672: PEDIATRIC LUNG DISEASE IN RESOURCE-LIMITED SETTINGS: A SECONDARY ANALYSIS OF THE GLOBAL PARITY STUDY
Bibliographic record
Abstract
Introduction: Hypoxia in children causes significant global mortality. We know that Pediatric Acute Respiratory Distress Syndrome (PARDS) contributes to pediatric mortality in high-resource settings; however, few studies have evaluated PARDS in resource-limited settings (RLS) where elements of diagnostic criteria are often unavailable. To better understand mortality associated with pediatric hypoxia in RLS, we measured prevalence of PARDS risk factors (pneumonia, sepsis, drowning, aspiration, trauma, non-septic shock) and association with hospital mortality through a secondary analysis of the Global PARITY study. Methods: Global PARITY was a multinational (20 countries, 47 sites) prospective point prevalence study of children (age 29 days to 14 years) presenting to an emergency department or directly admitted to a hospital in a self-identified RLS. Children were considered to have hypoxemia if they had oxygen saturation < 88% or required respiratory support at any time during their hospitalization. Using STATA (version 17.0), we performed descriptive statistical analyses and tests of comparison. A p-value < 0.05 was considered statistically significant. Results: Global PARITY enrolled 7466 children of which 36% (n=2685) were admitted to the hospital or died in the emergency department. Of this group, 29.5% (n=793) experienced hypoxemia. Among children admitted with hypoxemia, 44% (n=348) were female. The median age was 23 months (IQR 7m-5y). Latin America/Caribbean had the highest rate of hypoxemia (478 patients per 1000 admissions). Of patients admitted with hypoxemia, at least one PARDS risk factor was present in 41.7% (n=331) of children. Pneumonia and sepsis were predominant risk factors, present in 33.3% (n=264) and 7.6% (n=60) of patients respectively. Those with sepsis had a 16.7% (n=10) mortality compared to 6.1% (n=45) in those without sepsis (p=0.002). All-cause mortality for patients with hypoxemia during admission was 6.9% (n=55) compared with 0.7% (n=13) in those without hypoxemia (p< 0.0001). Conclusions: This study contributes to a growing body of pediatric literature on epidemiology and outcomes in RLS. Associations between PARDS risk factors and mortality require confirmation in further studies and can be used to stratify mortality risk in pediatric patients in resource-limited settings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".