Minimally invasive therapy for fetal sacrococcygeal teratoma: case series and systematic review of the literature
Bibliographic record
Abstract
OBJECTIVE: Large solid sacrococcygeal teratomas (SCT) can cause high-output cardiac failure and fetal or neonatal death. The aim of this study was to describe the outcomes of minimally invasive antenatal procedures for the treatment of fetal SCT. METHODS: A case review was performed of five fetuses with a large SCT treated antenatally using minimally invasive techniques, and a systematic literature review on fetal therapy for solid SCTs was carried out. RESULTS: Five women were referred between 17 + 5 and 26 + 4 weeks' gestation for a large fetal SCT with evidence of fetal cardiac failure. Vascular flow to the tumors was interrupted by fetoscopic laser ablation (n = 1), radiofrequency ablation (RFA; n = 2) or interstitial laser ablation ± vascular coiling (n = 2). There were two intrauterine fetal deaths. The other three cases resulted in preterm labor within 10 days of surgery. One neonate died. Two survived without procedure-related complications but had long-term morbidity related to prematurity. The systematic literature review revealed 16 SCTs treated minimally invasively for (early) hydrops. Including our cases, six of 20 hydropic fetuses survived after minimally invasive therapy (30%). Survival after RFA or interstitial laser ablation was 45% (5/11). Of 12 fetuses treated for SCT without obvious hydrops and for which perinatal survival data were available, eight (67%) survived. Mean gestational age at delivery after minimally invasive therapy was 29.7 ± 4.0 weeks. Survival after open fetal surgery in hydropic fetuses was 6/11 (55%), with a mean gestational age at delivery of 29.8 ± 2.9 weeks. CONCLUSIONS: Fetal therapy can potentially improve perinatal outcomes for hydropic fetuses with a solid SCT, but is often complicated by intrauterine death and preterm birth.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".