Validation of Long-term Recall of Pregnancy-related Weight in the Life-course Experiences And Pregnancy Study.

BACKGROUND: Prepregnancy body mass index (BMI) and gestational weight gain (GWG) are determinants of maternal and child health. However, many studies of these factors rely on error-prone self-reported measures. METHODS: Using data from Life-course Experiences And Pregnancy (LEAP), a US-based cohort, we assessed the validity of prepregnancy BMI and GWG recalled on average 8 years postpartum against medical record data treated as alloyed gold standard ("true") values. We calculated probabilities of being classified into a self-reported prepregnancy BMI or GWG category conditional on one's true category (analogous to sensitivities and specificities) and probabilities of truly being in each prepregnancy BMI or GWG category conditional on one's self-reported category (analogous to positive and negative predictive values). RESULTS: There was a tendency toward under-reporting prepregnancy BMI. Self-report misclassified 32% (95% confidence interval [CI] = 19%, 48%) of those in LEAP with truly overweight and 13% (5%, 27%) with obesity into a lower BMI category. Self-report correctly predicted the truth for 72% (55%, 84%) with self-reported overweight to 100% (90%, 100%) with self-reported obesity. For GWG, both under- and over-reporting were common; self-report misclassified 32% (15%, 55%) with truly low GWG as having moderate GWG and 50% (28%, 72%) with truly high GWG as moderate or low GWG. Self-report correctly predicted the truth for 45% (25%, 67%) with self-reported high GWG to 85% (76%, 91%) with self-reported moderate GWG. Misclassification of BMI and GWG varied across maternal characteristics. CONCLUSION: Findings can be used in quantitative bias analyses to estimate bias-adjusted associations with prepregnancy BMI and GWG.

Food insecurity in urban American Indian and Alaska Native populations during the COVID-19 pandemic.

BACKGROUND: Food insecurity is an important social determinant of health that was exacerbated by the COVID-19 pandemic. Both food insecurity and COVID-19 infection disproportionately affect racial and ethnic minority groups, particularly American Indian and Alaska Native communities; however, there is little evidence as to whether food insecurity is associated with COVID-19 infection or COVID-19 preventive behaviors such as vaccination uptake. The purpose of this study was to evaluate associations between food insecurity, COVID-19 infection, and vaccination status among urban American Indian and Alaska Native adults seen at 5 clinics serving urban Native people. METHODS: In partnership with health organizations in Alaska, Colorado, Kansas, Minnesota, and New Mexico, the study team conducted a cross-sectional survey in 2021 to assess food security status and attitudes, barriers, and facilitators for COVID-19 testing and vaccination. Logistic regression was used to examine the association of food security status with sociodemographic factors and COVID-19 infection and vaccination status. Marginal standardization was applied to present results as prevalence differences. RESULTS: Among 730 American Indian and Alaska Native adults, the prevalence of food insecurity measured during the pandemic was 38%. For participants who reported persistent food security status before and during the pandemic (n = 588), the prevalence of food insecurity was 25%. Prevalence of COVID-19 infection and vaccination did not vary by food security status after adjustment for confounders. CONCLUSIONS: High rates of food insecurity among American Indian and Alaska Native communities likely increased during the COVID-19 pandemic. However, despite the high prevalence of food insecurity, community-led efforts to reduce COVID-19 infection and increase vaccination uptake across Indian Health Service and Tribal healthcare facilities may have mitigated the negative impacts of the pandemic for families experiencing food insecurity. These successful approaches serve as an important reference for future public health efforts that require innovative strategies to improve overall health in American Indian and Alaska Native communities.

Opioid-related Mortality in United States Death Certificate Data: A Quantitative Bias Analysis With Expert Elicitation of Bias Parameters.

