ArticleIrish journal of medical science2022
An assessment of race and gender-based biases among readmission predicting tools (HOSPITAL, LACE, and RAHF) in heart failure population.
Article in Irish journal of medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Heart Failure Readmission Prevention Strategies-A Comparative Review of Medications, Devices, and Other Interventions.Journal of clinical medicine · 2025Review
- The role of continuous monitoring in acute-care settings for predicting all-cause 30-day hospital readmission: A pilot study.Heliyon · 2025Article
- Predicting 1 year readmission for heart failure: A comparative study of machine learning and the LACE index.ESC heart failure · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe objective of our study is to retrospectively investigate if the HOSPITAL score, LACE index, and RAHF scale exhibit any bias based on gender and race in heart failure readmissions.
methodsThis is a retrospective cohort study with all adult medical patients discharged with congestive heart failure from 2016 to 2018 from Southern Illinois University School of Medicine Hospitalist service. The receiver operating characteristic (ROC) curve was constructed comparing prediction tools (HOSPITAL score, LACE index, and RAHF scale) performance based on gender and race by measuring the area under the curve (AUC). Absolute Between-ROC Area (ABROCA) values were calculated. All statistical analyses were performed using R version 3.6.2.
resultsThe performance of the HOSPITAL score in the majority and minority population showed a statistically significant difference between AUCs (0.714 and 0.633, p = 0.029) and an ABROCA of 0.081 indicating superior performance in predicting hospital readmissions in the majority group vs. the minority. The performance of RAHF score in females and males showed statistically significant differences between AUCs (0.567 and 0.527, p = 0.04) and an ABROCA of 0.04 indicating the superior performance of the RAHF score in females compared with males.
conclusionsOur study demonstrated that the HOSPITAL score and the RAHF scale showed significant differences in predicting 30-day readmissions risk based on race and gender, respectively, in heart failure patients, whereas the LACE index did not show any significant difference.
Indexed as
Identifiers
What OpenQuestion holds
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.