The Current and Future State of Pediatric Sepsis Definitions: An International Survey
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Definitions for pediatric sepsis were established in 2005 without data-driven criteria. It is unknown whether the more recent adult Sepsis-3 definitions meet the needs of providers caring for children. We aimed to explore the use and applicability of criteria to diagnose sepsis and septic shock in children across the world. METHODS: This is an international electronic survey of clinicians distributed across international and national societies representing pediatric intensive care, emergency medicine, pediatrics, and pediatric infectious diseases. Respondents stated their preferences on a 5-point Likert scale. RESULTS: There were 2835 survey responses analyzed, of which 48% originated from upper-middle income countries, followed by high income countries (38%) and low or lower-middle income countries (14%). Abnormal vital signs, laboratory evidence of inflammation, and microbiologic diagnoses were the criteria most used for the diagnosis of "sepsis." The 2005 consensus definitions were perceived to be the most useful for sepsis recognition, while Sepsis-3 definitions were stated as more useful for benchmarking, disease classification, enrollment into trials, and prognostication. The World Health Organization definitions were perceived as least useful across all domains. Seventy one percent of respondents agreed that the term sepsis should be restricted to children with infection-associated organ dysfunction. CONCLUSIONS: Clinicians around the world apply a myriad of signs, symptoms, laboratory studies, and treatment factors when diagnosing sepsis. The concept of sepsis as infection with associated organ dysfunction is broadly supported. Currently available sepsis definitions fall short of the perceived needs. Future diagnostic algorithms should be pragmatic and sensitive to the clinical settings.
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 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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".