BACKGROUND: Opioid-related mortality is an important public health problem in the United States. Incidence estimates rely on death certificate data generated by health care providers and medical examiners. Opioid overdoses may be underreported when other causes of death appear plausible. We applied physician-elicited death certificate bias parameters to quantitative bias analyses assessing potential age-related differential misclassification in US opioid-related mortality estimates. METHODS: We obtained cause-of-death data (US, 2017) from the National Center for Health Statistics and calculated crude opioid-related outpatient death counts by age category (25-54, 55-64, 65+). We elicited beliefs from 10 primary care physicians on sensitivity of opioid-related death classification from death certificates. We summarized elicited sensitivity estimates, calculated plausible specificity values, and applied resulting parameters in a probabilistic bias analysis. RESULTS: Physicians estimated wide sensitivity ranges for classification of opioid-related mortality by death certificates, with lower estimated sensitivities among older age groups. Probabilistic bias analyses adjusting for physician-estimated misclassification indicated 3.1 times more (95% uncertainty interval: 1.2-23.5) opioid-related deaths than the observed death count in the 65+ age group. All age groups had substantial increases in bias-adjusted death counts. CONCLUSIONS: We developed and implemented a feasible method of eliciting physician expert opinion on bias parameters for sensitivity of a medical record-based death indicator and applied findings in quantitative bias analyses adjusting for differential misclassification. Our findings are consistent with the hypothesis that opioid-related mortality rates may be substantially underestimated, particularly among older adults, due to misclassification in cause-of-death data from death certificates.

Venous thromboembolism mortality and trends in older US adults, 2011-2019.

Venous thromboembolism (VTE) affects 1.2 million people per year in the United States. With several clinical changes in diagnosis and treatment approaches in the past decade, we evaluated contemporary post-VTE mortality risk profiles and trends. Incident VTE cases were identified from the 2011-2019 Medicare 20% Sample, which is representative of nearly all Americans aged 65 and older. The social deprivation index was linked from public data; race/ethnicity and sex were self-reported. The all-cause mortality risk 30 days and 1 year after incident VTE was calculated in demographic subgroups and by prevalent cancer diagnosis status using model-based standardization. Risks for major cancer types, risk differences by age, sex, race/ethnicity, and socio-economic status (SES), and trends over time are also reported. The all-cause mortality risk among older US adults following incident VTE was 3.1% (95% CI 3.0-3.2) at 30 days and 19.6% (95% CI 19.2-20.1) at 1 year. For cancer-related VTE events, the age-sex-race-standardized risk was 6.0% at 30 days and 34.7% at 1 year. The standardized 30-day and 1-year risks were higher among non-White beneficiaries and among those with low SES. One-year mortality risk decreased 0.28 percentage points per year (95% CI 0.16-0.40) on average across the study period, with no trend observed for 30-day mortality risk. In sum, all-cause mortality risk following incident VTE has decreased slightly in the last decade, but racial and socio-economic disparities persist. Understanding patterns of mortality among demographic subgroups and in cancer-associated events is important for targeting efforts to improve VTE management.

Impact of Community Support Workers in Rural Ethiopia on Emotional and Psychosocial Health of Persons Living with HIV: Results of a Three-Year Randomized Community Trial.

People living with HIV face multiple psychosocial challenges. In a large, predominantly rural Ethiopian region, 1799 HIV patients new to care were enrolled from 32 sites in a cluster randomized trial using trained community support workers with HIV to provide individual health education, counseling and social support. Participants received annual surveys through 36 months using items drawn from the Centre for Epidemiologic Studies Depression Scale-10, Medical Outcome Study Social Support Survey, and HIV/AIDS Stigma Instrument-PLWA. At 12 months (using linear mixed effects regression models controlling for enrollment site clustering), intervention participants had greater emotional/informational and tangible assistance social support scores, and lower scores assessing depression symptoms and negative self-perception due to HIV status. A significant treatment effect at 36 months was also seen on scores assessing emotional/informational social support, depression symptoms, and internalized stigma. An intervention using peer community support workers with HIV to provide individualized informational and psychological support had a positive impact on the emotional health of people living with HIV who were new to care.(ClinicalTrials.gov protocol ID: 1410S54203, May 19, 2015).

Sampling Validation Data to Achieve a Planned Precision of the Bias-Adjusted Estimate of Effect.

Data collected from a validation substudy permit calculation of a bias-adjusted estimate of effect that is expected to equal the estimate that would have been observed had the gold standard measurement been available for the entire study population. In this paper, we develop and apply a framework for adaptive validation to determine when sufficient validation data have been collected to yield a bias-adjusted effect estimate with a prespecified level of precision. Prespecified levels of precision are decided a priori by the investigator, based on the precision of the conventional estimate and allowing for wider confidence intervals that would still be substantively meaningful. We further present an applied example of the use of this method to address exposure misclassification in a study of transmasculine/transfeminine youth and self-harm. Our method provides a novel approach to effective and efficient estimation of classification parameters as validation data accrue, with emphasis on the precision of the bias-adjusted estimate. This method can be applied within the context of any parent epidemiologic study design in which validation data will be collected and modified to meet alternative criteria given specific study or validation study objectives.

