Brief Report: Frequency of Monitoring Kidney Function in HIV-Uninfected Persons Using Daily Oral Tenofovir Disoproxil Fumarate Pre-exposure Prophylaxis
Bibliographic record
Abstract
BACKGROUND: Wide-scale implementation of oral tenofovir-based pre-exposure prophylaxis (PrEP) for HIV prevention is now policy in many settings. However, the optimal frequency for monitoring kidney function remains uncertain. We investigated the impact of 6-monthly compared with 3-monthly creatinine clearance (CrCl) monitoring on the identification of moderate kidney dysfunction, defined as CrCl <60 mL/min. METHODS: Data were from 2 prospective daily oral PrEP studies in Kenya and Uganda: the Partners PrEP Study, a randomized safety, and efficacy trial of PrEP that conducted 3-monthly CrCl monitoring (n = 4404) and the Partners Demonstration Project (n = 954), an open-label delivery study of PrEP that used 6-monthly monitoring. CrCl ≥60 mL/min was required for enrollment in both studies. Abnormal results were followed with confirmatory testing within approximately 1 week. Follow-up was for up to 24 months. RESULTS: Of 5358 participants included in the analysis, 87% were younger than 45 years, a third were female, and 21% had a baseline CrCl between 60 and 90 mL/min. Confirmed CrCl <60 mL/min events were rare, occurring in 52 individuals (<1%) in 24 months. The 12-month cumulative proportion of persons with CrCl <60 mL/min was 0.2% with 3-monthly screening and 0.5% with 6-monthly screening. Older age (>45 years), lower weight (<55 kg), elevated blood pressure (>140 mm Hg), and baseline CrCl between 60 and 90 mL/min were independently associated with CrCl decline <60 mL/min during follow-up. CONCLUSIONS: In these 2 PrEP studies, with generally young participants, the occurrence and pattern of clinically relevant decline in CrCl were not qualitatively different based on 3- or 6-monthly CrCl monitoring schedule. These data suggest that for most persons receiving PrEP for up to 24 months, less frequent CrCl monitoring would be safe and reduce required expenditures for repeat confirmatory testing.
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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 | 0.002 | 0.010 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".