Evaluating a Remote Monitoring Program for Respiratory Diseases: Prospective Observational Study.

BACKGROUND: Patients with chronic respiratory diseases and those in the postdischarge period following hospitalization because of COVID-19 are particularly vulnerable, and little is known about the changes in their symptoms and physiological parameters. Continuous remote monitoring of physiological parameters and symptom changes offers the potential for timely intervention, improved patient outcomes, and reduced health care costs. OBJECTIVE: This study investigated whether a real-time multimodal program using commercially available wearable technology, home-based Bluetooth-enabled spirometers, finger pulse oximeters, and smartphone apps is feasible and acceptable for patients with chronic respiratory diseases, as well as the value of low-burden, long-term passive data collection. METHODS: In a 3-arm prospective observational cohort feasibility study, we recruited 60 patients from the Royal Free Hospital and University College Hospital. These patients had been diagnosed with interstitial lung disease, chronic obstructive pulmonary disease, or post-COVID-19 condition (n=20 per group) and were followed for 180 days. This study used a comprehensive remote monitoring system designed to provide real-time and relevant data for both patients and clinicians. Data were collected using REDCap (Research Electronic Data Capture; Vanderbilt University) periodic surveys, Remote Assessment of Disease and Relapses-base active app questionnaires, wearables, finger pulse oximeters, smartphone apps, and Bluetooth home-based spirometry. The feasibility of remote monitoring was measured through adherence to the protocol, engagement during the follow-up period, retention rate, acceptability, and data integrity. RESULTS: Lowest-burden passive data collection methods, via wearables, demonstrated superior adherence, engagement, and retention compared with active data collection methods, with an average wearable use of 18.66 (SD 4.69) hours daily (77.8% of the day), 123.91 (SD 33.73) hours weekly (72.6% of the week), and 463.82 (SD 156.70) hours monthly (64.4% of the month). Highest-burden spirometry tasks and high-burden active app tasks had the lowest adherence, engagement, and retention, followed by low-burden questionnaires. Spirometry and active questionnaires had the lowest retention at 0.5 survival probability, indicating that they were the most burdensome. Adherence to and quality of home spirometry were analyzed; of the 7200 sessions requested, 4248 (59%) were performed. Of these, 90.3% (3836/4248) were of acceptable quality according to American Thoracic Society grading. Inclusion of protocol holidays improved retention measures. The technologies used were generally well received. CONCLUSIONS: Our findings provide evidence supporting the feasibility and acceptability of remote monitoring for capturing both subjective and objective data from various sources for respiratory diseases. The high engagement level observed with passively collected data suggests the potential of wearables for long-term, user-friendly remote monitoring in respiratory disease management. The unique piloting of certain features such as protocol holidays, alert notifications for missing data, and flexible support from the study team provides a reference for future studies in this field. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/28873.

No Evidence to Suggest that the Use of Acetylcholinesterase Inhibitors Confounds the Results of Two Blood-Based Biomarker Studies in Alzheimer's Disease.

BACKGROUND: There is an urgent need to discover Alzheimer's disease (AD) biomarkers that are both easily measured and reliable. Research into blood-based biomarkers for AD using transcriptomics and proteomics has been an attractive and promising area of research. However, to date researchers have not looked into the possibility of AD medication being a confounding factor in these studies. OBJECTIVE: This study explored whether acetylcholinesterase inhibitors (AChEIs), the main class of AD medication, are a confounding factor in AD blood biomarker studies. METHODS: The most promising blood transcriptomic and proteomic biomarkers from two recent studies were analyzed to determine if they were differentially expressed between AD subjects on AChEIs and subjects that were not. RESULTS: None of the gene or protein biomarkers analyzed were found to be significantly altered between subjects in either group. CONCLUSION: This study found no evidence that AChEIs are a confounding factor in these published AD blood biomarker studies. Further work is needed to confirm that this is also the case for other proposed biomarkers.

Are blood-based protein biomarkers for Alzheimer's disease also involved in other brain disorders? A systematic review.

BACKGROUND: Alzheimer's disease (AD) biomarkers are urgently needed for both early and accurate diagnosis and prediction of disease progression. Past research has studied blood-based proteins as potential AD biomarkers, revealing many candidate proteins. To date only limited effort has been made to investigate the disease specificity of AD candidate proteins and whether these proteins are also involved in other neurodegenerative or psychiatric conditions. OBJECTIVE: This review seeks to determine if blood-based AD candidate protein biomarkers are disease specific. METHODS: A two-stage systematic literature search was conducted. Firstly, the most consistently identified AD protein biomarkers in blood were determined from a list of published discovery or panel-based (>100 proteins) blood proteomics studies in AD. Secondly, an online database search was conducted using the 10 most consistently identified proteins to determine if they were involved in other brain disorders, namely frontotemporal lobe dementia, vascular dementia, Lewy body disease, Parkinson's disease, schizophrenia, depression, and autism. RESULTS: Among the reviewed candidate proteins, plasma protease C1 inhibitor, pancreatic prohormone, and fibrinogen γ chain were found to have the least evidence for non-specificity to AD. All other candidates were found to be affected by other brain disorders. CONCLUSION: Since we found evidence that the majority of AD candidate proteins might also be involved in other brain disorders, more research into the disease specificity of AD protein biomarkers is required.