating on performance data. The only factor that was sufficient for improving quality of care during sustainment was the presence of a champion with plans for sustainment. Challenges during sustainment included competing demands, low volume, and potential problems with medical coding impairing use of performance data. Four factors were sufficient for declining quality of care during sustainment: low motivation, champion inactivity, no reflecting and evaluating on performance data, and absence of leadership engagement. CONCLUSIONS Although the intervention improved care quality during implementation; performance during sustainment was heterogeneous across intervention sites and not different from control sites. Learning Healthcare Systems seeking to sustain evidence-based practices should embed processes within routine care and establish systems for reviewing and reflecting upon performance. TRIAL REGISTRATION Clinicaltrials.gov ( NCT02769338 ).
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Affiliation(s)
- Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA.
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA.
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Regenstrief Institute, Indianapolis, IN, USA.
| | - Edward J Miech
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Anthony J Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- Department of Biostatistics, Indiana University School of Medicine, IN, Indianapolis, USA
| | - Ying Zhang
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA
| | - Nicholas A Rattray
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Sean A Baird
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - Lauren S Penney
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Elizabeth Dole Center of Excellence for Veteran and Caregiver Research, South Texas Veterans Health Care System, San Antonio, TX, USA
- Department of Medicine, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Curt Austin
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - Teresa M Damush
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
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Arling G, Perkins A, Myers LJ, Sico JJ, Bravata DM. Blood Pressure Trajectories and Outcomes for Veterans Presenting at VA Medical Centers with a Stroke or Transient Ischemic Attack. Am J Med 2022; 135:889-896.e1. [PMID: 35292287 DOI: 10.1016/j.amjmed.2022.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 01/31/2022] [Accepted: 02/10/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Blood pressure control has been shown to reduce risk of vascular events and mortality after an ischemic stroke or transient ischemic attack (TIA). Yet, questions remain about effectiveness, timing, and targeted blood pressure reduction. METHODS We analyzed data from a retrospective cohort of 18,837 veterans cared for 12 months prior and up to 12 months after an emergency department visit or inpatient admission for stroke or TIA. Latent class growth analysis was used to classify patients into systolic blood pressure trajectories. With Cox proportional hazard models, we examined relationships between blood pressure trajectories, intensification of antihypertensive medication, and stroke (fatal or non-fatal) and all-cause mortality in 12 months following the index event. RESULTS The cohort was classified into 4 systolic blood pressure trajectories: 19% with a low systolic blood pressure trajectory (mean systolic blood pressure = 116 mm Hg); 65% with a medium systolic blood pressure trajectory (mean systolic blood pressure = 136 mm Hg); 15% with a high systolic blood pressure trajectory (mean systolic blood pressure = 158 mm Hg), and 1% with a very high trajectory (mean systolic blood pressure = 183 mm Hg). After the stroke or TIA, individuals in the high and very high systolic blood pressure trajectories experienced a substantial decrease in systolic blood pressure that coincided with intensification of antihypertensive medication. Patients with very low and very high systolic blood pressure trajectories had a significantly greater (P < .05) hazard of mortality, while medication intensification was related significantly (P < .05) to lower hazard of mortality. CONCLUSIONS These findings point to the importance of monitoring blood pressure over multiple time points and of instituting enhanced hypertension management after stroke or TIA, particularly for individuals with high or very high blood pressure trajectories.
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Affiliation(s)
- Greg Arling
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; School of Nursing, Purdue University, West Lafayette, Indianapolis, IN.
