Opportunistic screening for asymptomatic left ventricular dysfunction in type 2 diabetes mellitus.

BACKGROUND: International guidelines recommend natriuretic peptide biomarker-based screening for patients at high heart failure (HF) risk to allow early detection. There have been few reports about the incorporation of screening procedure to existing clinical practice. OBJECTIVE: To implement screening of left ventricular dysfunction in patients with type 2 diabetes mellitus (DM). METHOD: A prospective screening study at the DM complication screening centre was performed. RESULTS: Between 2018 and 2019, 1043 patients (age: 63.7±12.4 years; male: 56.3%) with mean glycated haemoglobin of 7.25%±1.34% were recruited. 81.8% patients had concomitant hypertension, 31.1% had coronary artery disease, 8.0% had previous stroke, 5.5% had peripheral artery disease and 30.7% had chronic kidney disease (CKD) stages 3-5. 43 patients (4.1%) had an elevated N-terminal prohormone of brain natriuretic peptide (NT-proBNP) concentration above the age-specific diagnostic thresholds for HF, and 43 patients (4.1%) had newly detected atrial fibrillation (AF). The prevalence of elevated NT-proBNP increased with age from 0.85% in patients aged <50 years to 7.14% in those aged 70-79 years and worsening kidney function from 0.43% in patients with CKD stage 1 to 42.86% in CKD stage 5. In multivariate logistic regression, male gender (OR: 3.67 (1.47-9.16), p = 0.005*), prior stroke (OR: 3.26 (1.38-7.69), p = 0.007*), CKD (p<0.001*) and newly detected AF (OR: 7.02 (2.65-18.57), p<0.001*) were significantly associated with elevated NT-proBNP. Among patients with elevated NT-proBNP, their mean left ventricular ejection fraction (LVEF) was 51.4%±14.7%, and 45% patients had an LVEF <50%. CONCLUSION: NT-proBNP and ECG screening could be implemented with relative ease to facilitate early detection of cardiovascular complication and improve long-term outcomes.

Automatic detection of cardiac conditions from photos of electrocardiogram captured by smartphones.

BACKGROUND: Researchers have developed machine learning-based ECG diagnostic algorithms that match or even surpass cardiologist level of performance. However, most of them cannot be used in real-world, as older generation ECG machines do not permit installation of new algorithms. OBJECTIVE: To develop a smartphone application that automatically extract ECG waveforms from photos and to convert them to voltage-time series for downstream analysis by a variety of diagnostic algorithms built by researchers. METHODS: A novel approach of using objective detection and image segmentation models to automatically extract ECG waveforms from photos taken by clinicians was devised. Modular machine learning models were developed to sequentially perform waveform identification, gridline removal, and scale calibration. The extracted data were then analysed using a machine learning-based cardiac rhythm classifier. RESULTS: Waveforms from 40 516 scanned and 444 photographed ECGs were automatically extracted. 12 828 of 13 258 (96.8%) scanned and 5399 of 5743 (94.0%) photographed waveforms were correctly cropped and labelled. 11 604 of 12 735 (91.1%) scanned and 5062 of 5752 (88.0%) photographed waveforms achieved successful voltage-time signal extraction after automatic gridline and background noise removal. In a proof-of-concept demonstration, an atrial fibrillation diagnostic algorithm achieved 91.3% sensitivity, 94.2% specificity, 95.6% positive predictive value, 88.6% negative predictive value and 93.4% F1 score, using photos of ECGs as input. CONCLUSION: Object detection and image segmentation models allow automatic extraction of ECG signals from photos for downstream diagnostics. This novel pipeline circumvents the need for costly ECG hardware upgrades, thereby paving the way for large-scale implementation of machine learning-based diagnostic algorithms.

Daily ambulatory remote monitoring system for drug escalation in chronic heart failure with reduced ejection fraction: pilot phase of DAVID-HF study.

Aims: Underutilization of guideline-directed heart failure with reduced ejection fraction (HFrEF) medications contributes to poor outcomes. Methods and results: A pilot study to evaluate the safety and efficacy of a home-based remote monitoring system for HFrEF management was performed. The system included wearable armband monitors paired with the smartphone application. An HFrEF medication titration algorithm was used to adjust medication daily. The primary endpoint was HFrEF medication utilization at 120 days. Twenty patients (60.5 ± 8.2 years, men: 85%) with HFrEF were recruited. All received angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI) at recruitment; 45% received ≥50% maximal targeted dose (MTD) with % MTD of 44.4 ± 31.7%. At baseline, 90 and 70% received beta-adrenergic blocker and mineralocorticoid receptor antagonist (MRA), 35% received ≥50% MTD beta-adrenergic blocker with % MTD of 34.1 ± 29.6%, and 25% received ≥50% MTD MRA with % MTD of 25.0 ± 19.9%. At 120 days, 70% received ≥50% MTD ACEI/ARB/ARNI (P = 0.110) with % MTD increased to 64.4 ± 33.5% (P = 0.060). The proportion receiving ≥50% MTD ARNI increased from 15 to 55% (P = 0.089) with % MTD ARNI increased from 20.6 ± 30.9 to 53.1 ± 39.5% (P = 0.006*). More patients received ≥50% MTD MRA (65 vs. 25%, P = 0.011*) with % MTD MRA increased from 25.0 ± 19.9 to 46.2 ± 28.8% (P = 0.009*). Ninety-five per cent of patients had reduced NT-proBNP with the percentage reduction of 26.7 ± 19.7%. Conclusion: Heart failure with reduced ejection fraction medication escalation with remote monitoring appeared feasible.

