Contemporary Burden and Correlates of Symptomatic Paroxysmal Supraventricular Tachycardia

当代症状性阵发性室上性心动过速的负担及相关因素

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Abstract

BACKGROUND: Contemporary data about symptomatic paroxysmal supraventricular tachycardia (PSVT) epidemiology are limited. We characterized prevalence and correlates of symptomatic PSVT within a large healthcare delivery system and estimated national PSVT burden. METHODS AND RESULTS: We identified adults with an encounter for potential PSVT between 2010 and 2015 in Kaiser Permanente Northern California, excluding those with prior known atrial fibrillation or atrial flutter. We adjudicated medical records, ECGs, and other monitoring data to estimate positive predictive values for targeted International Classification of Diseases (ICD), 9th and 10th Revisions codes in inpatient, emergency department, and outpatient settings. Combinations of diagnosis codes and settings were used to calculate PSVT prevalence, and PSVT correlates were identified using multivariable regression. We estimated national rates by applying prevalence estimates in Kaiser Permanente to 2010 US Census data. The highest positive predictive values included codes for "PSVT" in the emergency department (82%), "unspecified cardiac dysrhythmia" in the emergency department (27%), "anomalous atrioventricular excitation" as a primary inpatient diagnosis (33%), and "unspecified paroxysmal tachycardia" as a primary inpatient diagnosis (23%). Prevalence of symptomatic PSVT was 140 per 100 000 (95% confidence interval, 100-179) and was higher for individuals who were older, women, white or black, or who had valvular heart disease, heart failure, diabetes mellitus, lung disease, or prior bleeding. We estimate the national prevalence of symptomatic PSVT to be 168 per 100 000 (95% confidence interval, 120-215). CONCLUSIONS: Selected diagnostic codes in inpatient and emergency department settings may be useful to identify symptomatic PSVT episodes. We project that at least 0.168% of US adults experience symptomatic PSVT, and certain characteristics can identify people at higher risk.

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