<p>Lipid profile improvement in virologically suppressed HIV-1-infected patients switched to dolutegravir/abacavir/lamivudine: data from the SCOLTA project</p>
Bibliographic record
Abstract
Introduction: Metabolic disorders are common amongst HIV-infected patients. Data from real-life setting on the impact of DTG/ABC/3TC in virologically suppressed HIV-infected patients are scarce. Methods: We investigated the modification of metabolic profile including fasting glucose, lipid profile and markers of insulin resistance (IR) in experienced patients switching from a boosted protease inhibitors (bPI) or a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen to DTG/ABC/3TC in a prospective, observational, multicenter study. Results: We enrolled 131 HIV-infected patients, of whom 91 (69.5%) males, mean age was 50.5±10.6 years. CDC stage was A in 66 (50.4%) patients, of whom 91 (69.5%) had acquired HIV through sexual contacts. The previous regimen was bPI-based in 79 patients (60.3%) and NNRTI-based in 52 (39.7%). Patients switching from NNRTI showed a significant reduction at week 24 in total cholesterol (TC) and low-density lipoprotein cholesterol (LDL). Triglycerides/high-density lipoprotein cholesterol (TG/HDL) ratio, HDL, median TG and TG/HDL ratio did not show significant modification during follow-up times. Among patients switching from a bPI, we observed a significant reduction in TC and LDL at both follow-up times and a slight increase in HDL. Triglycerides/HDL ratio, median TG and TG/HDL ratio showed a decrease over time that became significant at weeks 24 and 48. Blood glucose levels did not significantly vary during the observation period in patients switching from both bPI and NNRTI-based regimens. Conclusion: Our data suggest an improvement in lipid profile and TG/HDL ratio in pretreated HIV-1-infected patients who switched to DTG/ABC/3TC over 48 weeks, especially in those previously receiving a bPI-based regimen. Keywords: HIV-1 infection, dolutegravir/abacavir/lamivudine, lipid profile
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".