Core outcome set in paediatric sepsis in low- and middle-income countries: a study protocol
Bibliographic record
Abstract
INTRODUCTION: Sepsis is the leading cause of death in children worldwide and has recently been declared a major global health issue. New interventions and a concerted effort to enhance our understanding of sepsis are required to address the huge burden of disease, especially in low- and middle-income countries (LMIC) where it is highest. An opportunity therefore exists to ensure that ongoing research in this area is relevant to all stakeholders and is of consistently high quality. One method to address these issues is through the development of a core outcome set (COS). METHODS AND ANALYSIS: This study protocol outlines the phases in the development of a core outcome set for paediatric sepsis in LMIC. The first step involves performing a systematic review of all outcomes reported in the research of paediatric sepsis in low middle-income countries. A three-stage international Delphi process will then invite a broad range of participants to score each generated outcome for inclusion into the COS. This will include an initial two-step online survey and finally, a face-to-face consensus meeting where each outcome will be reviewed, voted on and ratified for inclusion into the COS. ETHICS AND DISSEMINATION: No core outcome sets exist for clinical trials in paediatric sepsis. This COS will serve to not only highlight the heavy burden of paediatric sepsis in this setting and aid collaboration and participation between all stakeholders, but to promote ongoing essential high quality and relevant research into the topic. A COS in paediatric sepsis in LMIC will advocate for a common language and facilitate interpretation of findings from a variety of settings. A waiver for ethics approval has been granted by University of British Columbia Children's and Women's Research Ethics Board.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".