Influence of Raised Plasma Osmolality on Clinical Outcome After Acute Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Abnormal physiological parameters after acute stroke may induce early neurological deterioration. Studies of the effect of dehydration on stroke outcome are limited. We examined the association of raised plasma osmolality on stroke outcome at 3 months and the change of plasma osmolality with hydration during the first week after stroke. METHODS: Acute stroke patients had their plasma osmolality measured at admission and at days 1, 3, and 7. Maximum plasma osmolality and the area under curve (AUC) were also calculated during the first week. Patients were stratified according to how they were hydrated: orally, intravenously, or both. Outcome included survival at 3 months after stroke. Logistic regression was performed to examine the association between raised plasma osmolality (>296 mOsm/kg) and survival, adjusting for stroke severity. Linear regression was performed to examine the pattern of plasma osmolality across hydration groups. RESULTS: One hundred sixty-seven patients were included. Mean admission (300 mOsm/kg, SD 11.4), maximum (308.1 mOsm/kg, SD 17.1), and AUC (298.3 mOsm/kg, SD 11.7) plasma osmolality were significantly higher in those who died compared with survivors (293.1 mOsm/kg [SD 8.2], 297.7 mOsm/kg [SD 8. 7], and 291.7 mOsm/kg [SD 8.1], respectively; P:<0.0001). Admission plasma osmolality >296 mOsm/kg was significantly associated with mortality (OR 2.4, 95% CI 1.0 to 5.9). In patients hydrated intravenously, there was no significant fall in plasma osmolality compared with patients hydrated orally (P:=0.68). CONCLUSIONS: Raised plasma osmolality on admission is associated with stroke mortality, after correcting for case mix. Correction of dehydration after stroke requires a more systematic approach. Trials are required to determine whether correcting dehydration after stroke improves outcome.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| 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".