Statins, Mortality, and Major Adverse Cardiovascular Events Among US Veterans With Chronic Kidney Disease.

Importance: There are limited data for the utility of statins for primary prevention of atherosclerotic cardiovascular disease (ASCVD) and death in adults with chronic kidney disease (CKD). Objective: To evaluate the association of statin use with all-cause mortality and major adverse cardiovascular events (MACE) among US veterans older than 65 years with CKD stages 3 to 4. Design, Setting, and Participants: This cohort study used a target trial emulation design for statin initiation among veterans with moderate CKD (stages 3 or 4) using nested trials with a propensity weighting approach. Linked Veterans Affairs (VA) Healthcare System, Medicare, and Medicaid data were used. This study considered veterans newly diagnosed with moderate CKD between 2005 and 2015 in the VA, with follow-up through December 31, 2017. Veterans were older than 65 years, within 5 years of CKD diagnosis, had no prior ASCVD or statin use, and had at least 1 clinical visit in the year prior to trial baseline. Eligibility criteria were assessed for each nested trial, and Cox proportional hazards models with bootstrapping were run. Analysis was conducted from July 2021 to October 2023. Exposure: Statin initiation vs none. Main Outcomes and Measures: Primary outcome was all-cause mortality; secondary outcome was time to first MACE (myocardial infarction, transient ischemic attack, stroke, revascularization, or mortality). Results: Included in the analysis were 14 828 veterans. Mean (SD) age at CKD diagnosis was 76.9 (8.2) years, 14 616 (99%) were men, 10 539 (72%) White, and 2568 (17%) Black. After expanding to person-trials and assessing eligibility at each baseline, there were 151 243 person-trials (14 685 individuals) of nonstatin initiators and 2924 person-trials (2924 individuals) of statin initiators included. Propensity score adjustment via overlap weighting with nonparametric bootstrapping resulted in covariate balance, with mean (SD) follow-up of 3.6 (2.7) years. The hazard ratio for all-cause mortality was 0.91 (95% CI, 0.85-0.97) comparing statin initiators to noninitiators. The hazard ratio for MACE was 0.96 (95% CI, 0.91-1.02). Results remained consistent in prespecified subgroup analyses. Conclusions and Relevance: In this target trial emulation of statin initiation in US veterans older than 65 years with CKD stages 3 to 4 and no prior ASCVD, statin initiation was significantly associated with a lower risk of all-cause mortality but not MACE. Results should be confirmed in a randomized clinical trial.

Why does the adverse effect of inappropriate MRI for LBP vary by geographic location? An exploratory analysis.

BACKGROUND: Early magnetic resonance imaging (eMRI) for nonspecific low back pain (LBP) not adherent to clinical guidelines is linked with prolonged work disability. Although the prevalence of eMRI for occupational LBP varies substantially among states, it is unknown whether the risk of prolonged disability associated with eMRI varies according to individual and area-level characteristics. The aim was to explore whether the known risk of increased length of disability (LOD) associated with eMRI scanning not adherent to guidelines for occupational LBP varies according to patient and area-level characteristics, and the potential reasons for any observed variations. METHODS: A retrospective cohort of 59,360 LBP cases from 49 states, filed between 2002 and 2008, and examined LOD as the outcome. LBP cases with at least 1 day of work disability were identified by reviewing indemnity service records and medical bills using a comprehensive list of codes from the International Classification of Diseases, Ninth Edition (ICD-9) indicating LBP or nonspecific back pain, excluding medically complicated cases. RESULTS: We found significant between-state variations in the negative impact of eMRI on LOD ranging from 3.4 days in Tennessee to 14.8 days in New Hampshire. Higher negative impact of eMRI on LOD was mainly associated with female gender, state workers' compensation (WC) policy not limiting initial treating provider choice, higher state orthopedic surgeon density, and lower state MRI facility density. CONCLUSION: State WC policies regulating selection of healthcare provider and structural factors affecting quality of medical care modify the impact of eMRI not adherent to guidelines. Targeted healthcare and work disability prevention interventions may improve work disability outcomes in patients with occupational LBP.

Regional socioeconomic disparities in outcomes for workers with low back pain in the United States.

BACKGROUND: Although regional socioeconomic (SE) factors have been associated with worse health outcomes, prior studies have not addressed important confounders or work disability. METHODS: A national sample of 59 360 workers' compensation (WC) cases to evaluate impact of regional SE factors on medical costs and length of disability (LOD) in occupational low back pain (LBP). RESULTS: Lower neighborhood median household incomes (MHI) and higher state unemployment rates were associated with longer LOD. Medical costs were lower in states with more workers receiving Social Security Disability, and in areas with lower MHI, but this varied in magnitude and direction among neighborhoods. Medical costs were higher in more urban, more racially diverse, and lower education neighborhoods. CONCLUSIONS: Regional SE disparities in medical costs and LOD occur even when health insurance, health care availability, and indemnity benefits are similar. Results suggest opportunities to improve care and disability outcomes through targeted health care and disability interventions.

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NBSW=NBBI-GRAM=SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as we have done here, utilizing readily-available off-the-shelf machine learning techniques and resulting in only a fraction of narratives that require manual review. Human-machine ensemble methods are likely to improve performance over total manual coding.

The direct cost burden of 13years of disabling workplace injuries in the U.S. (1998-2010): Findings from the Liberty Mutual Workplace Safety Index.

