MétaCan
Menu
Back to cohort
Record W1573659459 · doi:10.1093/pch/16.10.e78

Paediatric hanging and strangulation injuries: A 10-year retrospective description of clinical factors and outcomes

2011· article· en· W1573659459 on OpenAlexafffundabout
Dawn Davies, M Lang, Rick Watts

Bibliographic record

VenuePaediatrics & Child Health · 2011
Typearticle
Languageen
FieldMedicine
TopicRestraint-Related Deaths
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsMedicineAsphyxiaRetrospective cohort studyHypoxic Ischemic EncephalopathyPediatricsHypoxemiaMedical recordCardiopulmonary resuscitationEmergency medicineEncephalopathyResuscitationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To identify early clinical factors that are correlated with death or severe disability in paediatric patients who have sustained an injury by hanging or strangulation. METHODS: A retrospective review of all patient records from January 1, 1997, to September 30, 2007, was conducted. Patient records were identified by International Classification of Diseases and Related Health Problems, Tenth Revision, Canada diagnostic codes for asphyxia, strangulation, hypoxic-ischemic encephalopathy, hanging, hypoxemia, hypoxia or anoxia. RESULTS: A total of 109 records were identified. Of these, 41 met the inclusion criteria for the study. Of 19 (46%) children who were pulse-less and received cardiopulmonary resuscitation, 16 died and the survivors were severely disabled. Of the 22 (54%) children who were found with a pulse, 18 made a full recovery. CONCLUSIONS: Children who are pulseless at discovery for hanging injuries are at high risk of death or severe disability. Early clinical and neurophysiological indicators should be applied systematically to best guide clinicians and parents in their decision making.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.330
Teacher spread0.282 · 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
GenreEmpirical

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

Citations27
Published2011
Admission routes3
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicRestraint-Related DeathsFrench-language works237,207