Short stature as a screening test for endocrinopathy in slipped capital femoral epiphysis
Bibliographic record
Abstract
Slipped capital femoral epiphysis may be associated with hypothyroidism and other endocrinopathies. Routine screening for such abnormalities is unlikely to be cost-effective since the overall incidence of these disorders, in association with slipped capital femoral epiphysis, is low. The identification of a presenting characteristic which would predict the chance of an associated endocrinopathy would allow only selected children to be screened. Our aim was to determine if certain characteristics were useful as a screen for patients with an underlying endocrinopathy who presented with slipped capital femoral epiphysis. Between January 1988 and December 1996 we recorded gender, age, height, unilateral or bilateral involvement and an associated diagnosis of endocrinopathy for all patients who were treated for slipped capital femoral epiphysis. Of 166 such patients 13 (7.8%) had an endocrinopathy. Height was the only useful screening characteristic, although bilateral involvement was more likely in those with an endocrinopathy. Most (90.9%) of this latter group were below the tenth percentile for height compared with only 5.4% in those who did not have an endocrinopathy (p < 0.005). The sensitivity and negative predictive value of detecting an underlying endocrinopathy in a patient presenting with a slipped capital femoral epiphysis and short stature (tenth percentile or less) were 90.2% and 98.6%, respectively. Patients who are on or below the tenth percentile for height at the time of presentation should be screened for a possible endocrine abnormality using measurement of thyroid-stimulating hormone and free thyroxine as a preliminary screening test. These hormones are most likely to be abnormal in the presence of endocrine dysfunction.
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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 | 0.005 |
| 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".