Evidence map›Paper›PMID 27515069›Full record

ArticleCatheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions2017

Development and validation of a simple risk score to predict 30-day readmission after percutaneous coronary intervention in a cohort of medicare patients.

Karl E Minges, Jeph Herrin, Paul N Fiorilli, Jeptha P Curtis

Abstract readValidation Study
In one paragraph

Article in Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Trial
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  10. Predicting readmission risk following percutaneous coronary intervention at the time of admission.Cardiovascular revascularization medicine : including molecular interventions · 2017
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Karl E MingesCenter for Outcomes Research and Evaluation, Yale School of Medicine, Yale-New Haven Hospital, New Haven, Connecticut.
Jeph HerrinDepartment of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut.
Paul N FiorilliCardiovascular Division, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
Jeptha P CurtisCenter for Outcomes Research and Evaluation, Yale School of Medicine, Yale-New Haven Hospital, New Haven, Connecticut.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Institutional Career Development CoreKL2TR001862 · NCATS · YALE UNIVERSITY · PI CANTLEY, LLOYD G, EDELMAN, E. JENNIFER · 2016 to 2025
$12.2M
Center for Cardiovascular Outcomes Research at Yale UniversityU01HL105270 · NHLBI · YALE UNIVERSITY · PI CURTIS, JEPTHA PELHAM, KRUMHOLZ, HARLAN MARC · 2010 to 2013
$5.8M
NCATS NIH HHS KL2 TR001862NCATS NIH HHS UL1 TR001863NHLBI NIH HHS U01 HL105270
6 · The paper itself

Abstract

objectivesTo develop a risk model that can be used to identify PCI patients at higher risk of readmission who may benefit from additional resources at the time of discharge.

backgroundA high proportion of patients undergoing PCI are readmitted within 30 days of discharge.

methodsThe sample comprised patients aged ≥65 years who underwent PCI at a CathPCI Registry®-participating hospital and could be linked with 100% Medicare fee-for-service claims between 01/2007 and 12/2009. The sample (n = 388,078) was randomly divided into risk score development (n = 193,899) and validation (n = 194,179) cohorts. We did not count as readmissions those associated with staged revascularization procedures. Multivariable logistic regression models using stepwise selection models were estimated to identify variables independently associated with all-cause 30-day readmission.

resultsThe mean 30-day readmission rates for the development (11.36%) and validation (11.35%) cohorts were similar. In total, 19 variables were significantly associated with risk of 30-day readmission (P < 0.05), and model c-statistics were similar in the development (0.67) and validation (0.66) cohorts. The simple risk score based on 14 variables identified patients at high and low risk of readmission. Patients with a score of ≥13 (15.4% of sample) had more than an 18.5% risk of readmission, while patients with a score ≤6 (41.9% of sample) had less than an 8% risk of readmission.

conclusionAmong PCI patients, risk of readmission can be estimated using clinical factors present at the time of the procedure. This risk score may guide clinical decision-making and resource allocation for PCI patients at the time of hospital discharge. © 2016 Wiley Periodicals, Inc.

Indexed as

Decision Support TechniquesMedicarePatient ReadmissionAgedAged, 80 and overAlgorithmsFemaleHumansLogistic ModelsMaleMultivariate AnalysisOdds RatioPercutaneous Coronary InterventionPredictive Value of TestsRegistriesReproducibility of Resultshealth care outcomesMedicarepercutaneous coronary interventionquality improvementrisk stratification

Identifiers

PMID27515069
PMCPMC5397364

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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.