Prediction of Intraperitoneal Adhesions in Repeated Cesarean Deliveries with Stria Gravidarum Scoring System: A Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: The preoperative prediction of intraperitoneal adhesion (IPA) before repeated cesarean deliveries (CD), which are becoming more prevalent, is crucial for maternal health. AIM: The aim of the study was to preoperatively predict IPA in repeated CD with the stria gravidarum (SG) scoring system. METHODS: A total of 167 patients with at least one previous CD at or beyond 37 weeks of gestation were analyzed. Preoperative SG was calculated according to the Davey scoring system: 0-2 score were defined as mild SG (Group 1; n: 94, 56.2%), and 3-8 score were defined as severe SG (Group 2; n = 73, 43.8%). Preoperative previous cesarean incision features were evaluated according to the Vancouver scar scale. IPA was evaluated according to the Nair's and modified Nair's scoring systems. RESULTS: Parity, younger age at first pregnancy, higher body mass index, number of previous CDs, rate of scar symptoms, Nair's and the modified Nair's scores were statistically significant in Group 2 (P = 0.01; P = 0.04; P = 0.007; P = 0.004; P < 0.001; P = 0.007; P = 0.02, respectively). Davey score ≥3 and Vancouver score ≥4.5 were determined as the cut-off value to predict IPA (P = 0.1 and 0.07, respectively). According to multivariate analysis, both Davey and Vancouver scores are independent factors in predicting IPA (P = 0.02 and 0.04, respectively). CONCLUSION: Evaluating the SG score through the Davey score in women with a history of previous CD may assist in predicting IPA status before the planning of a subsequent surgery.
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 | 0.005 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".