| | - Anthony Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; Biostatistics, Indiana University School of Medicine, Indianapolis, IN
| | - Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN; Health Services Research, Regenstrief Institute, Indianapolis, IN
| | - Jason J Sico
- Neurology Service, VA Connecticut Healthcare System, West Haven, Conn; Department of Neurology, Yale School of Medicine, New Haven, Conn
| | - Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN; Health Services Research, Regenstrief Institute, Indianapolis, IN; Medicine Service, Richard L. Roudebush VA Medical Center, Indianapolis, IN
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Tarko L, Costa L, Galloway A, Ho YL, Gagnon D, Lioutas V, Seshadri S, Cho K, Wilson P, Aparicio HJ. Racial and Ethnic Differences in Short- and Long-term Mortality by Stroke Type. Neurology 2022; 98:e2465-e2473. [PMID: 35649728 DOI: 10.1212/wnl.0000000000200575] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 03/01/2022] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Racial and ethnic disparities in stroke outcomes exist, but differences by stroke type are less understood. We studied the association of race and ethnicity with stroke mortality, by stroke type, in a national sample of hospitalized patients in the Veterans Health Administration. METHODS A retrospective observational study was performed including non-Hispanic White, non-Hispanic Black, and Hispanic patients with a first hospitalization for stroke between 2002 and 2012. Stroke was determined using ICD-9 codes and date of death was obtained from the National Death Index. For each of acute ischemic stroke (AIS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH), we constructed a piecewise multivariable model for all-cause mortality, using follow-up intervals of ≤30 days, 31-90 days, 91 days to 1 year, and >1 year. RESULTS Among 37,790 patients with stroke (89% AIS, 9% ICH, 2% SAH), 25,492 (67%) were non-Hispanic White, 9,752 (26%) were non-Hispanic Black, and 2,546 (7%) were Hispanic. The cohort was predominantly male (98%). Compared with White patients, Black patients experienced better 30-day survival after AIS (hazard ratio [HR] 0.80, 95% CI 0.73-0.88; 1.4% risk difference) and worse 30-day survival after ICH (HR 1.24, 95% CI 1.06-1.44; 3.2% risk difference). Hispanic patients experienced reduced risk for >1-year mortality after AIS (HR 0.87, 95% CI 0.80-0.94), but had greater risk of 30-day mortality after SAH compared with White patients (HR 1.61, 95% CI 1.03-2.52; 10.3% risk difference). DISCUSSION Among US Veterans, absolute risk of 30-day mortality after ICH was 3.2% higher for Black patients and after SAH was 10.3% higher for Hispanic patients compared with White patients. These findings underscore the importance of investigating stroke outcomes by stroke type to better understand the factors driving observed racial and ethnic disparities.
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Affiliation(s)
- Laura Tarko
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Lauren Costa
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Ashley Galloway
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Yuk-Lam Ho
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - David Gagnon
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Vasileios Lioutas
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Sudha Seshadri
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Kelly Cho
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Peter Wilson
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA
| | - Hugo J Aparicio
- From the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) (L.T., L.C., A.G., Y.-L.H., D.G., V.L., S.S., K.C., H.J.A.), VA Boston Healthcare System; Department of Biostatistics (D.G.), Boston University School of Public Health; Department of Neurology (V.L.), Beth Israel Deaconess Medical Center, Harvard Medical School; Department of Neurology (S.S., H.J.A.), Boston University School of Medicine, MA; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases (S.S.), University of Texas Health San Antonio; Division of Aging (K.C.), Brigham & Women's Hospital, Harvard Medical School, Boston, MA; Atlanta VA Medical Center (P.W.), Decatur; Division of Cardiology (P.W.), Emory University School of Medicine; Department of Epidemiology (P.W.), Rollins School of Public Health, Emory University, Atlanta, GA; and Boston Medical Center (H.J.A.), MA.
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Miech EJ, Perkins AJ, Zhang Y, Myers LJ, Sico JJ, Daggy J, Bravata DM. Pairing regression and configurational analysis in health services research: modelling outcomes in an observational cohort using a split-sample design. BMJ Open 2022; 12:e061469. [PMID: 35672067 PMCID: PMC9174826 DOI: 10.1136/bmjopen-2022-061469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Configurational methods are increasingly being used in health services research. OBJECTIVES To use configurational analysis and logistic regression within a single data set to compare results from the two methods. DESIGN Secondary analysis of an observational cohort; a split-sample design involved randomly dividing patients into training and validation samples. PARTICIPANTS AND SETTING Patients who had a transient ischaemic attack (TIA) in US Department of Veterans Affairs hospitals. MEASURES The patient outcome was the combined endpoint of all-cause mortality or recurrent ischaemic stroke within 1 year post-TIA. The quality-of-care outcome was the without-fail rate (proportion of patients who received all processes for which they were eligible, among seven processes). RESULTS For the recurrent stroke or death outcome, configurational analysis yielded a three-pathway model identifying a set of (validation sample) patients where the prevalence was 15.0% (83/552), substantially higher than the overall sample prevalence of 11.0% (relative difference, 36%). The configurational model had a sensitivity (coverage) of 84.7% and specificity of 40.6%. The logistic regression model identified six factors associated with the combined endpoint (c-statistic, 0.632; sensitivity, 63.3%; specificity, 63.1%). None of these factors were elements of the configurational model. For the quality outcome, configurational analysis yielded a single-pathway model identifying a set of (validation sample) patients where the without-fail rate was 64.3% (231/359), nearly twice the overall sample prevalence (33.7%). The configurational model had a sensitivity (coverage) of 77.3% and specificity of 78.2%. The logistic regression model identified seven factors associated with the without-fail rate (c-statistic, 0.822; sensitivity, 80.3%; specificity, 84.2%). Two of these factors were also identified in the configurational analysis. CONCLUSIONS Configurational analysis and logistic regression represent different methods that can enhance our understanding of a data set when paired together. Configurational models optimise sensitivity with relatively few conditions. Logistic regression models discriminate cases from controls and provided inferential relationships between outcomes and independent variables.
