Heart Rate Variability as an Indicator of Autonomic Nervous System Disturbance in Tetanus

Abstract

Autonomic nervous system dysfunction (ANSD) is a significant cause of mortality in tetanus. Currently, diagnosis relies on nonspecific clinical signs. Heart rate variability (HRV) may indicate underlying autonomic nervous system activity and represents a potentially valuable noninvasive tool for ANSD diagnosis in tetanus. HRV was measured from three 5-minute electrocardiogram recordings during a 24-hour period in a cohort of patients with severe tetanus, all receiving mechanical ventilation. HRV measurements from all subjects-five with ANSD (Ablett Grade 4) and four patients without ANSD (Ablett Grade 3)-showed HRV was lower than reported ranges for healthy individuals. Comparing different severities of tetanus, raw data for both time and frequency measurements of HRV were reduced in those with ANSD compared with those without. Differences were statistically significant in all except root mean square SD, indicating HRV may be a valuable tool in ANSD diagnosis.

The management of tetanus in adults in an intensive care unit in Southern Vietnam

“…Autonomic nervous system dysfunction (ANSD) was defined as at least three of: heart rate >100 beats per minute (bpm), systolic blood pressure >140 mmHg, mean arterial pressure < 60 mmHg, pyrexia > 38°C, and fluctuating blood pressure. All features should be present within one day with no other apparent cause 14 . Sensitivity evaluation of mortality rates within this study was performed by comparing with overall hospital database for outcomes of all patients with tetanus (ICD10 code A35) during the period 2016- 2018.…”

Vital sign monitoring using wearable devices in a Vietnamese intensive care unit

“…For this study we chose standardised measures of HRV previously found to be of value in patients with tetanus and other cardiovascular syndromes. 16 17 Briefly these are divided into time domain variables (if analysed according to the distribution of RR intervals over time) and frequency domain variables if analysed after Fourier transformation (see figure 1 caption). RR intervals were identified from QRS complexes in ECG recordings using the Pan-Tompkins algorithm 18 implemented in EDFBrowser (https://www.…”

“…We specifically selected patients with tetanus as they have significant cardiovascular system disturbance as well as muscle spasms and increased sweating, thus posing a significant challenge for wearable monitors. 16 To evaluate quality of wearablerecorded data, we computed and compared heart rate variability (HRV) data with that from state-of-the-art clinical monitors.…”

Recent Advances in Cardiovascular Disease Biosensors and Monitoring Technologies

“…The variation in heart rate is caused by the alternation in sympathetic and parasympathetic control of the heart. Thus, HRV can also be used to demonstrate neural modulation activity on the cardiac system. , For patients at risk for heart disease, HRV serves as a reliable metric for assessing whether the heart is beating properly. For instance, the identification of arrhythmia, myocardial infarction, and other CVDs can be done through ECG signal interpretation and HRV analysis.…”