Reasons for Hospitalization Among Emergency Department Patients With Syncope
Bibliographic record
Abstract
BACKGROUND: Variations in syncope management exist. Our objective was to identify the reasons for consultations and hospitalizations and outcomes among emergency department (ED) syncope patients. METHODS: We conducted a prospective cohort study to enroll adult syncope patients at five EDs. We collected baseline characteristics, reasons for consultation and hospitalization, and hospital length of stay. Adjudicated 30-day serious adverse events (SAEs) including death, myocardial infarction, arrhythmia, structural heart disease, pulmonary embolism, significant hemorrhage, and procedural intervention. We used descriptive analysis. RESULTS: From 4,064 enrolled patients (mean ± SD age = 53.1 ± 23.2 years; 55.9% female), 3,255 (80.1%) were discharged directly by the ED physician. Of those with no SAEs identified in the ED (n = 600), 42.8% of referrals and 46.5% of hospitalizations were for suspected arrhythmias, and 71.2% of patients hospitalized for arrhythmias had no cause identified. SAEs among groups were 9.7% in total, 2.5% discharged by ED physician, 3.4% discharged by consultant, 21.7% as inpatient, and 4.8% following discharge from hospital. The median hospital length of stay for suspected arrhythmias was 5 days (interquartile range = 3 to 8 days). CONCLUSION: Cardiac syncope, particularly suspected arrhythmia, was the major reason for ED referrals and hospitalization. The majority of patients hospitalized for cardiac monitoring had no identified cause. An important number of patients suffered SAEs, particularly arrhythmias, outside the hospital. Development of a risk-stratification tool and out-of-hospital cardiac monitoring strategy should improve patient safety and save substantial resources.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".