Protocol for Home-Based Solution for Remote Atrial Fibrillation Screening to Prevent Recurrence Stroke (HUA-TUO AF Trial): a randomised controlled trial.

INTRODUCTION: Current international guidelines recommend ECG monitoring after an ischaemic stroke to detect atrial fibrillation (AF) in order to prevent stroke recurrence. However, optimal strategies to detect AF and the downstream management to prevent stroke recurrence remain to be established. The objective of the study was to explore the use of long-term home-based ECG monitoring for AF detection and stroke prevention in patients with a history of stroke. METHODS AND ANALYSIS: This prospective, randomised, open-label trial with blinded endpoint adjudication aimed to evaluate the efficacy of long-term home-based ECG monitoring for AF detection and stroke prevention in a 24-month period. Patients aged >18 years with a history of ischaemic stroke will be stratified according to the time from the index ischaemic stroke: <1, 1-3 and >3 years and then randomised in 1:1 to (1) home-based AF screening and (2) control. The home-based AF screening system comprises (1) a handheld single-lead ECG recorder (Comfit Healthcare Devices, Hong Kong SAR, China) and (2) a patient-facing smartphone application specially designed for the study. Patients randomised to the home-based AF group will record a 30 s single-lead ECG using a specially designed handheld ECG device every morning or when symptomatic. All remotely obtained data will be automatically transmitted in real-time through the study smartphone application to a secured cloud hosting and analysed using an artificial intelligence-based diagnostic system. When a diagnosis of AF is made with the system, the patients will be called back for a formal cardiology consultation within 1 week. The primary endpoint is the time to first detection of AF at 24 months of follow-up. Secondary endpoints include recurrent stroke or transient ischaemic attack, initiation of long-term anticoagulation therapy, hospitalisation for heart failure, cardiovascular death and all-cause death. ETHICS AND DISSEMINATION: The study protocol has been approved by the institutional review board of The University of Hong Kong, and Hong Kong West Cluster, Hospital Authority, Hong Kong SAR, China. Results will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04523649.

Observational study on wearable biosensors and machine learning-based remote monitoring of COVID-19 patients.

Patients infected with SARS-CoV-2 may deteriorate rapidly and therefore continuous monitoring is necessary. We conducted an observational study involving patients with mild COVID-19 to explore the potentials of wearable biosensors and machine learning-based analysis of physiology parameters to detect clinical deterioration. Thirty-four patients (median age: 32 years; male: 52.9%) with mild COVID-19 from Queen Mary Hospital were recruited. The mean National Early Warning Score 2 (NEWS2) were 0.59 ± 0.7. 1231 manual measurement of physiology parameters were performed during hospital stay (median 15 days). Physiology parameters obtained from wearable biosensors correlated well with manual measurement including pulse rate (r = 0.96, p < 0.0001) and oxygen saturation (r = 0.87, p < 0.0001). A machine learning-derived index reflecting overall health status, Biovitals Index (BI), was generated by autonomous analysis of physiology parameters, symptoms, and other medical data. Daily BI was linearly associated with respiratory tract viral load (p < 0.0001) and NEWS2 (r = 0.75, p < 0.001). BI was superior to NEWS2 in predicting clinical worsening events (sensitivity 94.1% and specificity 88.9%) and prolonged hospitalization (sensitivity 66.7% and specificity 72.7%). Wearable biosensors coupled with machine learning-derived health index allowed automated detection of clinical deterioration.

Cardiovascular sequalae in uncomplicated COVID-19 survivors.

BACKGROUND: A high proportion of COVID-19 patients were reported to have cardiac involvements. Data pertaining to cardiac sequalae is of urgent importance to define subsequent cardiac surveillance. METHODS: We performed a systematic cardiac screening for 97 consecutive COVID-19 survivors including electrocardiogram (ECG), echocardiography, serum troponin and NT-proBNP assay 1-4 weeks after hospital discharge. Treadmill exercise test and cardiac magnetic resonance imaging (CMR) were performed according to initial screening results. RESULTS: The mean age was 46.5 ± 18.6 years; 53.6% were men. All were classified with non-severe disease without overt cardiac manifestations and did not require intensive care. Median hospitalization stay was 17 days and median duration from discharge to screening was 11 days. Cardiac abnormalities were detected in 42.3% including sinus bradycardia (29.9%), newly detected T-wave abnormality (8.2%), elevated troponin level (6.2%), newly detected atrial fibrillation (1.0%), and newly detected left ventricular systolic dysfunction with elevated NT-proBNP level (1.0%). Significant sinus bradycardia with heart rate below 50 bpm was detected in 7.2% COVID-19 survivors, which appeared to be self-limiting and recovered over time. For COVID-19 survivors with persistent elevation of troponin level after discharge or newly detected T wave abnormality, echocardiography and CMR did not reveal any evidence of infarct, myocarditis, or left ventricular systolic dysfunction. CONCLUSION: Cardiac abnormality is common amongst COVID-survivors with mild disease, which is mostly self-limiting. Nonetheless, cardiac surveillance in form of ECG and/or serum biomarkers may be advisable to detect more severe cardiac involvement including atrial fibrillation and left ventricular dysfunction.

