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Record W4307690458 · doi:10.1136/bmjopen-2022-063183

Canadian infants presenting with Brief Resolved Unexplained Events (BRUEs) and validation of clinical prediction rules for risk stratification: a protocol for a multicentre, retrospective cohort study

2022· article· en· W4307690458 on OpenAlexafffundabout
Nassr Nama, Parnian Hosseini, Zerlyn Lee, Kara Picco, Jeffrey N. Bone, Jessica L. Foulds, Josée Anne Gagnon, Anupam Sehgal, Julie Quet, Olivier Drouin, Thuy Mai Luu, Gemma Vomiero, Ronik Kanani, Joanna Holland, Ran D. Goldman, Kristopher T. Kang, Sanjay Mahant, Falla Jin, Joel S. Tieder, Peter J. Gill

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsIzaak Walton Killam Health CentreNorth York General HospitalUniversity of CalgaryUniversity of OttawaQueen's UniversityHospital for Sick ChildrenUniversité de MontréalUniversity of AlbertaBC Children's HospitalUniversité LavalUniversity of British ColumbiaUniversity of Toronto
FundersBC Children's HospitalAmerican Academy of Pediatrics
KeywordsMedicineRisk stratificationProtocol (science)Retrospective cohort studyCohort studyCohortRisk assessmentEpidemiologyPediatricsBiostatisticsFamily medicineEmergency medicineAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Brief Resolved Unexplained Events (BRUEs) are a common presentation among infants. While most of these events are benign and self-limited, guidelines published by the American Academy of Pediatrics inaccurately identify many patients as higher-risk of a serious underlying aetiology (positive predictive value 5%). Recently, new clinical prediction rules have been derived to more accurately stratify patients. This data were however geographically limited to the USA, with no large studies to date assessing the BRUE population in a different healthcare setting. The study's aim is to describe the clinical management and outcomes of infants presenting to Canadian hospitals with BRUEs and to externally validate the BRUE clinical prediction rules in identified cases. METHODS AND ANALYSIS: This is a multicentre retrospective study, conducted within the Canadian Paediatric Inpatient Research Network (PIRN). Infants (<1 year) presenting with a BRUE at one of 11 Canadian paediatric centres between 1 January 2017 and 31 December 2021 will be included. Eligible patients will be identified using diagnostic codes.The primary outcome will be the presence of a serious underlying illness. Secondary outcomes will include BRUE recurrence and length of hospital stay. We will describe the rates of hospital admissions and whether hospitalisation was associated with an earlier diagnosis or treatment. Variation across Canadian hospitals will be assessed using intraclass correlation coefficient. To validate the newly developed clinical prediction rule, measures of goodness of fit will be evaluated. For this validation, a sample size of 1182 is required to provide a power of 80% to detect patients with a serious underlying illness with a significance level of 5%. ETHICS AND DISSEMINATION: Ethics approval has been granted by the UBC Children's and Women's Research Board (H21-02357). The results of this study will be disseminated as peer-reviewed manuscripts and presentations at national and international conferences.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.050
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.868
Threshold uncertainty score0.265

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.048
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0040.005
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0050.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0140.003

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 head0.127
GPT teacher head0.441
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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

Citations9
Published2022
Admission routes3
Has abstractyes

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