MétaCan
Menu
Back to cohort
Record W2609761959 · doi:10.1111/apa.13889

Using internal and external reviewers can help to optimise neonatal mortality and morbidity conferences

2017· article· en· W2609761959 on OpenAlexaffabout
Michael‐Andrew Assaad, Annie Janvier, Anie Lapointe

Bibliographic record

VenueActa Paediatrica · 2017
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineNeonatal intensive care unitIntensive care unitIntensive careClinical PracticeFamily medicineMEDLINEPediatricsIntensive care medicine

Abstract

fetched live from OpenAlex

AIM: This study determined whether there was a difference in the conclusions reached by neonatologists in morbidity and mortality conferences based on their level of involvement in a case. METHODS: All neonatal deaths occurring between August 2014 and September 2015 at the neonatal intensive care unit of Sainte-Justine Hospital, Montreal, Quebec, Canada, were reviewed by internal physicians involved in the case and external physicians who were not. The reviewers were asked to identify positive and negative clinical practice items and provide written recommendations. These were classified into eight categories and compared for each case. RESULTS: During the study, 55 patients died leading to 110 reviews and a total of 590 positive and negative items. Most items were in the communication (25.2%), ethical decision-making (16.7%) and clinical management (14.8%) categories. Both the internal and external reviewers were in agreement 48.5% of the time for positive items and 44.8% for negative items. There were 242 written recommendations, which differed significantly among the internal and external reviewers. CONCLUSION: Reviews of neonatal deaths by two independent reviewers, internal physicians and external physicians, led to different positive and negative practice items and recommendations. This could allow for a richer discussion and improve recommendations for patient care.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

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

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 head0.088
GPT teacher head0.351
Teacher spread0.262 · 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.

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

Citations3
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueActa PaediatricaSame topicInfant Development and Preterm CareFrench-language works237,207