[Stroke in the very old. Care in neurology units versus others general medical ward].
Bibliographic record
Abstract
INTRODUCTION: The aim of this study is to compare the diagnosis, management, clinical course and outcome of the very major patients with acute stroke in our sanitary area. METHOD: Retrospective collection of data from a hospital-based registry, between January 2002 and March 2004, 130 stroke patients aged 84 and older admitted consecutively. We compared the patients admitted to the neurology unit (NU) to those admitted to other services (GWs). Demographic analysis, risk factors, morbidity to hospital admission (dementia, cancer, previous stroke and laboratory variables), neurological deficit measured for Canadian Neurological Scale (CNS) score, diagnostic studies, length of stay, outcomes variables (in-hospital mortality, complications developed during hospitalization and Rankin scale at hospital discharge) and need for institutionalization were analyzed. RESULTS: from a total of 130 patients, 44 (34,1 %) admitted to NU and 85 (65,9 %) to GWs. No difference was seen in demographic analysis, risk factors, morbidity to hospital admission, neurological deficit and outcomes variables. Length of stay was 8,4 days; 5,5 in the NU and 12,87 days among patients in the GWs (p=0,0001). There are significant differences in diagnostic studies in favor to NU (p < 0,05). Among the patients admitted into GWs the percentage of institutionalization to the discharge was of 28,8 % opposite to 5,6 % in the NU (p=0,006). CONCLUSIONS: There are not evidences of age discrimination for access to neurological units for demographic, risk factors, morbidity or neurological deficit. The diagnostic process is more rigorous and less costly in the NU than in the GWs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".