Incidence, clinical features and outcomes of atrial fibrillation and stroke in Qatar
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation is an important risk factor for stroke but there are limited data on atrial fibrillation-related stroke from the Middle East. METHODS: We interrogated the Qatar Stroke Database to establish the occurrence, clinical features, and outcomes of atrial fibrillation-related stroke at Hamad General Hospital, the sole provider of acute stroke care in Qatar. RESULTS: A total of 4079 patients (81.4% male, mean age 55.4 ± 13.3 years) were enrolled in the stroke database between January 2014 and 21 October 2017. Atrial fibrillation was present in 260 (6.4%) patients, of whom 106 (2.6%) had newly diagnosed atrial fibrillation. The National Institute of Health Stroke Scale (NIHSS) was significantly higher (7.9 + 7.0 (median 6; IQR 11) vs. 5.9 + 6.4 (median 4; IQR 6), P < 0.001) in atrial fibrillation patients. The modified Rankin Score (mRS) (P < 0.001) and mortality at 90-day follow-up (P = 0.002) were significantly higher in atrial fibrillation compared to non-atrial fibrillation stroke patients. CONCLUSION: We demonstrate a low rate of atrial fibrillation and stroke in Qatar, perhaps reflecting the relatively young age of these patients. Atrial fibrillation-related strokes had higher admission NIHSS, greater disability, and higher mortality at 90 days when compared to non-atrial fibrillation strokes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".