The Impact of Maternal Body Mass Index on Fetoscopic Laser Surgery for Twin-Twin Transfusion Syndrome
Bibliographic record
Abstract
INTRODUCTION: Both a low and an increased body mass index (BMI) are risk factors for surgical complications. It is less clear whether they also affect the outcomes of fetoscopic procedures. In this manuscript, we aimed to assess the effect of maternal BMI on operative and pregnancy outcomes following fetoscopic laser ablation of placental anastomoses for twin-twin transfusion syndrome (TTTS). METHODS: We retrospectively reviewed all patients with twin pregnancies complicated by TTTS treated with fetoscopic laser surgery at the Ontario Fetal Centre, Toronto, over a 24-year period. Demographic and procedural data as well as pregnancy and delivery outcomes were prospectively collected as part of our quality control program. Patients were divided into 6 groups for BMI at the time of surgery: BMI <20, 20-24.9, 25-29.9, 30-34.9, 35-39.9, and ≥40 kg/m2. Collected variables included demographics, operative characteristics, operative complications, obstetric complications, twin anemia-polycythemia sequence, TTTS recurrence, intrauterine (fetal) death, gestational age at delivery, and survival. Outcomes of all groups were compared to the "normal weight" reference cohort (BMI: 20-24.9 kg/m2). RESULTS: Of 1,012 patients in our database, 859 were twin pregnancies treated with laser for TTTS. Pregnancy outcomes were available for 515. Of all patients, 47% were categorized as normal weight, 3% were underweight, 25% were obese, and 5% had a BMI of >40 kg/m2. Patients with a higher BMI had higher parity (p = 0.0001), longer cervical length (p = 0.008), and a significantly higher TTTS stage (p = 0.0003) at the time of surgery. There were no significant differences between groups in terms of surgical or anesthetic characteristics or perinatal complications. CONCLUSION: BMI does not significantly affect operative or perinatal outcomes in patients undergoing fetoscopic laser ablation for severe TTTS, despite being at a higher stage at diagnosis.
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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 | 0.000 | 0.000 |
| 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".