200: Health Related Quality of Life in Pediatric Cardiac ECLS Survivors: Is Alive Good Enough?
Bibliographic record
Abstract
Extra Corporeal Life Support (ECLS) has evolved to a standard of care in many pediatric centers, with thousands of patients supported to date. There is a lack of studies examining long-term outcomes including health related quality of life (HRQL). We aim to assess the HRQL of children who received cardiac ECLS, and to compare them with a healthy sample, children with chronic conditions and children who had cardiac surgery and did not receive ECLS. Prospective cohort study including children <5 years of age with diagnosis of cardiac disease who received ECLS at the Stollery Children's Hospital between 1999 and 2009. HRQL was assessed using the PedsQLTM 4.0 Generic Core Scales. Analysis was performed with t-test for independent samples and multiple linear regression. Study approved by institutional health research ethics board. Ninety-eight patients received ECLS between 2000 and 2009, 50 (51%) survived and 47 children were assessed at a median age of four years. Children who received veno-arterial ECLS have significantly lower PedsQLTM 4.0 than healthy children (64.9 vs. 82.2; P<0.0001), children with chronic conditions (64.9 vs. 73.1; P=0.007), and children who underwent cardiac surgery and who did not receive ECLS (64.9 vs. 81.1; P<0.0001). Multiple linear regression analysis found an independent association between higher inotrope score in the first 24 h of ECLS, longer hospital length of stay and lower PedsQLTM 4.0 scores. Pediatric cardiac ECLS survivors showed lower HRQL than healthy children, children with chronic conditions and those with congenital heart disease who did not receive ECLS.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".