Evidence map›Paper›PMID 40473518›Full record

ArticleSurgery2025

Factors associated with coronary artery bypass grafting excess readmission ratios.

Tyler Zander, Melissa A Kendall, Emily A Grimsley, Paul C Kuo

Abstract read
In one paragraph

Article in Surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Tyler ZanderDepartment of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL. Electronic address: tlzander@usf.edu.
Melissa A KendallDepartment of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL.
Emily A GrimsleyDepartment of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL.
Paul C KuoDepartment of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL.

Funding

Surgeon-Scientist Research Training in Injury Pathobiology and Outcomes In Critical IllnessT32GM144274 · NIGMS · UNIVERSITY OF SOUTH FLORIDA · PI PAUL C KUO, Matthias Majetschak · 2023 to 2026
$635k
NIGMS NIH HHS T32 GM144274
6 · The paper itself

Abstract

backgroundThe Hospital Readmissions Reduction Program determines Medicare readmission penalties through risk-adjusted excess readmissions ratios. This study uses interpretable machine learning to identify associations with coronary artery bypass grafting excess readmissions ratios.

methodsFlorida Agency for Healthcare Administration database (2017-2019) was queried for patients with Medicare who underwent coronary artery bypass grafting and linked to Hospital Readmissions Reduction Program and RAND Hospital data. Univariable analysis compared hospitals above compared with below the median excess readmissions ratios. LightGBM and XGBoost modeled excess readmissions ratios using patient data. SHapley Additive exPlanations were used for interpretation.

resultsThe cohort had 7,776 patients from 64 hospitals. Hospitals above the median excess readmissions ratios had more emergent admissions (35.4 vs 29.8%, P < .01), greater mortality (2.1 vs 1.3%, P < .01), and more expensive postoperative care charges (P < .01). Models had mean absolute errors <0.06 and R

conclusionHospitals with greater excess readmissions ratios charge more for postoperative care. Whether this association is caused by hospital differences alone or also by unadjusted differences in patient severity and functional status is unknown. The association of shorter length of stay with greater excess readmissions ratios could suggest that hospitals with greater excess readmissions ratios discharge patients too early. Future research should investigate the causes of these associations and their impact on excess readmissions ratios to ensure that hospitals are not unfairly penalized.

Indexed as

Coronary Artery BypassPatient ReadmissionPostoperative ComplicationsAgedFemaleFloridaHumansLength of StayMachine LearningMaleMedicareRetrospective StudiesRisk FactorsUnited States

Identifiers

PMID40473518
PMCPMC12354253

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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 OpenQuestion graph.