Insulin-like Growth Factor 1, but Not Insulin-Like Growth Factor-Binding Protein 3, Predicts Central Precocious Puberty in Girls 6–8 Years Old: A Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Central precocious puberty (CPP) in females is characterized by thelarche before 8 years of age. Evidence of reproductive axis activation confirms the diagnosis (basal serum luteinizing hormone (LH) ≥0.3 IU/L or LH-releasing hormone (LHRH)-stimulated LH ≥5 IU/L). Stimulation testing is the diagnostic gold standard but is time-consuming and costly. Serum levels of insulin-like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein 3 (IGFBP-3) are increased in girls with CPP. OBJECTIVE: The aim of the study was to assess the utility of serum IGF-1 and IGFBP-3 in identifying CPP in girls aged 6-8 years. METHODS: The study was a single-center retrospective study. Girls with confirmed CPP (n = 44) and isolated premature precocious adrenarche/ precocious thelarche (PA/PT, n = 16) had baseline biochemical profiling and LHRH stimulation testing. Serum IGF-1 and IGFBP-3 results were converted to standard deviation scores (SDS). Correlations were calculated and receiver operating characteristic curves were plotted. RESULTS: Girls with CPP had higher basal and peak LH, IGF-1 SDS, and growth velocity (p < 0.05). IGF-1 SDS correlated positively with basal and peak LH (p < 0.05). IGF-1 SDS (1.75-2.15) differentiated CPP and PA/PT with 89% sensitivity and 56% specificity (basal LH) and 94% specificity and 55% sensitivity (peak LH). IGFBP-3 SDS did not differ between groups or by CPP parameters. CONCLUSIONS: In clinical practice, IGF-1 SDS may be an additional tool for identifying CPP in girls aged 6 to 8 years when baseline clinical and laboratory diagnostic criteria are inconclusive, possibly avoiding more time-consuming and costly procedures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".