6686 Impact of practice change on the survival outcomes of babies with congenital diaphragmatic hernia
Bibliographic record
Abstract
Objectives The aim of this study was to assess the survival rate, following change in the pre-surgical postnatal management of the babies with CDH. Methods Clinical data on babies with CDH was collected from Badgernet database, between April 2019 to March 2023. Results In the study cohort of 44 patients, the survival rate improved from 62% to 75%. HFOV (48%) and inotropic therapy (36%) are being used in a select population of babies, as an escalation therapy. Greater proportion of babies who died, had poor prognostic factors like right sided herniation, abnormal genetics and associated congenital anomalies, most of them detected antenatally. Conclusion Tailored postnatal CDH management, in line with international guidelines, has showed a continued improvement in survival rate. On-going surveillance, risk assessment and targeted therapy needs to continue in the postnatal management of these babies. In addition, there is a need to establish multi-disciplinary care pathways to help improve long term morbidities associated with CDH. Table 1 shows The Antenatal and Postnatal management of babies who survived versus those who died. References Snoek KG, Reiss IK, Greenough A et al. CDH EURO Consortium. Standardized Postnatal Management of Infants with Congenital Diaphragmatic Hernia in Europe: The CDH EURO Consortium Consensus – 2015 Update. Neonatology 2016;110(1):66–74. doi: 10.1159/000444210. Epub 2016 Apr 15. PMID: 27077664. The Canadian Congenital Diaphragmatic Hernia Collaborative, Puligandla PS, Skarsgard ED, et al. Diagnosis and management of congenital diaphragmatic hernia: a clinical practice guideline. CMAJ 2018;190:E103–12.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".