Thunderstorms, Pollen, and Severe Asthma in a Midwestern, USA, Urban Environment, 2007-2018.

BACKGROUND: Previous research has shown an association between individual thunderstorm events in the presence of high pollen, commonly called thunderstorm asthma, and acute severe asthma events, but little work has studied risk over long periods of time, using detailed measurements of storms and pollen. METHODS: We estimated change in the risk of asthma-related emergency room visits related to thunderstorm asthma events in the Minneapolis-St. Paul metropolitan area over the years 2007-2018. We defined thunderstorm asthma events as daily occurrence of two or more lightning strikes during high pollen periods interpolating weather and pollen monitor data and modeling lightning counts. We acquired daily counts of asthma-related emergency department visits from the Minnesota Hospital Association and used a quasi-Poisson time-series regression to estimate overall relative risk of emergency department visits during thunderstorm asthma events. RESULTS: We observed a 1.047 times higher risk (95% confidence interval = 1.012, 1.083) of asthma-related emergency department visits on the day of thunderstorm asthma event. Our findings are robust to adjustment for temperature, humidity, wind, precipitation, ozone, PM 2.5 , day of week, and seasonal variation in asthma cases. Occurrence of lightning alone or pollen alone showed no association with the risk of severe asthma. A two-stage analysis combining individual zip code-level results shows similar RR, and we see no evidence of spatial correlation or spatial heterogeneity of effect. DISCUSSION: Our results support an association between co-occurrence of lightning and pollen and risk of severe asthma events. Our approach incorporates lightning and pollen data and small-spatial area exposure and outcome counts.

A three-year randomized community trial of community support workers in rural Ethiopia to promote retention in HIV care.

Retention in care is a major challenge for global AIDS control, including sub-Saharan Africa. In a large Ethiopian region, we evaluated an intervention where HIV positive community support workers (CSWs) provided HIV health education, personal counseling and social support for HIV patients new to care. We enrolled 1,799 patients recently entering care from 32 hospitals and health centers, randomized to intervention or control sites. Dates of all clinic visits, plus deaths or transfers were abstracted from HIV medical records. Primary outcomes were gap in clinical care (>90 days from a missed clinical or drug pickup appointment) and death. For 36 months of follow-up, and for the first 12 months after enrollment, weighted risk differences [RD] between treatment arms were modest and non-significant for gap in clinical care, death or either outcome. Through 36 months, 624 of 980 controls and 469 of 819 intervention participants had gaps in clinical care (RD = -5.5%, 95% confidence interval [CI] = -17.9%, 7.0%); 79 controls and 82 intervention participants died (RD = 2.5% 95% CI = -1.7%, 6.8%). Factors including HIV stigma and a volatile political climate may have attenuated the advantages we anticipated, demonstrating how benefits of CSW interventions may depend upon psychosocial, clinical and structural factors particular to specific community settings.

Bias Analysis Gone Bad.

Quantitative bias analysis comprises the tools used to estimate the direction, magnitude, and uncertainty from systematic errors affecting epidemiologic research. Despite the availability of methods and tools, and guidance for good practices, few reports of epidemiologic research incorporate quantitative estimates of bias impacts. The lack of familiarity with bias analysis allows for the possibility of misuse, which is likely most often unintentional but could occasionally include intentional efforts to mislead. We identified 3 examples of suboptimal bias analysis, one for each common bias. For each, we describe the original research and its bias analysis, compare the bias analysis with good practices, and describe how the bias analysis and research findings might have been improved. We assert no motive to the suboptimal bias analysis by the original authors. Common shortcomings in the examples were lack of a clear bias model, computed example, and computing code; poor selection of the values assigned to the bias model's parameters; and little effort to understand the range of uncertainty associated with the bias. Until bias analysis becomes more common, community expectations for the presentation, explanation, and interpretation of bias analyses will remain unstable. Attention to good practices should improve quality, avoid errors, and discourage manipulation.

Neighborhood Socioeconomic Status and Identification of Patients With CKD Using Electronic Health Records.

