Evidence map›Paper›PMID 30463734›Full record

ArticleThe Journal of surgical research2018

Put Me in the Game Coach! Resident Participation in High-risk Surgery in the Era of Big Data.

Adrienne N Cobb, Emanuel Eguia, Haroon Janjua, Paul C Kuo

Abstract read
In one paragraph

Article in The Journal of surgical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Big Data for Biomedical Education with a Focus on the COVID-19 Era: An Integrative Review of the Literature.International journal of environmental research and public health · 2021
    Review
  7. Article
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.

Adrienne N CobbDepartment of Surgery, Loyola University Medical Center, Maywood, Illinois; Department of Surgery, One:MAP Section of Surgical Analytics, Loyola University Chicago, Maywood, Illinois. Electronic address: adcobb@lumc.edu.
Emanuel EguiaDepartment of Surgery, Loyola University Medical Center, Maywood, Illinois; Department of Surgery, One:MAP Section of Surgical Analytics, Loyola University Chicago, Maywood, Illinois.
Haroon JanjuaDepartment of Surgery, Loyola University Medical Center, Maywood, Illinois; Department of Surgery, One:MAP Section of Surgical Analytics, Loyola University Chicago, Maywood, Illinois.
Paul C KuoDepartment of Surgery, One:MAP Section of Surgical Analytics, Loyola University Chicago, Maywood, Illinois; Department of Surgery, University of South Florida, Tampa, Florida.

Funding

TRAINING IN TRAUMA AND BURN RESEARCHT32GM008750 · NIGMS · LOYOLA UNIVERSITY CHICAGO · PI CHOUDHRY, MASHKOOR A, GONZALEZ, RICHARD PAUL · 2000 to 2023
$2.9M
NIGMS NIH HHS T32 GM008750
6 · The paper itself

Abstract

backgroundWith the emphasis on quality metrics guiding reimbursement, concerns have emerged regarding resident participation in patient care. This study aimed to evaluate whether resident participation in high-risk elective general surgery procedures is safe. MATERIALS AND

methodsThe American College of Surgeons National Surgical Quality Improvement Program database (2005-2012) was used to identify patients undergoing one of five high-risk general surgery procedures. Resident and nonresident groups were created using a 2:1 propensity score match. Postoperative outcomes were calculated using univariate statistics and multivariable logistic regression for the two groups. Predictors of mortality and morbidity were identified using machine learning in the form of decision trees.

resultsTwenty-five thousand three hundred sixty three patients met our inclusion criteria. Following matching, each group contained 500 patients and was comparable for matched characteristics. Thirty-day mortality was similar between the groups (2.4% versus 2.6%; P = 0.839). Deep surgical site infection (0% versus 1.6%; P = 0.005), urinary tract infection (5% versus 2.5%; P = 0.029), and operative time (275.6 min versus 250 min; P = 0.0064) were significantly higher with resident participation. Resident participation was not predictive of mortality or complications, while age, American society of anesthesiologists class, and functional status were leading predictors of both.

conclusionsDespite growing time constraints and pressure to perform, surgical resident participation remains safe. Residents should be given active roles in the operating room, even in the most challenging cases.

Indexed as

AgedClinical CompetenceDatabases, FactualFemaleHospital MortalityHumansInternship and ResidencyMaleMiddle AgedOperating RoomsOperative TimePostoperative ComplicationsQuality ImprovementSurgical Procedures, OperativeSurvival RateTreatment OutcomeOperative experienceResident participationSurgery residencySurgical education

Identifiers

PMID30463734
PMCPMC6251497

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.