Optimizing antiretroviral regimens in chronic kidney disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: To identify recent data that inform the management of individuals with HIV and chronic kidney disease. RECENT FINDINGS: Several nonnucleoside reverse transcriptase, protease, and integrase strand transfer inhibitors inhibit tubular creatinine secretion resulting in stable reductions in creatinine clearance of 5-20 ml/min in the absence of other manifestations of kidney injury. Progressive renal tubular dysfunction is observed with tenofovir disoproxil fumarate in clinical trials, and more rapid decline in estimated glomerular filtration rate in cohort studies of tenofovir disoproxil fumarate and atazanavir, with stabilization, improvement or recovery of kidney function upon discontinuation. Results from clinical trials of tenofovir alafenamide (TAF) in individuals with chronic kidney disease suggest that TAF is well tolerated in those with mild to moderate renal impairment (creatinine clearance >30 ml/min) but results in very high tenofovir exposures in those on haemodialysis. SUMMARY: Standard antiretroviral regimens remain appropriate for individuals with normal and/or stable, mildly impaired kidney function. In those with chronic kidney disease or progressive decline in estimated glomerular filtration rate, antiretrovirals with nephrotoxic potential should be avoided or discontinued. Although TAF provides a tenofovir formulation for individuals with impaired kidney function, TAF is best avoided in those with severe or end-stage kidney disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".