Calgary score and modified calgary score in the differential diagnosis between syncope and genetic generalized epilepsy in children
Bibliographic record
Abstract
The purpose of the study is to explore the use of Calgary scoring (CS) and Modified Calgary scoring (MCS) in the differentiation of genetic generalized epilepsy and syncope in children. The study involved 117 patients aged < 18 years who presented to our hospital's pediatric neurology outpatient clinic with TLOC between June 2020 and June 2022. In addition to CS and MCS scoring, all patients were subjected to statistical analysis based on their age, sex, number of episodes and distribution during the day, duration of syncope, and family history. Seventy-one patients with syncope and 46 with epilepsy were included in the study. At a CS value > - 1, sensitivity was 86.9% and specificity 63.4%, while at an MCS value > - 1, sensitivity was 76.1% and specificity 71.8%. CS had less specificity and sensitivity in predicting epilepsy when focal epilepsies were excluded. Abnormal behavior noted by bystanders, including witnessed unresponsive, unusual posturing, or limb jerking? (Q5) emerged as the most important question for the detection of epilepsy. Compared with other syncope findings, loss of consciousness during prolonged sitting or standing (Q9) emerged as the most important for the detection of 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".