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Geva A, Abman SH, Manzi SF, Ivy DD, Mullen MP, Griffin J, Lin C, Savova GK, Mandl KD. Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources. J Am Med Inform Assoc 2021; 27:294-300. [PMID: 31769835 PMCID: PMC7025334 DOI: 10.1093/jamia/ocz194] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 10/08/2019] [Accepted: 10/21/2019] [Indexed: 11/14/2022] Open
Abstract
Objective Real-world data (RWD) are increasingly used for pharmacoepidemiology and regulatory innovation. Our objective was to compare adverse drug event (ADE) rates determined from two RWD sources, electronic health records and administrative claims data, among children treated with drugs for pulmonary hypertension. Materials and Methods Textual mentions of medications and signs/symptoms that may represent ADEs were identified in clinical notes using natural language processing. Diagnostic codes for the same signs/symptoms were identified in our electronic data warehouse for the patients with textual evidence of taking pulmonary hypertension-targeted drugs. We compared rates of ADEs identified in clinical notes to those identified from diagnostic code data. In addition, we compared putative ADE rates from clinical notes to those from a healthcare claims dataset from a large, national insurer. Results Analysis of clinical notes identified up to 7-fold higher ADE rates than those ascertained from diagnostic codes. However, certain ADEs (eg, hearing loss) were more often identified in diagnostic code data. Similar results were found when ADE rates ascertained from clinical notes and national claims data were compared. Discussion While administrative claims and clinical notes are both increasingly used for RWD-based pharmacovigilance, ADE rates substantially differ depending on data source. Conclusion Pharmacovigilance based on RWD may lead to discrepant results depending on the data source analyzed. Further work is needed to confirm the validity of identified ADEs, to distinguish them from disease effects, and to understand tradeoffs in sensitivity and specificity between data sources.
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Castiñeira D, Schlosser KR, Geva A, Rahmani AR, Fiore G, Walsh BK, Smallwood CD, Arnold JH, Santillana M. Adding Continuous Vital Sign Information to Static Clinical Data Improves the Prediction of Length of Stay After Intubation: A Data-Driven Machine Learning Approach. Respir Care 2021; 65:1367-1377. [PMID: 32879034 DOI: 10.4187/respcare.07561] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND Bedside monitors in the ICU routinely measure and collect patients' physiologic data in real time to continuously assess the health status of patients who are critically ill. With the advent of increased computational power and the ability to store and rapidly process big data sets in recent years, these physiologic data show promise in identifying specific outcomes and/or events during patients' ICU hospitalization. METHODS We introduced a methodology designed to automatically extract information from continuous-in-time vital sign data collected from bedside monitors to predict if a patient will experience a prolonged stay (length of stay) on mechanical ventilation, defined as >4 d, in a pediatric ICU. RESULTS Continuous-in-time vital signs information and clinical history data were retrospectively collected for 284 ICU subjects from their first 24 h on mechanical ventilation from a medical-surgical pediatric ICU at Boston Children's Hospital. Multiple machine learning models were trained on multiple subsets of these subjects to predict the likelihood that each of these subjects would experience a long stay. We evaluated the predictive power of our models strictly on unseen hold-out validation sets of subjects. Our methodology achieved model performance of >83% (area under the curve) by using only vital sign information as input, and performances of 90% (area under the curve) by combining vital sign information with subjects' static clinical data readily available in electronic health records. We implemented this approach on 300 independently trained experiments with different choices of training and hold-out validation sets to ensure the consistency and robustness of our results in our study sample. The predictive power of our approach outperformed recent efforts that used deep learning to predict a similar task. CONCLUSIONS Our proposed workflow may prove useful in the design of scalable approaches for real-time predictive systems in ICU environments, exploiting real-time vital sign information from bedside monitors. (ClinicalTrials.gov registration NCT02184208.).
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Geva A, Liu M, Panickan VA, Avillach P, Cai T, Mandl KD. A high-throughput phenotyping algorithm is portable from adult to pediatric populations. J Am Med Inform Assoc 2021; 28:1265-1269. [PMID: 33594412 DOI: 10.1093/jamia/ocaa343] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 11/27/2020] [Accepted: 12/28/2020] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE Multimodal automated phenotyping (MAP) is a scalable, high-throughput phenotyping method, developed using electronic health record (EHR) data from an adult population. We tested transportability of MAP to a pediatric population. MATERIALS AND METHODS Without additional feature engineering or supervised training, we applied MAP to a pediatric population enrolled in a biobank and evaluated performance against physician-reviewed medical records. We also compared performance of MAP at the pediatric institution and the original adult institution where MAP was developed, including for 6 phenotypes validated at both institutions against physician-reviewed medical records. RESULTS MAP performed equally well in the pediatric setting (average AUC 0.98) as it did at the general adult hospital system (average AUC 0.96). MAP's performance in the pediatric sample was similar across the 6 specific phenotypes also validated against gold-standard labels in the adult biobank. CONCLUSIONS MAP is highly transportable across diverse populations and has potential for wide-scale use.
