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Record W3106968898 · doi:10.1093/ehjci/ehaa946.0701

Validation of the Canadian syncope risk score in a large prospective international multicenter study

2020· article· en· W3106968898 on OpenAlexaboutno aff
Tobias Zimmermann, Jeanne du Fay de Lavallaz, Devi Geesel Peñaranda Flórez, Velina Widmer, Michael Freese, J Walter, Pedro López‐Ayala, Maria Belkin, Jasper Boeddinghaus, Thomas Nestelberger, Patrick Badertscher, Jens Lohrmann, Raphael Twerenbold, M Kuehne, Christian Mueller

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVasovagal syncopeProspective cohort studyInternal medicineConfidence intervalEmergency departmentCohortCardiologySyncope (phonology)QRS complexPopulationCohort studyEmergency medicine

Abstract

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Abstract Background Management and risk stratification of patients with syncope in the emergency department (ED) is often challenging. In an effort to support ED physicians in disposition decisions, the Canadian Syncope Risk Score (CSRS) was developed to predict 30-day serious outcomes. Methods The CSRS was developed in a Canadian multicenter study and contains nine predictors: predisposition to vasovagal syncope, heart disease, systolic pressure <90 or >180mmHg in the ED, troponin level >99th percentile, abnormal QRS axis, QRS duration >130ms, QTc interval >480ms and an ED diagnosis of vasovagal or cardiac syncope. Patients can achieve a CSRS score between −3 and +11 points. We validated the CSRS in a large prospective international multicenter study recruiting patients 40 years or older presenting to the ED with a syncopal event within the last 12 hours. Recruitment centers contained smaller provincial hospitals, as well as big University Hospitals in eight countries on three continents. Primary outcome measure were 30-day serious arrhythmic and non-arrhythmic adverse events, as defined by the authors of the original score. Results 1581 patients were eligible for this analysis. The population in this validation cohort was older (mean age 68 vs 54 years) and had a considerably higher rate of serious outcomes compared to the derivation cohort (n=186 (11.8%) vs n=147 (3.6%)). The area under the receiver operating characteristic curve (AUC) for the CSRS was 0.88 (95% confidence interval (CI) 0.86–0.91) and significantly higher compared to the validated OESIL score (AUC 0.75, 95% CI 0.71–0.78, p<0.001). Calibration curve analysis showed an underestimation of risk in patients with a low CSRS and an overestimation in patients with a high CSRS. The rate of observed serious outcomes within 30d increased from 0.8% in the very low risk group (CSRS equal to or below −2) to 48% in the (very) high risk group (CSRS equal to or above 4, Hazard ratio 79.4, 95% CI 11.1–570.9). A Kaplan-Meier plot was used to visualize rates of serious outcomes in three different risk groups (Figure). Conclusion This is the first validation of the Canadian Syncope Risk Score in a large international syncope cohort. The prognostic discrimination of the CSRS for 30-day serious outcomes was very good in our validation cohort and comparable to that of the Canadian derivation study. Despite suboptimal calibration, prognostic analysis showed a high rate of serious outcomes in the CSRS (very) high risk group and a low rate of serious outcomes in the very low risk group. Allowing the clinical judgement of the ED physician in the form of suspected syncope etiology to be a part of the score seems to largely contribute to the high performance of the CSRS. Additional validation studies might be needed to further increase the accuracy of the CSRS in different patient populations with a different incidence of outcomes in settings outside of Canada. Figure 1 Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Swiss National Science Foundation; Swiss Heart Foundation

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.024
GPT teacher head0.268
Teacher spread0.244 · 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".

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Citations2
Published2020
Admission routes1
Has abstractyes

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