RATIONALE & OBJECTIVE: Screening for chronic kidney disease (CKD) is recommended for patients with diabetes and hypertension as stated by the respective professional societies. However, CKD, a silent disease usually detected at later stages, is associated with low socioeconomic status (SES). We assessed whether adding census tract SES status to the standard screening approach improves our ability to identify patients with CKD. STUDY DESIGN: Screening test analysis. SETTINGS & PARTICIPANTS: Electronic health records (EHR) of 256,162 patients seen at a health care system in the 7-county Minneapolis/St. Paul area and linked census tract data. EXPOSURE: The first quartile of census tract SES (median value of owner-occupied housing units <$165,200; average household income <$35,935; percentage of residents >25 years of age with a bachelor's degree or higher <20.4%), hypertension, and diabetes. OUTCOMES: CKD (eGFR <60 mL/min/1.73 m2, or urinary albumin-creatinine ratio >30mg/g, or urinary protein-creatinine ratio >150mg/g, or urinary analysis [albuminuria] >30 mg/d). ANALYTICAL APPROACH: Sensitivity, specificity, and number needed to screen (NNS) to detect CKD if we screened patients who had hypertension and/or diabetes and/or who lived in low-SES tracts (belonging to the first quartile of any of the 3 measures of tract SES) versus the standard approach. RESULTS: CKD was prevalent in 13% of our cohort. Sensitivity, specificity, and NNS of detecting CKD after adding tract SES to the screening approach were 67% (95% CI, 66.2%-67.2%), 61% (95% CI, 61.1%-61.5%), and 5, respectively. With the standard approach, sensitivity of detecting CKD was 60% (95% CI, 59.4%-60.4%), specificity was 73% (95% CI, 72.4%-72.7%), and NNS was 4. LIMITATIONS: One health care system and selection bias. CONCLUSIONS: Leveraging patients' addresses from the EHR and adding tract-level SES to the standard screening approach modestly increases the sensitivity of detecting patients with CKD at a cost of decreased specificity. Identifying further factors that improve CKD detection at an early stage are needed to slow the progression of CKD and prevent cardiovascular complications.

The Importance of Making Assumptions in Bias Analysis.

Quantitative bias analyses allow researchers to adjust for uncontrolled confounding, given specification of certain bias parameters. When researchers are concerned about unknown confounders, plausible values for these bias parameters will be difficult to specify. Ding and VanderWeele developed bounding factor and E-value approaches that require the user to specify only some of the bias parameters. We describe the mathematical meaning of bounding factors and E-values and the plausibility of these methods in an applied context. We encourage researchers to pay particular attention to the assumption made, when using E-values, that the prevalence of the uncontrolled confounder among the exposed is 100% (or, equivalently, the prevalence of the exposure among those without the confounder is 0%). We contrast methods that attempt to bound biases or effects and alternative approaches such as quantitative bias analysis. We provide an example where failure to make this distinction led to erroneous statements. If the primary concern in an analysis is with known but unmeasured potential confounders, then E-values are not needed and may be misleading. In cases where the concern is with unknown confounders, the E-value assumption of an extreme possible prevalence of the confounder limits its practical utility.

Disclosure of HIV status among patients new to HIV care in Southern Ethiopia: role of perceived social support and other factors.

Reports from Sub-Saharan Africa, with a large HIV-infected population, vary widely in how often HIV status is disclosed to others, including spouses and other partners. We surveyed 1799 Ethiopian HIV patients newly enrolled in care within the previous 3 months at one of 32 local hospitals and health centers about disclosure of HIV status and two perceived social support domains: emotional/informational (EI) and tangible assistance (TA) support. Disclosure to another person was reported by 1389 (77%) persons. Disclosure rates to specific persons were: spouses or other partners = 74%; mothers = 24%; fathers = 16%; children = 26%; other family members = 37%; friends = 19%, and neighbors/other community members = 13%. Disclosure to another person was associated with higher social support scores on both EI and TA domains, marriage, and a longer time knowing HIV status. In multivariate adjusted models, disclosure to any person, as well as disclosure specifically to a spouse or partner, were associated with higher EI and higher TA social support scores. Provision of knowledgeable and emotionally supportive assistance can be an important factor in facilitating HIV disclosure. Helping persons with HIV decide who to disclose to and how to do so in the most positive manner is an essential component of HIV care and support.

Sex differences in treatment strategy and adverse outcomes among patients 75 and older with atrial fibrillation in the MarketScan database.

