Studying the Effect of Long COVID-19 Infection on Sleep Quality Using Wearable Health Devices: Observational Study

Mekhael, Mario; Lim, Chan Ho; Hajjar, Abdel Hadi El; Noujaim, Charbel; Pottle, Christopher; Makan, Noor; Dagher, Lilas; Zhang, Yichi; Chouman, Nour; Li, Dan L.; Ayoub, Tarek; Marrouche, Nassir F.

doi:10.2196/38000

Cited by 40 publications

(30 citation statements)

References 43 publications

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“…Similarly, a study quantifying the population burden of ILI based on changes in activity showed that wearable sensors can be used to estimate the burden of ILI at individual and national levels in terms of the total daily step count [ 12 ]. Other studies have suggested that wearable sensors can potentially capture subtle within-person changes that could signal SARS-CoV-2 infection [ 14 , 15 , 18 , 19 , 21 , 23 ]. A study demonstrated differences in RHR elevations in individuals before and during COVID-19 illness compared with those with non–COVID-19 ILI [ 20 ], although another study cautioned about the potential impact of changes in wearer behavior after receiving a positive COVID-19 test result [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study

Hunter¹,

Shapiro²,

Chawla³

et al. 2023

J Med Internet Res

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Background The burden of influenza-like illness (ILI) is typically estimated via hospitalizations and deaths. However, ILI-associated morbidity that does not require hospitalization remains poorly characterized. Objective The main objective of this study was to characterize ILI burden using commercial wearable sensor data and investigate the extent to which these data correlate with self-reported illness severity and duration. Furthermore, we aimed to determine whether ILI-associated changes in wearable sensor data differed between care-seeking and non–care-seeking populations as well as between those with confirmed influenza infection and those with ILI symptoms only. Methods This study comprised participants enrolled in either the FluStudy2020 or the Home Testing of Respiratory Illness (HTRI) study; both studies were similar in design and conducted between December 2019 and October 2020 in the United States. The participants self-reported ILI-related symptoms and health care–seeking behaviors via daily, biweekly, and monthly surveys. Wearable sensor data were recorded for 120 and 150 days for FluStudy2020 and HTRI, respectively. The following features were assessed: total daily steps, active time (time spent with >50 steps per minute), sleep duration, sleep efficiency, and resting heart rate. ILI-related changes in wearable sensor data were compared between the participants who sought health care and those who did not and between the participants who tested positive for influenza and those with symptoms only. Correlative analyses were performed between wearable sensor data and patient-reported outcomes. Results After combining the FluStudy2020 and HTRI data sets, the final ILI population comprised 2435 participants. Compared with healthy days (baseline), the participants with ILI exhibited significantly reduced total daily steps, active time, and sleep efficiency as well as increased sleep duration and resting heart rate. Deviations from baseline typically began before symptom onset and were greater in the participants who sought health care than in those who did not and greater in the participants who tested positive for influenza than in those with symptoms only. During an ILI event, changes in wearable sensor data consistently varied with those in patient-reported outcomes. Conclusions Our results underscore the potential of wearable sensors to discriminate not only between individuals with and without influenza infections but also between care-seeking and non–care-seeking populations, which may have future application in health care resource planning. Trial Registration Clinicaltrials.gov NCT04245800; https://clinicaltrials.gov/ct2/show/NCT04245800

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Section: Discussionmentioning

confidence: 99%

“…Another study showed that abnormalities in RHR and sleep duration, measured using wearable sensors, could be leveraged to predict the real-time incidence of ILI [ 13 ]. Recently, wearable sensor data have also been used to assess the physiological signs associated with COVID-19 [ 14 - 23 ].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study

Hunter¹,

Shapiro²,

Chawla³

et al. 2023

J Med Internet Res

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“…69 There is limited evidence at this time on the prevalence of primary sleep disorders in long COVID, but disruption in sleep architecture that may not meet criteria for a specific diagnosis may still have effects and can provide a focus for management strategies. 70 Seizures do not appear to be a frequent finding in long COVID, but electroencephalogram should be performed if concerning symptoms are present. 9 Lumbar puncture and cerebrospinal fluid (CSF) testing are likely not needed in most cases unless there is a concern for an alternative, treatable process.…”

Section: Neurological Symptoms In Long Covid Navismentioning

confidence: 99%

A Review of Neurological Symptoms in Long COVID and Clinical Management

Navis

2023

Semin Neurol

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Long COVID is a clinical diagnosis generally referring to the persistence or development of new symptoms, affecting multiple organ systems after SARS-CoV-2 COVID-19 infection. Long COVID is thought to affect ∼20% of people after infection, including all age ranges and severity of infection. Fatigue, postexertional malaise, and respiratory and cardiac symptoms are commonly described. Neurological symptoms such as cognitive changes, sensory disturbances, headaches, and dysautonomia are common as well. The underlying pathophysiology remains unclear but immune dysregulation, autoimmunity, persistent viral reservoirs, and microvascular dysfunction have been implicated. As there are no tests at this time to diagnose long COVID, work-up should be focused on assessing reversible or treatable causes of symptoms. Furthermore, no treatments for long COVID currently exist, and management remains focused on a multimodal approach and symptom management, with many people showing improvement in symptoms over time.

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“…Sensors and commercial wearable devices have been widely used to monitor vital signs in COVID-19 patients over long periods of time (15)(16)(17)(18)(19). 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.…”

Section: Introductionmentioning

confidence: 99%

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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Studying the Effect of Long COVID-19 Infection on Sleep Quality Using Wearable Health Devices: Observational Study

Cited by 40 publications

References 43 publications

Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study

Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study

A Review of Neurological Symptoms in Long COVID and Clinical Management

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

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