[A modified Calgary syncope syndrome score in the differential diagnosis between cardiac syncope and vasovagal syncope].
Bibliographic record
Abstract
OBJECTIVE: This study aimed at analyzing the usefulness of a modified Calgary Syncope Syndrome Score in the differential diagnosis between cardiac syncope (CS) and vasovagal syncope (VVS) in children through a large sample clinical study. METHOD: Totally 189 children [112 males, 77 females, aged 2 - 18 yrs, mean age (12.4 ± 3.1) yrs] with CS and VVS who were at the syncope clinic or admitted to the Department of Pediatrics, Peking University First Hospital from August 2002 to April 2011 were included in the study. The diagnosis was analyzed by a modified Calgary Syncope Syndrome Score and receiver operating characteristic (ROC) curve was used to explore the predictive value of different Calgary Syncope Syndrome Scores in differential diagnosis between CS and VVS. RESULT: There were significant differences in the score between CS [-5.00(-7, 1)] and VVS [1(-4, 6)] (P < 0.01). When the score was ≤ -2.5, the sensitivity and specificity of the differential diagnosis between CS and VVS were 95.4% and 67.7%, respectively. Since the modified Calgary Syncope Syndrome Score was integer number, CS should be considered when the score was less than -3. CONCLUSION: The modified Calgary Syncope Syndrome Score might be used as an initial diagnostic method in differential diagnosis between CS and VVS, based on the history of the patients.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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 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".