Ambient heat exposure patterns and emergency department visits and hospitalizations among medicare beneficiaries 2008-2019.

OBJECTIVE: To assess the association between ambient heat and all-cause and cause-specific emergency department (ED) visits and acute hospitalizations among Medicare beneficiaries in the conterminous United States. DESIGN: Retrospective cohort study. SETTING: Conterminous US from 2008 and 2019. PARTICIPANTS: 2% random sample of all Medicare fee-for-service beneficiaries eligible for Parts A, B, and D. MAIN OUTCOME MEASURES: All-cause and cause-specific (cardiovascular, renal, and heat-related) ED visits and unplanned hospitalizations were identified using primary ICD-9 or ICD-10 diagnosis codes. We measured the association between ambient temperature - defined as daily mean temperature percentile of summer (June through September) - and the outcomes. Hazard ratios and their associated 95% confidence intervals were estimated using multivariable Cox proportional hazards regression, adjusting for individual level demographics, comorbidities, healthcare utilization factors and zip-code level social factors. RESULTS: Among 809,636 Medicare beneficiaries (58% female, 81% non-Hispanic White, 24% <65), older beneficiaries (aged ≥65) exposed to >95th percentile temperature had a 64% elevated adjusted risk of heat-related ED visits (HR [95% CI], 1.64 [1.46,1.85]) and a 4% higher risk of all-cause acute hospitalization (1.04 [1.01,1.06]) relative to <25th temperature percentile. Younger beneficiaries (aged <65) showed increased risk of heat-related ED visits (2.69 [2.23,3.23]) and all-cause ED visits (1.03 [1.01,1.05]). The associations with heat related events were stronger in males and individuals dually eligible for Medicare and Medicaid. No significant differences were observed by climatic region. We observed no significant relationship between temperature percentile and risk of CV-related ED visits or renal-related ED visits. CONCLUSIONS: Among Medicare beneficiaries from 2008 to 2019, exposure to daily mean temperature ≥ 95th percentile was associated with increased risk of heat-related ED visits, with stronger associations seen among beneficiaries <65, males, and patients with low socioeconomic position. Further longitudinal studies are needed to understand the impact of heat duration, intensity, and frequency on cause-specific hospitalization outcomes.

Ambient Heat and Risk of Serious Hypoglycemia in Older Adults With Diabetes Using Insulin in the U.S. and Taiwan: A Cross-National Case-Crossover Study.

OBJECTIVE: To measure the association between ambient heat and hypoglycemia-related emergency department visit or hospitalization in insulin users. RESEARCH DESIGN AND METHODS: We identified cases of serious hypoglycemia among adults using insulin aged ≥65 in the U.S. (via Medicare Part A/B/D-eligible beneficiaries) and Taiwan (via National Health Insurance Database) from June to September, 2016-2019. We then estimated odds of hypoglycemia by heat index (HI) percentile categories using conditional logistic regression with a time-stratified case-crossover design. RESULTS: Among ∼2 million insulin users in the U.S. (32,461 hypoglycemia case subjects), odds ratios of hypoglycemia for HI >99th, 95-98th, 85-94th, and 75-84th percentiles compared with the 25-74th percentile were 1.38 (95% CI, 1.28-1.48), 1.14 (1.08-1.20), 1.12 (1.08-1.17), and 1.09 (1.04-1.13) respectively. Overall patterns of associations were similar for insulin users in the Taiwan sample (∼283,000 insulin users, 10,162 hypoglycemia case subjects). CONCLUSIONS: In two national samples of older insulin users, higher ambient temperature was associated with increased hypoglycemia risk.

Retrospective cohort study investigating synergism of air pollution and corticosteroid exposure in promoting cardiovascular and thromboembolic events in older adults.

OBJECTIVE: To evaluate the synergistic effects created by fine particulate matter (PM2.5) and corticosteroid use on hospitalisation and mortality in older adults at high risk for cardiovascular thromboembolic events (CTEs). DESIGN AND SETTING: A retrospective cohort study using a US nationwide administrative healthcare claims database. PARTICIPANTS: A 50% random sample of participants with high-risk conditions for CTE from the 2008-2016 Medicare Fee-for-Service population. EXPOSURES: Corticosteroid therapy and seasonal-average PM2.5. MAIN OUTCOME MEASURES: Incidences of myocardial infarction or acute coronary syndrome (MI/ACS), ischaemic stroke or transient ischaemic attack, heart failure (HF), venous thromboembolism, atrial fibrillation and all-cause mortality. We assessed additive interactions between PM2.5 and corticosteroids using estimates of the relative excess risk due to interaction (RERI) obtained using marginal structural models for causal inference. RESULTS: Among the 1 936 786 individuals in the high CTE risk cohort (mean age 76.8, 40.0% male, 87.4% white), the mean PM2.5 exposure level was 8.3±2.4 µg/m3 and 37.7% had at least one prescription for a systemic corticosteroid during follow-up. For all outcomes, we observed increases in risk associated with corticosteroid use and with increasing PM2.5 exposure. PM2.5 demonstrated a non-linear relationship with some outcomes. We also observed evidence of an interaction existing between corticosteroid use and PM2.5 for some CTEs. For an increase in PM2.5 from 8 µg/m3 to 12 µg/m3 (a policy-relevant change), the RERI of corticosteroid use and PM2.5 was significant for HF (15.6%, 95% CI 4.0%, 27.3%). Increasing PM2.5 from 5 µg/m3 to 10 µg/m3 yielded significant RERIs for incidences of HF (32.4; 95% CI 14.9%, 49.9%) and MI/ACSs (29.8%; 95% CI 5.5%, 54.0%). CONCLUSION: PM2.5 and systemic corticosteroid use were independently associated with increases in CTE hospitalisations. We also found evidence of significant additive interactions between the two exposures for HF and MI/ACSs suggesting synergy between these two exposures.

