Registry on the Evaluation of Syncope Assessment Strategy in the Emergency Room (Resaster Study)
Bibliographic record
Abstract
Previous studies suggest that the management of patients (pts) with syncope admitted to the emergency room (ER) is not standardized. To perform a review of all ER visits in a period of three months, searching for syncope (Sync) and presyncope (Presync) consults, determining incidence, admission rates and diagnostic yield of pts admitted to the ER. Systematic review of electronic charts from 4 academic hospitals. Admission and discharge diagnosis were recorded. A simple standardized diagnostic algorithm based on clinical presentation, previous history, physical examination and ancillary diagnostic tests were blindly reviewed by 3 of the investigators and compared with the admission and discharge diagnosis. Sync/presync was the primary diagnosis in 438: Sync 318 (72%) and Presync 120 (28%). Mean age of pts with Sync and Presync was 56±23.5 years, and 50% were females. Structural heart disease was present in 20% (CAD 69%). 123 pts (28%) with Sync/Presync were admitted, representing 0.51% of all ER. Average length of stay was 7.4±9.8 days. Average estimated cost in admitted pts was CAN$ 4570.33±4700. Diagnosis at the ER visit, discharge and RESASTER diagnosis are summarized in the table: Application of a retrospective algorithmic diagnostic approach applied during ER assessment of pts with sync/presync increased diagnostic yield (15% to 77%), with vasovagal syncope accounting for more than half of the diagnosis. Simple clinical may reduce unnecessary testing, costs and hospital admissions in pts presenting with syncope to the ER.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".