Renal impairment associated with tenofovir disoproxil fumarate for antiretroviral therapy and HIV pre-exposure prophylaxis: An observational cohort study
Bibliographic record
Abstract
BACKGROUND: Tenofovir disoproxil fumarate (TDF) is associated with adverse renal outcomes when prescribed for HIV infection. There are few data concerning real-world renal outcomes amongst patients prescribed TDF for pre-exposure prophylaxis (PrEP). METHODS AND FINDINGS: Data were extracted from 52 sexual health clinics across Australia from 2009-2019. All patients prescribed TDF-containing antiretroviral therapy and PrEP were included. Rates of renal impairment (a fall in eGFR to <60 ml/min/1·73m2) were calculated for people living with HIV (PLWHIV) prescribed TDF and HIV negative PrEP-users. Risk factors were assessed using Cox-proportional hazards models. Sensitivity analysis of risk using 1:1 propensity-score matching to adjust for potential imbalance in HIV and PrEP cohorts was conducted. 5,973 patients on PrEP and 1,973 PLWHIV were included. There were 39 (0.7%) instances of renal impairment in the PrEP group and 81 (4.1%) in the PLWHIV cohort (hazard ratio [HR]:0.35 95% confidence interval [CI]: 0.22-0.56). Rates of renal impairment were 4.01/1000 person-years (95%CI:2.93-5.48) in the PrEP cohort and 16.18/1000 person-years (95%CI:13.01-20.11) in the PLWHIV cohort (p<0.001). Predictors of renal impairment were: older age (40-49 years (HR:5.09 95%CI: 2.12-12.17) and 50-82 years (HR:13.69 95%CI: 5.92-31.67) (compared with 30-39 years) and baseline eGFR<90ml/min (HR:61.19 95%CI: 19.27-194.30). After adjusting for age and baseline eGFR the rate of renal impairment remained lower in the PrEP cohort (aHR:0.62 95%CI: 0.40-0.94, p = 0.023). In propensity-matched analysis using 1,622 patients per cohort the risk of renal impairment remained higher in the PLWHIV cohort (log-rank p = 0.001). CONCLUSION: Patients prescribed TDF-based PrEP had lower rates of renal impairment than patients prescribed TDF for HIV infection. In propensity analysis, after matching for some risk factors, rates of renal impairment remained higher amongst patients with HIV.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".