Frequent injection cocaine use increases the risk of renal impairment among hepatitis C and HIV coinfected patients
Bibliographic record
Abstract
OBJECTIVE: To examine the association between injection cocaine use, hepatitis C virus (HCV) infection, and chronic renal impairment (CRI). DESIGN: Prospective observational cohort study of HIV-HCV coinfected patients. METHODS: Data from 1129 participants in the Canadian Co-Infection Cohort with baseline and follow-up serum creatinine measurements between 2003 and 2014 were analyzed. Prevalent and incident cohorts were created to examine the association between self-reported past, current, and cumulative cocaine use and chronic HCV with CRI. CRI was defined as an estimated glomerular filtration rate below 70 ml/min per 1.73 m. Multivariate logistic regression was used to calculate odds ratios, and discrete-time proportional-hazards models were used to calculate hazard ratios for cocaine use, in the two respective cohorts, adjusted for HCV RNA and important demographic, HIV disease stage, and comorbidity confounders. RESULTS: Eighty-seven participants (8%) had prevalent CRI. Past injection cocaine use was associated with a two-fold greater risk of prevalent CRI [odds ratio 2.03, 95% confidence interval (CI) 0.96, 4.32]. During follow-up, 126 of 1061 participants (12%) developed incident CRI (31 per 1000 person-years). Compared to nonusers, heavy (≥ 3 days/week) and frequent injection cocaine users (≥75% of follow-up time) experienced more rapid progression to CRI (hazard ratio 2.65, 95% CI 1.35, 5.21; and hazard ratio 1.82, 95% CI 1.07, 3.07, respectively). There was no association between chronic HCV and CRI in either cohort. CONCLUSION: After accounting for HCV RNA, frequent and cumulative injection cocaine abuse was associated with CRI progression and should be taken into consideration when evaluating impaired renal function in HIV-HCV coinfection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".