Venous thromboembolism mortality and trends in older US adults, 2011-2019.
Katherine GiorgioRob F WalkerRichard F MacLehoseDiego Adrianzen HerreraWendy WangAlvaro AlonsoNeil A ZakaiPamela L LutseyPublished in: American journal of hematology (2023)
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.
Keyphrases
- venous thromboembolism
- direct oral anticoagulants
- cardiovascular disease
- healthcare
- papillary thyroid
- physical activity
- cardiovascular events
- mental health
- risk factors
- squamous cell
- machine learning
- middle aged
- electronic health record
- cross sectional
- coronary artery disease
- risk assessment
- human health
- deep learning
- atrial fibrillation
- adverse drug
- affordable care act
- data analysis