Kanaka D Shetty

Mortality associated with adult congenital heart disease: Trends in the US population from 1979 to 2005

BACKGROUND Significant advances over the last 5 decades have allowed most patients with congenital heart disease to survive well past childhood and into adulthood. Population-based data from the United States are limited regarding mortality in adult survivors. METHODS We used the Center for Disease Control Multiple Cause-of-Death registry to determine trends in mortality from 1979 to 2005 among individuals with congenital heart disease in the United States. RESULTS There were significant reductions in death rates for adults with a number of congenital defects including ventricular septal defect, patent ductus arteriosus, coarctation of the aorta, and Ebstein anomaly. Notably, when all ages were analyzed, there was a 71% decline in deaths associated with transposition of the great arteries (P = .001) and a 40% reduction in deaths associated with tetralogy of Fallot (P < .001). Mortality related to other lesions declined as well. Among adults with cyanotic lesions, the primary contributing cause of death was arrhythmia followed by heart failure. For adults with noncyanotic lesions, the major contributing cause before 1990 was arrhythmia; after 1990, myocardial infarction became the leading contributing cause of death. There was an overall decrease in the incidence of arrhythmia as the cause of death in all ages, particularly among children. CONCLUSIONS Patients with congenital heart disease are living longer. Arrhythmia remains the primary contributing cause of death for those with cyanotic lesions. Myocardial infarction is now the leading contributing cause for adults with noncyanotic congenital heart disease consistent with late survival and an increasing impact of acquired heart disease.

Using information mining of the medical literature to improve drug safety.

OBJECTIVE Prescription drugs can be associated with adverse effects (AEs) that are unrecognized despite evidence in the medical literature, as shown by rofecoxibs late recall in 2004. We assessed whether applying information mining to PubMed could reveal major drug-AE associations if articles testing whether drugs cause AEs are over-represented in the literature. DESIGN MEDLINE citations published between 1949 and September 2009 were retrieved if they mentioned one of 38 drugs and one of 55 AEs. A statistical document classifier (using MeSH index terms) was constructed to remove irrelevant articles unlikely to test whether a drug caused an AE. The remaining relevant articles were analyzed using a disproportionality analysis that identified drug-AE associations (signals of disproportionate reporting) using step-up procedures developed to control the familywise type I error rate. MEASUREMENTS Sensitivity and positive predictive value (PPV) for empirical drug-AE associations as judged against drug-AE associations subject to FDA warnings. RESULTS In testing, the statistical document classifier identified relevant articles with 81% sensitivity and 87% PPV. Using data filtered by the statistical document classifier, base-case models showed 64.9% sensitivity and 42.4% PPV for detecting FDA warnings. Base-case models discovered 54% of all detected FDA warnings using literature published before warnings. For example, the rofecoxib-heart disease association was evident using literature published before 2002. Analyses incorporating literature mentioning AEs common to the drug class of interest yielded 71.4% sensitivity and 40.7% PPV. CONCLUSIONS Results from large-scale literature retrieval and analysis (literature mining) compared favorably with and could complement current drug safety methods.

Hormone replacement therapy and cardiovascular health in the United States.

Background:Hormone replacement therapy (HRT) was widely used among postmenopausal women until 2002 because observational studies suggested that HRT reduced cardiovascular risk. The Womens’ Health Initiative randomized trial reported opposite results in 2002, which caused HRT use to drop sharply. Objective:We examine the relationship between HRT use and cardiovascular outcomes (deaths and nonfatal hospitalizations) in the entire US population, which has not been studied in prior clinical trials or observational studies. Methods:We use an instrumental variables regression design to analyze the relationship between medication use, cardiovascular risk factors, and acute stroke and myocardial infarction event rates in women aged 40 to 79 years. The natural experiment of the 2002 decline in HRT usage mitigates confounding factors. We use US death records, hospital discharge data obtained from the Healthcare Cost and Utilization Projects Nationwide Inpatient Sample, and nationally representative surveys of medication usage, and behavioral risk factors. Results:Decreases in HRT use were not associated with statistically significant changes in hospitalizations or deaths due to acute stroke (0.000002, P = 0.999, 95% CI: −0.0027 to 0.0027). Decreased HRT use was associated with a decrease in the incidence of acute myocardial infarction (−0.0025 or −25 events/10,000 person-years, P = 0.021, 95% CI: −0.0047 to −0.0004). The results were similar in a sensitivity analysis using alternate data sources. Conclusions:Decreased HRT use was not associated with reduced acute stroke rate but was associated with a decreased acute myocardial infarction rate among women. Our results suggest that observational data can provide correct inferences on clinical outcomes in the overall population if a suitable natural experiment is identified.

