Occurrence of Relative Bradycardia and Relative Tachycardia in Individuals Diagnosed With COVID-19

Natarajan, Aravind; Su, Hao-Wei; Heneghan, Conor

doi:10.3389/fphys.2022.898251

Cited by 6 publications

(17 citation statements)

References 57 publications

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“…7 , 34 Natarajan et.al found RMSSD exhibits a similar three-stage temporal evolution as RHR, except that the phase is reversed, that is, when RHR increases, RMSSD decreases and vice versa. 22 However, contrary to previous research, we found no dynamic changes in HRV with the progression and exacerbation of the disease. This may be due to the less severe patients and shorter observation periods in this outbreak.…”

Section: Discussioncontrasting

confidence: 99%

“… 19 Natarajan et al showed that patients’ heart rates increased abnormally around the time of onset, began to decrease 1 week after onset, and returned to baseline around the 21st day after onset. 5 In their later study of long COVID, 22 they observed that RHR (the average heart rate during sleep) undergoes three distinct phases: (a) a rise during the onset of symptoms with an average peak increase relative to baseline, (b) a subsequent decline, reaching a minimum approximately 13 days after symptom onset, and (c) a subsequent increase, culminating in a second peak around 28 days after symptom onset, returning to baseline levels on average about 112 days after symptom onset. Similar changes were seen in the study by Radin et al 23 In our study, we observed a significant decrease in RHR and sleep heart rate in the more severe group at day 25 after onset, similar to the third stage of RHR change found by Natarajan et al Probably because our sample size was small and our observation period was not long enough, the pattern of RHR changes found by Natarajan et al was not fully represented in our study.…”

Section: Discussionmentioning

confidence: 99%

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COVID-19 surveillance based on consumer wearable devices

Zhang,

Sun,

Liao

et al. 2024

DIGITAL HEALTH

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Background Consumer wearable devices such as wristbands and smartwatches have potential application value in communicable disease surveillance. Objective We investigated the ability of wearable devices to monitor COVID-19 patients of varying severity. Methods COVID-19 patients with mobile phones supporting wearable device applications were selected from Dalian Sixth People Hospital. Physiological parameters from the wearable devices and electronic questionnaires were collected from the device wearing until 14 days post-discharge. Clinical information during hospitalization was also recorded. Based on imaging data, the patients were categorized into the milder group without pneumonia and the more severe group with pneumonia. We plotted the curves of the physiological parameters of the two groups to compare the differences and changes. Results Ninety-eight patients were included in the analysis. The mean age was 39.6 ± 10.5 years, including 45 males (45.9%). There were 24 asymptomatic patients, 10 mild patients, 60 moderate patients, and 4 severe patients. Compared with the milder group, the more severe group had higher heart rate-related parameters, while the heart rate variability (HRV) was the opposite. In the more severe group, the heart rate-related parameters showed a downward trend from 0 to 7 days after the fever resolution. Among them, the resting heart rate and sleep heart rate decreased on the 25th day after the onset and were close to the milder group 1 week after discharge. Conclusions Consumer wearable devices have the potential to monitor respiratory infections. Heart rate-related parameters obtained from these devices can be sensitive indicators of COVID-19 severity and correlate with disease evolution. Trial registration ClinicalTrials.gov NCT04459637.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussionmentioning

confidence: 99%

COVID-19 surveillance based on consumer wearable devices

Zhang,

Sun,

Liao

et al. 2024

DIGITAL HEALTH

View full text Add to dashboard Cite

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“…As has previously been reported [20,21], we observe a pattern of transient RHR elevation from COVID-19 infection onset for a week, followed by a period of transient reduced RHR from the second to third week, and finally a chronic or long-lasting increase in resting heart rate in some participants which can last several months or longer (Figure 4. This pattern of acute elevation and subsequent reduction is more prominent in the LCOVID cohort compared to the short COVID cohort, as shown in Figure 4.…”

