Identifying Cardiac Syncope Based on Clinical History: A Literature-Based Model Tested in Four Independent DatasetsReportar como inadecuado




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Background

We aimed to develop and test a literature-based model for symptoms that associate with cardiac causes of syncope.

Methods and Results

Seven studies the derivation sample reporting ≥2 predictors of cardiac syncope were identified 4 Italian, 1 Swiss, 1 Canadian, and 1 from the United States. From these, 10 criteria were identified as diagnostic predictors. The conditional probability of each predictor was calculated by summation of the reported frequencies. A model of conditional probabilities and a priori probabilities of cardiac syncope was constructed. The model was tested in four datasets of patients with syncope the test sample from Calgary n=670; 21% had cardiac syncope, Amsterdam n=503; 9%, Milan n=689; 5% and Rochester 3877; 11%. In the derivation sample ten variables were significantly associated with cardiac syncope: age, gender, structural heart disease, low number of spells, brief or absent prodrome, supine syncope, effort syncope, and absence of nausea, diaphoresis and blurred vision. Fitting the test datasets to the full model gave C-statistics of 0.87 Calgary, 0.84 Amsterdam, 0.72 Milan and 0.71 Rochester. Model sensitivity and specificity were 92% and 68% for Calgary, 86% and 67% for Amsterdam, 76% and 59% for Milan, and 73% and 52% for Rochester. A model with 5 variables age, gender, structural heart disease, low number of spells, and lack of prodromal symptoms was as accurate as the total set.

Conclusion

A simple literature-based Bayesian model of historical criteria can distinguish patients with cardiac syncope from other patients with syncope with moderate accuracy.



Autor: Janneke Berecki-Gisolf , Aaron Sheldon, Wouter Wieling, Nynke van Dijk, Giorgio Costantino, Raffaello Furlan, Win-Kuang Shen, Rob

Fuente: http://plos.srce.hr/



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