Standardized Reporting Guidelines for Emergency Department Syncope Risk‐stratification Research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it