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Affiliation(s)
- Edward J Miech
- Quality Enhancement Research Initiative (QUERI) and Health Services Research and Development (HSR&D), Roudebush VA Medical Center, Indianapolis, Indiana, USA
- Center for Health Services Research, Regenstrief Institute Inc, Indianapolis, Indiana, USA
| | - Anthony J Perkins
- Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ying Zhang
- Department of Biostatistics, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Laura J Myers
- Quality Enhancement Research Initiative (QUERI) and Health Services Research and Development (HSR&D), Roudebush VA Medical Center, Indianapolis, Indiana, USA
- Center for Health Services Research, Regenstrief Institute Inc, Indianapolis, Indiana, USA
| | - Jason J Sico
- Neurology Service, VA Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Joanne Daggy
- Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Dawn M Bravata
- Quality Enhancement Research Initiative (QUERI) and Health Services Research and Development (HSR&D), Roudebush VA Medical Center, Indianapolis, Indiana, USA
- Center for Health Services Research, Regenstrief Institute Inc, Indianapolis, Indiana, USA
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Taylor RS, Opara NU, Burg J. Comparing Treatment Outcomes Between In-Hospital and Emergency Department Management of Patients With Transient Ischemic Attacks. Cureus 2021; 13:e20261. [PMID: 35004065 PMCID: PMC8735838 DOI: 10.7759/cureus.20261] [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] [Accepted: 12/08/2021] [Indexed: 11/09/2022] Open
Abstract
Introduction A transient ischemic attack (TIA) is a medical emergency, as it is a sudden neurological episode caused by ischemia in a vascular territory in the brain, which lasts less than one hour. TIA definition has shifted from time-based to tissue-based according to modern literature. It is considered a warning sign for an impending stroke. Symptoms could range from weakness on one side of the body, diaphoresis, to slurred speech. In this study, we examined the differences in health outcomes, when patients diagnosed with TIA are treated and discharged home from the ED, versus when admitted to the hospital for additional care. Methods This is a descriptive and retrospective study. We examined all patients’ encounters from January 1, 2018 to December 31, 2019 at four emergency department locations. The cohort compared patients diagnosed with a TIA who takes medications (anti-lipid, antiplatelet drugs) versus patients diagnosed with a TIA who are not on any preventive medication. We compared the hospital readmission rate between these two group of patients and the need for additional medical treatments. Our study also considered hospital length of stay (LOS), admission rate, and its impact on patients with comorbidities. Results There were 983 patients included in the study. The patients on TIA prophylactic medications prior to coming to the ED made up (60.7%), and (51.2%) in this group required additional medications during hospital admission. The remaining 162 (39.3%), p=0.001 patients, were not on TIA prophylactic medications prior to presenting in the ED. The patients who required additional medications while in the ED were significantly older (mean +/-SD, 68.6 +/-14.0 years versus 62.18 +/- 17.4 years, p=0.001). Following a multivariate analysis, age greater than 60 (CI: 3.52-3.91, p=0.001) and results of the head CT/MRI investigations for any signs of neurological damage, were all found to be independent predictors of longer hospital stay and treatment outcomes. There were no significant differences in the treatment outcome for patients with TIA based on longer hospital stay and extra medication administration in the ED. Conclusion In our study, we observed that approximately, 75% of the patients who were on TIA prophylactic medications prior to presenting in the ED with symptoms of TIA were admitted to the hospital for further monitoring, compared to other group of patients who were not on TIA medications. We did also noted that there were no differences in mortality outcome between patients treated and discharged from the ED, versus patients admitted to the hospital for additional treatment. Lastly, patients who are 68 years and older, made up two-thirds of patient population admitted in the hospital and required additional medications, compared to younger patients.
