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Much of the data on BMI-mortality associations stem from 20th century U.S. cohorts. The purpose of this study was to determine the association between BMI and mortality in a contemporary, nationally representative, 21st century, U.S. adult population. This was a retrospective cohort study of U.S. adults from the 1999-2018 National Health Interview Study (NHIS), linked to the National Death Index (NDI) through December 31st, 2019. BMI was calculated using self-reported height & weight and categorized into 9 groups. We estimated risk of all-cause mortality using multivariable Cox proportional hazards regression, adjusting for covariates, accounting for the survey design, and performing subgroup analyses to reduce analytic bias. The study sample included 554,332 adults (mean age 46 years [SD 15], 50% female, 69% non-Hispanic White). Over a median follow-up of 9 years (IQR 5-14) and maximum follow-up of 20 years, there were 75,807 deaths. The risk of all-cause mortality was similar across a wide range of BMI categories: compared to BMI of 22.5-24.9 kg/m2, the adjusted HR was 0.95 [95% CI 0.92, 0.98] for BMI of 25.0-27.4 and 0.93 [0.90, 0.96] for BMI of 27.5-29.9. These results persisted after restriction to healthy never-smokers and exclusion of subjects who died within the first two years of follow-up. A 21-108% increased mortality risk was seen for BMI ≥30. Older adults showed no significant increase in mortality between BMI of 22.5 and 34.9, while in younger adults this lack of increase was limited to the BMI range of 22.5 to 27.4. The risk of all-cause mortality was elevated by 21-108% among participants with BMI ≥30. BMI may not necessarily increase mortality independently of other risk factors in adults, especially older adults, with overweight BMI. Further studies incorporating weight history, body composition, and morbidity outcomes are needed to fully characterize BMI-mortality associations.

To describe inpatient and outpatient cardiac rehabilitation (CR) utilization patterns over time and by subgroups among patients admitted for acute heart failure (AHF) in Japan. Cardiac rehabilitation (CR) is a crucial secondary prevention strategy for patients with heart failure. While the number of older patients with AHF continues to rise, trends in inpatient and outpatient CR participation following AHF in Japan have not been described to date. We conducted a retrospective cohort study of adult patients hospitalized for AHF in Japan between April 2008 and December 2020. Using data from the Medical Data Vision database, we measured trends in inpatient and outpatient CR participation following AHF. Descriptive analyses and summary statistics for AHF patients by CR participation status were reported. The analytic cohort included 88,052 patients. Among these patients, 37,810 (42.9%) participated in inpatient and/or outpatient CR. Of those, 36,431 (96.4%) participated in inpatient CR only and 1,277 (3.4%) participated in both inpatient and outpatient CR. Rates of inpatient CR rose more than 6-fold over the study period, from 9% in 2009 to 55% in 2020, whereas rates of outpatient CR were consistently low. The rate of inpatient CR participation among AHF patients in Japan rose dramatically over a 12-year period, whereas outpatient CR following AHF was vastly underutilized. Further study is needed to assess the clinical effectiveness of inpatient CR and to create infrastructure and incentives to support and encourage outpatient CR.

United States South Asians constitute a fast-growing ethnic group with high prevalence of type 2 diabetes (T2D) despite lower mean BMI and other traditional risk factors compared to other races/ethnicities. Bilirubin has gained attention as a potential antioxidant, cardio-protective marker. Hence we sought to determine whether total bilirubin was associated with prevalent and incident T2D in U.S. South Asians. We conducted a cross-sectional and prospective analysis of the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study. Total bilirubin was categorized into gender-specific quartiles (Men: <0.6, 0.6, 0.7-0.8, >0.8; Women: <0.5, 0.5, 0.6, >0.6 mg/dl). We estimated odds of type 2 diabetes as well as other cardiovascular (CV) risk factors using multivariable logistic regression. Among a total 1,149 participants (48% female, mean [SD] age of 57 [9] years), 38% had metabolic syndrome and 24% had T2D. Men and women in the lowest bilirubin quartile had 0.55% and 0.17% higher HbA1c than the highest quartile. Men, but not women, in the lowest bilirubin quartile had higher odds of T2D compared to the highest quartile (aOR [95% CI]; Men: 3.00 [1.72,5.23], Women: 1.15 [0.57,2.31]). There was no association between bilirubin and other CV risk factors. Total bilirubin was inversely associated with T2D in SA men but not women. Longitudinal studies are needed to understand temporality of association.

