Reporting of Social Determinants of Health in Pediatric Sepsis Studies*
Bibliographic record
Abstract
OBJECTIVE: Standardized, consistent reporting of social determinants of health (SDOH) in studies on children with sepsis would allow for: 1) understanding the association of SDOH with illness severity and outcomes, 2) comparing populations and extrapolating study results, and 3) identification of potentially modifiable socioeconomic factors for policy makers. We, therefore, sought to determine how frequently data on SDOH were reported, which factors were collected and how these factors were defined in studies of sepsis in children. DATA SOURCES AND SELECTION: We reviewed 106 articles (published between 2005 and 2020) utilized in a recent systematic review on physiologic criteria for pediatric sepsis. DATA EXTRACTION: Data were extracted by two reviewers on variables that fell within the World Health Organization's SDOH categories. DATA SYNTHESIS: SDOH were not the primary outcome in any of the included studies. Seventeen percent of articles (18/106) did not report on any SDOH, and a further 36.8% (39/106) only reported on gender/sex. Of the remaining 46.2% of articles, the most reported SDOH categories were preadmission nutritional status (35.8%, 38/106) and race/ethnicity (18.9%, 20/106). However, no two studies used the same definition of the variables reported within each of these categories. Six studies reported on socioeconomic status (3.8%, 6/106), including two from upper-middle-income and four from lower middle-income countries. Only three studies reported on parental education levels (2.8%, 3/106). No study reported on parental job security or structural conflict. CONCLUSIONS: We found overall low reporting of SDOH and marked variability in categorizations and definitions of SDOH variables. Consistent and standardized reporting of SDOH in pediatric sepsis studies is needed to understand the role these factors play in the development and severity of sepsis, to compare and extrapolate study results between settings and to implement policies aimed at improving socioeconomic conditions related to sepsis.
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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 | 0.292 | 0.622 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.039 | 0.033 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".