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13
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Lendaris AR, Lessen S, Cheng NT, Friedman BW, Esenwa C, Labovitz DL, Prabhakaran S, Lipton RB, Liberman AL. Under Treatment of High-Risk TIA Patients with Clopidogrel-Aspirin in the Emergency Setting. J Stroke Cerebrovasc Dis 2021; 30:106145. [PMID: 34649036 DOI: 10.1016/j.jstrokecerebrovasdis.2021.106145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/26/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Treating high-risk transient ischemic attack (TIA) with dual antiplatelet therapy (DAPT) reduces subsequent ischemic stroke risk yet current rates of clopidogrel-aspirin treatment are uncertain. MATERIALS AND METHODS We conducted a retrospective cohort study of consecutive TIA patients who presented to any of the four emergency departments (ED) of a single urban health system from 1/1/2018-3/1/2020. Medical record review was used to describe the cohort and assess clopidogrel-aspirin treatment. Patient eligibility for clopidogrel-aspirin was determined using relevant criteria from the Platelet-Oriented Inhibition in New TIA and Minor Ischemic Stroke (POINT) Trial. Comparisons among eligible patients who received versus did not receive clopidogrel-aspirin were conducted using t-test, chi-squared, and Mann-Whitney as indicated. RESULTS We identified 248 TIA patients of whom 95 met eligibility criteria for clopidogrel-aspirin treatment. Among these 95 patients, mean age was 69.5 (SD: 12), 68.4% were women, and median ABCD2 score was 5 (IQR: 4-6). A total of 26/95 (27.4%) eligible patients received clopidogrel-aspirin within 24 hours of symptom onset. Appropriate clopidogrel-aspirin use was associated with having a stroke code called upon ED arrival (88.5% vs. 34.8%; P<0.001), being evaluated by a vascular neurologist (88.5% vs. 21.1%; P<0.001), and not presenting to the community ED site wherein only a single patient received clopidogrel-aspirin. CONCLUSIONS In a multisite, single health system study, nearly three-fourths of high-risk TIA patients eligible for clopidogrel-aspirin treatment did not receive it. Appropriate clopidogrel-aspirin use was highest among patients seen by vascular neurologists and lowest at the community ED, though under treatment was evident at all sites.
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Affiliation(s)
- Andrea R Lendaris
- Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Samantha Lessen
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Natalie T Cheng
- Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Benjamin W Friedman
- Department of Emergency Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Charles Esenwa
- Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Daniel L Labovitz
- Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Shyam Prabhakaran
- Department of Neurology, University of Chicago School of Medicine, Chicago, IL, United States
| | - Richard B Lipton
- Department of Neurology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
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14
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Phan TG, Clissold B, Singhal S, Ly JV, Lim A, Vuong J, Ho S, Matley C, Kooblal T, Ma H. Network Mapping of Time to Antithrombotic Therapy Among Patients With Ischemic Stroke and Transient Ischemic Attack (TIA). Front Neurol 2021; 12:651869. [PMID: 34163420 PMCID: PMC8215274 DOI: 10.3389/fneur.2021.651869] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 05/14/2021] [Indexed: 11/18/2022] Open
Abstract
Background: There is emphasis on timely administration of thrombolysis and clot retrieval but not antithrombotic therapy within 48 h for ischemic stroke (frequency of 64% in Australia and 97% in North America). We planned to assess the time metrics and variables associated with delaying antithrombotics (antiplatelet and anticoagulant therapy) administration. Methods: This was a retrospective study at Monash Health over 12 months in 2015. We plotted the cumulative event and mapped the key drivers (dimensionless variable Shapley value/SV) of antithrombotics. Results: There were 42 patients with transient ischemic attack/TIA and 483 with ischemic stroke [mean age was 71.8 ± 15.4; 56.0% male; nil by mouth (NBM) 74.5 and 49.3% of patients received “stat” (immediate and one off) dose antithrombotics]. The median time to imaging for the patients who did not have stroke code activated was 2.3 h (IQR 1.4–3.7), from imaging to dysphagia screen was 14.6 h (IQR 6.2–20.3), and from stopping NBM to antithrombotics was 1.7 h (IQR 0–16.5). TIA patients received antithrombotics earlier than those with ischemic stroke (90.5 vs. 86.5%, p = 0.01). Significant variables in regression analysis for time to antithrombotics were time to dysphagia screen (β 0.20 ± 0.03, SV = 3.2), nasogastric tube (β 19.8 ± 5.9, SV = −0.20), Alteplase (β 8.6 ± 3.6, SV = −1.9), stat dose antithrombotic (β −18.9 ± 2.9, SV = −10.8) and stroke code (β −5.9 ± 2.5, SV = 2.8). The partial correlation network showed that the time to antithrombotics increased with delay in dysphagia screen (coefficient = 0.33) and decreased if “stat” dose of antithrombotics was given (coefficient = −0.32). Conclusion: The proportion of patients receiving antithrombotics within 48 h was higher than previously reported in Australia but remained lower than the standard achieved in North American hospitals. Our process map and network analysis show avenues to shorten the time to antithrombotic.