Heatwaves kill more people than floods, tornadoes, and earthquakes combined and disproportionally affect older persons and those with chronic conditions. Commonly used medications for chronic conditions, e.g., diuretics, antipsychotics disrupt thermoregulation or fluid/electrolyte balance and may sensitive patients to heat. However, the effect of heat-sensitizing medications and their interactions with heatwaves are not well-quantified. We evaluated effects of potentially heat-sensitizing medications in vulnerable older patients. US Medicare data were linked at the zip code level to climate data with surface air temperatures for June-August of 2007-2012. Patients were Medicare beneficiaries aged ≥65 years with chronic conditions including diabetes, dementia, and cardiovascular, lung, or kidney disease. Exposures were potentially heat-sensitizing medications including diuretics, anticholinergics, antipsychotics, beta blockers, stimulants, and anti-hypertensives. A heatwave was defined as ≥2 days above the 95th percentile of historical zip code-specific surface air temperatures. We estimated associations of heat-sensitizing medications and heatwaves with heat-related hospitalization using self-controlled case series analysis. We identified 9,721 patients with at least one chronic condition and heat-related hospitalization; 42.1% of these patients experienced a heatwave. Heatwaves were associated with an increase in heat-related hospitalizations ranging from 21% (95% CI: 7% to 38%) to 33% (95% CI: 14% to 55%) across medication classes. Several drug classes were associated with moderately elevated risk of heat-related hospitalization in the absence of heatwaves, with rate ratios ranging from 1.16 (95% CI: 1.00 to 1.35) to 1.37 (95% CI: 1.14 to 1.66). We did not observe meaningful synergistic interactions between heatwaves and medications. Older patients with chronic conditions may be at heightened risk for heat-related hospitalization due to the use of heat-sensitizing medications throughout the summer months, even in the absence of heatwaves. Further studies are needed to confirm these findings and also to understand the effect of milder and shorter heat exposure.

In this study of nationwide Medicaid data, there was no significant increase in the risk of any congenital cardiac defect associated with the use of selective serotonin-reuptake inhibitors or other antidepressants, after adjustment for depression and other confounders. Clinical depression occurs in 10 to 15% of pregnant women. 1 The use of antidepressant medications during pregnancy has increased steadily over time, with reported prevalences of 8 to 13% in the United States. 2 – 4 Selective serotonin-reuptake inhibitors (SSRIs) are the most commonly prescribed antidepressants during pregnancy. 4 In 2005, on the basis of early results of two epidemiologic studies, the Food and Drug Administration (FDA) warned health care professionals that early prenatal exposure to paroxetine may increase the risk of congenital cardiac malformations, and the FDA reclassified the drug to pregnancy category D (evidence of human fetal risk, but benefits may . . .

Identification of patients at high risk of death is critical for appropriate management of patients and health care resources. The impact of repeated heart failure (HF) hospitalization on mortality has not been studied for a large community population with HF. We aimed to characterize survival of patients in relation to the number of HF hospitalizations. Using the health care utilization databases, we identified a cohort of patients with a first hospitalization for HF among all residents of British Columbia between 2000 and 2004. Survival time was measured after patients' first and each subsequent HF hospitalization. Kaplan-Meier cumulative mortality curves were constructed after each subsequent HF hospitalization. Hazard ratios for the number of HF hospitalizations were estimated using a multivariate Cox regression adjusting for major comorbidities. Of 14 374 patients hospitalized for HF, 7401 died during the 24 766 person-years of follow-up. Mortality significantly increased after each HF hospitalization. After adjusting for age, sex, and major comorbidities, the number of HF hospitalizations was a strong predictor of all-cause death. Median survival after the first, second, third, and fourth hospitalization was 2.4, 1.4, 1.0, and 0.6 years. Advanced age, renal disease, and history of cardiac arrest attenuated the impact of the number of HF hospitalizations. The number of HF hospitalizations is a strong predictor of mortality in community HF patients. This simple predictor of mortality in HF patients should help triage management and resources for HF and trigger patient planning for prognosis.

