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Worsening of Symptoms Before Presentation with Vasovagal Syncope

2007· article· en· W2065858698 on OpenAlexaff
Robert S. Sheldon, Aaron Sheldon, Anna Serletis, Stuart J. Connolly, Carlos A. Morillo, Thomas Klingenheben, Andrew D. Krahn, MARY‐LOU KOSHMAN, Debbie Ritchie

Bibliographic record

VenueJournal of Cardiovascular Electrophysiology · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsWestern UniversityMcMaster UniversityLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMedicineSyncope (phonology)Vasovagal syncopeFaintingPopulationPediatricsReferralInternal medicineCardiologyAnesthesia

Abstract

fetched live from OpenAlex

INTRODUCTION: Much of the natural history of vasovagal syncope is unknown. We determined whether patients presenting for care have had a recently worsened syncope frequency. METHODS AND RESULTS: We compared 208 subjects in the referral-based Prevention of Syncope Trial (POST) and 122 subjects who fainted > or =1 in a community survey study. Their mean ages and gender proportions were similar. The POST population had a higher median lifetime syncope frequency (1.16 vs 0.12 spells/year, P < 0.0001) and more subjects began fainting at age > or =35 years (26% vs 6%, P < 0.0001). In POST, the median frequency of syncopal spells in the preceding year was higher than in all previous years (3 vs 0.57, P < 0.0001). POST subjects presented sooner after their first spell (median 11.0 vs 16.8 years, P = 0.0002), and after their last spell (median 0.3 vs 7.4 years, P < 0.0001). POST subjects > or =35 years old had a shorter history than similar community-survey subjects (2.8 vs 14.9 y, P < 0.0001) and presented earlier after their first syncopal spell than POST subjects with a younger onset of syncope (median 2.8 vs 14.7 y, P < 0.0001), despite having fewer faints (median 6 vs 10, P = 0.0002). CONCLUSIONS: Many syncope patients present for care after a recent worsening of their frequency of syncope.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.223
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2007
Admission routes1
Has abstractyes

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