Placental Molar Disease
Bibliographic record
Abstract
The molecular cytogenetic analysis of specimens (genotyping) suspicious for hydatidiform mole (HM) significantly improves diagnostic accuracy over histopathology and immunohistochemical analysis alone, particularly in the classification of partial mole. However, the implementation of this advance in diagnostics has been slow. This study sought to identify the major benefit and potential barriers to the adoption of genotyping. A pilot Placental Molar Diagnostic (PMD) Service was established combining histopathology, p57 immunohistochemistry, and molecular genotyping analysis for both in-house and referred-in cases suspicious for HM or with a preliminary diagnosis of HM. A retrospective analysis of 117 cases received in the first 16 mo was conducted to identify the utility of the PMD Service and factors or barriers which precluded optimal results. A final diagnosis of HM was made in 73 cases (37 complete HMs and 36 partial HMs). The remaining 44 cases were hydropic abortuses. Three potential barriers were identified that could lead to less than optimal results from a PMD Service: prevalence of noninformative genotyping, lack of any available or appropriate paraffin blocks, and inappropriate deferral of genotyping. The major utility of this pilot PMD Service was to increase the specificity of a diagnosis of HM, and avoid unnecessary clinical follow-up in 37% of cases with an initial suspicion or diagnosis of HM. Measures can be undertaken to address potential barriers to the implementation of a comprehensive placental diagnostic platform. Underutilization of molecular genotyping in the diagnosis of HM likely leads to inappropriate management and "downstream" costs in a significant proportion of patients suspected of having HM.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".