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Geva A, Stedman JP, Manzi SF, Lin C, Savova GK, Avillach P, Mandl KD. Adverse drug event presentation and tracking (ADEPT): semiautomated, high throughput pharmacovigilance using real-world data. JAMIA Open 2020; 3:413-421. [PMID: 33215076 PMCID: PMC7660953 DOI: 10.1093/jamiaopen/ooaa031] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 06/23/2020] [Accepted: 06/27/2020] [Indexed: 11/24/2022] Open
Abstract
Objective To advance use of real-world data (RWD) for pharmacovigilance, we sought to integrate a high-sensitivity natural language processing (NLP) pipeline for detecting potential adverse drug events (ADEs) with easily interpretable output for high-efficiency human review and adjudication of true ADEs. Materials and methods The adverse drug event presentation and tracking (ADEPT) system employs an open source NLP pipeline to identify in clinical notes mentions of medications and signs and symptoms potentially indicative of ADEs. ADEPT presents the output to human reviewers by highlighting these drug-event pairs within the context of the clinical note. To measure incidence of seizures associated with sildenafil, we applied ADEPT to 149 029 notes for 982 patients with pediatric pulmonary hypertension. Results Of 416 patients identified as taking sildenafil, NLP found 72 [17%, 95% confidence interval (CI) 14–21] with seizures as a potential ADE. Upon human review and adjudication, only 4 (0.96%, 95% CI 0.37–2.4) patients with seizures were determined to have true ADEs. Reviewers using ADEPT required a median of 89 s (interquartile range 57–142 s) per patient to review potential ADEs. Discussion ADEPT combines high throughput NLP to increase sensitivity of ADE detection and human review, to increase specificity by differentiating true ADEs from signs and symptoms related to comorbidities, effects of other medications, or other confounders. Conclusion ADEPT is a promising tool for creating gold standard, patient-level labels for advancing NLP-based pharmacovigilance. ADEPT is a potentially time savings platform for computer-assisted pharmacovigilance based on RWD.
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Shani-Hershkovitz R, Avirame K, Alyagon U, Zangen A, Harel E, Levkovitz Y, Geva A, Peremen Z. P235 An EEG based tool to inform responsiveness to rTMS treatment for subjects with major depression. Clin Neurophysiol 2020. [DOI: 10.1016/j.clinph.2019.12.346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Schlosser KR, Fiore GA, Smallwood CD, Griffin JF, Geva A, Santillana M, Arnold JH. Noninvasive Ventilation Is Interrupted Frequently and Mostly Used at Night in the Pediatric Intensive Care Unit. Respir Care 2019; 65:341-346. [PMID: 31551282 DOI: 10.4187/respcare.06883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND Noninvasive ventilation (NIV) is commonly used to support children with respiratory failure, but detailed patterns of real-world use are lacking. The aim of our study was to describe use patterns of NIV via electronic medical record (EMR) data. METHODS We performed a retrospective electronic chart review in a tertiary care pediatric ICU in the United States. Subjects admitted to the pediatric ICU from 2014 to 2017 who were mechanically ventilated were included in the study. RESULTS The median number of discrete device episodes, defined as a time on support without interruption, was 20 (interquartile range [IQR] 8-49) per subject. The median duration of bi-level positive airway pressure (BPAP) support prior to interruption was 6.3 h (IQR 2.4-10.4); the median duration of CPAP was 6 h (IQR 2.1-10.4). Interruptions to BPAP had a median duration of 6.3 h (IQR 2-15.5); interruptions to CPAP had a median duration of 8.6 h (IQR 2.2-16.8). Use of NIV followed a diurnal pattern, with 44% of BPAP and 42% of CPAP subjects initiating support between 7:00 pm and midnight, and 49% of BPAP and 46% of CPAP subjects stopping support between 5:00 am and 10:00 am. CONCLUSIONS NIV was frequently interrupted, and initiation and discontinuation of NIV follows a diurnal pattern. Use of EMR data collected for routine clinical care allowed the analysis of granular details of typical use patterns. Understanding NIV use patterns may be particularly important to understanding the burden of pediatric ICU bed utilization for nocturnal NIV. To our knowledge, this is the first study to examine in detail the use of pediatric NIV and to define diurnal use and frequent interruptions to support.
