Bibliographic record
Abstract
Background 200 million patients undergo noncardiac surgery every year. Overt stroke after noncardiac surgery is not common, but has a substantial impact on duration and quality of life. Covert stroke in the nonsurgical setting is much more common than overt stroke, and associated with an increased risk of cognitive decline and dementia. Little is known about covert stroke after noncardiac, noncarotid artery surgery. Methods We undertook a prospective cohort pilot study to inform the incidence of covert stroke after noncardiac, noncarotid artery surgery, and to determine the feasibility of a full prospective cohort study to characterize the epidemiology of perioperative covert stroke. Patients underwent a brain MRI study between postoperative days 3-10, and were followed up at 30 days after surgery. Results of the pilot study We enrolled a total of 100 patients from 6 centres in 4 countries, demonstrating excellent recruitment and no loss to follow-up at 30 days after surgery. The incidence of perioperative covert stroke was 10.0% (10/100 patients, 95% confidence interval 5.5% to 17.4%). Full study protocol We describe a proposal for a prospective cohort study of 1,500 patients. An MRI study of the brain will be performed between postoperative days 2 and 9. The primary outcome is cognitive function, measured 1 year after surgery using the Montreal Cognitive Assessment tool. We will perform multivariable logistic regression analysis where the dependent variable is the change in cognitive function 1 year after surgery, and the independent variables are incidence of perioperative covert stroke and other risk factors for cognitive decline. Conclusions This international multicentre pilot study suggests that 1 in 10 patients ≥65 years of age experiences a perioperative covert stroke. The proposed protocol describes a larger study which will determine the impact of perioperative covert stroke on patient-important outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 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 teacher head, 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".