The risk of sodium overcorrections in severe hyponatremia and the utility of desmopressin: a large retrospective study
Bibliographic record
Abstract
Background: The suggested narrow rate of serum sodium (sNa) correction in hyponatremia can be difficult to respect, leading to overcorrections. Our ability to anticipate the rapidity of correction according to the mechanism of hyponatremia is uncertain. While desmopressin is often used to pause a rapid rise in sNa, its dose-related effect is also not well described. We studied the rate of hyponatremia overcorrections, its prediction and the utility of desmopressin in its management. Methods: We retrospectively reviewed all cases of severe hyponatremia (sNa <120 mmol/L) in a large university hospital that occurred over 10 years. We assessed investigations, causes and treatments. We compared all sNa separated by at least 8 h and calculated correction rates. Significant overcorrection rates were defined by any rise of sNa >9 mmol/L per day sustained over at least 24 h. Results: After exclusions, we found 355 episodes of severe hyponatremia. Low, appropriate and inappropriate antidiuretic hormone (ADH)-defined mechanisms accounted for 17%, 24% and 29% of etiologies, respectively, with the remaining 25% secondary to diuretics and 5% of uncertain causes. First urinary sodium and osmolality were consistent with the final diagnosis in 73%. Significant overcorrections were seen in 45% and were frequent in the setting of low ADH. Desmopressin was given in 82 episodes, more often as a rescue than a preventive measure, with the subsequent sNa dropping by ≥5 mmol/L by 12 h in eight instances. The dose of desmopressin (≥2 µg versus 1 µg) and a higher volume of intravenous free-water coadministration resulted in a clinically meaningful greater reduction in sNa in the following 12 h. Conclusions: Overcorrections in severe hyponatremia are common, mainly when ADH is low. Initial urinary measurements anticipate this risk. Desmopressin effectively halted the rate of correction in a dose-dependent manner. Caution should be given when coadministrating water, which can significantly lower the sNa.
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How this classification was reachedexpand
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 | 0.004 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".