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Ning W, Chan S, Beam A, Yu M, Geva A, Liao K, Mullen M, Mandl KD, Kohane I, Cai T, Yu S. Feature extraction for phenotyping from semantic and knowledge resources. J Biomed Inform 2019; 91:103122. [PMID: 30738949 PMCID: PMC6424621 DOI: 10.1016/j.jbi.2019.103122] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVE Phenotyping algorithms can efficiently and accurately identify patients with a specific disease phenotype and construct electronic health records (EHR)-based cohorts for subsequent clinical or genomic studies. Previous studies have introduced unsupervised EHR-based feature selection methods that yielded algorithms with high accuracy. However, those selection methods still require expert intervention to tweak the parameter settings according to the EHR data distribution for each phenotype. To further accelerate the development of phenotyping algorithms, we propose a fully automated and robust unsupervised feature selection method that leverages only publicly available medical knowledge sources, instead of EHR data. METHODS SEmantics-Driven Feature Extraction (SEDFE) collects medical concepts from online knowledge sources as candidate features and gives them vector-form distributional semantic representations derived with neural word embedding and the Unified Medical Language System Metathesaurus. A number of features that are semantically closest and that sufficiently characterize the target phenotype are determined by a linear decomposition criterion and are selected for the final classification algorithm. RESULTS SEDFE was compared with the EHR-based SAFE algorithm and domain experts on feature selection for the classification of five phenotypes including coronary artery disease, rheumatoid arthritis, Crohn's disease, ulcerative colitis, and pediatric pulmonary arterial hypertension using both supervised and unsupervised approaches. Algorithms yielded by SEDFE achieved comparable accuracy to those yielded by SAFE and expert-curated features. SEDFE is also robust to the input semantic vectors. CONCLUSION SEDFE attains satisfying performance in unsupervised feature selection for EHR phenotyping. Both fully automated and EHR-independent, this method promises efficiency and accuracy in developing algorithms for high-throughput phenotyping.
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Reches A, Or-ly H, Weiss M, Stern Y, Baumeister J, Foss K, Ellis J, Laish B, Laufer O, Sadeh B, Ettinger M, Arthur T, Shaham G, Myer G, Kehat O, Shani-Hershkovich R, Peremen Z, Geva A. P 136 Brain network analysis of EEG data in the service of clinical assessment – utilizing big data and prior theoretical knowledge to identify a biomarker for mTBI in adolscents. Clin Neurophysiol 2017. [DOI: 10.1016/j.clinph.2017.06.209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Geva A, Gronsbell JL, Cai T, Cai T, Murphy SN, Lyons JC, Heinz MM, Natter MD, Patibandla N, Bickel J, Mullen MP, Mandl KD. A Computable Phenotype Improves Cohort Ascertainment in a Pediatric Pulmonary Hypertension Registry. J Pediatr 2017; 188. [PMID: 28625502 PMCID: PMC5572538 DOI: 10.1016/j.jpeds.2017.05.037] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVES To compare registry and electronic health record (EHR) data mining approaches for cohort ascertainment in patients with pediatric pulmonary hypertension (PH) in an effort to overcome some of the limitations of registry enrollment alone in identifying patients with particular disease phenotypes. STUDY DESIGN This study was a single-center retrospective analysis of EHR and registry data at Boston Children's Hospital. The local Informatics for Integrating Biology and the Bedside (i2b2) data warehouse was queried for billing codes, prescriptions, and narrative data related to pediatric PH. Computable phenotype algorithms were developed by fitting penalized logistic regression models to a physician-annotated training set. Algorithms were applied to a candidate patient cohort, and performance was evaluated using a separate set of 136 records and 179 registry patients. We compared clinical and demographic characteristics of patients identified by computable phenotype and the registry. RESULTS The computable phenotype had an area under the receiver operating characteristics curve of 90% (95% CI, 85%-95%), a positive predictive value of 85% (95% CI, 77%-93%), and identified 413 patients (an additional 231%) with pediatric PH who were not enrolled in the registry. Patients identified by the computable phenotype were clinically distinct from registry patients, with a greater prevalence of diagnoses related to perinatal distress and left heart disease. CONCLUSIONS Mining of EHRs using computable phenotypes identified a large cohort of patients not recruited using a classic registry. Fusion of EHR and registry data can improve cohort ascertainment for the study of rare diseases. TRIAL REGISTRATION ClinicalTrials.gov: NCT02249923.
