Bibliographic record
Abstract
OBJECTIVE: To estimate the incidence and factors associated with combined vaginal-cesarean delivery in twin pregnancies. METHODS: We studied all twin births weighing 500 g or more during a 20-year period (1980-1999) at a tertiary care center. Major anomalies, monoamniotic and conjoined twins, and antepartum fetal deaths were excluded. RESULTS: During this 20-year period, 105,987 women delivered, of whom 1565 (1.5%) had twins. Of these, 1151 twin sets fulfilled the study criteria. The mode of delivery was vaginal in 653 (56.8%), cesarean in 448 (38.9%), and vaginal-cesarean in 50 (4.3%). During the 20 years there was a statistically significant increase in combined vaginal-cesarean and elective cesarean deliveries, with a decrease in vaginal deliveries. Parity, gestational age, and birth weight discordance (>25%) were not associated with combined delivery. Compared with vaginal delivery, the nonvertex second twin was associated with a twofold higher risk of cesarean delivery (relative risk [RR] 2.3; 95% confidence interval [CI] 1.3, 3.8; P =.002); and an interdelivery interval of over 60 minutes with an eightfold higher risk (RR 8.2; CI 4.6,14.6; P <.001). Vaginal-cesarean delivery had a 22-fold higher use of general anesthesia compared with vaginal delivery (RR 21.8; CI 5.4, 88.5; P <.001). CONCLUSION: There has been a significant increase in combined vaginal-cesarean and elective cesarean deliveries among twin gestations, with a decrease in vaginal births. Vaginal-cesarean delivery is associated with nonvertex second twin and a prolonged interdelivery interval.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".