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Record W4362733905 · doi:10.1002/ppul.26410

Physical fitness trajectories from childhood to adolescence in extremely preterm children: A longitudinal cohort study

2023· article· en· W4362733905 on OpenAlexaff
Marina Praprotnik, Irena Štucin Gantar, Uroš Krivec, Miha Lučovnik, Jasna Rodman Berlot, Gregor Starc

Bibliographic record

VenuePediatric Pulmonology · 2023
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsEducation and Early Childhood Development
FundersJavna Agencija za Raziskovalno Dejavnost RS
KeywordsMedicineBronchopulmonary dysplasiaPediatricsCohortPercentileCohort studyGestational ageLongitudinal studyPhysical fitnessPhysical therapyPregnancyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objective Cohort studies on physical fitness (PF) in former extremely preterm children are scarce and yield conflicting results. Therefore, this study aimed to assess the effect of extremely preterm birth on PF in school‐age with a focus on bronchopulmonary dysplasia (BPD). Methods Eighty school‐aged children were enrolled in the longitudinal cohort study. Fifty were born extremely preterm ( Results Preterm children with BPD had significantly and persistently lower PFI than preterm children without BPD and term‐born children throughout primary school age. Their PFI was less than half that of national median values (15.1st–19.7th percentile). Preterm children without BPD experienced progressive improvement in PFI during their school age (from 32.6th to 44.7th percentile of national median PFI values), while the ones with BPD did not. Conclusion Extreme prematurity per se is not a risk factor for lower PF at school age. However, if complicated by BPD, PF is significantly and sustainably reduced.

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)0.002
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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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