Atypical Squamous Cells, Cannot Exclude High-Grade Squamous Intraepithelial Lesion
Bibliographic record
Abstract
OBJECTIVE: In the current study, we explore the diagnostic parameters and pitfalls in the follow-up of 123 cases of Pap smears diagnosed as high-grade atypical squamous cells (ASC-H) at our institution. STUDY DESIGN: A computer database search was performed from the archives of the Ottawa Hospital Cytopathology Service for cases diagnosed with ASC-H between January 2003 and July 2005. RESULTS: Follow-up of the 123 cases of ASC-H showed high grade squamous intraepithelial lesion (HSIL) in 73 patients (59.4%), low grade squamous intraepithelial lesion (LSIL) in 11 (8.9%), immature squamous metaplasia in 23 (18.7%), reactive squamous cell changes in 12 (9.8%), benign glandular lesions (endocervical atypia, degenerated glandular cells) in 2 (1.6%) and atrophy in 2 (1.6%). In our study, 83 patients were younger than 40 years (67.4%), with biopsy-proven HSIL found in 54 patients (65.1%). The remaining 40 patients (32.6%) were older than 40 years of age, and follow-up biopsies showed HSIL in 19 patients (47.5%). CONCLUSION: In our study, 59.4% of the cases that were diagnosed cytologically as ASC-H were found to have HSIL on subsequent biopsies. This correlation was stronger in patients below the age of 40 years (65.1% vs. 47.5%). The cytopathologic feature most strongly associated with HSIL was the presence of coarse nuclear chromatin (84%).
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".