BACKGROUND: Women with atrial fibrillation (AF) experience greater symptomatology, worse quality of life, and have a higher risk of stroke as compared to men, but are less likely to receive rhythm control treatment. Whether these differences exist in elderly patients with AF, and whether sex modifies the effectiveness of rhythm versus rate control therapy has not been assessed. METHODS: We studied 135,850 men and 139,767 women aged ≥ 75 years diagnosed with AF in the MarketScan Medicare database between 2007 and 2015. Anticoagulant use was defined as use of warfarin or a direct oral anticoagulant. Rate control was defined as use of rate control medication or atrioventricular node ablation. Rhythm control was defined by use of anti-arrhythmic medication, catheter ablation or cardioversion. We used multivariable Poisson and Cox regression models to estimate the association of sex with treatment strategy and to determine whether the association of treatment strategy with adverse outcomes (bleeding, heart failure and stroke) differed by sex. RESULTS: At the time of AF, women were on average (SD) 83.8 (5.6) years old and men 82.5 (5.2) years, respectively. Compared to men, women were less likely to receive an anticoagulant or rhythm control treatment. Rhythm control (vs. rate) was associated with a greater risk for heart failure with a significantly stronger association in women (HR women = 1.41, 95% CI 1.34-1.49; HR men = 1.21, 95% CI 1.15-1.28, p < 0.0001 for interaction). No sex differences were observed for the association of treatment strategy with the risk of bleeding or stroke. CONCLUSION: Sex differences exist in the treatment of AF among patients aged 75 years and older. Women are less likely to receive an anticoagulant and rhythm control treatment. Women were also at a greater risk of experiencing heart failure as compared to men, when treated with rhythm control strategies for AF. Efforts are needed to enhance use AF therapies among women. Future studies will need to delve into the mechanisms underlying these differences.

Weight change over 9 years and subsequent risk of venous thromboembolism in the ARIC cohort.

BACKGROUND/OBJECTIVES: Weight gain increases risk of cardiovascular disease, but has not been examined extensively in relationship to venous thromboembolism (VTE). The association between weight change over 9 years and subsequent VTE among participants in the Atherosclerosis Risk in Communities (ARIC) study was examined, with a hypothesis that excess weight gain is a risk factor for VTE, relative to no weight change. SUBJECTS/METHODS: Quintiles of 9-year weight change were calculated (visit 4 1996-1998 weight minus visit 1 1987-1989 weight in kg: Quintile 1: ≥-1.81 kg; Quintile 2: <-1.81 to ≤1.36 kg; Quintile 3: >1.36 to ≤4.08 kg; Quintile 4: >4.08 to ≤7.71 kg; Quintile 5: >7.71 kg). Incident VTEs from visit 4 (1996-1998) through 2015 were identified and adjudicated using medical records. Hazard ratios (HRs) were calculated using Cox models. RESULTS: 529 incident VTEs were identified during an average of 19 years of follow up. Compared to Quintile 2, participants in Quintile 5 of weight change had 1.46 times the rate of incident VTE (HR = 1.46 (95% CI 1.09, 1.95), adjusted for age, race, sex, income, physical activity, smoking, and prevalent CVD). The HR for Quintile 5 was modestly attenuated to 1.38 (95% CI 1.03, 1.84) when visit 1 BMI was included in the model. When examined separately, results were significant for unprovoked VTE, but not for provoked VTE. Among those obese at visit 1, both weight gain (HR 1.86 95% CI 1.27, 2.71) and weight loss (HR 2.11 95% CI 1.39, 3.19) were associated with incident VTE, compared with normal-weight participants with no weight change. CONCLUSIONS: Weight gain later life was associated with increased risk for unprovoked VTE. Among those with obesity, both weight gain and weight loss were associated with increased risk for VTE.

Adaptive Validation Design: A Bayesian Approach to Validation Substudy Design With Prospective Data Collection.

An internal validation substudy compares an imperfect measurement of a variable with a gold-standard measurement in a subset of the study population. Validation data permit calculation of a bias-adjusted estimate, which has the same expected value as the association that would have been observed had the gold-standard measurement been available for the entire study population. Existing guidance on optimal sampling for validation substudies assumes complete enrollment and follow-up of the target cohort. No guidance exists for validation substudy design while cohort data are actively being collected. In this article, we use the framework of Bayesian monitoring methods to develop an adaptive approach to validation study design. This method monitors whether sufficient validation data have been collected to meet predefined criteria for estimation of the positive and negative predictive values. We demonstrate the utility of this method using the Study of Transition, Outcomes and Gender-a cohort study of transgender and gender nonconforming people. We demonstrate the method's ability to determine efficacy (when sufficient validation data have accumulated to obtain estimates of the predictive values that fall above a threshold value) and futility (when sufficient validation data have accumulated to conclude the mismeasured variable is an untenable substitute for the gold-standard measurement). This proposed method can be applied within the context of any parent epidemiologic study design and modified to meet alternative criteria given specific study or validation study objectives. Our method provides a novel approach to effective and efficient estimation of classification parameters as validation data accrue.

