MétaCan
Menu
Back to cohort
Record W4318038293 · doi:10.1097/pcc.0000000000003184

Reporting of Social Determinants of Health in Pediatric Sepsis Studies*

2023· review· en· W4318038293 on OpenAlexaff
Kusum Menon, Lauren R. Sorce, Andrew C. Argent, Tellen D. Bennett, Enitan D. Carrol, Niranjan Kissoon, L. Nelson Sanchez‐Pinto, Luregn J. Schlapbach, Daniela Carla de Souza, R. Scott Watson, James L. Wynn, Jerry J. Zimmerman, Suchitra Ranjit

Bibliographic record

VenuePediatric Critical Care Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersChildren's Hospital of PittsburghGreat Ormond Street Institute of Child HealthNational Institute of Biomedical Imaging and BioengineeringCenter for Child Health, Behavior and DevelopmentFeinberg School of MedicineUniversity of California, San DiegoUniversity of Cape TownChildren's Hospital of PhiladelphiaUniversity of CambridgeNational Institute of General Medical SciencesNational Institute for Health and Care ResearchChildren’s Hospital of Wisconsin Research InstituteImperial College LondonUniversity of QueenslandFudan UniversityNorthwestern UniversitySeattle Children's Research InstituteUniversity College LondonNationwide Children's HospitalEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversidade de São PauloWorld Health Organization
KeywordsMedicineSocioeconomic statusSepsisSocial determinants of healthAssociation (psychology)Environmental healthPublic healthImmunologyPopulationPathologyPsychology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.292
metaresearch head score (Gemma)0.622
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.708
Threshold uncertainty score0.874

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2920.622
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.008
Bibliometrics0.0390.033
Science and technology studies0.0020.004
Scholarly communication0.0060.006
Open science0.0040.009
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.429
GPT teacher head0.569
Teacher spread0.140 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainReporting
GenreReview

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".

Quick stats

Citations20
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuePediatric Critical Care MedicineSame topicSepsis Diagnosis and TreatmentFrench-language works237,207