A Pilot Study Using Machine Learning and Domain Knowledge To Facilitate Comparative Effectiveness Review Updating

Background. Comparative effectiveness and systematic reviews require frequent and time-consuming updating. Results of earlier screening should be useful in reducing the effort needed to screen relevant articles. Methods. We collected 16,707 PubMed citation classification decisions from 2 comparative effectiveness reviews: interventions to prevent fractures in low bone density (LBD) and off-label uses of atypical antipsychotic drugs (AAP). We used previously written search strategies to guide extraction of a limited number of explanatory variables pertaining to the intervention, outcome, and study design. We empirically derived statistical models (based on a sparse generalized linear model with convex penalties [GLMnet] and a gradient boosting machine [GBM]) that predicted article relevance. We evaluated model sensitivity, positive predictive value (PPV), and screening workload reductions using 11,003 PubMed citations retrieved for the LBD and AAP updates. Results. GLMnet-based models performed slightly better than GBM-based models. When attempting to maximize sensitivity for all relevant articles, GLMnet-based models achieved high sensitivities (0.99 and 1.0 for AAP and LBD, respectively) while reducing projected screening by 55.4% and 63.2%. The GLMnet-based model yielded sensitivities of 0.921 and 0.905 and PPVs of 0.185 and 0.102 when predicting articles relevant to the AAP and LBD efficacy/effectiveness analyses, respectively (using a threshold of P ≥ 0.02). GLMnet performed better when identifying adverse effect relevant articles for the AAP review (sensitivity = 0.981) than for the LBD review (0.685). The system currently requires MEDLINE-indexed articles. Conclusions. We evaluated statistical classifiers that used previous classification decisions and explanatory variables derived from MEDLINE indexing terms to predict inclusion decisions. This pilot system reduced workload associated with screening 2 simulated comparative effectiveness review updates by more than 50% with minimal loss of relevant articles.

Challenges in Assessing the Process–Outcome Link in Practice

The expanded use of clinical process-of-care measures to assess the quality of health care in the context of public reporting and pay-for-performance applications has led to a desire to demonstrate the value of such efforts in terms of improved patient outcomes. The inability to observe associations between improved delivery of clinical processes and improved clinical outcomes in practice has raised concerns about the value of holding providers accountable for delivery of clinical processes of care. Analyses that attempt to investigate this relationship are fraught with many challenges, including selection of an appropriate outcome, the proximity of the outcome to the receipt of the clinical process, limited power to detect an effect, small expected effect sizes in practice, potential bias due to unmeasured confounding factors, and difficulties due to changes in measure specification over time. To avoid potentially misleading conclusions about an observed or lack of observed association between a clinical process of care and an outcome in the context of observational studies, individuals conducting and interpreting such studies should carefully consider, evaluate, and acknowledge these types of challenges.

Economic Evaluation of Quality Improvement Interventions Designed to Improve Glycemic Control in Diabetes: A Systematic Review and Weighted Regression Analysis

OBJECTIVE Quality improvement (QI) interventions can improve glycemic control, but little is known about their value. We systematically reviewed economic evaluations of QI interventions for glycemic control among adults with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS We used English-language studies from high-income countries that evaluated organizational changes and reported program and utilization-related costs, chosen from PubMed, EconLit, Centre for Reviews and Dissemination, New York Academy of Medicines Grey Literature Report, and WorldCat (January 2004 to August 2016). We extracted data regarding intervention, study design, change in HbA1c, time horizon, perspective, incremental net cost (studies lasting ≤3 years), incremental cost-effectiveness ratio (ICER) (studies lasting ≥20 years), and study quality. Weighted least-squares regression analysis was used to estimate mean changes in HbA1c and incremental net cost. RESULTS Of 3,646 records, 46 unique studies were eligible. Across 19 randomized controlled trials (RCTs), HbA1c declined by 0.26% (95% CI 0.17–0.35) or 3 mmol/mol (2 to 4) relative to usual care. In 8 RCTs lasting ≤3 years, incremental net costs were

Machine Learning Versus Standard Techniques for Updating Searches for Systematic Reviews: A Diagnostic Accuracy Study

116 (95% CI −

Changes in Hospital Mortality Associated with Residency Work-Hour Regulations

612 to

Evaluating the feasibility and utility of translating Choosing Wisely recommendations into e-Measures.

843) per patient annually. Long-term ICERs were

Changes in U.S. Hospitalization and Mortality Rates Following Smoking Bans

100,000–