Section: Discussionsupporting

confidence: 84%

Presentation of long COVID and associated risk factors in a mobile health study

Stewart

Ranjan

Conde

et al. 2022

Preprint

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Background The Covid Collab study was a citizen science mobile health research project set up in June 2020 to monitor COVID-19 symptoms and mental health through questionnaire self-reports and passive wearable device data. Methods Using mobile health data, we consider whether a participant is suffering from long COVID in two ways. Firstly, by whether the participant has a persistent change in a physiological signal commencing at a diagnosis of COVID-19 that last for at least twelve weeks. Secondly, by whether a participant has self-reported persistent symptoms for at least twelve weeks. We assess sociodemographic and wearable-based risk factors for the development of long COVID according to the above two categorisations. Findings Persistent changes to physiological signals measured by com- mercial fitness wearables, including heart rate, sleep, and activity, are visible following a COVID-19 infection and may help differentiate people who develop long COVID. Anxiety and depression are significantly and persistently affected at a group level following a COVID-19 infection. We found the level of activity undertaken in the year prior to illness was protective against long COVID and that symptoms of depression before and during the acute illness may be a risk factor. Interpretation Mobile health and wearable devices may prove to be a useful resource for tracking recovery and presence of long-term sequelae to COVID-19. Mental wellbeing is significantly negatively effected on average for an extended period of time following a COVID-19 infection.

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“…Studies utilizing data from fitbit devices have shown modification in the Resting Heart Rate (RHR) for up to 3 months following symptom onset with substantial intraindividual variability. A pattern of bradycardia and tachycardia in the RHR were also observed in the patients over this period ( 17 , 18 ). For patients with underlying heart conditions and respiratory disease, COVID-19 can have fatal consequences.…”

Section: Introductionmentioning

confidence: 52%

A descriptive study of the clinical impacts on COVID-19 survivors using telemonitoring (The TeleCOVID Study)

Chow

D’Souza

Ford

et al. 2023

Front. Med. Technol.

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BackgroundThere is increasing evidence that COVID-19 survivors are at increased risk of experiencing a wide range of cardiovascular complications post infection; however, there are no validated models or clear guidelines for remotely monitoring the cardiac health of COVID-19 survivors.ObjectiveThis study aims to test a virtual, in-home healthcare monitoring model of care for detection of clinical symptoms and impacts on COVID-19 survivors. It also aims to demonstrate system usability and feasibility.MethodsThis open label, prospective, descriptive study was conducted in South Western Sydney. Included in the study were patients admitted to the hospital with the diagnosis of COVID-19 between June 2021 and November 2021. Eligible participants after consent were provided with a pulse oximeter to measure oxygen saturation and a S-Patch EX to monitor their electrocardiogram (ECG) for a duration of 3 months. Data was transmitted in real-time to a mobile phone via Bluetooth technology and results were sent to the study team via a cloud-based platform. All the data was reviewed in a timely manner by the investigator team, for post COVID-19 related symptoms, such as reduction in oxygen saturation and arrhythmia.Outcome measureThis study was designed for feasibility in real clinical setting implementation, enabling the study team to develop and utilise a virtual, in-home healthcare monitoring model of care to detect post COVID-19 clinical symptoms and impacts on COVID-19 survivors.ResultsDuring the study period, 23 patients provided consent for participation. Out of which 19 patients commenced monitoring. Sixteen patients with 81 (73.6%) valid tests were included in the analysis and amongst them seven patients were detected by artificial intelligence to have cardiac arrhythmias but not clinically symptomatic. The patients with arrhythmias had a higher occurrence of supraventricular ectopy, and most of them took at least 2 tests before detection. Notably, patients with arrhythmia had significantly more tests than those without [t-test, t (13) = 2.29, p < 0.05].ConclusionsPreliminary observations have identified cardiac arrhythmias on prolonged cardiac monitoring in 7 out of the first 16 participants who completed their 3 months follow-up. This has allowed early escalation to their treating doctors for further investigations and early interventions.

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Occurrence of Relative Bradycardia and Relative Tachycardia in Individuals Diagnosed With COVID-19

Cited by 6 publications

References 57 publications

COVID-19 surveillance based on consumer wearable devices

COVID-19 surveillance based on consumer wearable devices

Presentation of long COVID and associated risk factors in a mobile health study

A descriptive study of the clinical impacts on COVID-19 survivors using telemonitoring (The TeleCOVID Study)

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