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Affiliation(s)
- Thanh G Phan
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - Benjamin Clissold
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - Shaloo Singhal
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - John Van Ly
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - Andy Lim
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Emergency Medicine, Monash Medical Center, Monash University, Clayton, VIC, Australia
| | - Jason Vuong
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - Stella Ho
- Department of Pharmacy Monash Medical Center, Monash University, Clayton, VIC, Australia
| | - Chelsea Matley
- Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - Talvika Kooblal
- Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
| | - Henry Ma
- Stroke & Aging Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Department of Neurology, Monash Health, Monash University, Clayton, VIC, Australia
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15
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Levine DA, Perkins AJ, Sico JJ, Myers LJ, Phipps MS, Zhang Y, Bravata DM. Hospital Factors, Performance on Process Measures After Transient Ischemic Attack, and 90-Day Ischemic Stroke Incidence. Stroke 2021; 52:2371-2378. [PMID: 34039034 DOI: 10.1161/strokeaha.120.031721] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Deborah A Levine
- University of Michigan Departments of Internal Medicine and Neurology, and Cognitive Health Services Research Program, Ann Arbor (D.A.L.)
| | - Anthony J Perkins
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis (A.J.P., D.M.B.).,Department of Veterans Affairs Health Services Research and Development Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Indianapolis, IN (A.J.P., L.J.M., D.M.B.)
| | - Jason J Sico
- Department of Neurology, VA Connecticut Healthcare System, West Haven, CT (J.J.S.).,Yale School of Medicine Departments of Neurology and Internal Medicine, New Haven, CT (J.J.S.)
| | - Laura J Myers
- Department of Veterans Affairs Health Services Research and Development Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Indianapolis, IN (A.J.P., L.J.M., D.M.B.).,VA HSR&D Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN (L.J.M., M.S.P., D.M.B.)
| | - Michael S Phipps
- VA HSR&D Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN (L.J.M., M.S.P., D.M.B.)
| | - Ying Zhang
- Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha (Y.Z.)
| | - Dawn M Bravata
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis (A.J.P., D.M.B.).,Department of Veterans Affairs Health Services Research and Development Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Indianapolis, IN (A.J.P., L.J.M., D.M.B.).,VA HSR&D Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN (L.J.M., M.S.P., D.M.B.)
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16
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Bhatia K, Jain V, Aggarwal D, Vaduganathan M, Arora S, Hussain Z, Uberoi G, Tafur A, Zhang C, Ricciardi M, Qamar A. Dual Antiplatelet Therapy Versus Aspirin in Patients With Stroke or Transient Ischemic Attack: Meta-Analysis of Randomized Controlled Trials. Stroke 2021; 52:e217-e223. [PMID: 33902301 DOI: 10.1161/strokeaha.120.033033] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Kirtipal Bhatia
- Department of Medicine, Icahn School of Medicine at Mount Sinai, NY (K.B.)
| | - Vardhmaan Jain
- Department of Medicine, Cleveland Clinic, Cleveland, OH (V.J.)
| | - Devika Aggarwal
- Department of Medicine, Beaumont Hospital, Royal Oak, MI (D.A.)
| | - Muthiah Vaduganathan
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (M.V.)
| | - Sameer Arora
- Cardiovascular Division, University of North Carolina School of Medicine, Chapel Hill (S.A.)
| | | | - Guneesh Uberoi
- Division of Cardiology, Loyola University School of Medicine, Maywood, IL. Department of Medicine, Emory University School of Medicine, Atlanta, GA (G.U.)
| | - Alfonso Tafur
- Section of Interventional Cardiology and Vascular Medicine, NorthShore University Health System, Evanston, IL (A.T., M.R., A.Q.)
| | - Cen Zhang
- Department of Neurology, New York University Grossman School of Medicine (C.Z.)
| | - Mark Ricciardi
- Section of Interventional Cardiology and Vascular Medicine, NorthShore University Health System, Evanston, IL (A.T., M.R., A.Q.)
| | - Arman Qamar
- Section of Interventional Cardiology and Vascular Medicine, NorthShore University Health System, Evanston, IL (A.T., M.R., A.Q.)
