Early neurological deterioration in acute stroke
Bibliographic record
Abstract
Sir, The recent article by Kwan and Hand 1 highlighted the increasingly recognized fact that early neurological deterioration (progressing stroke) is a common and important complication in acute stroke, which affects long-term prognosis. The authors correctly point out that there is no accepted international definition of early neurological deterioration, but the proposal from the European Progressive Stroke Study (EPSS) appears to be more reliable than alternative definitions. 2 We studied 873 consecutive patients admitted to Glasgow Royal Infirmary over a 2-year period. 3 They had baseline assessments of stroke characteristics and stroke severity. Early neurological deterioration was assessed at day three, using a definition very similar to that of the EPSS. Our results were very similar to those of Kwan and Hand, confirming that patients with early neurological deterioration were more likely to have a poor outcome. We subsequently carried out a logistic regression analysis incorporating the following characteristics: age category (by decade), gender, pre-stroke dependency, history of atrial fibrillation (AF) or diabetes mellitus, severe stroke (Total or Partial Anterior Circulation Stroke), cerebral haemorrhage, adverse physiological complications in the first three days (pyrexia, hypoxia, hypoglycaemia or dehydration) and stage of service development (before or after the opening of the acute stroke unit). The analysis indicated the following were potential independent predictors of the development of early neurological deterioration: age (OR 1.18 per decade, p = 0.04), pre-stroke dependency (OR 1.45, p = 0.065), severe stroke (OR 1.86, p = 0.0007), cerebral haemorrhage (OR 2.57, p = 0.0005), adverse physiological complications (OR 1.49, p = 0.022) and stroke-unit care (OR 0.72, p = 0.072). Gender and a history of AF or diabetes were not independent factors. While our results confirm the observations of Kwan and Hand in a larger dataset, they also provide some hope that improving the quality of care in stroke units may contribute to reducing this serious complication.
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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 | 0.016 |
| 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 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".