10 The use of speckle tracking echocardiography to assess myocardial performance in monochorionic diamniotic twins with and without twin to twin transfusion syndrome
Bibliographic record
Abstract
Purpose Data on myocardial performance in monochorionic diamniotic (MCDA) twins during the early neonatal period is lacking. These infants are at risk of developing twin to twin transfusion syndrome (TTTS). We aimed to assess myocardial function using speckle tracking echocardiography (STE) in MCDA twins with and without TTTS. We hypothesise that infants exposed to TTTS would exhibit lower values for strain and strain rate measured using (STE) during the early neonatal period. Methods We performed a prospective observational study of 4 twin groups: Uncomplicated MCDA, MCDA twins with selective IUGR, MCDA with TTTS in receipt of SLPCV (MCDA and LASER) and MCDA twins with TTTS not receiving SLPCV (MCDA no LASER). Serial echocardiography was performed on day one, day two and between days 5–7 of life. Assessment of myocardial performance included the use of STE. Results Forty seven twin pairs were enrolled in the study: 21 uncomplicated MCDA; 14 selective IUGR; 6 TTTS no LASER, and 6 TTTS and LASER. Recipient TTTS no LASER infants had lower LV and RV strain (which persisted throughout the first week. Function measurements in the TTTS no LASER donor group were significantly higher than the recipient counterparts. Conclusion This is the first study using STE to highlight the poor myocardial performance in MCDA twins exposed to TTTS who do not undergo SLPCV. This highlights the need for close monitoring of their haemodynamic status during the early neonatal period. Further study is warranted to explore this condition further.
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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 | 0.001 | 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) | 0.000 | 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 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".