Complementary, Integrative, and Nondrug Therapy Use for Pain Among US Military Veterans on Long-term Opioids.

BACKGROUND: Long-term opioid therapy for chronic pain arose amid limited availability and awareness of other pain therapies. Although many complementary and integrative health (CIH) and nondrug therapies are effective for chronic pain, little is known about CIH/nondrug therapy use patterns among people prescribed opioid analgesics. OBJECTIVE: The objective of this study was to estimate patterns and predictors of self-reported CIH/nondrug therapy use for chronic pain within a representative national sample of US military veterans prescribed long-term opioids for chronic pain. RESEARCH DESIGN: National two-stage stratified random sample survey combined with electronic medical record data. Data were analyzed using logistic regressions and latent class analysis. SUBJECTS: US military veterans in Veterans Affairs (VA) primary care who received ≥6 months of opioid analgesics. MEASURES: Self-reported use of each of 10 CIH/nondrug therapies to treat or cope with chronic pain in the past year: meditation/mindfulness, relaxation, psychotherapy, yoga, t'ai chi, aerobic exercise, stretching/strengthening, acupuncture, chiropractic, massage; Brief Pain Inventory-Interference (BPI-I) scale as a measure of pain-related function. RESULTS: In total, 8891 (65%) of 13,660 invitees completed the questionnaire. Eighty percent of veterans reported past-year use of at least 1 nondrug therapy for pain. Younger age and female sex were associated with the use of most nondrug therapies. Higher pain interference was associated with lower use of exercise/movement therapies. Nondrug therapy use patterns reflected functional categories (psychological/behavioral, exercise/movement, manual). CONCLUSIONS: Use of CIH/nondrug therapies for pain was common among patients receiving long-term opioids. Future analyses will examine nondrug therapy use in relation to pain and quality of life outcomes over time.

Impact of oral anticoagulation choice on healthcare utilization for the primary treatment of venous thromboembolism.

Little is known about the impact of oral anticoagulation (OAC) choice on healthcare encounters during venous thromboembolism (VTE) primary treatment. Among anticoagulant-naïve patients with VTE, we tested the hypotheses that healthcare utilization would be lower among users of direct OACs (DOACs; rivaroxaban or apixaban) than among users of warfarin. MarketScan databases for years 2016 and 2017 were used; healthcare utilization was identified in the first 6 months after initial VTE diagnoses. The 23,864 patients with VTE had on average 0.2 ± 0.5 hospitalizations, spent 1.3 ± 5.2 days in the hospital, had 5.7 ± 5.1 outpatient encounters, and visited an emergency department 0.4 ± 1.1 times. As compared to warfarin, rivaroxaban and apixaban were associated with fewer hospitalizations, days hospitalized, outpatient office visits, and emergency department visits after accounting for age, sex, comorbidities, and medications. Hospitalization rates were 24% lower (incidence rate ratio (IRR): 0.76; 95% CI: 0.69, 0.83) with rivaroxaban and 22% lower (IRR: 0.78; 95% CI: 0.71, 0.87) with apixaban, as compared to warfarin (IRR: 1.00 (reference)). Healthcare utilization was similar between apixaban and rivaroxaban users. Patients with VTE prescribed rivaroxaban and apixaban had lower healthcare utilization than those prescribed warfarin, while there was no difference when comparing apixaban to rivaroxaban. These findings complement existing literature supporting the use of DOACs over warfarin.

The impact of different approaches to exposure assessment on understanding non-malignant respiratory disease risk in taconite miners.

