Pre-operative Predictors of Survival in Twin-Twin Transfusion Syndrome Undergoing Fetoscopic Laser Treatment
Bibliographic record
Abstract
INTRODUCTION: Limited data exist regarding the effect of pre-operative risk factors on fetal survival for patients undergoing fetoscopic laser photocoagulation (FLP) for twin-twin transfusion syndrome (TTTS). The primary objective of this study was to determine the pre-operative variables predictive of single and dual fetal survival at birth for subjects treated with laser for TTTS. The secondary objective was to determine the combined effect of multiple risk factors on single and dual fetal survival at birth. METHODS: This was a prospective cohort study of TTTS pregnancies treated with FLP between 2001 and 2023. Cases were identified through the Monochorionic Twin Pregnancy Registry of the North American Fetal Therapy Network. Several pre-operative risk factors were evaluated, including maternal body mass index, gestational age at laser, fetal growth restriction (FGR), cervical length, placental location, and TTTS stage. Higher order multiples, fetal anomalies, karyotypic abnormalities, and cases with missing data were excluded. Risk factors influencing survival were assessed with uni- and multi-variate regression analyses. The predicted probability of single/dual survival based on these risk factors was assessed with multiple logistic regression analysis. RESULTS: Of 2,728 FLP cases, 1,066 met inclusion criteria. Dual survival is reduced in stage 3 and 4 disease compared to stage 1 and 2 (OR 0.75: 0.58, 0.98; p = 0.032) with the lowest survival in all stages occurring with FGR. An anterior placenta (aOR 0.58: 0.37, 0.91; p = 0.017) and FGR <10th percentile (aOR 0.57: 0.35, 0.92; p = 0.02) were independent predictors of reduced survival. With regression modeling, sequential addition of any pre-operative risk factor progressively reduces survival of at least one or both twins. CONCLUSIONS: In this large registry, anterior placental location and FGR were most predictive of reduced survival for both twins. As the number of pre-operative risk factors increases for a given TTTS case, there is a progressive reduction in survival probability and these reported probability rates may be useful in counseling patients.
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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".