Standardized Reporting Guidelines for Emergency Department Syncope Risk‐stratification Research
Bibliographic record
Abstract
There is increasing research interest in the risk stratification of emergency department (ED) syncope patients. A major barrier to comparing and synthesizing existing research is wide variation in the conduct and reporting of studies. The authors wanted to create standardized reporting guidelines for ED syncope risk-stratification research using an expert consensus process. In that pursuit, a panel of syncope researchers was convened and a literature review was performed to identify candidate reporting guideline elements. Candidate elements were grouped into four sections: eligibility criteria, outcomes, electrocardiogram (ECG) findings, and predictors. A two-round, modified Delphi consensus process was conducted using an Internet-based survey application. In the first round, candidate elements were rated on a five-point Likert scale. In the second round, panelists rerated items after receiving information about group ratings from the first round. Items that were rated by >80% of the panelists at the two highest levels of the Likert scale were included in the final guidelines. There were 24 panelists from eight countries who represented five clinical specialties. The panel identified an initial set of 183 candidate elements. After two survey rounds, the final reporting guidelines included 92 items that achieved >80% consensus. These included 10 items for study eligibility, 23 items for outcomes, nine items for ECG abnormalities, and 50 items for candidate predictors. Adherence to these guidelines should facilitate comparison of future research in this area.
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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 | 0.399 | 0.500 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.025 | 0.020 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.010 | 0.008 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".