Evidence map›Paper›PMID 34474638›Full record

ArticleHospital practice (1995)2021

Early (0-7 day) and late (8-30 day) readmission predictors in acute coronary syndrome, atrial fibrillation, and congestive heart failure patients.

George Cholack, Joshua Garfein, Josh Errickson, Rachel Krallman, Daniel Montgomery, Eva Kline-Rogers, Kim Eagle, Melvyn Rubenfire, Sherry Bumpus, Geoffrey D Barnes

Open access · greenAbstract read
In one paragraph

Article in Hospital practice (1995), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 39% of its field
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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

10 authors at 4 institutions in 1 country.

George CholackMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0001-6774-7326
Joshua GarfeinMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0002-6884-9479
Josh ErricksonDepartment of Statistics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-4289-1417
Rachel KrallmanMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0002-4466-7697
Daniel MontgomeryMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.
Eva Kline-RogersMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0002-3245-7895
Kim EagleMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0003-0031-0191
Melvyn RubenfireMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0002-0290-7154
Sherry BumpusMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0002-7812-5183
Geoffrey D BarnesMichigan Medicine, Department of Internal Medicine, Division of Cardiovascular Medicine, Ann Arbor, MI, USA.ORCID 0000-0002-6532-8440
Michigan Medicine · USEastern Michigan University · USOakland University · USUniversity of Michigan · US

Funding

NRSA Training CoreTL1TR002242 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HOLINSTAT, MICHAEL ALLAN · 2017 to 2021
$2.8M
NCATS NIH HHS TL1 TR002242
6 · The paper itself

Abstract

objectivesThirty-day readmission following hospitalization for acute coronary syndrome (ACS), atrial fibrillation (AF), or congestive heart failure (CHF) is common, and many occur within one week of discharge. Using a cohort of patients hospitalized for ACS, AF, or CHF, we sought to identify predictors of 30-day, early (0-7 day), and late (8-30 day) all-cause readmission.

methodsWe identified 3531 hospitalizations for ACS, AF, or CHF at a large academic medical center between 2008 and 2018. Multivariable logistic regression models were created to identify predictors of 30-day, early, and late unplanned, all-cause readmission, adjusting for discharge diagnosis and other demographics and comorbidities.

resultsOf 3531 patients hospitalized for ACS, AF, or CHF, 700 (19.8%) were readmitted within 30 days, and 205 (29.3%) readmissions were early. Of all 30-day readmissions, 34.8% of ACS, 16.8% of AF, and 26.0% of the CHF cohorts' readmissions occurred early. Higher hemoglobin was associated with lower 30-day readmission [adjusted (adj) OR 0.92, 95% CI 0.88-0.97] while patients requiring intensive care unit (ICU) admission were more likely readmitted within 30 days (adj OR 1.31, 95% CI 1.03-1.67). Among patients with a 30-day readmission, females (adj OR 1.73, 95% CI 1.22, 2.47) and patients requiring ICU admission (adj OR 2.03, 95% CI 1.27, 3.26) were more likely readmitted early than late. Readmission predictors did not vary substantively by discharge diagnosis.

conclusionPatients admitted to the ICU were more likely readmitted in the early and 30-day periods. Other predictors varied between readmission groups. Since outpatient follow-up often occurs beyond 1 week of discharge, early readmission predictors can help healthcare providers identify patients who may benefit from particular post-discharge services.

Indexed as

Severity of Illness IndexAcute Coronary SyndromeAgedFemaleHeart FailureHumansMaleMiddle AgedPatient ReadmissionRetrospective StudiesRisk AssessmentRisk FactorsTreatment OutcomeAcute coronary syndromeatrial fibrillationheart failureintensive care unitreadmission

Identifiers

PMID34474638
PMCPMC8688234
OpenAlexW3197631856

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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 OpenQuestion graph.