The Association between the Level of Ankle-Brachial Index and the Risk of Poor Physical Function in Patients with Cardiovascular Disease
Bibliographic record
Abstract
AIMS: The progression of atherosclerosis and decline in physical function are poor prognostic factors in patients with cardiovascular disease (CVD). The ankle-brachial index (ABI) is a widely used indicator of the degree of progression of atherosclerosis, which may be used to identify patients with CVD who are at risk of poor physical function. This study examined the association between ABI and poor physical function in patients with CVD. METHODS: We reviewed the data of patients with CVD who completed the ABI assessment and physical function tests (6-min walking distance, gait speed, quadriceps isometric strength, and short physical performance battery). Patients were divided into five categories according to the level of ABI, and the association between ABI and poor physical function was examined using multiple logistic regression analysis. Additionally, restricted cubic splines were used to examine the nonlinear association between ABI and physical function. RESULTS: A total of 2982 patients (median [interquartile range] age: 71[62-78] years, 65.8% males) were included in this study. Using an ABI range of 1.11-1.20 as a reference, logistic regression analysis showed that ABI ≤ 1.10 was associated with poor physical function. The restricted cubic spline analysis showed that all physical functions increased with an increase in ABI level. The increase in physical function plateaued at an ABI level of approximately 1.1. CONCLUSIONS: ABI may be used to identify patients with poor physical function. ABI levels below 1.1 are potentially associated with poor physical function in patients with CVD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".