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Frequency of respiratory deterioration after immunisation in preterm infants

2010· article· en· W1953991022 on OpenAlexaff
Douglas F. Hacking, Peter G. Davis, Esther Wong, Kevin Wheeler, Jodie McVernon

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2010
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicinePediatricsContinuous positive airway pressureIncidence (geometry)Odds ratioConfidence intervalCohort studyCohortRespiratory systemMechanical ventilationLow birth weightPregnancyAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

AIM: To determine the relationship between the initiation of respiratory support and the first routine immunisation of neonates at 2 months of age during primary hospitalisation. METHODS: An historical cohort study design was used to study the neonatal factors associated with the initiation of respiratory support within 7 days of immunisation in a cohort of 7629 preterm and term infants admitted to the Neonatal Unit of the Royal Women's Hospital between 2001 and 2008. RESULTS: The 411 infants who received their first immunisations in hospital were both very preterm and of extremely low birth weight (ELBW, below 1000 g). Twenty-two infants experienced post-immunisation apnoea of sufficient severity to warrant the initiation of either intermittent positive pressure ventilation (two cases) or continuous positive airway pressure (20 cases). Infants exhibiting a respiratory deterioration following immunisation had a higher incidence of previous septicaemia (Odds ratio 2.5, 95% confidence interval 1.0, 6.1; P = 0.04) and received CPAP for a longer period prior to vaccination (P = 0.03). CONCLUSION: Apnoea following immunisation may be an aetiological factor in the requirement of respiratory support in a small number of preterm, ELBW infants particularly those with significant lung disease and those who have previously experienced septicaemia.

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)0.002
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 score0.098
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.348
Teacher spread0.326 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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