Predicting Outcome in Primary Fetal Hydrothorax
Bibliographic record
Abstract
OBJECTIVE: This study examines the role of serial ultrasound in predicting fetal outcomes based on progress, resolution or stability of pleural effusions in primary fetal hydrothorax (PFHT). METHODS: Records from consecutive cases of fetal pleural effusions referred to the fetal echocardiography unit over a 12-year period were reviewed. Study patients underwent thorough investigation to rule out secondary causes of pleural effusions. The clinical course was monitored with serial ultrasound studies every 2 weeks until delivery. Pleurocentesis and pleuroamniotic shunts were performed in select cases of PFHT. Fetal survival was the primary outcome variable. RESULTS: Eighteen of 44 patients referred for perinatal evaluation of fetal pleural effusions met the study criteria for PFHT. Diagnosis was made at 28 +/- 7 weeks and fetuses delivered at 35 +/- 3 weeks' gestational age. Overall survival was 78%. Effusion progression, greater effusion ratios, earlier gestational age at delivery, and lower Apgar scores at birth were associated with poor outcome. Conservative management was appropriate for most cases. CONCLUSIONS: Serial ultrasound studies to evaluate the clinical course of the pleural effusions are essential in the management of PFHT. Expectant management of stable and resolving effusions was appropriate in all cases.
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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 | 0.008 |
| 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".