ArticleScientific data2026
CardioEHR: A longitudinal electronic health record dataset of cardiovascular patients from central China.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
We present a longitudinal electronic health record (EHR) dataset from Wuhan Union Hospital, compiled from two distinct hospital information systems. The first dataset, derived from a legacy system, includes 35,243 patients and covers the period from 2010 to 2020. The second dataset, collected via the research-oriented YIDUYUN system, includes 37,975 patients and spans from 2011 to 2024. Both datasets provide structured and de-identified clinical information, including medical record number, demographics, diagnoses, admissions, discharges, timestamps record, laboratory test results (including COVID-19 test records) and patients' residential region. Using the patients' residential regions, we combined the data with information from the China Statistical Yearbook to collect regional socioeconomic indices. While not specifically designed for pandemic research, the dataset captures both pre-pandemic and post-pandemic periods with de-identified exact timestamps, making it suitable for analyzing long-term healthcare utilization, population behavior, and policy impacts. With comprehensive metadata and rigorous validation, this resource supports a wide range of applications in longitudinal health system research and data-driven modeling.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.