Low Bone Mineral Density is Associated with Poor Clinical Outcome in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: Chronic low bone mineral density is associated with an increased risk of stroke. However, little is known about the influence of bone mineral density at the time of stroke on clinical outcome. We investigated the association between bone mineral density and functional disability at three-months in patients with acute ischemic stroke. METHODS: We retrospectively examined consecutive acute ischemic stroke patients who underwent bone densitometry tests within seven-days of stroke symptom onset. Patient demographics, risk factors, and initial National Institute of Health Stroke Scale scores were assessed. Bone mineral density was measured at the lumbar spine and bilateral femoral necks. Osteoporosis was defined as bone mineral density ≤-2·5 T-scores at each site. The primary outcome was modified Rankin Scale at 90 days poststroke. A favorable outcome was defined as modified Rankin Scale 0-1 and poor outcome as modified Rankin Scale 2-6. RESULTS: Of the 191 patients included, 61 (31·9%) were men. Mean age (±standard deviation) was 69·8 ± 11·1 years. Patients with osteoporosis of the right femoral neck were more likely to have poor outcome (25/82; 30·5%) than those without (12/109; 11·0%, P = 0·001). After adjustment for age, sex, and initial National Institute of Health Stroke Scale score, osteoporosis of the right femoral neck was significantly associated with poor outcome (odds ratio, 2·97; 95% confidence interval 1·21 to 7·32, P = 0·018). CONCLUSIONS: Low bone mineral density of the right femur in the acute poststroke period is associated with poor outcome at three-months. Assessment of bone mineral density in acute stroke patients may be a useful prognosticator and facilitate early intervention.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".