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Ong MS, Mullen MP, Austin ED, Szolovits P, Natter MD, Geva A, Cai T, Kong SW, Mandl KD. Learning a Comorbidity-Driven Taxonomy of Pediatric Pulmonary Hypertension. Circ Res 2017; 121:341-353. [PMID: 28611076 PMCID: PMC5559726 DOI: 10.1161/circresaha.117.310804] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 06/07/2017] [Accepted: 06/12/2017] [Indexed: 11/16/2022]
Abstract
RATIONALE Pediatric pulmonary hypertension (PH) is a heterogeneous condition with varying natural history and therapeutic response. Precise classification of PH subtypes is, therefore, crucial for individualizing care. However, gaps remain in our understanding of the spectrum of PH in children. OBJECTIVE We seek to study the manifestations of PH in children and to assess the feasibility of applying a network-based approach to discern disease subtypes from comorbidity data recorded in longitudinal data sets. METHODS AND RESULTS A retrospective cohort study comprising 6 943 263 children (<18 years of age) enrolled in a commercial health insurance plan in the United States, between January 2010 and May 2013. A total of 1583 (0.02%) children met the criteria for PH. We identified comorbidities significantly associated with PH compared with the general population of children without PH. A Bayesian comorbidity network was constructed to model the interdependencies of these comorbidities, and network-clustering analysis was applied to derive disease subtypes comprising subgraphs of highly connected comorbid conditions. A total of 186 comorbidities were found to be significantly associated with PH. Network analysis of comorbidity patterns captured most of the major PH subtypes with known pathological basis defined by the World Health Organization and Panama classifications. The analysis further identified many subtypes documented in only a few case studies, including rare subtypes associated with several well-described genetic syndromes. CONCLUSIONS Application of network science to model comorbidity patterns recorded in longitudinal data sets can facilitate the discovery of disease subtypes. Our analysis relearned established subtypes, thus validating the approach, and identified rare subtypes that are difficult to discern through clinical observations, providing impetus for deeper investigation of the disease subtypes that will enrich current disease classifications.
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Geva A, Olson KL, Liu C, Mandl KD. Provider Connectedness to Other Providers Reduces Risk of Readmission After Hospitalization for Heart Failure. Med Care Res Rev 2017; 76:115-128. [PMID: 29148301 DOI: 10.1177/1077558717718626] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Provider interactions other than explicit care coordination, which is challenging to measure, may influence practice and outcomes. We performed a network analysis using claims data from a commercial payor. Networks were identified based on provider pairs billing outpatient care for the same patient. We compared network variables among patients who had and did not have a 30-day readmission after hospitalization for heart failure. After adjusting for comorbidities, high median provider connectedness-normalized degree, which for each provider is the number of connections to other providers normalized to the number of providers in the region-was the network variable associated with reduced odds of readmission after heart failure hospitalization (odds ratio = 0.55; 95% confidence interval [0.35, 0.86]). We conclude that heart failure patients with high provider connectedness are less likely to require readmission. The structure and importance of provider relationships using claims data merits further study.
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Biederman J, Hammerness P, Sadeh B, Peremen Z, Amit A, Or-Ly H, Stern Y, Reches A, Geva A, Faraone SV. Diagnostic utility of brain activity flow patterns analysis in attention deficit hyperactivity disorder. Psychol Med 2017; 47:1259-1270. [PMID: 28065167 DOI: 10.1017/s0033291716003329] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND A previous small study suggested that Brain Network Activation (BNA), a novel ERP-based brain network analysis, may have diagnostic utility in attention deficit hyperactivity disorder (ADHD). In this study we examined the diagnostic capability of a new advanced version of the BNA methodology on a larger population of adults with and without ADHD. METHOD Subjects were unmedicated right-handed 18- to 55-year-old adults of both sexes with and without a DSM-IV diagnosis of ADHD. We collected EEG while the subjects were performing a response inhibition task (Go/NoGo) and then applied a spatio-temporal Brain Network Activation (BNA) analysis of the EEG data. This analysis produced a display of qualitative measures of brain states (BNA scores) providing information on cortical connectivity. This complex set of scores was then fed into a machine learning algorithm. RESULTS The BNA analysis of the EEG data recorded during the Go/NoGo task demonstrated a high discriminative capacity between ADHD patients and controls (AUC = 0.92, specificity = 0.95, sensitivity = 0.86 for the Go condition; AUC = 0.84, specificity = 0.91, sensitivity = 0.76 for the NoGo condition). CONCLUSIONS BNA methodology can help differentiate between ADHD and healthy controls based on functional brain connectivity. The data support the utility of the tool to augment clinical examinations by objective evaluation of electrophysiological changes associated with ADHD. Results also support a network-based approach to the study of ADHD.
