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Record W2204222903 · doi:10.1017/s0950268815003015

High burden of RSV hospitalization in very young children: a data linkage study

2015· article· en· W2204222903 on OpenAlexaff
Nusrat Homaira, Ju Lee Oei, Kylie‐Ann Mallitt, Mohamed Abdellatif, Lisa Hilder, Barbara Bajuk, Kei Lui, Mark J Ferson, Alma Nurkic, Georgina Chambers, William D. Rawlinson, Tom Snelling, Adam Jaffé

Bibliographic record

VenueEpidemiology and Infection · 2015
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsChildren's & Women's Health Centre of British Columbia
Fundersnot available
KeywordsMedicinePediatricsIncidence (geometry)Bronchopulmonary dysplasiaCohortPopulationEpidemiologyGestational ageCohort studyPregnancyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Linked administrative population data were used to estimate the burden of childhood respiratory syncytial virus (RSV) hospitalization in an Australian cohort aged <5 years. RSV-coded hospitalizations data were extracted for all children aged <5 years born in New South Wales (NSW), Australia between 2001 and 2010. Incidence was calculated as the total number of new episodes of RSV hospitalization divided by the child-years at risk. Mean cost per episode of RSV hospitalization was estimated using public hospital cost weights. The cohort comprised of 870 314 children. The population-based incidence/1000 child-years of RSV hospitalization for children aged <5 years was 4·9 with a rate of 25·6 in children aged <3 months. The incidence of RSV hospitalization (per 1000 child-years) was 11·0 for Indigenous children, 81·5 for children with bronchopulmonary dysplasia (BPD), 10·2 for preterm children with gestational age (GA) 32-36 weeks, 27·0 for children with GA 28-31 weeks, 39·0 for children with GA <28 weeks and 6·7 for term children with low birthweight. RSV hospitalization was associated with an average annual cost of more than AUD 9 million in NSW. RSV was associated with a substantial burden of childhood hospitalization specifically in children aged <3 months and in Indigenous children and children born preterm or with BPD.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.008
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
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 head0.126
GPT teacher head0.416
Teacher spread0.291 · 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

Citations93
Published2015
Admission routes1
Has abstractyes

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