Central diabetes insipidus and pain medications – a risky combination
Bibliographic record
Abstract
BACKGROUND: Central Diabetes Insipidus (CDI) results from decreased production of antidiuretic hormone (ADH) leading to an inability to concentrate urine. CDI is treated with desmopressin (DDAVP). Rarely reported in the literature, opioids and non-steroidal anti-inflammatories (NSAIDs) can induce hyponatremia in individuals treated for CDI. CASE PRESENTATION: A 10-year-old boy with septo-optic dysplasia and CDI was treated with DDAVP 1.6 mg orally TID maintaining normal sodium levels. Post admission for a femur fracture, he was discharged on ibuprofen and hydromorphone. Sodium was 136 mmol/l two days before discharge. He returned to the ED after having a seizure at home. He was euvolemic and mildly lethargic. Sodium was low at 108 mmol/l. DDAVP and hydromorphone were held and he was fluid restricted, but the sodium remained low. Sodium began to rise when Ibuprofen was stopped. Intermittent small doses of DDAVP were given to facilitate gradual correction of hyponatremia. At discharge, sodium had normalized. CONCLUSION: Hyponatremia has occasionally been described as a side effect of opioids and rarely of NSAIDs in patients with CDI. Stimulation of the thirst centre may play a role with opioids while a decrease in urine output may be the mechanism with NSAIDs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".