MétaCan
Menu
Back to cohort
Record W4313379784 · doi:10.1038/s41372-022-01593-1

Increased risk of bradycardia in vigorous infants receiving early as compared to delayed cord clamping at birth

2022· article· en· W4313379784 on OpenAlexfundno aff
Ashish KC, So Yeon Kong, Solveig Haukås Haaland, Joar Eilevstjønn, Helge Myklebust, Ram Chandra Bastola, Thomas R. Wood, Susan Niermeyer, Sara K. Berkelhamer

Bibliographic record

VenueJournal of Perinatology · 2022
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsnot available
FundersGrand Challenges CanadaUppsala UniversitetLaerdal Foundation for Acute Medicine
KeywordsMedicineCord clampingBradycardiaNeonatologyPediatricsCordGestational ageAnesthesiaObstetricsPregnancyHeart rateInternal medicineSurgeryBlood pressure

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare HR pattern of vigorous newborns during the first 180 s with early (≤60 s, ECC) or delayed (>60 s, DCC) cord clamping. STUDY DESIGN: Observational study including dry-electrode ECG monitoring of 610 vaginally-born singleton term and late-preterm (≥34 weeks) who were vigorous after birth. RESULTS: 198 received ECC while 412 received DCC with median cord clamping at 37 s and 94 s. Median HR remained stable from 30 to 180 s with DCC (172 and 170 bpm respectively) but increased with ECC (169 and 184 bpm). The proportion with bradycardia was higher among ECC than DCC at 30 s and fell faster in the DCC through 60 s. After adjusting for factors affecting timing of cord clamping, ECC had significant risk of bradycardia compared to DCC (aRR 1.51; 95% CI; 1.01-2.26). CONCLUSION: Early heart instability and higher risk of bradycardia with ECC as compared to DCC supports the recommended clinical practice of DCC.

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)0.004
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0010.000

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 head0.012
GPT teacher head0.276
Teacher spread0.264 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of PerinatologySame topicNeonatal and fetal brain pathologyFrench-language works237,207