Predictive Value of Single or Combined Ultrasound Signs in the Diagnosis of Ovarian Torsion
Bibliographic record
Abstract
OBJECTIVES: To determine predictive values of isolated and combined ultrasound signs in the diagnosis of adnexal torsion. METHODS: This work was a retrospective study of 129 adult female patients who underwent an ultrasound examination followed by a definitive surgical procedure within a 24-hour period to determine whether adnexal torsion was present. RESULTS: The positive predictive value (PPV) of the ultrasound diagnosis of adnexal torsion was 82.2%. The statistically significant ultrasound signs in multivariate logistic regression with single-predictor analyses were relative enlargement of the ovary, an abnormal adnexal position, a twisted vascular pedicle, and the follicular edema "ring sign." Possible combinations of these ultrasound criteria showed high specificities (74%-100%), high PPVs (93%-100%), and lower sensitivities (29%-71%) and negative predictive values (24%-35%). Any combination that included a twisted vascular pedicle or the follicular ring sign as one of the signs had high odds ratios and positive likelihood ratios. CONCLUSIONS: Ultrasound has a high PPV as a first-choice imaging modality in the diagnosis of adnexal torsion. The combinations of the following 4 statistically significant ultrasound signs, consisting of an abnormal position, relative enlargement of the index ovary, a twisted vascular pedicle, and the follicular edema ring sign, substantially narrow the imaging differential diagnosis in such cases. The presence of vascular pedicle twisting and the follicular ring sign was highly associated with a positive ovarian torsion diagnosis, with 100% specificity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".