INTRODUCTION: We examined the association between cumulative silica exposures in taconite mining and non-malignant respiratory disease (NMRD) using a comprehensive assessment of current and historical exposure measurements in a cross-sectional study of Minnesota taconite mining workers. We also explored the impact of exposure measurement methods by comparing estimated exposure risk from two different exposure measurement modeling approaches. METHODS: Miners were screened with an occupational and medical history questionnaire, spirometry testing and chest x-rays per ILO guidelines. Current and historical occupational exposure assessments were obtained, the former measuring about 679 personal samples over the period of the study for respirable dusts, including silica, in 28 major job functions. Cumulative silica exposure ((mg/m3) × years) was estimated as a cumulative product of time worked and year-specific silica job exposure concentrations. Chest x-ray abnormalities were based on B-reader agreement with a third B-reader for arbitration. Forced vital capacity (FVC) less than lower limits of normal for age, height, race and gender was used to determine spirometric restrictive ventilatory defect (RVD). Prevalence ratios (PR) of exposure-outcome associations, with 95% confidence intervals (CI), were estimated using multivariate Poisson regression. RESULTS: Cumulative silica exposure was associated with RVD prevalence (PR = 1.41, 95% CI = 1.09-1.81) and prevalence of parenchymal abnormalities on chest x-ray (PR = 1.30, 95% CI = 1.00-1.69) using exposure estimates based primarily on current study measurements, and assuming unchanged historical exposure trend. Conversely, when exposures were defined incorporating available actual historical values, no associations were observed between silica exposure and either RVD (PR = 0.76, 95% CI = 0.41-1.40) or parenchymal (PR = 0.87, 95% CI = 0.45-1.70) outcomes. CONCLUSIONS: This study demonstrated that the estimated association between silica dust exposure and lung disease is highly sensitive to the approach used to estimate cumulative exposure. Cumulative values based on conservative estimates of past exposure, modeled from recently measured respirable silica, showed an association with restriction RVD on spirometry. Silica exposure was also significantly associated with increased parenchymal findings on chest x-ray using this approach. Conversely, these findings were absent when actual available historical data was used to estimate cumulative silica exposure. These differences highlight the challenges with estimating occupational dust exposure, the potential impact on calculated exposure risk and the need for long term quality exposure data gathering in industries prone to risk from inhaled respirable dusts.

CHA2DS2-VASc Score and Stroke Prediction in Atrial Fibrillation in Whites, Blacks, and Hispanics.

Background and Purpose- Despite modest predictive ability for ischemic stroke (IS), the CHA2DS2-VASc score is widely used for stroke prediction in atrial fibrillation. Among patients with atrial fibrillation, we aimed to (1) compare the IS or transient ischemic attack (TIA) incidence by CHA2DS2-VASc in blacks and Hispanics versus whites; (2) compare predictive ability of CHA2DS2-VASc score for IS or TIA in blacks and Hispanics versus whites; and (3) determine improvement in predictive ability of CHA2DS2-VASc score from addition of race/ethnicity. Methods- Using data from Optum Clinformatics, a large administrative claims database, we analyzed patients with atrial fibrillation enrolled in commercial and Medicare Advantage health plans from 2009 to 2015. We computed IS or TIA incidence rates, improvement in C statistic, continuous and categorical net reclassification improvement, and relative integrated discrimination improvement from addition of race/ethnicity to CHA2DS2-VASc. Results- A total of 267 419 patients (mean age, 73.1 [SD, 12.3] years; 46.6% women; 84.2% white, 8.5% black, 7.3% Hispanic) were studied. After a mean follow-up of 22 months, there were 6202 IS or TIA events. IS or TIA incidence rates were higher in blacks than Hispanics or whites (1.65, 1.40, and 1.22 cases per 100 person-years, respectively) and increased with higher CHA2DS2-VASc, with no race/ethnicity-based differences (P for interaction=0.17). The CHA2DS2-VASc and CHA2DS2-VASc+race/ethnicity C statistic (95% CI) were 0.679 (0.670-0.686) and 0.679 (0.671-0.688). The CHA2DS2-VASc C statistic in the 3 groups were comparable. With addition of race/ethnicity, the categorical net reclassification improvement, continuous net reclassification improvement, and relative integrated discrimination improvement were -0.045 (95% CI, -0.067 to -0.025), 0.045 (95% CI, 0.025-0.068), and 0.016 (95% CI, 0.014-0.018). Conclusions- The predictive ability of CHA2DS2-VASc for IS or TIA in atrial fibrillation is comparable among whites, blacks, and Hispanics; hence, it can be used in the latter 2 groups. Addition of race/ethnicity to the CHA2DS2-VASc does not improve its predictive ability.