Background In Japan, several large healthcare databases have become available for research since the early 2000’s. However, validation studies to examine the accuracy of these databases remain scarce. We conducted a validation study in order to estimate the positive predictive value (PPV) of local or ICD-10 codes for acute myocardial infarction (AMI) in Japanese claims. In particular, we examined whether the PPV differs between claims in the Diagnosis Procedure Combination case mix scheme (DPC claims) and in non-DPC claims. Methods We selected a random sample of 200 patients from all patients hospitalized at a large tertiary-care university hospital between January 1, 2009 and December 31, 2011 who had an inpatient claim assigned a local or ICD-10 code for AMI. We used a standardized data abstraction form to collect the relevant information from an electronic medical records system. Abstracted information was then categorized by a single cardiologist as being either definite or not having AMI. Results In a random sample of 200 patients, the average age was 67.7 years and the proportion of males was 78.0%. The PPV of the local or ICD-10 code for AMI was 82.5% in this sample of 200 patients. Further, of 178 patients who had an ICD-10 code for AMI based on any of the 7 types of condition codes in the DPC claims, the PPV was 89.3%, whereas of the 161 patients who had an ICD-10 code for AMI based on any of 3 major types of condition codes in the DPC claims, the PPV was 93.8%. Conclusion The PPV of the local or ICD-10 code for AMI was high for inpatient claims in Japan. The PPV was even higher for the ICD-10 code for AMI for those patients who received AMI care through the DPC case mix scheme. The current study was conducted in a single center, suggesting that a multi-center study involving different types of hospitals is needed in the future. The accuracy of condition codes for DPC claims in Japan may also be worth examining for conditions other than AMI such as stroke.

In the absence of clinical trial data, large post-marketing observational studies are essential to evaluate the safety and effectiveness of medications during pregnancy. We identified a cohort of pregnancies ending in live birth within the 2000-2007 Medicaid Analytic eXtract (MAX). Herein, we provide a blueprint to guide investigators who wish to create similar cohorts from healthcare utilization data and we describe the limitations in detail. Among females ages 12-55, we identified pregnancies using delivery-related codes from healthcare utilization claims. We linked women with pregnancies to their offspring by state, Medicaid Case Number (family identifier) and delivery/birth dates. Then we removed inaccurate linkages and duplicate records and implemented cohort eligibility criteria (i.e., continuous and appropriate enrollment type, no private insurance, no restricted benefits) for claim information completeness. From 13,460,273 deliveries and 22,408,810 child observations, 6,107,572 pregnancies ending in live birth were available after linkage, cleaning, and removal of duplicate records. The percentage of linked deliveries varied greatly by state, from 0 to 96%. The cohort size was reduced to 1,248,875 pregnancies after requiring maternal eligibility criteria throughout pregnancy and to 1,173,280 pregnancies after further applying infant eligibility criteria. Ninety-one percent of women were dispensed at least one medication during pregnancy. Mother-infant linkage is feasible and yields a large pregnancy cohort, although the size decreases with increasing eligibility requirements. MAX is a useful resource for studying medications in pregnancy and a spectrum of maternal and infant outcomes within the indigent population of women and their infants enrolled in Medicaid. It may also be used to study maternal characteristics, the impact of Medicaid policy, and healthcare utilization during pregnancy. However, careful attention to the limitations of these data is necessary to reduce biases.

