P221 ANKLE BRACHIAL INDEX AND ASSOCIATION WITH CHRONIC KIDNEY DISEASE IN THE H3 AFRICA KIDNEY DISEASE RESEARCH NETWORK
Bibliographic record
Abstract
Background and Objective: Abnormal ankle brachial index (ABI) is common in patients with chronic kidney disease (CKD). We evaluated the association of ABI, a non-invasive tool to evaluate peripheral arterial disease and arterial stiffness, with CKD among West Africans enrolled in the H3Africa Kidney Disease Research Network (H3AKDRN). Methods: We recruited 9206 participants (5356 with CKD), from Ghana and Nigeria in the H3AKDRN, a multinational case-control study. CKD was defined as estimated glomerular filtration rate of <60 ml/min/1.73m2 and/or albuminuria as albumin/creatinine ratio >3.0 mg/mmol (>30 mg/g) for ≥3months. ABI was divided into low (≤0.9), normal (0.91 – 1.3), and high (>1.3). We assessed low ABI, a marker of peripheral artery disease, and high ABI, the marker of arterial stiffness. We determined association of ABI with CKD by multivariate logistic regression. Results: The mean age of participants was 45.8±15.36 years and 56.3% were males. The prevalence of low ABI was higher in CKD group (32%% versus 16% (control), p=0.013). The prevalence of high ABI was also higher in CKD (15% versus 10.9% (control), p = 0.01). Patients with CKD and low ABI have reduced BMI, low haemoglobin, higher systolic BP and increased albuminuria. Male gender, history of hypertension and diabetes were independently associated with CKD. Higher BMI was associated with reduced odds of CKD (p = < 0.03). After adjustment for covariates, low ABI was associated with CKD, with 26% increased odd (aOR 1.26 (CI, 1.01 – 1.56; p = 0.037)), but high ABI was not associated with CKD (aOR 1.45 (0.88 – 2.38, p = 0.147)). Conclusion: The prevalence of abnormal ankle brachial index is high among adult populations of Ghana and Nigeria, with and without CKD. The Marker of peripheral arterial disease, but not marker of arterial stiffness was associated with CKD. A longitudinal study is required to determine the true relationship between ABI and CKD in West Africa.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".