Evidence map›Paper›PMID 40631000›Full record

ArticleJTCVS open2025

Quantifying random variability in decision-making in pediatric cardiac surgery.

Kayla V Dlugos, Mjaye Mazwi, Marisa Signorile, Chun-Po Steve Fan, Patricia Trbovich, Osami Honjo

Abstract read
In one paragraph

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

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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

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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

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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

6 authors.

Kayla V DlugosInstitute of Medical Science, University of Toronto, Ontario, Canada.
Mjaye MazwiDivision of Cardiac Critical Care, Seattle Children's Hospital, Seattle, Wash.
Marisa SignorileTed Rogers Computational Program, Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, UHN, Toronto, Ontario, Canada.
Chun-Po Steve FanTed Rogers Computational Program, Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, UHN, Toronto, Ontario, Canada.
Patricia TrbovichInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
Osami HonjoDivision of Cardiovascular Surgery, The Labatt Family Heart Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Random variability in day-to-day decision-making referred to as "noise" is associated with variation that negatively affects both the reproducibility and quality of decision-making. Although well described in other fields, the prevalence and significance of noise in medical decision-making are understudied and largely unknown. The goal of this study was to quantify noise in medical decision-making using a noise audit. Methods: A noise audit was completed by 71 (n = 71) Heart Centre staff at the Hospital for Sick Children and Seattle Children's Hospital and involved a series of cases and questions surrounding decisions commonly encountered in the care for patients with transposition of the great arteries and critical aortic stenosis. Entropy was used to quantify total variation in responses. Because absolute entropy was not immediately comparable across audit questions with a different number of prespecified options, we reported a standardized version of entropy, which was calculated by dividing the absolute entropy by its theoretical maximum for each case. To compare responses in easy to hard questions across years of experience (<10 years and >10 years) and role, we reported aggregate entropy ratios. Aggregate entropy ratios were calculated by first stratifying by group of comparison and then calculating the standardized entropy for each question and taking the average of standardized entropies for easy questions and hard questions. Finally, to determine the ratio (easy to hard), we divided the average standardized entropy of the easy questions by the average standardized entropy of the hard questions. Results: The overall audit aggregate entropy ratio was 0.85 less than 1, indicating lower-complexity questions had less variation than higher-complexity questions. The aggregate entropy ratio for those with more than 10 years of experience was 0.8 and 0.87, respectively, for those with less than 10 years of experience. The aggregate entropy ratios for those in cardiac critical care, cardiology, and cardiovascular surgery were 0.85, 0.83, and 0.96, respectively. Conclusions: Noise was pervasive in medical decision-making in the analysis of our responses to common medical decisions made for patients with congenital heart disease and can be quantified in a manner that facilitates comparisons.

Indexed as

congenital heart surgery entropymedical decision-makingnoisenoise auditrandom variability

Identifiers

PMID40631000
PMCPMC12230459

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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.