Long-Term Follow-up of a Cohort of HIV-Infected Patients Who Discontinued Maintenance Therapy for Cytomegalovirus Retinitis
Bibliographic record
Abstract
PURPOSE: To determine the long-term safety of discontinuation of maintenance therapy for cytomegalovirus retinitis (CMVR) and to identify predictors for relapse. METHOD: This was a prospective cohort study. Patients with treated CMVR who responded to HAART were followed by ophthalmologic assessment, markers for CMV replication (blood and urine cultures, CMV antigenemia, CMV DNA by PCR), and in vitro lymphoproliferative responses to CMV and other antigens after discontinuation of CMVR maintenance therapy. RESULTS: 23 patients were followed a median of 34 (range, 5-61) months. Median CD4 count was 321/mm3 at enrollment and 395/mm3 at last follow-up. HIV RNA was <50 copies/mL in 78% of patients at enrollment and 65% at last follow-up. One CMVR reactivation occurred at 12 months at a CD4 count of 395/mm3 (21%) and HIV RNA <50 copies/mL. Urine cultures were a poor predictive marker for reactivation. Other CMV replication markers had good negative predictive value. 96% of patients had a good lymphoproliferative response to CMV antigen in vitro. CONCLUSION: Maintenance therapy for CMVR can safely be discontinued in patients who have responded to HAART. Combining our results with the published literature, the risk of reactivation is estimated at 0.016 per person year of follow-up. Markers to predict relapse and the need for re-initiation of maintenance therapy are not yet identified.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".