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17
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Pu C, Guo JY, Yu-Hua-Yeh, Sankara P. Comparison of knowledge on stroke for stroke patients and the general population in Burkina Faso: a cross-sectional study. AIMS Public Health 2020; 7:723-735. [PMID: 33294477 PMCID: PMC7719564 DOI: 10.3934/publichealth.2020056] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 09/07/2020] [Indexed: 11/18/2022] Open
Abstract
Background In many parts of Africa, there is limited information on awareness of symptoms of stroke, risk factors for stroke and willingness for stroke prevention, both in the general population and in people with stroke. Knowledge and preventive efforts for stroke in patients with a history of the illness are rarely investigated. This study aims to investigate awareness of stroke symptoms in stroke patients who were admitted to hospitals within 72 hours of a confirmed stroke event in Burkina Faso. This study also aims to investigate preventive behavior for stroke for the general population. Methods Face-to-face interviews were conducted with the participants. The sample included 110 first-time stroke patients who had been admitted to one of three tertiary teaching hospitals in Burkina Faso within 72 hours and 750 participants from the general population, who were recruited through clustered sampling. Knowledge of stroke warning signs and current and future efforts on stroke prevention were also assessed. Results Only 30.9% of the stroke patients believed that they were at risk before the stroke episode. Obvious warning signs were unfamiliar to both groups. Only 1.3% of the respondents from the general population group knew sudden weakness face arm or leg as a sign of stroke. For all future efforts in stroke prevention, stroke patients demonstrated significantly lower willingness to undertake behavioral changes than the general population. Sixty-six percent and 85% of the stroke patients and the general population, respectively, were willing to take steps to reduce blood pressure. Conclusion Public education on stroke warning signs and strategies to increase willingness to engage in preventive behaviors are urgent in African countries. Strategies to improve public awareness for developing countries such as Burkina Faso should be designed differently from that of developed countries to incorporate local beliefs.
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Affiliation(s)
- Christy Pu
- Institute of Public Health, National Yang-Ming University, Taipei, Taiwan
| | - Jiun-Yu Guo
- Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Hua-Yeh
- Institute of Public Health, National Yang-Ming University, Taipei, Taiwan
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18
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Haas K, Rücker V, Hermanek P, Misselwitz B, Berger K, Seidel G, Janssen A, Rode S, Burmeister C, Matthis C, Koennecke HC, Heuschmann PU. Association Between Adherence to Quality Indicators and 7-Day In-Hospital Mortality After Acute Ischemic Stroke. Stroke 2020; 51:3664-3672. [DOI: 10.1161/strokeaha.120.029968] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Background and Purpose:
Quality indicators (QI) are an accepted tool to measure performance of hospitals in routine care. We investigated the association between quality of acute stroke care defined by overall adherence to evidence-based QI and early outcome in German acute care hospitals.
Methods:
Patients with ischemic stroke admitted to one of the hospitals cooperating within the ADSR (German Stroke Register Study Group) were analyzed. The ADSR is a voluntary network of 9 regional stroke registers monitoring quality of acute stroke care across 736 hospitals in Germany. Quality of stroke care was defined by adherence to 11 evidence-based indicators of early processes of stroke care. The correlation between overall adherence to QI with outcome was investigated by assessing the association between 7-day in-hospital mortality with the proportion of QI fulfilled from the total number of QI the individual patient was eligible for. Generalized linear mixed model analysis was performed adjusted for the variables age, sex, National Institutes of Health Stroke Scale and living will and as random effect for the variable hospital.
Results:
Between 2015 and 2016, 388 012 patients with ischemic stroke were reported (median age 76 years, 52.4% male). Adherence to distinct QI ranged between 41.0% (thrombolysis in eligible patients) and 95.2% (early physiotherapy). Seven-day in-hospital mortality was 3.4%. The overall proportion of QI fulfilled was median 90% (interquartile range, 75%–100%). In multivariable analysis, a linear association between overall adherence to QI and 7-day in-hospital-mortality was observed (odds ratio adherence <50% versus 100%, 12.7 [95% CI, 11.8–13.7];
P
<0.001).
Conclusions:
Higher quality of care measured by adherence to a set of evidence-based process QI for the early phase of stroke treatment was associated with lower in-hospital mortality.
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Affiliation(s)
- Kirsten Haas
- Institute of Clinical Epidemiology and Biometry, University of Würzburg (K.H., V.R., P.U.H.)
| | - Viktoria Rücker
- Institute of Clinical Epidemiology and Biometry, University of Würzburg (K.H., V.R., P.U.H.)
| | - Peter Hermanek
- Bavarian Permanent Working Party for Quality Assurance (BAQ), Munich (P.H.)
| | | | - Klaus Berger
- Quality Assurance Project ”Stroke Register Northwest Germany”, Institute of Epidemiology and Social Medicine, University of Münster (K.B.)
| | - Günter Seidel
- Department of Neurology, Asklepios Klinik Nord, Hamburg (G.S.)
| | - Alfred Janssen
- Quality Assurance in Stroke Management in North Rhine–Westphalia, Medical Association North Rhine (A.J.)
| | - Susanne Rode
- Office for Quality Assurance in Health Care Baden-Württemberg GmbH (QiG BW GmbH), Stuttgart (S.R.)
| | | | - Christine Matthis
- Quality Association for Acute Stroke Treatment Schleswig-Holstein (QugSS), Institute of Social Medicine and Epidemiology, University of Lübeck (C.M.)
| | | | - Peter U. Heuschmann
- Institute of Clinical Epidemiology and Biometry, University of Würzburg (K.H., V.R., P.U.H.)
