Proposed Core Outcomes After Neonatal Sepsis
Bibliographic record
Abstract
Importance: Sepsis is one of the leading causes of neonatal mortality. There is heterogeneity in the outcomes measured and reported in studies of neonatal sepsis. To address this challenge, a core outcome set (COS) for research on neonatal sepsis was needed. Objective: The Neonatal Sepsis Core Outcome Set (NESCOS) project aims to develop a COS for research evaluating the effectiveness of neonatal sepsis treatments. Evidence Review: For this consensus statement, the research team obtained ethics approval and used a 4-stage process: (1) a systematic review of qualitative studies, (2) a real-time Delphi (RTD) survey to identify important outcomes for consensus meetings, (3) consensus meetings to finalize the COS, and (4) dissemination of the findings. The study was conducted from May 2, 2022, to October 27, 2023. The steering group and project participants consisted of health care workers, researchers, academics, parents, and parent representatives from low-, middle-, and high-income countries. An RTD survey and consensus meetings were conducted, with measures including a 9-point Likert scale rating (where 1 indicated not at all important and 9 indicated critically important) for outcome importance and a minimum 80% agreement threshold among stakeholders for final COS inclusion. The systematic review identified 19 outcomes, which were combined with outcomes from previous systematic reviews of clinical trials. Findings: The RTD survey included 306 participants, leading to the identification of 55 outcomes for further discussion in consensus meetings. The finalized COS comprises 9 outcomes: all-cause mortality, need for mechanical ventilation, brain injury on imaging, neurologic status at discharge, escalation of antimicrobial therapy, central nervous system infections, multiorgan dysfunction, neurodevelopmental impairment, and quality of life of parents. Conclusions and Relevance: This consensus-based COS for research on neonatal sepsis treatments will help standardize the outcomes measured and reported, enhancing the comparability of research findings. Future efforts should focus on establishing standardized and reliable methods for measuring these outcomes.
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 | 0.124 | 0.266 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".