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Record W4317567890 · doi:10.1097/pcc.0000000000003125

Defining Pediatric Chronic Critical Illness: A Scoping Review*

2022· article· en· W4317567890 on OpenAlexaff
David J. Zorko, James Dayre McNally, Bram Rochwerg, Neethi Pinto, Katie O’Hearn, Mohammed Almazyad, Stefanie G. Ames, Peter Brooke, Florence Cayouette, Cristelle Chow, José Colleti, Conall Francoeur, Julia A. Heneghan, Yasser Kazzaz, Elizabeth Y. Killien, Supun Kotteduwa Jayawarden, Rubén Lasso, Laurie A. Lee, Aoife O’Mahony, Mallory Perry, Miguel Rodríguez-Rubio, Ryan Sandarage, Hazel Smith, Alexandra Welten, Belinda Yee, Karen Choong

Bibliographic record

VenuePediatric Critical Care Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of OttawaAlberta Children's HospitalUniversity of British ColumbiaUniversity of CalgaryImpactUniversité LavalUniversity of TorontoAgricultural Research Institute of OntarioAlberta Health ServicesMcMaster University
Fundersnot available
KeywordsMedicineCINAHLMEDLINEData extractionCrowdsourcingPopulationIntensive care medicinePsychological interventionWorld Wide WebNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: Children with chronic critical illness (CCI) are hypothesized to be a high-risk patient population with persistent multiple organ dysfunction and functional morbidities resulting in recurrent or prolonged critical care; however, it is unclear how CCI should be defined. The aim of this scoping review was to evaluate the existing literature for case definitions of pediatric CCI and case definitions of prolonged PICU admission and to explore the methodologies used to derive these definitions. DATA SOURCES: Four electronic databases (Ovid Medline, Embase, CINAHL, and Web of Science) from inception to March 3, 2021. STUDY SELECTION: We included studies that provided a specific case definition for CCI or prolonged PICU admission. Crowdsourcing was used to screen citations independently and in duplicate. A machine-learning algorithm was developed and validated using 6,284 citations assessed in duplicate by trained crowd reviewers. A hybrid of crowdsourcing and machine-learning methods was used to complete the remaining citation screening. DATA EXTRACTION: We extracted details of case definitions, study demographics, participant characteristics, and outcomes assessed. DATA SYNTHESIS: Sixty-seven studies were included. Twelve studies (18%) provided a definition for CCI that included concepts of PICU length of stay (n = 12), medical complexity or chronic conditions (n = 9), recurrent admissions (n = 9), technology dependence (n = 5), and uncertain prognosis (n = 1). Definitions were commonly referenced from another source (n = 6) or opinion-based (n = 5). The remaining 55 studies (82%) provided a definition for prolonged PICU admission, most frequently greater than or equal to 14 (n = 11) or greater than or equal to 28 days (n = 10). Most of these definitions were derived by investigator opinion (n = 24) or statistical method (n = 18). CONCLUSIONS: Pediatric CCI has been variably defined with regard to the concepts of patient complexity and chronicity of critical illness. A consensus definition is needed to advance this emerging and important area of pediatric critical care research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.414
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2022
Admission routes1
Has abstractyes

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