Population‐based review of tetralogy of Fallot with absent pulmonary valve: is prenatal diagnosis really associated with a poor prognosis?
Bibliographic record
Abstract
OBJECTIVES: Tetralogy of Fallot with absent pulmonary valve syndrome (TETAPV) is reported in obstetric literature to have an extremely poor prognosis. We sought to determine the clinical outcome associated with TETAPV and whether prenatal diagnosis confers a poor prognosis. METHODS: All cases of TETAPV diagnosed in British Columbia between 1980 and 2009 were reviewed and grouped according to time of diagnosis, either prenatal or postnatal. The groups were compared with respect to mortality, respiratory problems, number of interventions and functional capacity at last follow-up. RESULTS: Eight and 11 patients were included in the prenatally and postnatally diagnosed groups, with overall long-term survival of 71% and 82%, respectively. There was no significant difference in mortality, frequency of preoperative intubation, number of interventions or functional capacity between groups. CONCLUSION: From a population-based retrospective analysis of TETAPV cases identified over three decades it is concluded that the prognosis for TETAPV is better than that previously reported in the obstetric literature. This information should be used to guide prenatal counseling.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".