Background No study has compared the cardiovascular outcomes for sodium–glucose cotransporter-2 inhibitors (SGLT2i) head-to-head against other glucose-lowering therapies, including dipeptidyl peptidase 4 inhibitor (DDP4i) or glucagon-like peptide-1 receptor agonist (GLP-1RA)—which also have cardiovascular benefits—in patients with heart failure with reduced (HFrEF) or preserved (HFpEF) ejection fraction. Methods Medicare fee-for-service data (2013–2019) were used to create four pair-wise comparison cohorts of type 2 diabetes patients with: (1a) HFrEF initiating SGLT2i versus DPP4i; (1b) HFrEF initiating SGLT2i versus GLP-1RA; (2a) HFpEF initiating SGLT2i versus DPP4i; and (2b) HFpEF initiating SGLT2i versus GLP-1RA. The primary outcomes were (1) hospitalization for heart failure (HHF) and (2) myocardial infarction (MI) or stroke hospitalizations. Adjusted hazards ratios (HR) and 95% CIs were estimated using inverse probability of treatment weighting. Results Among HFrEF patients, initiation of SGLT2i versus DPP4i (cohort 1a; n = 13,882) was associated with a lower risk of HHF (adjusted Hazard Ratio [HR (95% confidence interval)], 0.67 (0.63, 0.72) and MI or stroke (HR: 0.86 [0.75, 0.99]), and initiation of SGLT2i versus GLP-1RA (cohort 1b; n = 6951) was associated with lower risk of HHF (HR: 0.86 [0.79, 0.93]), but not MI or stroke (HR: 1.02 [0.85, 1.22]). Among HFpEF patients, initiation of SGLT2i versus DPP4i (cohort 2a; n = 17,493) was associated with lower risk of HHF (HR: 0.65 [0.61, 0.69]) but not MI or stroke (HR: 0.90 [0.79, 1.02]), and initiation of SGLT2i versus GLP-1RA (cohort 2b; n = 9053) was associated with lower risk of HHF (0.89 [0.83, 0.96]), but not MI or stroke (HR: 0.97 [0.83, 1.14]). Results were robust across range of secondary outcomes (e.g., all-cause mortality) and sensitivity analyses. Conclusions Bias from residual confounding cannot be ruled out. Use of SGLT2i was associated with reduced risk of HHF against DPP4i and GLP-1RA, reduced risk of MI or stroke against DPP4i within the HFrEF subgroup, and comparable risk of MI or stroke against GLP-1RA. Notably, the magnitude of cardiovascular benefit conferred by SGLT2i was similar among patients with HFrEF and HFpEF.

Linkage of medical databases, including insurer claims and electronic health records (EHRs), is increasingly common. However, few studies have investigated the behavior and output of linkage software. To determine how linkage quality is affected by different algorithms, blocking variables, methods for string matching and weight determination, and decision rules, we compared the performance of 4 nonproprietary linkage software packages linking patient identifiers from noninteroperable inpatient and outpatient EHRs. We linked datasets using first and last name, gender, and date of birth (DOB). We evaluated DOB and year of birth (YOB) as blocking variables and used exact and inexact matching methods. We compared the weights assigned to record pairs and evaluated how matching weights corresponded to a gold standard, medical record number. Deduplicated datasets contained 69,523 inpatient and 176,154 outpatient records, respectively. Linkage runs blocking on DOB produced weights ranging in number from 8 for exact matching to 64,273 for inexact matching. Linkage runs blocking on YOB produced 8 to 916,806 weights. Exact matching matched record pairs with identical test characteristics (sensitivity 90.48%, specificity 99.78%) for the highest ranked group, but algorithms differentially prioritized certain variables. Inexact matching behaved more variably, leading to dramatic differences in sensitivity (range 0.04-93.36%) and positive predictive value (PPV) (range 86.67-97.35%), even for the most highly ranked record pairs. Blocking on DOB led to higher PPV of highly ranked record pairs. An ensemble approach based on averaging scaled matching weights led to modestly improved accuracy. In summary, we found few differences in the rankings of record pairs with the highest matching weights across 4 linkage packages. Performance was more consistent for exact string matching than for inexact string matching. Most methods and software packages performed similarly when comparing matching accuracy with the gold standard. In some settings, an ensemble matching approach may outperform individual linkage algorithms.