Management of Cervical Neoplasia: A 13-Year Experience with Cryotherapy and Laser
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether cryotherapy is as effective as laser therapy in treating cervical intraepithelial neoplasia (CIN), and to determine the optimal time for follow up. MATERIALS AND METHODS: Patients with biopsy-proven CIN were treated with cryotherapy or laser therapy. Specific data, including grade of CIN, rate of recurrence, and time to recurrence, were compared between the groups. RESULTS: From 2240 eligible patients, 1126 were treated with laser and 1114 with cryotherapy. Ninety-two percent of patients in the laser group and 91.6% in the cryotherapy group had no evidence of CIN after a median follow up of 60 months. The 183 patients with recurrent/persistent disease were retreated with the same treatment modality as initially received. Eighty-seven of the 90 (96.7%) patients retreated with laser and 90 of the 93 patients (96.8%) retreated with cryotherapy had no further evidence of CIN. The majority (128 out of 183; 75.4%) of recurrent/persistent disease was detected within 18 months after treatment. CONCLUSIONS: CIN can be treated with similar success by cryotherapy or laser ablation. Optimal follow up would be two years for CIN1 lesions and five years for CIN2/3 lesions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.003 | 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 teacher head, 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".