Changes in renal and metabolic indices after switching from tenofovir disoproxil fumarate– to tenofovir alafenamide–containing ART among individuals with HIV in Canada: A retrospective study
Bibliographic record
Abstract
We assessed renal and metabolic changes associated with switching from tenofovir disoproxil fumarate (TDF)– to tenofovir alafenamide (TAF)–containing regimens among patients with HIV at the Maple Leaf Medical Clinic, Toronto, Canada. Using an electronic medical records retrospective chart review from July 2005 to December 2019, 651 patients aged ≥16 years taking TDF-containing regimens for ≥6 months who switched to TAF-containing regimens for ≥6 months were included. Change in estimated glomerular filtration rate (eGFR) was examined at 12-month follow-up. Secondary outcomes included change in urine albumin-to-creatinine ratio, serum phosphate, alkaline phosphatase (ALP), cholesterol markers, HbA1C, and weight. After 12 months, eGFR increased in 63% of the baseline eGFR <60 mL/min/1.73 m<sup>2</sup> group (mean change [SD] = +5.1 [10.8], <i>p</i> = 0.002), 52% for the baseline eGFR = 60–90 mL/min/1.73 m<sup>2</sup> group (+0.5 [10.4], <i>p</i> = 0.490), and 26% for baseline eGFR >90 mL/min/1.73 m<sup>2</sup> group (−7.2 [11.2], <i>p</i> <0.001). The multivariable generalized estimating equations model showed a significant reduction in eGFR after 12 months. Advanced age, HCV coinfection, and being switched to or on integrase inhibitors were significantly associated with reduced eGFR. Among secondary outcomes, ALP significantly decreased, while high-density lipoprotein, low-density lipoprotein, and weight significantly increased. Our findings suggest that TDF-to-TAF switching was beneficial for those with preexisting renal impairment (eGFR <60 mL/min/1.73 m<sup>2</sup>).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".