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Record W4414571598 · doi:10.1016/j.bglo.2025.100031

Development of disease-specific growth curves from Kenyan children with sickle cell anemia

2025· article· en· W4414571598 on OpenAlexaff
George Tomlinson, Philippe Backeljauw, George Mochamah, Luke R. Smart, Teresa Latham, Russell E. Ware, Thomas N. Williams

Bibliographic record

VenueBlood Global Hematology · 2025
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsToronto General HospitalUniversity of Toronto
FundersNational Heart, Lung, and Blood InstituteCincinnati Children’s Research FoundationWellcome Trust
KeywordsPercentileSickle cell anemiaCohortBody mass indexAnemiaGrowth curve (statistics)HemoglobinopathyKenyaAnthropometry

Abstract

fetched live from OpenAlex

• The lack of appropriate reference growth curves for children in Africa living with SCA impedes assessment of the effect of therapy on growth. • Our new growth curves, based on a Kenyan cohort with SCA, will provide useful disease-specific references for clinicians and researchers. Sickle cell anemia (SCA) is a life-threatening hemoglobinopathy with worldwide distribution. Featuring multiple acute and chronic complications, SCA is also associated with growth impairment. A lack of appropriate reference data on height, weight, and body mass index (BMI) impedes assessment of the effect of therapies on growth in African children with SCA. The World Health Organization (WHO) growth curves are derived from healthy populations. We analyzed 6095 height and weight paired measurements (2875 in females, 3220 in males; median, 5 measurements/child) from 864 children with SCA, aged 6 months to 19 years, in Kilifi, Kenya. The growth percentile trajectories showed substantial delays when compared with the WHO curves. The female deficits in median height were 7 cm at age 5 years, 11 cm at 10 years, and 13 cm at age 15 years. Male height deficits were 6 cm at 5 years, 10 cm at 10 years, and 21 cm at 15 years. Median weight deficits were 3.4 kg at 5 years and 9.1 kg at 10 years for females, and 3.0 kg at 5 years and 7.7 kg at 10 years for males. The median BMI was lower by 5 kg/m 2 at 15 years for both females and males. These newly developed Kilifi SCA growth curves provide useful disease-specific references for clinicians and researchers.

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 score0.037
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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