Current models of care for disorders of sex development – results from an International survey of specialist centres
Bibliographic record
Abstract
BACKGROUND: To explore the current models of practice in centres delivering specialist care for children with disorders of sex development (DSD), an international survey of 124 clinicians, identified through DSDnet and the I-DSD Registry, was performed in the last quarter of 2014. RESULTS: A total of 78 (63 %) clinicians, in 75 centres, from 38 countries responded to the survey. A formal national network for managing DSD was reported to exist in 12 (32 %) countries. The paediatric specialists routinely involved in the initial evaluation of a newborn included: endocrinologist (99 %), surgeon/urologist (95 %), radiologist (93 %), neonatologist (91 %), clinical geneticist (81 %) and clinical psychologist (69 %). A team consisting of paediatric specialists in endocrinology, surgery/urology, clinical psychology, and nursing was only possible in 31 (41 %) centres. Of the 75 centres, 26 (35 %) kept only a local DSD registry and 40 (53 %) shared their data in a multicentre DSD registry. Attendance in local, national and international DSD-related educational programs was reported by 69, 78 and 84 % clinicians, respectively. Participation in audits/quality improvement exercises in DSD care was reported by 14 (19 %) centres. In addition to complex biochemistry and molecular genetic investigations, 40 clinicians (51 %) also had access to next generation sequencing. A genetic test was reported to be more preferable than biochemical tests for diagnosing 5-alpha reductase deficiency and 17-beta hydroxysteroid dehydrogenase 3 deficiency by 50 and 55 % clinicians, respectively. CONCLUSION: DSD centres report a high level of interaction at an international level, have access to specialist staff and are increasingly relying on molecular genetics for routine diagnostics. The quality of care provided by these centres locally requires further exploration.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".