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      A scoring algorithm for the accurate differential diagnosis of regular wide QRS complex tachycardia

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      https://www.riss.kr/link?id=O119810232

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      다국어 초록 (Multilingual Abstract)

      The differential diagnosis of regular wide QRS complex tachycardia (RWQRST) remains the subject of numerous publications, all of which aim at diagnosis during the acute phase. Although an accurate diagnosis is necessary to make long‐term decisions, ...

      The differential diagnosis of regular wide QRS complex tachycardia (RWQRST) remains the subject of numerous publications, all of which aim at diagnosis during the acute phase. Although an accurate diagnosis is necessary to make long‐term decisions, it often leads to invasive testing.
      Criteria with high positive predictive values (PPVs) for diagnosis can be obtained by analyzing the electrocardiogram (ECG) data during RWQRST and comparing them with these data at baseline. By assigning points to these criteria, a scoring algorithm to accurately diagnose numerous patients can be obtained. A total of 352 consecutive patients with RWQRST were included. Two electrophysiologists blind to patient condition analyzed the 16 criteria considered as having high PPVs.
      A total of 149 (42.3%) cases were supraventricular tachycardia (SVT), and 203 (57.7%) cases were ventricular tachycardia (VT). A higher percentage of patients with VT had structural heart disease (86.7% vs 16.1%). Seven of the 16 criteria analyzed had PPVs > 95%, and each criterion was assigned a score. A final score of –1 was indicative of SVT (PPV 98%); a score of 1 was indicative of VT (PPV 98%); and a score of ≥2 was indicative of VT (PPV 100%). A score of ≠0 was obtained for 51.7% of all cases of tachycardia, making it possible to reach a highly accurate diagnosis in approximately half of all cases. No cases of VT scored –1, and no cases of SVT scored ≥2.
      The current scoring system stands out for its high PPV (98%) and specificity (98%), enabling an accurate diagnosis for more than half of the patients.

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