- Clinical Trial Center, University Hospital Würzburg (P.U.H.)
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19
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Bravata DM, Myers LJ, Perkins AJ, Zhang Y, Miech EJ, Rattray NA, Penney LS, Levine D, Sico JJ, Cheng EM, Damush TM. Assessment of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) Program for Improving Quality of Care for Transient Ischemic Attack: A Nonrandomized Cluster Trial. JAMA Netw Open 2020; 3:e2015920. [PMID: 32897372 PMCID: PMC7489850 DOI: 10.1001/jamanetworkopen.2020.15920] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
IMPORTANCE Patients with transient ischemic attack (TIA) are at high risk of recurrent vascular events. Timely management can reduce that risk by 70%; however, gaps in TIA quality of care exist. OBJECTIVE To assess the performance of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) intervention to improve TIA quality of care. DESIGN, SETTING, AND PARTICIPANTS This nonrandomized cluster trial with matched controls evaluated a multicomponent intervention to improve TIA quality of care at 6 diverse medical centers in 6 geographically diverse states in the US and assessed change over time in quality of care among 36 matched control sites (6 control sites matched to each PREVENT site on TIA patient volume, facility complexity, and quality of care). The study period (defined as the data period) started on August 21, 2015, and extended to May 12, 2019, including 1-year baseline and active implementation periods for each site. The intervention targeted clinical teams caring for patients with TIA. INTERVENTION The quality improvement (QI) intervention included the following 5 components: clinical programs, data feedback, professional education, electronic health record tools, and QI support. MAIN OUTCOMES AND MEASURES The primary outcome was the without-fail rate, which was calculated as the proportion of veterans with TIA at a specific facility who received all 7 guideline-recommended processes of care for which they were eligible (ie, anticoagulation for atrial fibrillation, antithrombotic use, brain imaging, carotid artery imaging, high- or moderate-potency statin therapy, hypertension control, and neurological consultation). Generalized mixed-effects models with multilevel hierarchical random effects were constructed to evaluate the intervention associations with the change in the mean without-fail rate from the 1-year baseline period to the 1-year intervention period. RESULTS Six facilities implemented the PREVENT QI intervention, and 36 facilities were identified as matched control sites. The mean (SD) age of patients at baseline was 69.85 (11.19) years at PREVENT sites and 71.66 (11.29) years at matched control sites. Most patients were male (95.1% [154 of 162] at PREVENT sites and 94.6% [920 of 973] at matched control sites at baseline). Among the PREVENT sites, the mean without-fail rate improved substantially from 36.7% (58 of 158 patients) at baseline to 54.0% (95 of 176 patients) during a 1-year implementation period (adjusted odds ratio, 2.10; 95% CI, 1.27-3.48; P = .004). Comparing the change in quality at the PREVENT sites with the matched control sites, the improvement in the mean without-fail rate was greater at the PREVENT sites than at the matched control sites (36.7% [58 of 158 patients] to 54.0% [95 of 176 patients] [17.3% absolute improvement] vs 38.6% [345 of 893 patients] to 41.8% [363 of 869 patients] [3.2% absolute improvement], respectively; absolute difference, 14%; P = .008). CONCLUSIONS AND RELEVANCE The implementation of this multifaceted program was associated with improved TIA quality of care across the participating sites. The PREVENT QI program is an example of a health care system using QI strategies to improve performance, and may serve as a model for other health systems seeking to provide better care. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02769338.
