Utilization of Echocardiogram, Carotid Ultrasound, and Cranial Imaging in the Inpatient Investigation of Syncope: Its Impact on the Diagnosis and the Patient’s Length of Hospitalization
Bibliographic record
Abstract
BACKGROUND: Although guidelines suggest that the best strategy for evaluating syncope is clinical history and physical examination, the inappropriate utilization of diagnostic imaging is common. METHODS: A single center retrospective analysis conducted in adult patients admitted for evaluation and management of syncope for a period of 12 months. Charts were reviewed to abstract demographic data, admitting and discharge diagnosis, diagnostic investigatory tests including imaging modalities (echocardiogram, carotid ultrasound, and cranial computed tomography (CT)) ordered, subspecialty consultation requested, treatment rendered and hospital length of stay (LOS). RESULTS: A total of 109 patients were admitted for syncope, mean age was 68.74 ± 21.04 years and 39.44% were men. Echocardiogram, carotid ultrasound, and cranial CT were ordered in 69.72%, 33.02%, and 76.14% respectively. The mean hospital LOS was 2.6 days. Patients with no imaging test, one imaging test, two imaging tests, and three imaging tests ordered have an average hospital LOS of 2.22 days, 2.44 days, 2.58 days, and 3.07 days respectively. The number of imaging test and its relation to the admitting (Chi-square (chi-sq) P = 0.4165, nominal logistic regression (LR) P = 0.939) and discharge (chi-sq P = 0.1507, nominal LR P = 0.782) diagnosis as well as the LOS in relation to the number of imaging test ordered (analysis of variance (ANOVA) P = 0.368, Kruskal Wallis (KW) P = 0.352) were not statistically significant although there was a trend of prolonged hospital LOS the more imaging diagnostic test had been ordered. Syncope was the admitting and discharge diagnosis in 89.9% and 91.74% respectively. CONCLUSIONS: Choosing the appropriate diagnostic tests as dictated by the patient's clinical manifestation and utilizing less expensive test would be appropriate and cost-effective approach in appraising patients with syncope.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".