The Use of DDAVP During Overcorrection of Severe Hyponatremia
Bibliographic record
Abstract
Background: The correction of severe hyponatremia can be challenging. A too slow or rapid pace increases the risk of neurological complications. Current guidelines recommend a serum sodium (sNa) correction rate of ˜6 mmol/L per day. Overcorrection can justify lowering the sNa. Desmopressin (DDAVP) is used to decrease free water excretion and thus stabilize or decrease the sNa but to date, the evidence supporting its use is scarce. We studied sNa trends after subcutaneous (SC) DDAVP administration in cases of severe hyponatremia. Methods: We performed a single-center retrospective cohort study looking at all episodes of hypoosmolar hyponatremia. Every sNa value < 120 mmol/L from 2012 to 2022 was identified and all subsequent serum and urinary sodium and osmolarities were extracted. Spurious cases were excluded. Correction rates between all measurements separated by ≥ 8 hours were calculated and categorized from most to least clinically significant (Table). We also reviewed SC DDAVP administration and sNa trends following it. Results: There were 388 episodes of severe hyponatremia in 356 patients. The correction rates and DDAVP received are listed in the table: 45% of patients had an overcorrection >9 over > 24h. Ninety episodes received DDAVP, 70 of which were followed by a drop in sNa. The average drop in sNa 12 h after receiving doses of 1 mcg (35 doses) and 2 mcg (31 doses) were -0.6 ± 3.5 mmol/L and -2.2 ± 3.1 mmol/L, respectively (p=0.035). Thirteen episodes treated with DDAVP experienced a >6 mmol/L maximal drop in sNa. Conclusions: This cohort highlights frequent sNa overcorrections and the usefulness of SC DDAVP to slow or decrease sNa correction rates. One mcg SC DDAVP stabilized sNa for 12 hours whereas 2 mcg SC resulted in a mean 2 mmol/L decrease. The amount of water ingested must be carefully assessed when using DDAVP, as some experience worrisome drops in sNa. Funding: Private Foundation Support
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".