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Sand D, Peremen Z, Haor D, Arkadir D, Bergman H, Geva A. Optimization of deep brain stimulation in STN among patients with Parkinson's disease using a novel EEG-based tool. Brain Stimul 2017. [DOI: 10.1016/j.brs.2017.01.490] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Reches A, Kutcher J, Elbin RJ, Or-Ly H, Sadeh B, Greer J, McAllister DJ, Geva A, Kontos AP. Preliminary investigation of Brain Network Activation (BNA) and its clinical utility in sport-related concussion. Brain Inj 2017; 31:237-246. [PMID: 28055228 PMCID: PMC5351793 DOI: 10.1080/02699052.2016.1231343] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background: The clinical diagnosis and management of patients with sport-related concussion is largely dependent on subjectively reported symptoms, clinical examinations, cognitive, balance, vestibular and oculomotor testing. Consequently, there is an unmet need for objective assessment tools that can identify the injury from a physiological perspective and add an important layer of information to the clinician’s decision-making process. Objective: The goal of the study was to evaluate the clinical utility of the EEG-based tool named Brain Network Activation (BNA) as a longitudinal assessment method of brain function in the management of young athletes with concussion. Methods: Athletes with concussion (n = 86) and age-matched controls (n = 81) were evaluated at four time points with symptom questionnaires and BNA. BNA scores were calculated by comparing functional networks to a previously defined normative reference brain network model to the same cognitive task. Results: Subjects above 16 years of age exhibited a significant decrease in BNA scores immediately following injury, as well as notable changes in functional network activity, relative to the controls. Three representative case studies of the tested population are discussed in detail, to demonstrate the clinical utility of BNA. Conclusion: The data support the utility of BNA to augment clinical examinations, symptoms and additional tests by providing an effective method for evaluating objective electrophysiological changes associated with sport-related concussions.
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Pickard SS, Geva A, Gauvreau K, del Nido PJ, Geva T. Long-term outcomes and risk factors for aortic regurgitation after discrete subvalvular aortic stenosis resection in children. Heart 2015; 101:1547-53. [PMID: 26238147 DOI: 10.1136/heartjnl-2015-307460] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2015] [Accepted: 06/18/2015] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVES To characterise long-term outcomes after discrete subaortic stenosis (DSS) resection and to identify risk factors for reoperation and aortic regurgitation (AR) requiring repair or replacement. METHODS All patients who underwent DSS resection between 1984 and 2009 at our institution with at least 36 months' follow-up were included. Demographic, surgical and echocardiographic data were reviewed. Outcomes were reoperation for recurrent DSS, surgery for AR, death and morbidities, including heart transplant, endocarditis and complete heart block. RESULTS Median length of postoperative follow-up was 10.9 years (3-27.2 years). Reoperation occurred in 32 patients (21%) and plateaued 10 years after initial resection. Survival at 10 years and 20 years was 98.6% and 86.3%, respectively. Aortic valve (AoV) repair or replacement for predominant AR occurred in 31 patients (20%) during or after DSS resection. By multivariable analysis, prior aortic stenosis (AS) intervention (HR 22.4, p<0.001) was strongly associated with AoV repair or replacement. Risk factors for reoperation by multivariable analysis included younger age at resection (HR 1.24, p=0.003), preoperative gradient ≥60 mm Hg (HR 2.23, p=0.04), peeling of membrane off AoV or mitral valve (HR 2.52, p=0.01), distance of membrane to AoV <7.0 mm (HR 4.03, p=0.03) and AS (HR 2.58, p=0.01). CONCLUSIONS In this cohort, the incidence of reoperations after initial DSS resection plateaued after 10 years. Despite a significant rate of reoperation, overall survival was good. Concomitant congenital AS and its associated interventions significantly increased the risk of AR requiring surgical intervention.
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Geva A, Wright SB, Baldini LM, Smallcomb JA, Safran C, Gray JE. Spread of methicillin-resistant Staphylococcus aureus in a large tertiary NICU: network analysis. Pediatrics 2011; 128:e1173-80. [PMID: 22007011 PMCID: PMC3208963 DOI: 10.1542/peds.2010-2562] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE Methicillin-resistant Staphylococcus aureus (MRSA) colonization in NICUs increases the risk of nosocomial infection. Network analysis provides tools to examine the interactions among patients and staff members that put patients at risk of colonization. METHODS Data from MRSA surveillance cultures were combined with patient room locations, nursing assignments, and sibship information to create patient- and unit-based networks. Multivariate models were constructed to quantify the risk of incident MRSA colonization as a function of exposure to MRSA-colonized infants in these networks. RESULTS A MRSA-negative infant in the NICU simultaneously with a MRSA-positive infant had higher odds of becoming colonized when the colonized infant was a sibling, compared with an unrelated patient (odds ratio: 8.8 [95% confidence interval [CI]: 5.3-14.8]). Although knowing that a patient was MRSA-positive and was placed on contact precautions reduced the overall odds of another patient becoming colonized by 35% (95% CI: 20%-47%), having a nurse in common with that patient still increased the odds of colonization by 43% (95% CI: 14%-80%). Normalized group degree centrality, a unitwide network measure of connectedness between colonized and uncolonized patients, was a significant predictor of incident MRSA cases (odds ratio: 18.1 [95% CI: 3.6-90.0]). CONCLUSIONS Despite current infection-control strategies, patients remain at significant risk of MRSA colonization from MRSA-positive siblings and from other patients with whom they share nursing care. Strategies that minimize the frequency of staff members caring for both colonized and uncolonized infants may be beneficial in reducing the spread of MRSA colonization.
