ArticleJournal of clinical hypertension (Greenwich, Conn.)2024
Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.
Article in Journal of clinical hypertension (Greenwich, Conn.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Review
- Article
- Characterizing apparent treatment resistant hypertension in the United States: insights from the All of Us Research Program.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.Journal of clinical hypertension (Greenwich, Conn.) · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment with three antihypertensives, is associated with an increased risk of developing cardiovascular and renal complications compared with controlled hypertension. We aimed to identify the characteristics of aTRH patients with an elevated risk of major adverse cardiovascular events plus (MACE+; defined as stroke, myocardial infarction, or heart failure hospitalization) and end stage renal disease (ESRD). This retrospective cohort study included aTRH patients (BP ≥140/90 mmHg and taking ≥3 antihypertensives) from the United States-based Optum
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