Treatment and long-term outcome in primary nephrogenic diabetes insipidus
Bibliographic record
Abstract
BACKGROUND: Primary nephrogenic diabetes insipidus (NDI) is a rare disorder and little is known about treatment practices and long-term outcome. METHODS: Paediatric and adult nephrologists contacted through European professional organizations entered data in an online form. RESULTS: Data were collected on 315 patients (22 countries, male 84%, adults 35%). Mutation testing had been performed in 270 (86%); pathogenic variants were identified in 258 (96%). The median (range) age at diagnosis was 0.6 (0.0-60) years and at last follow-up 14.0 (0.1-70) years. In adults, height was normal with a mean (standard deviation) score of -0.39 (±1.0), yet there was increased prevalence of obesity (body mass index >30 kg/m2; 41% versus 16% European average; P < 0.001). There was also increased prevalence of chronic kidney disease (CKD) Stage ≥2 in children (32%) and adults (48%). Evidence of flow uropathy was present in 38%. A higher proportion of children than adults (85% versus 54%; P < 0.001) received medications to reduce urine output. Patients ≥25 years were less likely to have a university degree than the European average (21% versus 35%; P = 0.003) but full-time employment was similar. Mental health problems, predominantly attention-deficit hyperactivity disorder (16%), were reported in 36% of patients. CONCLUSION: This large NDI cohort shows an overall favourable outcome with normal adult height and only mild to moderate CKD in most. Yet, while full-time employment was similar to the European average, educational achievement was lower, and more than half had urological and/or mental health problems.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".