Retention on third agents in HAART regimens at the Maple Leaf Clinic in Toronto, Ontario, Canada
Bibliographic record
Abstract
This study evaluated the 12‐month retention rate of third agents in HAART (highly active anti‐retroviral therapy) regimens in routine clinical practice in a Canadian HIV clinic. This is a descriptive retrospective database analysis of HIV‐positive patients naïve to antiretroviral therapy (ART). The study included male and female HIV patients≥18 years of age at HAART initiation date, seen in routine consultation at the Maple Leaf Medical Clinic (MLMC), Toronto, Ontario, Canada. Data were extracted from the MLMC database for the period of September 1st, 2003 to August 31st, 2010 for patients who commenced a protease inhibitor (PI), a non‐nucleoside reverse‐transcriptase inhibitor (NNRTI), or an integrase inhibitor (II) ‐based regimen in combination with two nucleoside reverse transcriptase inhibitors (NRTI). Demographic and baseline disease characteristics were extracted and include age, gender, disease duration, baseline HIV‐1 RNA count, CD4 cell count, and hepatitis B and C co‐infection status at baseline. A total of 722 patients were included in the analysis. The primary outcome of the study was the proportion of HIV patients remaining on their initial third agent (PI, NNRTI, or II) at one year post‐treatment initiation. For therapies used by more than 10% of patients (efavirenz [EFV]=315, atazanavir [ATV]=104, lopinavir [LPV]=162, as other agents were used but in limited numbers), the percentage of patients still on the initial third agents at one year was 77%, 64% and 62%, respectively. In addition, viral load (VL) was less than 50 copies/mL in 95% of EFV, 79% of ATV and 76% of LPV patients at one year. The rate of discontinuation at 12 months from EFV, ATV, and LPV due to efficacy (i.e. lack of virologic suppression) or safety (i.e. adverse events) were 15.56%, 19.23%, and 19.75% respectively. In a clinical practice setting, the majority of patients treated with HAART regimens were maintained on therapy at one year and were able to suppress their viral load consistently. Of those reported here, EFV resulted in the best retention rate and viral suppression overall.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".