Evidence map›Paper›PMID 37554694›Full record

ArticleInternational journal of heart failure2023

Etiologies and Predictors of 30-Day Readmission in Heart Failure: An Updated Analysis.

Akhil Jain, Shilpkumar Arora, Viral Patel, Maharshi Raval, Karnav Modi, Nirav Arora, Rupak Desai, Behnam Bozorgnia, Raphael Bonita

Abstract read
In one paragraph

Article in International journal of heart failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  8. ClinNoteAgents: An LLM Multi-Agent System for Predicting and Interpreting Heart Failure 30-Day Readmission from Clinical Notes.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Akhil JainDepartment of Internal Medicine, Mercy Fitzgerald Hospital, Darby, PA, USA.ORCID https://orcid.org/0000-0001-7298-4246
Shilpkumar AroraDepartment of Interventional Cardiology, Houston Methodist Hospital, Houston, TX, USA.ORCID https://orcid.org/0000-0002-7246-7262
Viral PatelDepartment of Internal Medicine, New York Presbyterian Hospital, Queens, NY, USA.ORCID https://orcid.org/0000-0002-6245-0299
Maharshi RavalDepartment of Internal Medicine, Landmark Medical Center, Woonsocket, RI, USA.ORCID https://orcid.org/0000-0002-3016-0078
Karnav ModiDivision of Research, Moffitt Cancer Center & Research Institute, Tampa, FL, USA.ORCID https://orcid.org/0000-0003-3351-8829
Nirav AroraDepartment of Data Science, Lamar University, Beaumont, TX, USA.ORCID https://orcid.org/0009-0004-6070-5210
Rupak DesaiDivision of Cardiology. Atlanta VA Medical Center, Atlanta, GA, USA.ORCID https://orcid.org/0000-0002-5315-6426
Behnam BozorgniaDivision of Cardiology, Einstein Medical Center, Philadelphia, PA, USA.
Raphael BonitaDivision of Cardiology, Einstein Medical Center, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0001-5784-4798

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Readmissions in heart failure (HF), historically reported as 20%, contribute to significant patient morbidity and high financial cost to the healthcare system. The changing population landscape and risk factor dynamics mandate periodic epidemiologic reassessment of HF readmissions. Methods: National Readmission Database (NRD, 2019) was used to identify HF-related hospitalizations and evaluated for demographic, admission characteristics, and comorbidity differences between patients readmitted vs. those not readmitted at 30-days. Causes of readmission and predictors of all-cause, HF-specific, and non-HF-related readmissions were analyzed. Results: Of 48,971 HF patients, the readmitted cohort was younger (mean 67.4 vs. 68.9 years, p≤0.001), had higher proportion of males (56.3% vs. 53.7%), lowest income quartiles (33.3% vs. 28.9%), Charlson comorbidity index (CCI) ≥3 (61.7% vs. 52.8%), resource utilization including large bed-size hospitalizations, Medicaid enrollees, mean length of stay (6.2 vs. 5.4 days), and disposition to other facilities (23.9% vs. 20%) than non-readmitted. Readmission (30-day) rate was 21.2% (10,370) with cardiovascular causes in 50.3% (HF being the most common: 39%), and non-cardiac in 49.7%. Independent predictors for readmission were male sex, lower socioeconomic status, nonelective admissions, atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, anemia, and CCI ≥3. HF-specific readmissions were significantly associated with prior coronary artery disease and Medicaid enrollment. Conclusions: Our analysis revealed cardiac and noncardiac causes of readmission were equally common for 30-day readmissions in HF patients with HF itself being the most common etiology highlighting the importance of addressing the comorbidities, both cardiac and non-cardiac, to mitigate the risk of readmission.

Indexed as

30 day readmissionHeart failureOutcome assessment, health careThirty day readmissionUnited States Agency for Healthcare Research and Quality, Etiology

Identifiers

PMID37554694
PMCPMC10406555

What Socratic holds

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LicenceCC BY-NC
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Registered trials

None linked

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 Socratic graph.