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Geva A, Gray J. A quantitative analysis of optimal treatment capacity for perinatal asphyxia. Med Decis Making 2011; 32:266-72. [PMID: 21933991 DOI: 10.1177/0272989x11421527] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE In centers electing to offer therapeutic hypothermia for treating hypoxic-ischemic encephalopathy (HIE), determining the optimal number of cooling devices is not straightforward. The authors used computer-based modeling to determine the level of service as a function of local HIE caseload and number of cooling devices available. METHODS The authors used discrete event simulation to create a model that varied the number of HIE cases and number of cooling devices available. Outcomes of interest were percentage of HIE-affected infants not cooled, number of infants not cooled, and percentage of time that all cooling devices were in use. RESULTS With 1 cooling device, even the smallest perinatal center did not achieve a cooling rate of 99% of eligible infants. In contrast, 2 devices ensured 99% service in centers treating as many as 20 infants annually. In centers averaging no more than 1 HIE infant monthly, the addition of a third cooling device did not result in a substantial reduction in the number of infants who would not be cooled. CONCLUSION Centers electing to offer therapeutic hypothermia with only a single cooling device are at significant risk of being unable to provide treatment to eligible infants, whereas 2 devices appear to suffice for most institutions treating as many as 20 annual HIE cases. Three devices would rarely be needed given current caseloads seen at individual institutions. The quantitative nature of this analysis allows decision makers to determine the number of devices necessary to ensure adequate availability of therapeutic hypothermia given the HIE caseload of a particular institution.
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Abstract
Objective. To use meta-analytic techniques to examine the effect of dexamethasone on the risk of postoperative bleeding following tonsillectomy. Data Sources. PubMed and Embase databases accessed on April 23, 2009, and April 28, 2009. Review Methods. Using principles of meta-analysis, inclusion and exclusion criteria were developed to identify all randomized controlled trials of patients undergoing tonsillectomy in which perioperative intravenous dexamethasone was administered in at least 1 treatment arm and bleeding complications were reported. Electronic databases were searched to identify candidate articles. Two authors independently abstracted data from each article. Discrepancies were resolved by consensus. A fixed-effects model was used to pool relative risks among studies using the Mantel-Haenszel method. Studies were assessed for publication bias using a funnel plot of studies’ effect size vs standard error of the effect size as well as Begg test and Egger test. A P value <.05 was considered significant. Results. The primary search identified 85 potential studies. Fourteen met inclusion criteria and were selected for meta-analysis. No significant heterogeneity was found among studies (I2< 0.1%; 95% confidence interval [CI], 0%-55%; P = .68). The pooled relative risk (RR) of postoperative bleeding did not differ significantly between patients receiving dexamethasone and controls (RR, 1.02; 95% CI, 0.65-1.61; P = .92). When studies were stratified by age, primary vs secondary hemorrhage, and follow-up duration, no further significant differences in bleeding rate were identified. No evidence of publication bias was found using Begg ( P = .70) or Egger ( P = .73) tests. Conclusion. The results of this meta-analysis indicate that perioperative dexamethasone does not confer an increased risk of postoperative bleeding in patients undergoing tonsillectomy.
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Gray JE, Davis DA, Pursley DM, Smallcomb JE, Geva A, Chawla NV. Network analysis of team structure in the neonatal intensive care unit. Pediatrics 2010; 125:e1460-7. [PMID: 20457681 DOI: 10.1542/peds.2009-2621] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE The goal was to examine nursing team structure and its relationship with family satisfaction. METHODS We used electronic health records to create patient-based, 1-mode networks of nursing handoffs. In these networks, nurses were represented as nodes and handoffs as edges. For each patient, we calculated network statistics including team size and diameter, network centrality index, proportion of newcomers to care teams according to day of hospitalization, and a novel measure of the average number of shifts between repeat caregivers, which was meant to quantify nursing continuity. We assessed parental satisfaction by using a standardized survey. RESULTS Team size increased with increasing length of stay. At 2 weeks of age, 50% of shifts were staffed by a newcomer nurse who had not previously cared for the index patient. The patterns of newcomers to teams did not differ according to birth weight. When the population was dichotomized according to median mean repeat caregiver interval value, increased reports of problems with nursing care were seen with less-consistent staffing by familiar nurses. This relationship persisted after controlling for factors including birth weight, length of stay, and team size. CONCLUSIONS Family perceptions of nursing care quality are more strongly associated with team structure and the sequence of nursing participation than with team size. Objective measures of health care team structure and function can be examined by applying network analytic techniques to information contained in electronic health records.
