Assessing the clinical significance of echocardiograms in determining treatment of patent ductus arteriosus in neonates
Bibliographic record
Abstract
BACKGROUND: To evaluate the utility of echocardiogram (ECHO) in detection and treatment of patent ductus arteriosus (PDA) and hemodynamically significant PDA (hsPDA) in preterm neonates. METHODS: This was a retrospective case-control study of all preterm infants born or admitted to the level III Neonatal Intensive Care Unit in McMaster Children's Hospital from January 2009 to January 2013. These cases were further classified into the following sub-groups: group A) hsPDA confirmed on ECHO; and the control, group B) PDA (but not hemodynamically significant) confirmed on ECHO. Patients without an ECHO were excluded from all analyses. The primary outcome was incidence of treatment for PDA. RESULTS: PDA treatment was administered in 83.3% and 11.2% of patients in groups A and B respectively (P < 0.05). Among patients with a hsPDA within group A, 17% did not receive treatment, while 11% of patients with non-hemodynamically significant PDA received treatment for the PDA. Within the cohort of patients who received treatment for a hsPDA, gestational age below 35 weeks as well as murmurs heard on auscultation were both found to be predictors of treatment. CONCLUSION: While the ECHO remains the gold standard for detecting pathological PDA, there is evidence that other traditional clinical measures continue to guide clinical practice and treatment decisions. Further research is required to gain an understanding of how clinical measures and ECHO may be used in conjunction to optimize resource utilization.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".