Statistical Note: Using Scoping and Systematic Reviews

Toh, Theresa Shu Wen; Lee, Jan Hau

doi:10.1097/pcc.0000000000002738

Cited by 6 publications

(7 citation statements)

References 13 publications

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“…Recent publications by the group have included topics of clinical decision support, model development, and model validation (11–14). This review adhered to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews guidelines (15, 16) ( Supplemental Digital Content 1 , http://links.lww.com/PCC/C458).…”

Section: Methodsmentioning

confidence: 99%

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research

Heneghan,

Walker,

Fawcett

et al. 2023

Pediatric Critical Care Medicine

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OBJECTIVE: Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care. DESIGN: Scoping review and expert opinion. SETTING: We queried CINAHL Plus with Full Text (EBSCO), Cochrane Library (Wiley), Embase (Elsevier), Ovid Medline, and PubMed for articles published between 2000 and 2022 related to machine learning concepts and pediatric critical illness. Articles were excluded if the majority of patients were adults or neonates, if unsupervised machine learning was the primary methodology, or if information related to the development, validation, and/or implementation of the model was not reported. Article selection and data extraction were performed using dual review in the Covidence tool, with discrepancies resolved by consensus. SUBJECTS: Articles reporting on the development, validation, or implementation of supervised machine learning models in the field of pediatric critical care medicine. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 5075 identified studies, 141 articles were included. Studies were primarily (57%) performed at a single site. The majority took place in the United States (70%). Most were retrospective observational cohort studies. More than three-quarters of the articles were published between 2018 and 2022. The most common algorithms included logistic regression and random forest. Predicted events were most commonly death, transfer to ICU, and sepsis. Only 14% of articles reported external validation, and only a single model was implemented at publication. Reporting of validation methods, performance assessments, and implementation varied widely. Follow-up with authors suggests that implementation remains uncommon after model publication. CONCLUSIONS: Publication of supervised machine learning models to address clinical challenges in pediatric critical care medicine has increased dramatically in the last 5 years. While these approaches have the potential to benefit children with critical illness, the literature demonstrates incomplete reporting, absence of external validation, and infrequent clinical implementation.

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Section: Methodsmentioning

confidence: 99%

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research

Heneghan,

Walker,

Fawcett

et al. 2023

Pediatric Critical Care Medicine

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“…Scoping reviews are exploratory pieces of work and writing-up should follow the format recently reviewed in PCCM (10). To qualify for consideration, authors should be able to make the argument that the content and reasoning of the scoping review is immediately relevant to the contemporary narrative portrayed in the pages of PCCM .…”

Section: Notes On Certain Types Of Research Methodologiesmentioning

confidence: 99%

“…The reporting of systematic reviews and meta-analyses should follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement (9). Checklists and other materials (10). To qualify for consideration, authors should be able to make the argument that the content and reasoning of the scoping review is immediately relevant to the contemporary narrative portrayed in the pages of PCCM.…”

Section: Systematic Reviews Meta-analyses and Scoping Reviewsmentioning

confidence: 99%

Writing for PCCM: Instructions for Authors

Tasker¹

2022

Pediatric Critical Care Medicine

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ediatric Critical Care Medicine (PCCM) is one of three journals in the Society of Critical Care Medicine (SCCM) stable of journals that also includes Critical Care Medicine and Critical Care Explorations. Along with the other journals in this group, we have updated the Instructions for Authors on the journal's website (see https://journals.lww.com/pccmjournal/ pages/default.aspx). In this PCCM Notes, Methods, and Statistics article, I provide some further clarifying points for authors submitting to PCCM. WHO IS AN AUTHOR AND WHAT ARE THEIR RESPONSIBILITIES?PCCM welcomes submissions from all over the world and all pediatric intensive care professionals. Our journal is unique in that both SCCM and the World Federation of Pediatric Intensive and Critical Care Societies (WFPICCS) acknowledge that its main purpose is to publish new information that will benefit patients. This mission is hugely important, and readers as well as authors, should be aware of the responsibilities that come with authorship.According to the International Committee of Medical Journal Editors (ICMJE, see https://www.icmje.org/recommendations/browse/roles-andresponsibilities/defining-the-role-of-authors-and-contributors.html), authorship is based on meeting the requirements of all four of the following criteria: 1) providing "substantial contributions to the conception or design of the work, or the acquisition, analysis, or interpretation of data for the work"; 2) "drafting" or critically "revising" the work for "important intellectual content"; 3) giving approval of the version of the work to be submitted to PCCM; and 4) agreeing to be "accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. " At PCCM, the corresponding author is also responsible for determining the selection and order of authors, and is accountable to their sponsoring organization, university, or department in the event of disputes about authorship. PCCM takes no position on these choices.Like other journals, we acknowledge that contemporary science often involves extended collaborations and not all contributors meet the ICMJE standard for authorship. Some manuscripts may be a collective work product, involving several contributors. Hence, large research enterprises have the option of deciding to make the distinction between authors and collaborators. In this circumstance, PCCM recommends that the corresponding author assess each contributor's role and determine which contributors are also authors and which are collaborators. At the time of submission each contributor's role can be described using the Contributor Roles Taxonomy (CRediT, see https:// credit.niso.org/). The journal places no limit on the number of individuals who are listed as contributors, and they will be identified in the United States (US) National Institutes of Health National Library of Medicine (NLM) database curated at PubMed.gov (see https://pubmed.ncbi.nlm.nih.gov).

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“…This next item in the PCCM Notes, Methods, and Statistics series—already seven to date (1, 2, 17–21)—is therefore focused on a new framework for engaging with references in our Journal articles. The purpose is to elevate writing for PCCM , and in no way is it a criticism of past publications and our exemplary authors.…”

Section: Pccm In the New Era: A Framework For Engaging With Referencesmentioning

confidence: 99%

Writing for Pediatric Critical Care Medicine: Engaging With Citations to References in the Chatbot Generative Pre-Trained Transformer Era

Tasker

2023

Pediatric Critical Care Medicine

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Statistical Note: Using Scoping and Systematic Reviews

Cited by 6 publications

References 13 publications

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research

Writing for PCCM: Instructions for Authors

Writing for Pediatric Critical Care Medicine: Engaging With Citations to References in the Chatbot Generative Pre-Trained Transformer Era

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