Sensitivity and Specificity of the Ankle–Brachial Index to Predict Future Cardiovascular Outcomes
Bibliographic record
Abstract
OBJECTIVE: The ankle-brachial index is the ratio of the ankle and the brachial systolic blood pressure and is used to assess individuals with peripheral arterial disease. An ankle-brachial index <0.90 suggests the presence of peripheral arterial disease and is a marker of cardiovascular risk. The objective of this review is to determine the sensitivity and specificity of an ankle-brachial index <0.90 to predict future cardiovascular events, including coronary heart disease, stroke, and death. METHODS AND RESULTS: We conducted a systematic review of the literature and included studies that used an ankle-brachial index cutoff between 0.80 and 0.90 to classify patients with or without peripheral arterial disease, followed patients prospectively, and recorded cardiovascular outcomes (ie, myocardial infarction, stroke, or mortality). Data were combined using a random-effects model meta-analysis to determine the sensitivity, specificity, relative risks, and likelihood ratios of a low ankle-brachial index to predict future cardiovascular disease. A total of 22 studies were identified, 13 were excluded, and 9 studies were included in the meta-analysis. The sensitivity and specificity of a low ankle-brachial index to predict incident coronary heart diseases were 16.5% and 92.7%, for incident stroke were 16.0% and 92.2%, and for cardiovascular mortality were 41.0% and 87.9%, respectively. The corresponding positive likelihood ratios were 2.53 (95% CI, 1.45 to 4.40) for coronary heart disease, 2.45 (95% CI, 1.76 to 3.41) for stroke, and 5.61 (95% CI, 3.45 to 9.13) for cardiovascular death. CONCLUSIONS: The specificity of a low ankle-brachial index to predict future cardiovascular outcomes is high, but its sensitivity is low. The ankle-brachial index should become part of the vascular risk assessment among selected individuals.
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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 | 0.043 | 0.124 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.030 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".