Growth patterns of patients with Noonan syndrome: correlation with age and genotype
Bibliographic record
Abstract
BACKGROUND: Growth patterns of patients with Noonan syndrome (NS) were established before the involved genes were identified. OBJECTIVE: The goal of this study was to compare growth parameters according to genotype in patients with NS. SUBJECTS AND METHODS: The study population included 420 patients (176 females and 244 males) harboring mutations in the PTPN11, SOS1, RAF1, or KRAS genes. NS-associated PTPN11 mutations (NS-PTPN11) and NS with multiple lentigines-associated PTPN11 mutations (NSML-PTPN11) were distinguished. Birth measures and height and body mass index (BMI) measures at 2, 5, 10 years, and adulthood were compared with the general population and between genotypes. RESULTS: Patients with NS were shorter at birth (mean birth length standard deviation score (SDS): -1.0 ± 1.4; P < 0.001) and throughout childhood than the healthy population, with height SDS being -2.1 ± 1.3 at 2 years, and -2.1 ± 1.2 at 5 and 10 years and adulthood (P < 0.001). At birth, patients with NS-PTPN11 were significantly shorter and thinner than patients with NSML-PTPN11, SOS1, or KRAS. Growth retardation was significantly less severe and less frequent at 2 years in patients with NSML-PTPN11 and SOS1 than in patients with NS-PTPN11 (P < 0.001 and P = 0.002 respectively). Patients with NS had lower BMI at 10 years (P < 0.001). No difference between genotypes was demonstrated. CONCLUSION: Determining the growth patterns of patients with NS according to genotype should better inform clinicians about the natural course of growth in NS so that they can optimize the follow-up and management of these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".