Low urine pH is associated with reduced indinavir crystalluria in indinavir-treated HIV-infected individuals
Bibliographic record
Abstract
Indinavir is a potent HIV-1 protease inhibitor included in current antiretroviral therapeutic regimens. It is associated with renal and urological complications ascribed to indinavir crystalluria. We have previously reported that indinavir crystalluria is frequently observed soon after initiation of therapy. In a cohort of 54 asymptomatic indinavir-naive HIV-1-infected individuals during their first year of treatment with indinavir, approximately 25% of urinalyses (U/A) contained indinavir crystals. Because the determinants of the crystalluria are unknown, we examined the relationship between urine specific gravity (SG) and pH, singly and in combination, and indinavir crystalluria in these subjects. A total of 579 U/A were obtained from the study subjects at their scheduled monthly outpatient medical assessments. The frequency of indinavir crystalluria was lower in U/A with lower pH, irrespective of the SG. Conversely, U/A with high pH (> or = 6.0) had a higher frequency of indinavir crystalluria, which was further influenced by the urine SG. As a result, nearly half of the U/A (46.7%) with high pH (> or = 6.0) and intermediate-high SG (> or = 1.015) contained indinavir crystals. In conclusion, the frequency of indinavir crystalluria in asymptomatic HIV-1 infected individuals during their first year of treatment with indinavir was markedly influenced by the urine pH and SG. Our findings suggest that low urine pH may have a protective effect against indinavir crystalluria across the entire range of urine SG.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".