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.

Protocol, rationale and design of DAbigatran for Stroke PreVention In Atrial Fibrillation in MoDerate or Severe Mitral Stenosis (DAVID-MS): a randomised, open-label study.

INTRODUCTION: Current international guidelines recommend non-vitamin K oral anticoagulants (NOACs) for stroke prevention among patients with non-valvular atrial fibrillation (AF) at significant ischaemic stroke risk given the superior safety and comparable efficacy of NOACs over warfarin. Nonetheless, the safety and effectiveness of NOACs have not been evaluated in patients with AF with underlying moderate or severe mitral stenosis (MS), hence the recommended stroke prevention strategy remains warfarin therapy. METHOD AND ANALYSIS: MS remains disproportionately prevalent in Asian countries compared with the developed countries. This prospective, randomised, open-label trial with blinded endpoint adjudication aims to evaluate the safety and efficacy of dabigatran for stroke prevention in AF patients with moderate or severe MS. Patients with AF aged ≥18 years with moderate or severe MS not planned for valvular intervention in the coming 12 months will be randomised in a 1:1 ratio to receive dabigatran 110 mg or 150 mg two times per day or warfarin with international normalised ratio 2-3 in an open-label design. Patients with estimated creatinine clearance <30 mL/min, or with a concomitant indication for antiplatelet therapy will be excluded. The primary outcome is a composite of stroke and systemic embolism. Secondary outcomes are ischaemic stroke, systemic embolism, haemorrhagic stroke, intracranial haemorrhage, major bleeding and death. The estimated required sample size is approximately 686 participants. ETHICS AND DISSEMINATION: The study protocol has been approved by the Institutional Review Board of the University of Hong Kong and Hong Kong West Cluster, Hospital Authority, Hong Kong for Fung Yiu King Hospital, Grantham Hospital, Queen Mary Hospital and Tung Wah Hospital in Hong Kong. Results will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT04045093); pre-results.

Postoperative Rigid Cervical Collar Leads to Less Axial Neck Pain in the Early Stage After Open-Door Laminoplasty-A Single-Blinded Randomized Controlled Trial.

BACKGROUND: Cervical collars are used after laminoplasty to protect the hinge opening, reduce risks of hinge fractures, and avoid spring-back phenomena. However, their use may lead to reduced range of motion and worse neck pain. OBJECTIVE: To investigate the clinical, radiological, and functional outcomes of patients undergoing single-door laminoplasty with or without collar immobilization. METHODS: This was a prospective, parallel, single-blinded randomized controlled trial. Patients underwent standardized single-door laminoplasty with mini-plates for cervical myelopathy and were randomly allocated into 2 groups based on the use of collar postoperatively. Clinical assessments included cervical range of motion, axial neck pain (VAS [visual analogue scale]), and objective scores (short-form 36-item, neck disability index, and modified Japanese Orthopaedic Association). All assessments were performed preoperatively and at postoperative 1, 2, 3, and 6 wk, and 3, 6, and 12 mo. Comparative analysis was performed via analysis of variance adjusted by baseline scores, sex, and age as covariates. RESULTS: A total of 35 patients were recruited and randomized to collar use (n = 16) and without (n = 19). There were no dropouts or complications. There were no differences between groups at baseline. Subjects had comparable objective scores and range of motion at postoperative time-points. Patients without collar use had higher VAS at postoperative 1 wk (5.4 vs 3.5; P = .038) and 2 wk (3.5 vs 1.5; P = .028) but subsequently follow-up revealed no differences between the 2 groups. CONCLUSION: The use of a rigid collar after laminoplasty leads to less axial neck pain in the first 2 wk after surgery. However, there is no additional benefit with regards to range of motion, quality of life, and complication risk.

Asystole in focal epilepsy complicating a traumatic subdural hematoma.

Ictal asystole due to sinus node suppression is a cause of sudden unexplained death in epilepsy. Here, for the first time, we describe a complete atrioventricular nodal block in a patient with non-compressive traumatic subdural hematoma, who developed ictal asystole as a delayed presentation. A leadless VVI pacemaker (ventricular paced, ventricular sensed, and pacing inhibited in response to a sensed beat) was implanted as a preventive measure against seizure-related heart block.