Prevalence of QTc Prolongation in Patients with Parkinson's Disease. Assessment of the Effects of Drugs, Clinical Risk Factors and Used Correction Formula

Index of cardio-electrophysiological balance and Parkinson disease

Neurodegeneration of the autonomic nervous systems due to Parkinson disease (PD) may lead to increase in the QT duration. In recent years, a new parameter index of cardio-electrophysiological balance (ICEB) was found. ICEB is a significant parameter of medicine related dysrhythmia. The purpose of this research is to assess ICEB in PD. Twenty-eight PD cases and 26 controls participated in our investigation. First diagnosed PD patients were registered in the research. The symptom progression of PD was assessed Modified Hoehn and Yahr Scale. Analyzed ECG variables are QRS, PR, QT, corrected QT (QTc) interval, ICEB and corrected index of cardio-electrophysiological balance (ICEBc). All cases had sinus rhythm. ICEB was analyzed by the ratio of QT/QRS. ICEBc was analyzed by the ratio of QTc/QRS. Twenty-eight PD cases participated in this research. Among PD cases, 15 patients were female (53.5%). The mean age of PD patients are 59.03 ± 9.94 years. There was no important difference between groups with respect to the clinical variables. The Modified Hoehn and Yahr Scale was appreciably higher in the PD group than the Control group. The heart rate of the PD group was significantly lower than that of the control group. PR intervals and QRS duration were similar in both groups. QT and QTc duration were significantly longer in PD patients. Also, the ICEB and ICEBc variables were appreciably higher in PD cases. The findings of our investigation suggest that ICEB is related to PD. ICEB can help to evaluate arrhythmia risk in patients with PD.

Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening

BACKGROUND

Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagnosis of IPD. Cardiac autonomic dysfunction begins in the early stages of IPD, and an electrocardiogram (ECG) contains precise information on the heart.

OBJECTIVE

This study is to develop an ECG deep learning algorithm that can efficiently screen for IPD.

METHODS

Data were collected from 751 IPD patients (2,138 ECGs), 751 age and sex-matched non-IPD patients (2,673 ECGs) as a control group, and 297 drug-induced Parkinsonism (DPD) patients (875 ECGs) as a disease control group. ECG data were randomly divided into training set, validation set, and test set at a ratio of 6:2:2. We developed a deep-convolutional neural network (CNN) consisting of 16 layers with Bayesian optimization that classified IPD patients by ECG data. The robustness of the deep learning model was verified through 5-fold cross-validation.

RESULTS

The AUROC of the model for detection of IPD was 0.924 (95% CI, 0.913-0.936) in the test set. That for detecting DPD was 0.473 (95% CI, 0.453-0.504). The sensitivities of the model according to Unified Parkinson's Disease Rating Scale III and Hoehn & Yahr scale were also similar.

CONCLUSION

In conclusion, the CNN-based deep learning model using ECG data showed quite good performance in identifying IPD patients. Standardized 12-lead ECG test could be one of the clinically feasible candidate methods for early screening of IPD in the future.

Assessment of the QT interval in right bundle branch block

BACKGROUND

Identifying prolonged QT interval in RBBB has been problematic.

METHODS

Four approaches were compared to adjust for the QT prolongation in intermittent RBBB. The implications were assessed in a separate group of 200 persons with established RBBB.

RESULTS

In 12 individuals, mean age 74.5 years with intermittent RBBB, the presence of RBBB significantly (p < 0.05) increased the QT interval in each of six different heart rate correction formulae by an amount ranging from 35.4 ms in the Hodges formula to 50.2 ms in the Bazett formula. Four different equations were tested to adjust the QT interval and one approach QTc_RBBB = 0.945*QTc_RBBB - 26 was the best method to adjust for the increased QT in RBBB as it produced a QT value that was not significantly different from the QT interval in the absence of RBBB in intermittent RBBB.Failure to adjust the QT interval in RBBB produces an overestimate of the QT interval which in some heart rate adjustment formulae was marked. For the Bazett heart rate adjustment approach QTc 450 ms was found in 73.9% of men and QTc over 460 ms was found in 60.6% of women.

CONCLUSION

These data suggest the implementation of a new approach to recalculate the QT intervals in RBBB. QTc_RBBB = 0.945*QTc_RBBB - 26 with an appropriate heart rate adjustment formula (other than the Bazett formula) accurately predicts the QT interval in the absence of RBBB.