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Directed Acyclic Graphs in Surgical Research. [Review]

MedStar author(s):

Citation: Journal of Surgical Research. 2022 Aug 29PMID: 36045022Department: MedStar General Surgery Residency | MedStar Georgetown University Hospital/MedStar Washington Hospital CenterForm of publication: Journal ArticleMedline article type(s): Journal Article | ReviewSubject headings: IN PROCESS -- NOT YET INDEXEDYear: 2022 ISSN:

0022-4804

Name of journal: The Journal of surgical researchAbstract: Surgical research often utilizes multivariable regression to evaluate causal relationships between variables, but there is usually little explanation of the decision-making regarding which variables were controlled for. We propose that directed acyclic graphs (DAGs)-a formal logic tool that illustrates connections between variables-should be used to define and communicate variable relationships to readers and other audiences. While literature in epidemiology and other medical fields has recently started to incorporate DAGs more, they are still seldom seen in surgical publications. In this review, we describe the background and need for DAGs and argue for their use. Next, we explain how bias can be introduced without a thoughtful approach to control variable selection. Finally, we recommend that researchers communicate their choices and rationale when selecting control variables in published surgical research. Copyright © 2022 Elsevier Inc. All rights reserved.All authors: Bradshaw JC, Gongola AFiscal year: FY2023 Digital Object Identifier:

https://dx.doi.org/10.1016/j.jss.2022.07.017

Date added to catalog: 2022-10-20

Holdings ( 1 )
Title notes ( 2 )

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Journal Article	MedStar Authors Catalog	Article	36045022	Available		36045022

Surgical research often utilizes multivariable regression to evaluate causal relationships between variables, but there is usually little explanation of the decision-making regarding which variables were controlled for. We propose that directed acyclic graphs (DAGs)-a formal logic tool that illustrates connections between variables-should be used to define and communicate variable relationships to readers and other audiences. While literature in epidemiology and other medical fields has recently started to incorporate DAGs more, they are still seldom seen in surgical publications. In this review, we describe the background and need for DAGs and argue for their use. Next, we explain how bias can be introduced without a thoughtful approach to control variable selection. Finally, we recommend that researchers communicate their choices and rationale when selecting control variables in published surgical research. Copyright © 2022 Elsevier Inc. All rights reserved.

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