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Affiliation(s)
- Dawn M. Bravata
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- Veterans Affairs Health Services Research and Development, Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, Indiana
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis
- Department of Neurology, Indiana University School of Medicine, Indianapolis
- Regenstrief Institute, Indianapolis, Indiana
| | - Laura J. Myers
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- Veterans Affairs Health Services Research and Development, Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, Indiana
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis
- Regenstrief Institute, Indianapolis, Indiana
| | - Anthony J. Perkins
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis
| | - Ying Zhang
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- now with Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha
| | - Edward J. Miech
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- Veterans Affairs Health Services Research and Development, Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, Indiana
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis
- Regenstrief Institute, Indianapolis, Indiana
| | - Nicholas A. Rattray
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- Veterans Affairs Health Services Research and Development, Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, Indiana
- Regenstrief Institute, Indianapolis, Indiana
| | - Lauren S. Penney
- South Texas Veterans Health Care System, San Antonio
- Department of Medicine, University of Texas Health, San Antonio
| | - Deborah Levine
- Department of Medicine, University of Michigan School of Medicine, Ann Arbor
| | - Jason J. Sico
- Clinical Epidemiology Research Center, VA Connecticut Healthcare System, West Haven
- VA Neurology Service, VA Connecticut Healthcare System, West Haven
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
- Department of Neurology and Center for Neuroepidemiology and Clinical Neurological Research, Yale University School of Medicine, New Haven, Connecticut
| | - Eric M. Cheng
- Department of Neurology, VA Greater Los Angeles Healthcare System, Los Angeles, California
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles
| | - Teresa M. Damush
- Veterans Affairs Health Services Research and Development, Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Department of Veterans Affairs, Indianapolis, Indiana
- Veterans Affairs Health Services Research and Development, Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, Indiana
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis
- Regenstrief Institute, Indianapolis, Indiana
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20
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Bravata DM, Myers LJ, Homoya B, Miech EJ, Rattray NA, Perkins AJ, Zhang Y, Ferguson J, Myers J, Cheatham AJ, Murphy L, Giacherio B, Kumar M, Cheng E, Levine DA, Sico JJ, Ward MJ, Damush TM. The protocol-guided rapid evaluation of veterans experiencing new transient neurological symptoms (PREVENT) quality improvement program: rationale and methods. BMC Neurol 2019; 19:294. [PMID: 31747879 PMCID: PMC6865042 DOI: 10.1186/s12883-019-1517-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 10/28/2019] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Transient ischemic attack (TIA) patients are at high risk of recurrent vascular events; timely management can reduce that risk by 70%. The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) developed, implemented, and evaluated a TIA quality improvement (QI) intervention aligned with Learning Healthcare System principles. METHODS This stepped-wedge trial developed, implemented and evaluated a provider-facing, multi-component intervention to improve TIA care at six facilities. The unit of analysis was the medical center. The intervention was developed based on benchmarking data, staff interviews, literature, and electronic quality measures and included: performance data, clinical protocols, professional education, electronic health record tools, and QI support. The effectiveness outcome was the without-fail rate: the proportion of patients who receive all processes of care for which they are eligible among seven processes. The implementation outcomes were the number of implementation activities completed and final team organization level. The intervention effects on the without-fail rate were analyzed using generalized mixed-effects models with multilevel hierarchical random effects. Mixed methods were used to assess implementation, user satisfaction, and sustainability. DISCUSSION PREVENT advanced three aspects of a Learning Healthcare System. Learning from Data: teams examined and interacted with their performance data to explore hypotheses, plan QI activities, and evaluate change over time. Learning from Each Other: Teams participated in monthly virtual collaborative calls. Sharing Best Practices: Teams shared tools and best practices. The approach used to design and implement PREVENT may be generalizable to other clinical conditions where time-sensitive care spans clinical settings and medical disciplines. TRIAL REGISTRATION clinicaltrials.gov: NCT02769338 [May 11, 2016].
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Affiliation(s)
- D M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA.
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA.
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Regenstrief Institute, Indianapolis, IN, USA.
| | - L J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - B Homoya
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - E J Miech
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - N A Rattray
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - A J Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Y Zhang
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA
| | - J Ferguson
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - A J Cheatham
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - L Murphy
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - B Giacherio
- Office of Healthcare Transformation (OHT), Veterans Health Administration (VHA), Washington, DC, USA
| | - M Kumar
- Office of Healthcare Transformation (OHT), Veterans Health Administration (VHA), Washington, DC, USA
| | - E Cheng
- Department of Neurology, VA Greater Los Angeles Healthcare System, California, Los Angeles, USA
- Department of Neurology, David Geffen School of Medicine, University of California at Los Angeles, California, Los Angeles, USA
| | - D A Levine
- Department of Internal Medicine and Neurology and Institute for Health Policy and Innovation, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - J J Sico
- Clinical Epidemiology Research Center and Neurology Service, VA Connecticut Healthcare System, West Haven, CT, USA
- Departments of Internal Medicine and Neurology and Center for Neuroepidemiology and Clinical Neurological Research, Yale School of Medicine, New Haven, CT, USA
| | - M J Ward
- VA Tennessee Valley Healthcare System, Nashville, TN, USA
- Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - T M Damush
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
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