INTRODUCTION: Although occupational injuries are among the leading causes of death and disability around the world, the burden due to occupational injuries has historically been under-recognized, obscuring the need to address a major public health problem. METHODS: We established the Liberty Mutual Workplace Safety Index (LMWSI) to provide a reliable annual metric of the leading causes of the most serious workplace injuries in the United States based on direct workers compensation (WC) costs. RESULTS: More than $600 billion in direct WC costs were spent on the most disabling compensable non-fatal injuries and illnesses in the United States from 1998 to 2010. The burden in 2010 remained similar to the burden in 1998 in real terms. The categories of overexertion ($13.6B, 2010) and fall on same level ($8.6B, 2010) were consistently ranked 1st and 2nd. PRACTICAL APPLICATION: The LMWSI was created to establish the relative burdens of events leading to work-related injury so they could be better recognized and prioritized. Such a ranking might be used to develop research goals and interventions to reduce the burden of workplace injury in the United States.

Length of Disability and Medical Costs in Low Back Pain: Do State Workers' Compensation Policies Make a Difference?

OBJECTIVE: The aim of the study was to examine the impact of state workers' compensation (WC) policies regarding wage replacement and medical benefits on medical costs and length of disability (LOD) in workers with low back pain (LBP). METHODS: Retrospective cohort analysis of LBP claims from 49 states (n = 59,360) filed between 2002 and 2008, extracted from a large WC administrative database. RESULTS: Longer retroactive periods and state WC laws allowing treating provider choice were associated with higher medical costs and longer LOD. Limiting the option to change providers and having a fee schedule were associated with longer LOD, except that allowing a one-time treating provider change was associated with lower medical costs and shorter LOD. CONCLUSIONS: WC policies about wage replacement and medical treatment appear to be associated with WC LBP outcomes, and might represent opportunities to improve LOD and reduce medical costs in occupational LBP.

A practical tool for public health surveillance: Semi-automated coding of short injury narratives from large administrative databases using Naïve Bayes algorithms.

Public health surveillance programs in the U.S. are undergoing landmark changes with the availability of electronic health records and advancements in information technology. Injury narratives gathered from hospital records, workers compensation claims or national surveys can be very useful for identifying antecedents to injury or emerging risks. However, classifying narratives manually can become prohibitive for large datasets. The purpose of this study was to develop a human-machine system that could be relatively easily tailored to routinely and accurately classify injury narratives from large administrative databases such as workers compensation. We used a semi-automated approach based on two Naïve Bayesian algorithms to classify 15,000 workers compensation narratives into two-digit Bureau of Labor Statistics (BLS) event (leading to injury) codes. Narratives were filtered out for manual review if the algorithms disagreed or made weak predictions. This approach resulted in an overall accuracy of 87%, with consistently high positive predictive values across all two-digit BLS event categories including the very small categories (e.g., exposure to noise, needle sticks). The Naïve Bayes algorithms were able to identify and accurately machine code most narratives leaving only 32% (4853) for manual review. This strategy substantially reduces the need for resources compared with manual review alone.

The burden of occupational injury: a 1-year prospective study in Xuan Tien Commune, Viet Nam.

BACKGROUND: Developing nations carry a substantial portion of the global burden of injury, but without reliable injury surveillance, there is no way to characterize or prioritize the causes of work-related injury for prevention. METHODS: Injury data from 52 treatment sites in the Xuan Tien Commune, Vietnam with over 10,000 inhabitants were collected between January 1 and December 31, 2006. Injured residents were interviewed to determine work-relatedness, relevant causes, disability, and burden. RESULTS: Five hundred four work-related injuries were reported from formal treatment sites (incidence rate of 87 per 1,000 FTE) with a mean lost work day of 11 days. Four thousand five hundred seventy-four lost work day equivalents were estimated based on actual days lost to recover plus work days lost earning income to pay for medical costs, accumulating a total direct burden to the community of 8,641 lost work day equivalents. Almost half of that burden was caused by work in manufacturing. First aid boxes placed in 40 manufacturing enterprises yielded the 2nd highest reporting source. CONCLUSION: This study demonstrated the feasibility and value at the local level to build an active injury surveillance system which could have a large impact on preventing the burden of injuries in workplaces in Vietnam.

Work-related carpal tunnel syndrome (WR-CTS) in Massachusetts, 1992-1997: source of WR-CTS, outcomes, and employer intervention practices.

BACKGROUND: The Massachusetts Sentinel Event Notification System for Occupational Risks (MASS SENSOR) receives reports of work-related carpal tunnel syndrome (WR-CTS) cases from (1) workers' compensation (WC) disability claims for 5 or more lost work days; and (2) physician reports (PR). METHODS: From 1992 through 1997, 1,330 WC cases and 571 PR cases completed follow-back surveys to provide information on industry, occupation, attributed source of WR-CTS, outcomes, and employer intervention practices. RESULTS: Sixty-four percent of the respondents had bilateral CTS and 61% had surgery, both of which were proportionally more frequent among WC cases. Office and business machinery was the leading source of WR-CTS (42% of classifiable sources) in every economic sector except construction, followed by hand tools (20%). Managers and professional specialty workers were the most likely to report employers' interventions and were up to four times more likely to report equipment or work environment changes than higher risk groups. CONCLUSIONS: State-based surveillance data on the source of WR-CTS provided valuable information on how and where to implement interventions. New occurrences of WR-CTS are likely, especially in the highest risk industries where very few cases reported primary prevention measures (e.g., changes to equipment or work environment) implemented by their employers.