Comparative Efficacy of Photodynamic Therapy and Cold Knife Conization for Cervical High-Grade Squamous Intraepithelial Lesions
Bibliographic record
Abstract
(1) Background: Photodynamic therapy (PDT) using 5-aminolevulinic acid (5-ALA) offers a non-invasive alternative for managing cervical intraepithelial neoplasia. This comparative study assessed the efficacy and safety of 5-ALA PDT versus cervical conization in treating HSIL. (2) Methods: A total of 137 patients with HSIL and HPV infection, confirmed by pathological biopsy, were included. Based on patient preference and gynecological evaluation, participants were allocated into the PDT group and the CKC group. Follow-up assessments were conducted at 6 months post-treatment, involving HPV testing, cytology, and colposcopy. Additionally, any discomfort or side effects experienced during treatment were documented, along with a preliminary analysis of treatment costs and duration. (3) Results: The overall lesion remission rates were 88.0% for the PDT group and 89.6% for the CKC group, while HPV clearance rates were 80.0% and 82.7%, respectively. Although no statistically significant difference in efficacy was observed between the two groups, the PDT group exhibited a notably lower incidence of side effects. Nevertheless, the PDT group was associated with higher costs and longer treatment duration. (4) Conclusions: These findings indicate that 5-ALA PDT achieves comparable efficacy to CKC in the treatment of HSIL. Therefore, PDT may serve as a valuable therapeutic option for patients seeking fertility preservation or less invasive management strategies.
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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) | 0.001 | 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) | 0.002 | 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".