Artificial intelligence mobile health platform for early detection of COVID-19 in quarantine subjects using a wearable biosensor: protocol for a randomised controlled trial

INTRODUCTION

There is an outbreak of COVID-19 worldwide. As there is no effective therapy or vaccine yet, rigorous implementation of traditional public health measures such as isolation and quarantine remains the most effective tool to control the outbreak. When an asymptomatic individual with COVID-19 exposure is being quarantined, it is necessary to perform temperature and symptom surveillance. As such surveillance is intermittent in nature and highly dependent on self-discipline, it has limited effectiveness. Advances in biosensor technologies made it possible to continuously monitor physiological parameters using wearable biosensors with a variety of form factors.

OBJECTIVE

To explore the potential of using wearable biosensors to continuously monitor multidimensional physiological parameters for early detection of COVID-19 clinical progression.

METHOD

This randomised controlled open-labelled trial will involve 200-1000 asymptomatic subjects with close COVID-19 contact under mandatory quarantine at designated facilities in Hong Kong. Subjects will be randomised to receive a remote monitoring strategy (intervention group) or standard strategy (control group) in a 1:1 ratio during the 14 day-quarantine period. In addition to fever and symptom surveillance in the control group, subjects in the intervention group will wear wearable biosensors on their arms to continuously monitor skin temperature, respiratory rate, blood pressure, pulse rate, blood oxygen saturation and daily activities. These physiological parameters will be transferred in real time to a smartphone application called Biovitals Sentinel. These data will then be processed using a cloud-based multivariate physiology analytics engine called Biovitals to detect subtle physiological changes. The results will be displayed on a web-based dashboard for clinicians' review. The primary outcome is the time to diagnosis of COVID-19.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from institutional review boards at the study sites. Results will be published in peer-reviewed journals.

Respiratory virus infection among hospitalized adult patients with or without clinically apparent respiratory infection: a prospective cohort study

Objectives

To determine the viral epidemiology and clinical characteristics of patients with and without clinically apparent respiratory tract infection.

Methods

This prospective cohort study was conducted during the 2018 winter influenza season. Adult patients with fever/respiratory symptoms (fever/RS group) were age- and sex-matched with patients without fever/RS (non-fever/RS group) in a 1:1 ratio. Respiratory viruses were tested using NxTAG™ Respiratory Pathogen Panel IVD, a commercially-available multiplex PCR panel.

Results

A total of 214 acutely hospitalized patients were included in the final analysis, consisting of 107 with fever/RS (fever/RS group), and 107 age- and sex-matched patients without fever/RS (non-fever/RS group). Respiratory viruses were detected in 34.1% (73/214) of patients, and co-infection occurred in 7.9% (17/214) of patients. The incidence of respiratory virus was higher in the fever/RS group than in the non-fever/RS group (44.9% (48/107) versus 23.4% (25/107), p 0.001). Influenza B virus, enterovirus/rhinovirus and coronaviruses were detected more frequently in the fever/RS group, whereas parainfluenza virus 4B and adenovirus were detected more frequently in the non-fever/RS group. Among the non-fever/RS group, chest discomfort was more common among patients tested positive for respiratory viruses than those without respiratory virus detected (44% (11/25) versus 22% (18/82), p 0.04).

Conclusions

Respiratory viruses can be frequently detected among hospitalized patients without typical features of respiratory tract infection. These patients may be a source of nosocomial outbreaks.

Genetic Polymorphisms in Estrogen Metabolic Pathway Associated with Risks of Alzheimer's Disease: Evidence from a Southern Chinese Population

OBJECTIVES

To investigate whether genetic variations on the estrogen metabolic pathway would be associated with risk of Alzheimer's disease (AD).

DESIGN

Cross-sectional study.

SETTING

Individuals were recruited at the Memory Clinic, Queen Mary Hospital, Hong Kong.

PARTICIPANTS

Chinese individuals with (n = 426) and without (n = 350) AD.

MEASUREMENTS

All subjects underwent a standardized cognitive assessment and genotyping of four candidate genes on the estrogen metabolic pathway (estrogen receptor α gene (ESR1), estrogen receptor β gene (ESR2), cytochrome P450 19A1 gene (CYP19A1), cytochrome P450 11A1 gene (CYP11A1)).

RESULTS

Apart from consistent results showing an association between apolipoprotein (APO)E and AD, strong evidence of disease associations were found for polymorphisms in ESR2 and CYP11A1 based on the entire data set. For ESR2, significant protective effects were found for A alleles of rs4986938 (permuted P = .02) and rs867443 (permuted P = .02). For CYP11A1, significant risk effects were found for G alleles of rs11638442 (permuted P = .03) and rs11632698 (permuted P = .03). Stratifying subjects according to APOE ε4 status, their genetic effects continued to be significant in the APOE ε4-negative subgroup. Associations between CYP11A1 polymorphisms (rs2279357, rs2073475) and risk of AD were detected in women but not men. Further gene-level analysis confirmed the above association between ESR2 and CYP11A1, and pathway-level analysis highlighted the genetic effect of the estrogen metabolic pathway on disease susceptibility (permuted pathway-level P = .03).

CONCLUSION

Consistent with previous biological findings for sex steroid hormones in the central nervous system, genetic alterations on the estrogen metabolic pathway were revealed in the Chinese population. Confirmation of these present findings in an independent population is warranted to elucidate disease pathogenesis and to explore the potential of hormone therapy in the treatment of AD.