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Gray J, Geva A, Zheng Z, Zupancic JAF. CoolSim: using industrial modeling techniques to examine the impact of selective head cooling in a model of perinatal regionalization. Pediatrics 2008; 121:28-36. [PMID: 18166554 DOI: 10.1542/peds.2007-0633] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE A selective head-cooling device for the treatment of moderate to severe hypoxic-ischemic encephalopathy has been approved by the Food and Drug Administration for use in the United States. To reflect the complexity of health care delivery at the systems level, we used the industrial modeling technique of discrete event simulation to analyze the impact of various deployment strategies for selective head cooling and its partner technology, amplitude-integrated electroencephalography. METHODS We modeled the course through the perinatal system of all births in Massachusetts over a 1-year period. Cohort and care characteristics were drawn from existing databases. Results of a recently published trial were used to estimate the effects of selective head cooling. One thousand cohort replications were conducted to assess uncertainty. Several policy alternatives were examined, including no use of selective head cooling and scenarios that altered the number and placement of selective head-cooling and amplitude-integrated electroencephalography units throughout the state. Patient-level outcome and cost data were assessed. RESULTS For all scenarios tested, the use of amplitude-integrated electroencephalography/selective head cooling resulted in better outcomes at lower cost. However, substantial differences in transfer rates, failure-to-cool rates, and total costs were seen across scenarios. Optimal decision-making regarding the number and placement of devices led to a 16% improvement in cost savings and a 10-fold decrease in failure-to-cool rates, compared with other deployment scenarios. These results were insensitive to significant changes in model inputs. CONCLUSIONS On the basis of currently available data, the package of amplitude-integrated electroencephalography and selective head cooling seems to be an economically desirable intervention. Quantifiable techniques to assess system-wide technology performance provide a powerful approach to informing decisions regarding the structure and function of health care systems.
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Geva A, McMahon CJ, Gauvreau K, Mohammed L, del Nido PJ, Geva T. Risk factors for reoperation after repair of discrete subaortic stenosis in children. J Am Coll Cardiol 2007; 50:1498-504. [PMID: 17919571 DOI: 10.1016/j.jacc.2007.07.013] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2007] [Revised: 05/30/2007] [Accepted: 07/01/2007] [Indexed: 10/22/2022]
Abstract
OBJECTIVES This study aimed to identify independent predictors of reoperation after successful resection of discrete subaortic stenosis (DSS). BACKGROUND Recurrence of DSS has been reported to range from 0% to 55% of patients. Factors associated with recurrence have not been adequately defined. METHODS Patients were included if they had a diagnosis of DSS, normal segmental cardiac anatomy, previous resection of DSS, and at least 36 months' follow-up. Demographic, surgical, and echocardiographic data were analyzed. Primary outcome was repeat resection of DSS in patients after successful primary resection. RESULTS Of 111 subjects who had successful surgical resection of DSS, 16 patients (14%) required reoperation. Median follow-up time was 8.2 years. Form of DSS and gender did not differ significantly between those with reoperation and those without. In multivariate analysis, independent predictors of reoperation that would be available before first surgery were <6 mm distance between the aortic valve (AoV) and the obstruction (hazard ratio [HR] 5.1; p = 0.013) and peak gradient by Doppler > or =60 mm Hg (HR 4.2; p = 0.016). If intraoperative variables are also considered, peeling of the membrane from the AoV or mitral valve at first surgery, <6 mm distance between the DSS and AoV, and peak gradient by Doppler > or =60 mm Hg were independent predictors of reoperation. CONCLUSIONS Proximity of the obstructive lesion to the AoV and severe obstruction determined by preoperative echocardiography, as well as involvement of valve leaflets requiring surgical peeling, predict recurrent DSS requiring reoperation.
