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Disabilities and health of extremely low‐birthweight teenagers: a population‐based study

2011· article· en· W2121009782 on OpenAlexaboutno aff
Ingibjörg Georgsdóttir, Gígja Erlingsdóttir, Birgir Hrafnkelsson, Ásgeir Haraldsson, Atli Dagbjartsson

Bibliographic record

VenueActa Paediatrica · 2011
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
FundersHáskóli Íslands
KeywordsMedicineQuarter (Canadian coin)PediatricsLearning disabilityLow birth weightPopulationAffect (linguistics)Intellectual disabilityPsychiatryGerontologyPsychologyEnvironmental healthPregnancy

Abstract

fetched live from OpenAlex

AIM: Evaluation of long-term outcome of extremely low-birthweight (ELBW) teenagers born in Iceland in 1991-1995. METHOD: Participants, 30 of 35 ELBW survivors and 30 full term control teenagers (14-19 years), were assessed for disabilities, health problems and learning difficulties. Results of national standardized tests in mathematics and Icelandic language were compared with results of neurodevelopmental assessment at 5 years of age. RESULTS: A quarter of the ELBW teenagers had disabilities. All were initially diagnosed with neurodevelopmental disorders early in life and neurosensory and/or intellectual disabilities were confirmed later in childhood. Chronic lung disorders, neurological problems and psychiatric disorders were most common health problems. Growth parameters were within normal limits for most of the ELBW teenagers. Learning difficulties affected 57% of the ELBW teenagers, 20% attended special education classes and 37% required special teaching. Results of national standardized tests were significantly lower for ELBW survivors and were significantly related to the results of neurodevelopmental assessment at 5 years of age. INTERPRETATION: A quarter of ELBW teenagers have disabilities albeit most of them mild. Chronic health problems and learning difficulties affect many ELBW survivors. Changes with time emphasize need of long-term follow-up.

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 score0.008
Threshold uncertainty score0.419

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 head0.045
GPT teacher head0.278
Teacher spread0.234 · 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

Citations11
Published2011
Admission routes1
Has abstractyes

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