"Current practices for cohort reporting and statistical adjustment in s" by Thomas Schwann MD
 

Current practices for cohort reporting and statistical adjustment in studies from the STS Adult Cardiac Surgery Database

Author Department

Surgery

Document Type

Article, Peer-reviewed

Publication Date

3-2025

Abstract

Background: Current reporting and statistical adjustment practices of studies based on the Society of Thoracic Surgeons Adult Cardiac Surgery Database (STS ACSD) have not been described.

Methods: A review identified all published studies based on STS ACSD data from January 2016 to March 2024. Data were extracted by two authors and independently checked by the senior author.

Results: A total of 134 studies were included. Forty-six (34.3%) were on coronary artery bypass grafting, 22 (16.4%) on mitral valve surgery, 16 (11.9%) on aortic surgery, 14 (10.4%) on surgical aortic valve replacement, 3 (2.2%) on tricuspid valve surgery, 18 (13.4%) on combined procedures, and 15 (11.2%) on other surgeries. Forty-nine (44.0%) studies used the Participant User File (PUF) program, with a significant increase over time (p trend = 0.005). Of the 1239 variables available in the STS ACSD (version 4.20.2), 136 (11.0%) (median 21 variables per study, interquartile range 16-25) were used to describe the baseline patient characteristics populations and 191 (15.4%) (median 22 variables per study, interquartile range 17 - 33) for statistical adjustment; 121 studies (90.3%) performed statical adjustment, with multivariable regression used in the majority (80, 66.1%). PUF manuscripts had significantly more junior first authors (20.3% vs. 1.3%, p=0.001) and were published in higher-impact journals (median impact factor 4.90 [IQR 3.70-9.15] vs. 3.90 [IQR 3.60-4.70]; p=0.002) compared to non-PUF manuscripts.

Conclusions: Our analysis provides data that may inform efforts to standardize reporting and analytic practices in studies based on the STS ACSD.

Keywords: STS National Database; cardiothoracic surgery; outcomes research; risk adjustment; variable selection.

PMID

40049382

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