ABSTRACT 639
Bibliographic record
Abstract
Background and aims: Viral respiratory illness (VRI) is the leading cause of pediatric hospitalizations in North America. An association between respiratory viruses with extra pulmonary manifestations has been identified. The incidence, timing and severity of myocardial dysfunction (MD) associated with VRI have not been well studied. A prospective observational study is ongoing to define criteria and examine independent predictors. Aims: The primary objective of this portion of the study is to retrospectively identify independent predictors of VRI with MD (VRI/MD). Methods: Retrospective chart review was performed at a pediatric intensive care unit (PICU) in a university hospital. Charts were reviewed from 2011–2013 for patients that tested positive for a VRI (n=50). Logistic regression analysis was performed with multiple independent predictors for MD with VRI. This study was approved by the university board of ethics. Results: 54% (95% CI 40–68%) of the children with confirmed VRI had MD. 72% of VRI patients with congenital heart defects developed MD. 78.9% (p=0.006) of the patients with a secondary bacterial infection developed MD. VRI patients with history of extreme prematurity or younger than 6 months of age showed an increased rate MD. Ethnicity, gender and type of virus were not independent predictors of MD/VRI. Conclusions: 54% of patients with VRI in the PICU developed MD. Congenital heart defects, history of prematurity, and secondary bacterial infections are important independent predictors of MD in VRI. These findings emphasize the need for further examination through the prospective component of this trial.
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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.655 | 0.496 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".