Hystero-salpingo scintigraphy for fallopian tubal patency assessment: results from a prospective study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the diagnostic accuracy of a bygone method, hystero-salpingo-scintigraphy (HSSG), for tubal patency assessment of infertile women. MATERIAL AND METHODS: Prospective cohort study involving women in the infertility workup at the University of Debrecen, Hungary. Seventy infertile patients were scheduled to either basic dynamic HSSG, post-purge dynamic HSSG, or post-purge dynamic HSSG followed by SPECT/CT for reducing tracer contamination. The primary endpoint was the evaluation of the diagnostic accuracy of HSSG for the three methods. RESULTS: During the basic dynamic group, the examination yielded a sensitivity of 87.5%, with a specificity of 71.7%, while positive and negative predictive values were 31.8%, and 97.4% respectively. Using post purge dynamic HSSG, it resulted in a sensitivity of 87.5%, a specificity of 88.7%, a positive predictive value of 53.8%, and a negative predictive value of 97.9%. Adding SPECT/CT to post-purge dynamic HSSG increased diagnostic accuracy with 100% sensitivity and 88.7% specificity, while positive and negative predictive values were 57.1% and 100%, respectively. CONCLUSION: HSSG is a non-invasive and well-tolerated technique for tubal patency. It could be used initially to predict tubal patency in case of infertility. Its diagnostic accuracy is higher when it is carried out by adding SPECT/CT to the post-purge dynamic method.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".