Adiponectin and atherosclerosis risk factors in African hemodialysis patients: A population at low risk for atherosclerotic cardiovascular disease
Bibliographic record
Abstract
Atherosclerotic cardiovascular disease (CVD) is the major cause of morbidity and mortality in hemodialysis (HD) patients. Adiponectin (ADPN), a recently discovered collagen-like protein, is secreted exclusively by adipocytes. It has anti-atherogenic properties and reduced serum ADPN levels have been shown to be predictive of cardiovascular events. In this study, we determined the atherosclerotic risk and the significance of ADPN levels in our HD patients and also examined its relationship to other traditional CVD risk factors. A cross-sectional study of 84 patients on maintenance HD (58 Blacks and 26 non-Blacks) and 63 healthy controls matched for age, sex and race (35 Blacks and 28 non-Blacks) was undertaken. Serum ADPN levels and other risk factors, including blood pressure, serum lipid, and C-reactive protein, were studied in HD patients and were compared with the controls. Carotid artery intima-media thickness and plaque occurrence was measured by B-mode ultrasonography while echocardiography was done according to American Society of Echocardiography guidelines. Serum ADPN levels were higher in the HD group compared with the control subjects (22.19 ± 0.98 mg/mL vs. 9.93 ± 0.68 mg/mL; P < 0.001). Higher ADPN levels in HD patients were associated with lower triglyceride levels. ADPN correlated positively (r = 0.49, P < 0.0001) with left ventricular mass index (LVMI) in the total study population. ADPN levels were raised in HD patients and correlated with LVMI, possibly because of the confounding effect of low glomerular filtration rate. ADPN levels were inversely related to risk factors for atherosclerosis and may provide possible targets for therapeutic interventions.
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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 | 0.000 | 0.001 |
| 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".