Air Pollution and Cardiovascular and Thromboembolic Events in Older Adults With High-Risk Conditions.

Little epidemiologic research has focused on pollution-related risks in medically vulnerable or marginalized groups. Using a nationwide 50% random sample of 2008-2016 Medicare Part D-eligible fee-for-service participants in the United States, we identified a cohort with high-risk conditions for cardiovascular and thromboembolic events (CTEs) and linked individuals with seasonal average zip-code-level concentrations of fine particulate matter (particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5)). We assessed the relationship between seasonal PM2.5 exposure and hospitalization for each of 7 CTE-related causes using history-adjusted marginal structural models with adjustment for individual demographic and neighborhood socioeconomic variables, as well as baseline comorbidity, health behaviors, and health-service measures. We examined effect modification across geographically and demographically defined subgroups. The cohort included 1,934,453 individuals with high-risk conditions (mean age = 77 years; 60% female, 87% White). A 1-µg/m3 increase in PM2.5 exposure was significantly associated with increased risk of 6 out of 7 types of CTE hospitalization. Strong increases were observed for transient ischemic attack (hazard ratio (HR) = 1.039, 95% confidence interval (CI): 1.034, 1.044), venous thromboembolism (HR = 1.031, 95% CI: 1.027, 1.035), and heart failure (HR = 1.019, 95% CI: 1.017, 1.020). Asian Americans were found to be particularly susceptible to thromboembolic effects of PM2.5 (venous thromboembolism: HR = 1.063, 95% CI: 1.021, 1.106), while Native Americans were most vulnerable to cerebrovascular effects (transient ischemic attack: HR = 1.093, 95% CI: 1.030, 1.161).

Validity of International Classification of Diseases (ICD)-10 Diagnosis Codes for Identification of Acute Heart Failure Hospitalization and Heart Failure with Reduced Versus Preserved Ejection Fraction in a National Medicare Sample.

BACKGROUND: Heart failure (HF) is a leading cause of hospitalization in older adults. Medicare data have been used to assess HF outcomes. However, the validity of ICD-10 diagnosis codes (used since 2015) to identify acute HF hospitalization or distinguish reduced (heart failure with reduced ejection fraction) versus preserved ejection fraction (HFpEF) is unknown in Medicare data. METHODS: Using Medicare data (2015-2017), we randomly sampled 200 HF hospitalizations with ICD-10 diagnosis codes for HF in the first/second claim position in a 1:1:2 ratio for systolic HF (I50.2), diastolic HF (I50.3), and other HF (I50.X). The primary gold standards included recorded HF diagnosis by a treating physician for HF hospitalization, ejection fraction (EF)≤50 for heart failure with reduced ejection fraction, and EF>50 for HFpEF. If the quantitative EF was not present, then qualitative descriptions of EF were used for heart failure with reduced ejection fraction/HFpEF gold standards. Multiple secondary gold standards were also tested. Gold standard data were extracted from medical records using standardized forms and adjudicated by cardiology fellows/staff. We calculated positive predictive values with 95% CIs. RESULTS: The 200-chart validation sample included 50 systolic, 50 diastolic, 47 combined dysfunction, and 53 unspecified HF patients. The positive predictive values of acute HF hospitalization was 98% [95% CI, 95-100] for first-position ICD-10 HF diagnosis and 66% [95% CI, 58-74] for first/second-position diagnosis. Quantitative EF was available for ≥80% of patients with systolic, diastolic, or combined dysfunction ICD-10 codes. The positive predictive value of systolic HF codes was 90% [95% CI, 82-98] for EFs≤50% and 72% [95% CI, 60-85] for EFs≤40%. The positive predictive value was 92% [95% CI, 85-100] for HFpEF for EFs>50%. The ICD-10 codes for combined or unspecified HF poorly predicted heart failure with reduced ejection fraction or HFpEF. CONCLUSIONS: ICD-10 principal diagnosis identified acute HF hospitalization with a high positive predictive value. Systolic and diastolic ICD-10 diagnoses reliably identified heart failure with reduced ejection fraction and HFpEF when EF 50% was used as the cutoff.

Influence of social deprivation index on in-hospital outcomes of COVID-19.

While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient's residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70-0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71-0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79-0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79-0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.