MétaCan
Menu
Back to cohort
Record W4367693837 · doi:10.1007/s12630-023-02418-1

Ancillary investigations for death determination in infants and children: a systematic review and meta-analysis

2023· review· en· W4367693837 on OpenAlexafffund
Nicole K. McKinnon, Christina Maratta, Lionel S. Zuckier, J. Gordon Boyd, Michaël Chassé, Laura Hornby, Andreas H. Kramer, Julie Kromm, Owen T. Mooney, Prakash Muthusami, Roy Nitulescu, Jae-Woo Park, Marat Slessarev, John Basmaji

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2023
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsUniversity of ManitobaCanadian Blood ServicesUniversité de MontréalKingston General HospitalUniversity of CalgaryCentre Hospitalier de l’Université de MontréalSickKids FoundationAlberta Health ServicesQueen's UniversityOttawa HospitalUniversity of OttawaWestern UniversityUniversity of Toronto
FundersCanadian Blood Services
KeywordsMedicineMeta-analysisMEDLINEObservational studySystematic reviewRandomized controlled trialGrading (engineering)Medical physicsNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

Purpose We performed a systematic review and meta-analysis to determine the diagnostic test accuracy of ancillary investigations for declaration of death by neurologic criteria (DNC) in infants and children. Source We searched MEDLINE, EMBASE, Web of Science, and Cochrane databases from their inception to June 2021 for relevant randomized controlled trials, observational studies, and abstracts published in the last three years. We identified relevant studies using Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology and a two-stage review. We assessed the risk of bias using the QUADAS-2 tool, and applied Grading of Recommendations Assessment, Development, and Evaluation methodology to determine the certainty of evidence. A fixed-effects model was used to meta-analyze pooled sensitivity and specificity data for each ancillary investigation with at least two studies. Principal findings Thirty-nine eligible manuscripts assessing 18 unique ancillary investigations (n = 866) were identified. The sensitivity and specificity ranged from 0.00 to 1.00 and 0.50 to 1.00, respectively. The quality of evidence was low to very low for all ancillary investigations, with the exception of radionuclide dynamic flow studies for which it was graded as moderate. Radionuclide scintigraphy using the lipophilic radiopharmaceutical 99mTc-hexamethylpropyleneamine oxime (HMPAO) with or without tomographic imaging were the most accurate ancillary investigations with a combined sensitivity of 0.99 (95% highest density interval [HDI], 0.89 to 1.00) and specificity of 0.97 (95% HDI, 0.65 to 1.00). Conclusion The ancillary investigation for DNC in infants and children with the greatest accuracy appears to be radionuclide scintigraphy using HMPAO with or without tomographic imaging; however, the certainty of the evidence is low. Nonimaging modalities performed at the bedside require further investigation. Study registration: PROSPERO (CRD42021278788); registered 16 October 2021.

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)0.024
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.052
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0250.050
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.318
Teacher spread0.219 · 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 designMeta-analysis
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

Citations17
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Anesthesia/Journal canadien d anesthésieSame topicNeuroscience of respiration and sleepFrench-language works237,207