Use of local data to enhance uptake of published recommendations: an example from the diagnostic evaluation of precocious puberty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: It has been recommended that basal luteinising hormone (LH) levels be used as the initial test to identify cases of central precocious puberty (CPP) in children. However, in clinical practice, gonadotropin-releasing hormone (GnRH) stimulation tests are frequently still used. OBJECTIVE: To assess the diagnostic utility of a single LH to identify CPP in girls, as a means to safely reduce GnRH stimulation testing rates. DESIGN: Retrospective analysis of patients referred for GnRH stimulation between August 2007 and December 2010, with prospective 12-month follow-up of GnRH stimulation testing rates post implementation of management algorithm. PATIENTS: 57 girls (6.2 ± 2.1 years) with early signs of puberty. MAIN OUTCOME MEASURE: Ability of basal LH to predict clinical pubertal progression, 6 months following the GnRH stimulation test. RESULTS: Pubertal progression occurred in 18 patients. All patients with a basal LH level ≥ 0.3 IU/L had subsequent pubertal progression, while 39 of 41 patients with a basal LH ≤ 0.2 IU/L did not progress, resulting in 100% specificity (95% CI 92% to 100%) and 90.5% sensitivity (69.6% to 98.8%). Using the locally derived algorithm, GnRH stimulation testing was redirected to patients with pubertal progression that was discordant with basal LH data. Post intervention, there was a 75% reduction in GnRH stimulation testing without comprising the rate of diagnosis of CPP. CONCLUSIONS: Our results confirm the diagnostic utility of basal LH levels in the diagnosis of CPP and demonstrate that dissemination and interpretation of local data may facilitate change in clinical practice, resulting in streamlined patient care and cost savings.
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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 | 0.001 | 0.009 |
| 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 | 0.001 |
| Open science | 0.001 | 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 it