Reporting of social determinants of health in randomized controlled trials conducted in the pediatric intensive care unit
Bibliographic record
Abstract
Introduction: The influence of social determinants of health (SDOH) on access to care and outcomes for critically ill children remains an understudied area with a paucity of high-quality data. Recent publications have highlighted the importance of incorporating SDOH considerations into research but the frequency with which this occurs in pediatric intensive care unit (PICU) research is unclear. Our objective was to determine the frequency and categories of SDOH variables reported and how these variables were defined in published PICU randomized controlled trials (RCTs). Methods: We searched Medline, Embase, Lilacs, and Central from inception to Dec 2022. Inclusion criteria were randomized controlled trials of any intervention on children or their families in a PICU. Data related to study demographics and nine WHO SDOH categories were extracted, and descriptive statistics and qualitative data generated. Results: 586 unique RCTs were included. Studies had a median sample size of 60 patients (IQR 40-106) with 73.0% of studies including ≤100 patients and 41.1% including ≤50 patients. A total of 181 (181/586, 30.9%) studies reported ≥1 SDOH variable of which 163 (163/586, 27.8%) reported them by randomization group. The most frequently reported categories were food insecurity (100/586, 17.1%) and social inclusion and non-discrimination (73/586, 12.5%). Twenty-five of 57 studies (43.9%) investigating feeding or nutrition and 11 of 82 (13.4%) assessing mechanical ventilation reported baseline nutritional assessments. Forty-one studies investigated interventions in children with asthma or bronchiolitis of which six reported on smoking in the home (6/41, 14.6%). Discussion: Reporting of relevant SDOH variables occurs infrequently in PICU RCTs. In addition, when available, categorizations and definitions of SDOH vary considerably between studies. Standardization of SDOH variable collection along with consistent minimal reporting requirements for PICU RCT publications is needed.
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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 | 0.509 | 0.789 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.016 |
| Bibliometrics | 0.014 | 0.020 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".