Correlation of placental laterality and uterine artery Doppler in pre-eclampsia
Bibliographic record
Abstract
Background: Pre-eclampsia is a complex condition associated with maternal and fetal mortality and morbidity. Various screening tests have been proposed for the prediction of pre-eclampsia with varying results. Non-invasive doppler velocimetry studies of uterine arteries in second trimester with abnormal forms can predict the occurrence of pre-eclampsia. This abnormal wave forms indicate defective uterine perfusion and is consequence of placental implantation laterally. The objective of this study was to correlate placental laterality and uterine artery doppler in pre-eclampsia. Methods: It was prospective study from November 2019 to March 2021 at M S Ramaiah medical college and hospitals, Bangalore. Results: In the present study, preeclampsia was seen in 36.5 % with lateral location of placenta, 19.3% with posterior location of placenta and 15.9% with anterior location of placenta. This was statistically significant with p<0.001. Uterine artery doppler, the pulsatality index (PI) was <95th centile in 88.1% and 11.9% had >95th centile The subjects with PI >95th centile, 65.5% developed preeclampsia and <95th centile, 13.1% developed pre-eclampsia. This was statistically significant. In this study, with PI at 1.68, the sensitivity was 53.19%, specificity was 92.86%, positive predictive value (PPV) of 64.1% and negative predictive value (NPV) was 89.2%. Conclusions: USG is a simple, non-invasive, easy to perform and cost-effective method to locate the placenta. Every attempt should be made to do Uterine artery doppler at the same sitting. Both these are non-invasive and can predict the occurrence of pre-eclampsia. These patients can be managed as high risk and monitored more carefully. Surveillance will help in decreasing maternal and perinatal mortality and morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".