Social determinants of health associated with the development of sepsis in adults: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Sepsis, the life-threatening immune response to infection, affects millions of people annually. Understanding of the factors associated with the development of sepsis is crucial for improving population health and public health efforts; in particular, literature exploring the relationship between sepsis and social determinants of health is lacking. This review seeks to establish and amalgamate existing evidence of the relationships between sepsis and the following social determinants: frailty, registration with a family physician, mental illness, alcohol abuse, social support levels, smoking status, illicit drug use disorders, socioeconomic status, gender and race/ethnicity. METHODS AND ANALYSIS: This study will analyse qualitative and quantitative studies using standard processes. The selected social determinants of health and their potential link to adult sepsis will be analysed separately under distinct headings. Findings will be consolidated in a final discussion. PubMed and Medline will be searched for articles published between 1970 and 2020 using search strings combining 'sepsis' and other variations, such as 'septicaemia' with each social determinant of interest. 'Sepsis' and at least one social determinant of interest must be present in a study's title for inclusion in the review; the results of the initial search will be filtered based on predetermined inclusion and exclusion criteria. Evidence from this scoping review will provide information on the impact of social determinants of health on the risk of developing adult sepsis, which can inform clinicians of the various risk factors to consider when admitting patients. ETHICS AND DISSEMINATION: Approval from a research ethics board is not needed for this amalgamation of information from studies for which the primary investigators have obtained their own, respective ethics board approval. Once completed, the review will be submitted for publication in a peer-reviewed journal, and findings will be presented in local and national forums.
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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 | 0.082 | 0.062 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.071 | 0.011 |
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".