OP13.05: Stage I Twin–twin transfusion syndrome: a North American Fetal Therapy Network (<scp>NAFTNet</scp>) retrospective cohort study
Bibliographic record
Abstract
Describe the natural history of stage I Twin–twin transfusion syndrome (TTTS), assess for predictors of disease behaviour, and compare pregnancy outcomes after treatment at stage I versus expectant management. 10 NAFTNet centres participated in the study. Cases were retrospectively divided into two management strategies: those initially managed expectantly and those initially treated at stage I. Outcomes included number of survivors to birth and Good (twin live birth ≥ 30.0 weeks), Mixed (single fetal demise or delivery between 26.0 and 29.9 weeks) or Poor (double fetal demise or delivery < 26.0 weeks) outcome categories. Outcomes were analysed by initial management strategy. 124 cases of stage I TTTS were studied. 49 (40%) cases were managed expectantly while 75 (60%) were treated at stage I (30 amnioreductions and 45 laser photocoagulations). 50 out of 248 fetuses died (20%). Of those managed expectantly, 11(22%) regressed, 4(8%) remained stage I, 29(60%) advanced in stage, and 5(10%) experienced spontaneous previable births during observation. A change in status was noted on average after 11.1 days (SD 14.3 days). Both amnioreduction and laser therapy at stage I decreased the likelihood of no survivors to birth (OR 0.11, 95% CI 0.02-0.68 and 0.07, 95% CI 0.01-0.37, respectively). Only laser, however, was protective against Poor outcome (OR 0.12, 95% CI 0.03-0.44 for laser versus 0.29, 95% CI 0.07-1.30 for amnioreduction). Adjusting for pregnancy characteristics had little effect on the odds ratio. Stage I Twin–twin transfusion syndrome was associated with substantial fetal mortality. Spontaneous resolution was observed, although the majority of expectantly managed cases progressed. Both amnioreduction and laser therapy decreased the chance of no survivors, whereas only laser was protective against a poor outcome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".