Low Virologic Failure and Drug Resistance among HIV-Infected Patients Receiving Hospital-Based ART While Care and Outreach through Community in Guangxi, China
Bibliographic record
Abstract
OBJECTIVES: To investigate human immunodeficiency virus (HIV) virologic suppression and drug resistance among HIV-infected patients receiving first-line antiretroviral treatment (ART) in hospitals while community care and outreach through local health workers in Guangxi, China. DESIGN: This was a series of cross-sectional surveys from 2004 to 2012 in Guangxi, supported by the Chinese National HIVDR Surveillance and Monitoring Network Working Group. SETTINGS: Guangxi, China. METHODS: Demographic, ART, and laboratory data (CD4(+) cell count, viral load, and drug resistance) were analyzed. Factors associated with virologic suppression were identified by logistic regression analysis. RESULTS: A total of 780 patients were included in this study. The median treatment duration was 20.6 months (IQR 6.6-35.9). Of 780 study participants, 95.4% of patients (744/780) had HIV virologic suppression. Among these, of the 143 patients who were infected through drug injection, only 10 (7.0%) experienced virologic failure, and the overall prevalence of HIV drug resistance was 2.8% (22/789). Factors associated with virologic suppression in the final multivariate models included self-reported missing doses in the past month (compared to not missing doses in the past month, AOR = 0.2, 95% CI: 0.1-0.6) and initial ART regimen without 3TC (compared to initial ART regimen with 3TC, AOR = 0.2, 95% CI: 0.1-0.4). Moreover, the trend chi-square test showed that the proportion of virologic suppression increased over time from 2004 to 2012 (P = 0.002). CONCLUSION: This study first demonstrated that HIV patients infected through various transmission routes can achieve an excellent treatment outcome in hospitals at or above the county level for free first-line ART in Guangxi. It is an important of ART education and adherence to intervention for achieving better treatment outcomes.
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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 | 0.001 |
| 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 | 0.001 | 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".