Syncope: a narrative review of the scores and their applicability in the emergency room
Bibliographic record
Abstract
Goal: To explain the clinical scores related to syncope and their applicability in the management of this syndrome.Methods: Narrative review of the literature based on 32 articles that ranged between 2019 and 2023.Results: Syncope, in most cases, has an underlying benign etiology.However, 20% of patients who consult emergency services present manifestations of concomitant potentially fatal disease, generally of cardiovascular origin.Scales that can be used to assess short-term outcomes include the So Francisco scale, for predicting death and serious events within 7 days; the Boston Scale, ROSE and the Canadian Syncope Risk Score, which seek to predict serious events within a month.The EGSYS and OESIL scales, in turn, are used for long-term assessment, the first to predict serious outcomes within one year and the second within two years.Conclusion: It was evident that the Canadian Syncope Risk Score represents the score with the best performance and greatest applicability in the clinical context.However, this score still has significant limitations -low specificity, for example -, making additional studies essential.
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".