Core outcomes and definitions for pediatric fever and neutropenia research: A consensus statement from an international panel
Bibliographic record
Abstract
BACKGROUND: There are no specific recommendations for the design and reporting of studies of children with fever and neutropenia (FN). As a result, there is marked heterogeneity in the variables and outcomes that are reported and new definitions continue to emerge. These inconsistencies hinder the ability of researchers and clinicians to compare, contrast and combine results. The objective was to achieve expert consensus on a core set of variables and outcomes that should be measured and reported, as a minimum, in pediatric FN studies. PROCEDURE: The Delphi method was used to achieve consensus among an international group of clinicians, pharmacists, researchers, and patient representatives. Four surveys focusing on (i) the identification of a core set of variables and outcomes; and (ii) definitions of these variables and outcomes, were administered electronically. Consensus was predefined as more than 80% agreement on any statement. RESULTS: There were forty-five survey participants and the response rate ranged between 84 and 96%. There was consensus on eight core variables and 10 core outcomes that should be collected and reported in all studies of children with FN. Consensus definitions were identified for all of the core outcomes. CONCLUSION: Using the Delphi method, expert consensus on a set of core variables and outcomes, and their corresponding definitions, was achieved. These core sets represent the minimum that should be collected and reported in all studies of children with FN. This will promote collaboration and ensure consistency and comparability between studies.
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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 | 0.498 | 0.320 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.016 | 0.009 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.011 | 0.020 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".