PC.32 The Impact of a Dedicated PDA Ligation Triaging and Management System: A single centre experience
Bibliographic record
Abstract
Background There is a lack of standardised criteria for selecting patients for ligation of a patent ductus arteriosus. This may lead to delays in referring patients and inappropriate intervention for other patients. A neonatologist-led PDA ligation categorisation and triaging process was introduced in 2005 at a large quaternary hospital to streamline the admission process and enhance peri-operative care through use of Targeted Neonatal Echocardiography. Objective To investigate the impact of a dedicated PDA ligation triaging system on referrals and quality indicators. Methods A retrospective comparative analysis of two epochs [EP1 (2003–5) and EP2 (2010–12)] was conducted. All referrals for PDA ligation were evaluated for severity of pre-operative illness and morbidities, postoperative instability, length of post-operative stay and effectiveness of triaging system between the two epochs. The primary outcome was incidence of PDA ligations per year / per total number of live births < 30 weeks gestation. Secondary outcomes included procedural cancellation or delay, postoperative need for inotropes or cardiovascular support and oxygenation support. Results A total of 198 babies [EP1(n = 117) vs EP2(n = 81)] had PDA ligations in two epochs. There was no difference in baseline demographics or pre-procedural neonatal morbidity between epochs. The incidence of PDA ligation was lower in the second epoch [EP 1: 117/1092 (10.7%) vs EP2: 81/1520 (5.3%)]. Although pre-procedural illness severity was greater in epoch II the incidence of post-ligation cardiac syndrome and recovery time were lower on babies <1000 g at surgery. Conclusions The presence of a dedicated triaging and management system enhances the efficiency of the referral process through careful selection of patients for PDA ligation and optimises perioperative management.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".