Cerebral salt wasting: Truths, fallacies, theories, and challenges
Bibliographic record
Abstract
BACKGROUND: The reported prevalence of cerebral salt wasting has increased in the past three decades. A cerebral lesion and a large natriuresis without a known stimulus to excrete so much sodium (Na ) constitute its essential two elements. OBJECTIVES: To review the topic of cerebral salt wasting. There is a diagnostic problem because it is difficult to confirm that a stimulus for the renal excretion of Na is absent. DESIGN: Review article. INTERVENTION: None. MAIN RESULTS: Three fallacies concerning cerebral salt wasting are stressed: first, cerebral salt wasting is a common disorder; second, hyponatremia should be one of its diagnostic features; and third, most patients have a negative balance for Na when the diagnosis of cerebral salt wasting is made. Three causes for the large natriuresis were considered: first, a severe degree of extracellular fluid volume expansion could down-regulate transporters involved in renal Na resorption; second, an adrenergic surge could cause a pressure natriuresis; and third, natriuretic agents might become more potent when the effective extracellular fluid volume is high. CONCLUSIONS: Cerebral salt wasting is probably much less common than the literature suggests. With optimal treatment in the intensive care unit, hyponatremia should not develop.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".