OUTCOMES IN EXTREMELY PREMATURE INFANTS WITH TWIN-TWIN TRANSFUSION SYNDROME TREATED BY LASER THERAPY
Bibliographic record
Abstract
Abstract BACKGROUND Twin pregnancies and fetal therapies are associated with increased risk of preterm delivery. Limited literature exists on outcomes for extremely preterm infants born in the context of a pregnancy complicated with twin-twin transfusion syndrome (TTTS). OBJECTIVES To compare mortality of preterm newborns who received laser therapy for TTTS to preterm controls born in the context of a dichorionic-diamniotic (di-di) pregnancy. Secondary outcomes are: short-term neonatal morbidities and neurodevelopmental measures at 18 months of corrected gestational age (cGA). DESIGN/METHODS Case-control retrospective study of all twins infant born <29 weeks of gestation between 2006 and 2015 at Sainte-Justine Hospital. Preterm with TTTS and fetal laser therapy were compared to preterm di-di twins. Survival analysis was done using Cox proportional regression model. RESULTS Thirty-three preterms with TTTS (TTTS-laser group) were compared to 101 preterms without TTTS (non-TTTS group). Demographic data and comparisons for short-term morbidities are presented in Table 1. TTTS status was not associated with increased mortality when adjusting for birth weight and antenatal steroids (Table 2). No differences were found for Bayley-3rd edition score, cerebral palsy, vision impairment, hearing impairment and growth parameters at 18-month cGA. CONCLUSION Extremely premature newborns exposed to fetal laser therapy due to TTTS had similar survival and neurodevelopmental outcomes compared to contemporaneous extremely preterm di-di twins.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".