Syncope causes transient focal neurological symptoms
Bibliographic record
Abstract
AIMS: The prevalence of focal neurology (FN) as a consequence of syncope is unknown. The aim of the study was to determine its prevalence, risk factors and short-term consequences. METHODS: A consecutive sample of syncope-unit attendees during a 9-month period had detailed diagnostic syncope evaluation as per European Cardiac Society guidelines coupled with assessment for FN present during syncope/pre-syncope by screening questionnaire, follow-up interview and neuroimaging (1.5T magnetic resonance imaging [MRI]). All participants were followed up for 24 months. Risk factors for FN were identified by comparing FN cases with syncope controls without FN (3:1 ratio). RESULTS: Five-hundred and forty consecutively attended for investigation of syncope (n = 401) and pre-syncope (n = 139). Thirty-one (5.7%) had FN events during hypotensive symptoms, mean age 49 years (19-85). The majority of FN cases had vasovagal syncope (VVS); 22 (71%), whereas eight had OH (25.8%) and one (3.2%) had cardiac arrhythmia. Median duration of FN was 15 min (IQR: 34.5). MRI in 28 (90%) was normal and in 3, old cerebral infarction was evident. Risk factors for FN/syncope were frequent syncope (P = 0·008), childhood syncope (P < 0.0005) and delayed diastolic recovery during active stand (P = 0·02). During 24-month follow-up and targeted intervention, no patients developed recurrence of FN. CONCLUSION: One in 20 patients with syncope/pre-syncope have co-extant FN, which during 24-month follow-up, does not progress to a persistent deficit (>24 h). Awareness of co-occurrence of FN and syncope is important as stroke misdiagnosis results in aggressive anti-hypertensive management and future events may ensue.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".