Evidence map›Paper›PMID 39069119›Full record

ArticleThe Journal of thoracic and cardiovascular surgery2025

Development of American Association for Thoracic Surgery Quality Gateway outcome models, analytics, and visualizations for quality assurance.

Hemant Ishwaran, Eugene H Blackstone

Abstract readMulticenter Study
In one paragraph

Article in The Journal of thoracic and cardiovascular surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

2 authors.

Hemant IshwaranDivision of Biostatistics, University of Miami, Miami, Fla.
Eugene H BlackstoneDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio; Department of Thoracic and Cardiovascular Surgery, Cleveland Clinic, Cleveland, Ohio. Electronic address: blackse@ccf.org.

Funding

Real time risk prognostication via scalable hazard trees and forestsR01HL164405 · NHLBI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Hemant Ishwaran · 2023 to 2026
$2.3M
Super Greedy TreesR35GM139659 · NIGMS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI ISHWARAN, HEMANT · 2021 to 2025
$2.1M
NHLBI NIH HHS R01 HL164405NIGMS NIH HHS R35 GM139659
6 · The paper itself

Abstract

objectiveThe study objective was to develop comprehensive quality assurance models for procedural outcomes after adult cardiac surgery.

methodsBased on 52,792 cardiac operations in adults performed in 19 hospitals of 3 high-performing hospital systems, models were developed for operative mortality (n = 1271), stroke (n = 895), deep sternal wound infection (n = 122), prolonged intubation (6182), renal failure (1265), prolonged postoperative stay (n = 5418), and reoperations (n = 1693). Random forest quantile classification, a method tailored for challenges of rare events, and model-free variable priority screening were used to identify predictors of events.

resultsA small set of preoperative variables was sufficient to model procedural outcomes for virtually all cardiac operations, including older age; advanced symptoms; left ventricular, pulmonary, renal, and hepatic dysfunction; lower albumin; higher acuity; and greater complexity of the planned operation. Geometric mean performance ranged from .63 to .76. Calibration covered large areas of probability. Continuous risk factors provided high information content, and their association with outcomes was visualized with partial plots. These risk factors differed in strength and configuration among hospitals, as did their risk-adjusted outcomes according to patient risk as determined by counterfactual causal inference within a framework of virtual (digital) twins.

conclusionsBy using a small set of variables and contemporary machine-learning methods, comprehensive models for procedural operative mortality and major morbidity after adult cardiac surgery were developed based on data from 3 exemplary hospital systems. They provide surgeons, their patients, and hospital systems with 21st century tools for assessing their risks compared with these advanced hospital systems and improving cardiac surgery quality.

Indexed as

Cardiac Surgical ProceduresPostoperative ComplicationsQuality Assurance, Health CareQuality Indicators, Health CareAdultAgedFemaleHospital MortalityHumansMaleMiddle AgedRisk AssessmentRisk FactorsSocieties, MedicalTreatment OutcomeUnited Statescausal analysisimbalanced datamachine learningquantile classificationvariable importancevirtual twins

Identifiers

PMID39069119
PMCPMC13576646

What OpenQuestion holds

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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.