Assessment of Canadian Syncope Risk Score in the prediction of outcomes of patients with syncope at the Emergency Department of Suez Canal University
Bibliographic record
Abstract
ABSTRACT: Syncope is a temporary loss of consciousness usually related to insufficient blood flow to the brain. It's also called fainting or "passing out." Syncope is responsible for 3% to 5% of emergency department visits, with a hospitalization rate in about 40% of cases, with an average stay of 5.5 days. The Canadian Syncope Risk Score showed good discrimination and calibration for 30-day risk of serious adverse events after disposition from the emergency department.The aim was to assess Canadian Syncope Risk Score in predicting outcomes and mortality at the emergency department of Suez Canal University Hospitals.A prospective observational cohort study was carried out in emergency department in Suez Canal University Hospital. After approval by the Ethical and Research Committee of Faculty of Medicine, Suez Canal University, 60 patients with syncope attending to emergency department were included to this study. All included participants were assessed by history taking and they also assessed by the Canadian Syncope Risk Score.The Canadian Syncope Risk Score's mean of the study group was 4.9 and the range of the scores was from -2 to 11. The mean of the percentage of risk of serious events at 30 days in the study group was 29.17% and it ranged from 0.7% to 83.6%.There was a statistically significant difference between means Canadian Syncope Risk Score's score regarding complication occurrence. Cases which showed complications had a mean score of 7.33 compared to a mean score of 1.25 in case of no complication occurrence P-value <.001. At a cut-off point of more than 3 for the Canadian Syncope Risk Score's, sensitivity of that score in complication's occurrence prediction was 100% and the specificity was 87.5% P-value <.001.The Canadian Syncope Risk Score's is strong predictor for risk of serious adverse events and a good indicator for admission, with 100% sensitivity and 87.5% specificity at cut off point more than 3.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".