Intrapartum sonography for fetal head asynclitism and transverse position: sonographic signs and comparison of diagnostic performance between transvaginal and digital examination
Bibliographic record
Abstract
OBJECTIVE: The primary goal of this study was to determine the ultrasonographic signs of asynclitic and transverse head positioning. In addition, we compared the performance of intrapartum ultrasound to vaginal digital examination. MATERIAL & METHODS: 150 women were evaluated by 2D transabdominal and translabial ultrasound (US) to detect the asynclitic and deep transverse positions. Transvaginal sterile digital examinations were performed immediately after each intrapartum US assessments, the examinations were repeated at intervals of 45-90 minutes. Examiners were blinded to each other's findings (clinical or sonographic). Data were reviewed and analyzed by an independent reviewer. RESULTS: The efficacy of digital examination was significantly lower than US evaluation for the detection of either transverse position or asynclitism. The most frequent transverse position was the left one, while the most frequent asynclitism was the anterior one. CONCLUSIONS: Digital pelvic examination for detection of fetal head transverse position during labor is inferior to US, especially in the deep transverse positioning, where caput succedaneum occurs and reduces the diagnostic accuracy of vaginal digital examination. The US examination leads to early detection of persistent transverse position allowing for earlier timing and optimal technique for the operative vaginal delivery. We describe two signs for diagnosing asynclitism. The "squint sign" and the "sunset of thalamus and cerebellum signs" are two simple US signs allowing detection of anterior and posterior asynclitism.
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 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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".