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Geva A, Clark JJ, Zhang Y, Popowicz A, Manning JM, Neufeld EJ. Hemoglobin Jamaica plain--a sickling hemoglobin with reduced oxygen affinity. N Engl J Med 2004; 351:1532-8. [PMID: 15470216 DOI: 10.1056/nejmoa040771] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
A baby girl presented with symptomatic sickle cell disease exacerbated by mild hypoxemia, despite a newborn-screening diagnosis of sickle cell trait. DNA sequencing of the beta globin gene revealed that her maternal beta globin allele was normal. Her paternal allele had not only the expected sickle-trait mutation, betaGlu6Val, but also a second, charge-neutral mutation, betaLeu68Phe. Analysis of the patient's hemoglobin revealed that the double-mutant protein, which we called "hemoglobin Jamaica Plain," had severely reduced oxygen affinity. Structural modeling suggested destabilization of the oxy conformation as a molecular mechanism for sickling in a heterozygote at an ambient partial pressure of oxygen.
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Yao DC, Tolan DR, Murray MF, Harris DJ, Darras BT, Geva A, Neufeld EJ. Hemolytic anemia and severe rhabdomyolysis caused by compound heterozygous mutations of the gene for erythrocyte/muscle isozyme of aldolase, ALDOA(Arg303X/Cys338Tyr). Blood 2003; 103:2401-3. [PMID: 14615364 DOI: 10.1182/blood-2003-09-3160] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Aldolase (E.C. 4.1.2.13), a homotetrameric protein encoded by the ALDOA gene, converts fructose-1,6-bisphosphate to dihydroxyacetone phosphate and glyceraldehyde-3-phosphate. Three isozymes are encoded by distinct genes. The sole aldolase present in red blood cells and skeletal muscle is the A isozyme. We report here the case of a girl of Sicilian descent with aldolase A deficiency. Clinical manifestations included transfusion-dependent anemia until splenectomy at age 3 and increasing muscle weakness, with death at age 4 associated with rhabdomyolysis and hyperkalemia. Sequence analysis of the ALDOA coding regions revealed 2 novel heterozygous ALDOA mutations in conserved regions of the protein. The paternal allele encoded a nonsense mutation, Arg303X, in the enzyme-active site. The maternal allele encoded a missense mutation, Cys338Tyr, predicted to cause enzyme instability. This is the most severely affected patient reported to date and only the second with both rhabdomyolysis and hemolysis.
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Steinkamp M, Geva A, Joffe S, Lapp CN, Neufeld EJ. Chronic disseminated intravascular coagulation and childhood-onset skin necrosis resulting from homozygosity for a protein C Gla domain mutation, Arg15Trp. J Pediatr Hematol Oncol 2002; 24:685-8. [PMID: 12439046 DOI: 10.1097/00043426-200211000-00018] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
A toddler of Haitian descent presented with an 18-month history of chronic consumption coagulopathy, followed by catastrophic skin necrosis. Protein C deficiency (1% to 3% of control) was noted by functional assay; chromogenic assay and antigen levels were 30% of control. Plasma infusion abrogated the disseminated intravascular coagulation-like state. The authors identified a homozygous mutation, C1432T, resulting in a missense, Arg15Trp, in the gamma-carboxyglutamate domain of the protein. Chronic consumption coagulopathy without purpura fulminans or venous thrombosis is a rare presentation of defective protein C pathway. The result of this mutation is a mixed type I (low antigen) and type II (low function) phenotype.
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Kaplan B, Yogev Y, Sulkas J, Geva A, Nahum R, Fisher M. Attitude towards health and hormone replacement therapy among female obstetrician-gynecologists in Israel. Maturitas 2002; 43:113-6. [PMID: 12385859 DOI: 10.1016/s0378-5122(02)00187-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
OBJECTIVE To assess Israeli women gynecologists toward their own health, their health related behaviors and to assess attitude towards and the use of hormone replacement therapy (HRT). METHODS Ninety five actively employed hospital and community women gynecologist completed a questionnaire on attitude towards self-health, way of life, smoking habits, and regular breast, blood, pap smear examinations and HRT. RESULTS Mean BMI was 25.3 Kg/m(2)+/-4.2, 61% considered themselves above average weight, and only 39% estimated their weight as appropriate. Fifty six percent were on active weight-loss diets, and 35% were current smokers. Blood tests, pap smears and breast evaluations were regularly done by 73.4, 91.5, and 64.1%, respectively. Overall, 74% of the gynecologists had a positive opinion about HRT; 70% of the menopausal subgroup had ever used HRT, and 93.3% of the perimenopausal subgroup intended to use it. The main reason for starting HRT was climacteric symptoms, and for stopping or avoiding HRT were equally bleeding, fear of cancer and adverse reactions towards HRT. By far the oral HRT mode was the most popular and 90% of users expressed satisfaction with treatment. CONCLUSIONS Israeli women gynecologists are aware and maintain carefully their health, excluding cigarette smoking. The high rate of use and awareness of HRT among this group is encouraging considering that gynecologist serves as role model for the public and maintains the main source of HRT in the community.
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