Cervical Conization for Cervical Intraepithelial Neoplasia (CIN) 2 and 3 in HIV-Positive Women
Bibliographic record
Abstract
OBJECTIVE: The purposes of the study were to investigate the outcomes of cervical conization for cervical intraepithelial neoplasia (CIN) 2 and 3 in HIV-positive women and age-matched HIV-negative controls and to determine whether positive margin, positive endocervical curettage, CD4 count, or viral load was associated with the persistence of CIN 2,3 or residual CIN 2,3 on the specimen from repeat excision procedure or hysterectomy. MATERIALS AND METHODS: HIV-positive women and HIV-negative controls with CIN 2,3 on cervical conization were enrolled in the study. Patients who underwent repeat conization or hysterectomy were identified, and the specimens were evaluated for residual CIN 2,3. CD4 count and viral load within 8 weeks of procedure were analyzed. RESULTS: A total of 44 patients and 44 age-matched controls were identified. Persistent CIN 2,3 was diagnosed in 28 HIV-positive (63.6%) and 14 HIV-negative patients (31.8%; odds ratio [OR] = 4.7, 95% confidence interval [CI] = 1.9-11.5, p < .001). In HIV-positive women, a positive margin was associated with a higher persistence rate after cervical conization (OR = 5.3, 95% CI = 1.17-24.14, p = .03). In HIV-negative patients, positive endocervical curettage was associated with a higher persistence rate after conization (OR = 12, 95% CI = 2.24-64.23, p = .004). Of HIV-positive women, 75% had residual CIN 2,3 on the specimen from repeat procedure compared to 45.2% of controls (OR = 3.6, 95% CI = 1.3-10.6, p = .018). CD4 count or viral load was not associated with the rate of residual disease or persistence rate after cervical conization, but the lowest OR that the sample size allowed to assess with 90% power was 5.02. CONCLUSIONS: HIV-positive women have a higher rate of residual disease and higher persistence rate after conization for CIN 2,3 than age-matched HIV-negative controls.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".