Prediction of QTc length as function of BMI: a clinical tool to establish arrhythmias risk in obesity

AIMS

Among the electrocardiographic alterations used for stratifying the cardiovascular risk of life threatening arrhythmias (LFA) and sudden death (SD) there is the increment of the corrected QT(QTc). This increment is usually observable in obese patients (OP). Therefore, a study has been planned to investigate the possibility to predict QTc values in OP simply by detecting the best fitting regression method that represents the relationship between QTc and Body Mass Index (BMI).

MATERIALS AND METHODS

The study has been carried on 144 individuals classified as a function of their BMI in normoponderal subjects (NPS, No. 24; F/M=15/9; BMI=21.8± 1.7 kg/m(2)), Class I OP (No. 24; F/M=17/7; BMI=32.5± 1.1 kg/m(2)); Class II OP (No. 24; F/M=17/7; BMI=37.7± 1.5 kg/m(2)). Class IIIa (No. 24, F/M=15/9; BMI=44.4± 27 kg/m(2)), Class IIIb (No. 24; F/M=14/10; BMI 54.3± 2.7 kg/m(2)); Class IIIc (No. 24; F/M=14/10; BMI=63.3± 4.5 kg/m(2)). Both linear and non-linear fitting modes have been tested.

RESULTS

While the BMI progressively increases in classified OP, the QTc shows an intergroup difference that is not only not constant but also declining in Class IIIc obesity. The optimal regressive model was found to be the following fourth order degree polynomial: QTc=317,15+(7,47xBMI)+(-0,28*BMI(2))+(0,005xBMI(3))+ (-0,00003xBMI(4)).

CONCLUSION

By entering the BMI of a given OP into the above-cited formula, the QTc can be easily predicted and compared to that of NPS. Importantly, to have the possibility for a pre-electrocardiographic estimation of QTc allows all the medical and paramedical personnel, involved in the multidisciplinary treatment of obesity, to immediately establish the cardiovascular risk in the OP under observation.

[Diagnosing silent cardiac dysautonomia via ambulatory blood pressure monitoring: early diagnosis shown by the lack of heart rate circadian rhythm in type 1 diabetes mellitus]

INTRODUCTION

Diabetes mellitus (DM) can be complicated by an involvement of Neurovegetative System (NVS), conventionally and non-invasively diagnosed by the means of Ewing's test and Heart Rate Variability (HRV) analysis. It is well known that the NVS is physiologically responsible, via biological clocks, for the regulation of Circadian Rhythms (CR) characterizing the majority of biological functions. Therefore, this study is aimed at investigating the CR of Heart Rate (HR) and Blood Pressure (BP) in DM, postulating that the diagnosis of Silent Cardiac Dysautonomia (SCD) could be facilitated by detecting anomalous rhythmometric changes, including the worse one, i.e., the lose of a CR.

MATERIALS AND METHODS

The study has been performed on 30 clinically healthy subjects (CHS), 10 patients with DM1 and 30 patients with DM2, who underwent an ambulatory BP monitoring (ABPM) collecting data equidistantly every 30 minutes, under standardized conditions of lifestyle. The group specific monitored values of systolic (S), diastolic (D) BP, as well as HR have been analyzed via: 1. a conventional analysis of their intradiem variability; 2. a chronobiometric analysis (Cosinor method) of their CR.

RESULTS

The conventional analysis disclosed that in CHS, DM1 and DM2, both the HR and BP show an intradiem variability that is significant (p less than 0.001). The chronobiological analysis showed that in CHS and DM2, both the HR and BP show a significant CR (p less than 0.001), viceversa in DM1 HR is characterized by a non significant CR (p=0.124), notwithstanding that the SBP and DBP maintain a significant CR (p less than 0.001).

CONCLUSIONS

The disappearance of HR CR in DM1 reveals the involvement of neurovegetative biological clock that selectively controls the HR CR, as it is demonstrated by the pathophysiological finding of an internal desynchronization between the HR and BP CR. The selective lose of HR CR in DM1 leads to conclude that the ABPM, along with its Cosinor analysis, might be a practical, repeatable, low cost, low risk technique for diagnosing the SCD, at least in DM1.