Management of Fever, Hyperglycemia, and Swallowing Dysfunction following Hospital Admission for Acute Stroke in New South Wales, Australia
Bibliographic record
Abstract
BACKGROUND: Fever, hyperglycemia, and swallow dysfunction poststroke are associated with significantly worse outcomes. We report treatment and monitoring practices for these three items from a cohort of acute stroke patients prior to randomization in the Quality in Acute Stroke Care trial. METHOD: Retrospective medical record audits were undertaken for prospective patients from 19 stroke units. For the first three-days following stroke, we recorded all temperature readings and administration of paracetamol for fever (≥37·5°C) and all glucose readings and administration of insulin for hyperglycemia (>11 mmol/L). We also recorded swallow screening and assessment during the first 24 h of admission. RESULTS: Data for 718 (98%) patients were available; 138 (19%) had four hourly or more temperature readings and 204 patients (29%) had a fever, with 44 (22%) receiving paracetamol. A quarter of patients (n = 102/412, 25%) had six hourly or more glucose readings and 23% (95/412) had hyperglycemia, with 31% (29/95) of these treated with insulin. The majority of patients received a swallow assessment (n = 562, 78%) by a speech pathologist in the first instance rather than a swallow screen by a nonspeech pathologist (n = 156, 22%). Of those who passed a screen (n = 108 of 156, 69%), 68% (n = 73) were reassessed by a speech pathologist and 97% (n = 71) were reconfirmed to be able to swallow safely. CONCLUSIONS: Our results showed that acute stroke patients were: undermonitored and undertreated for fever and hyperglycemia; and underscreened for swallowing dysfunction and unnecessarily reassessed by a speech pathologist, indicating the need for urgent behavior change.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".