Digital Biomarker-Based Interventions: Systematic Review of Systematic Reviews

Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed

BACKGROUND

The demand for high-quality systematic literature reviews (SRs) for evidence-based medical decision-making is growing. SRs are costly and require the scarce resource of highly skilled reviewers. Automation technology has been proposed to save workload and expedite the SR workflow. We aimed to provide a comprehensive overview of SR automation studies indexed in PubMed, focusing on the applicability of these technologies in real world practice.

METHODS

In November 2022, we extracted, combined, and ran an integrated PubMed search for SRs on SR automation. Full-text English peer-reviewed articles were included if they reported studies on SR automation methods (SSAM), or automated SRs (ASR). Bibliographic analyses and knowledge-discovery studies were excluded. Record screening was performed by single reviewers, and the selection of full text papers was performed in duplicate. We summarized the publication details, automated review stages, automation goals, applied tools, data sources, methods, results, and Google Scholar citations of SR automation studies.

RESULTS

From 5321 records screened by title and abstract, we included 123 full text articles, of which 108 were SSAM and 15 ASR. Automation was applied for search (19/123, 15.4%), record screening (89/123, 72.4%), full-text selection (6/123, 4.9%), data extraction (13/123, 10.6%), risk of bias assessment (9/123, 7.3%), evidence synthesis (2/123, 1.6%), assessment of evidence quality (2/123, 1.6%), and reporting (2/123, 1.6%). Multiple SR stages were automated by 11 (8.9%) studies. The performance of automated record screening varied largely across SR topics. In published ASR, we found examples of automated search, record screening, full-text selection, and data extraction. In some ASRs, automation fully complemented manual reviews to increase sensitivity rather than to save workload. Reporting of automation details was often incomplete in ASRs.

CONCLUSIONS

Automation techniques are being developed for all SR stages, but with limited real-world adoption. Most SR automation tools target single SR stages, with modest time savings for the entire SR process and varying sensitivity and specificity across studies. Therefore, the real-world benefits of SR automation remain uncertain. Standardizing the terminology, reporting, and metrics of study reports could enhance the adoption of SR automation techniques in real-world practice.

The Bitemporal Lens Model-toward a holistic approach to chronic disease prevention with digital biomarkers

Objectives

We introduce the Bitemporal Lens Model, a comprehensive methodology for chronic disease prevention using digital biomarkers.

Materials and Methods

The Bitemporal Lens Model integrates the change-point model, focusing on critical disease-specific parameters, and the recurrent-pattern model, emphasizing lifestyle and behavioral patterns, for early risk identification.

Results

By incorporating both the change-point and recurrent-pattern models, the Bitemporal Lens Model offers a comprehensive approach to preventive healthcare, enabling a more nuanced understanding of individual health trajectories, demonstrated through its application in cardiovascular disease prevention.

Discussion

We explore the benefits of the Bitemporal Lens Model, highlighting its capacity for personalized risk assessment through the integration of two distinct lenses. We also acknowledge challenges associated with handling intricate data across dual temporal dimensions, maintaining data integrity, and addressing ethical concerns pertaining to privacy and data protection.

Conclusion

The Bitemporal Lens Model presents a novel approach to enhancing preventive healthcare effectiveness.

Digital measures in epilepsy in low-resourced environments

INTRODUCTION

Digital measures and digital health-care delivery have been rarely implemented in lower-and-middle-income countries (LMICs), contributing to worsening global disparities and inequities. Sustainable ways to implement and use digital approaches will help to improve time to access, management, and quality of life in persons with epilepsy, goals that remain unreachable in under-resourced communities. As under-resourced environments differ in human and economic resources, no one approach will be appropriate to all LMICs.

AREAS COVERED

Digital health and tools to monitor and measure digital endpoints and metrics of quality of life will need to be developed or adapted to the specific needs of under-resourced areas. Portable technologies may partially address the urban-rural divide. Careful delineation of stakeholders and their engagement and alignment in all efforts is critically important if these initiatives are to be successfully sustained. Privacy issues, neglected in many regions globally, must be purposefully addressed.

EXPERT OPINION

Epilepsy care in under-resourced environments has been limited by the lack of relevant technologies for diagnosis and treatment. Digital biomarkers, and investigative technological advances, may finally make it feasible to sustainably improve care delivery and ultimately quality of life including personalized epilepsy care.

[Developments in the digitalization of public health since 2020 : Examples from the Leibniz ScienceCampus Digital Public Health Bremen]

Digital public health has received a significant boost in recent years, especially due to the demands associated with the COVID-19 pandemic. In this report, we provide an overview of the developments in digitalization in the field of public health in Germany since 2020 and illustrate these with examples from the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH).The following topics are central: How do digital survey methods as well as digital biomarkers and artificial intelligence methods shape modern epidemiology and prevention research? What is the status of digitalization in public health offices? Which approaches to health economics evaluation of digital public health interventions have been utilized so far? What is the status of training and further education in digital public health?The first years of the Leibniz ScienceCampus Digital Public Health Bremen (LSC DiPH) were also strongly influenced by the COVID-19 pandemic. Repeated population-based digital surveys of the LSC indicated an increase in use of health apps in the population, for example, in applications to support physical activity. The COVID-19-pandemic has also shown that the digitalization of public health enhances the risk of misinformation and disinformation.

Machine Learning and Digital Biomarkers Can Detect Early Stages of Neurodegenerative Diseases

Neurodegenerative diseases (NDs) such as Alzheimer's Disease (AD) and Parkinson's Disease (PD) are devastating conditions that can develop without noticeable symptoms, causing irreversible damage to neurons before any signs become clinically evident. NDs are a major cause of disability and mortality worldwide. Currently, there are no cures or treatments to halt their progression. Therefore, the development of early detection methods is urgently needed to delay neuronal loss as soon as possible. Despite advancements in Medtech, the early diagnosis of NDs remains a challenge at the intersection of medical, IT, and regulatory fields. Thus, this review explores "digital biomarkers" (tools designed for remote neurocognitive data collection and AI analysis) as a potential solution. The review summarizes that recent studies combining AI with digital biomarkers suggest the possibility of identifying pre-symptomatic indicators of NDs. For instance, research utilizing convolutional neural networks for eye tracking has achieved significant diagnostic accuracies. ROC-AUC scores reached up to 0.88, indicating high model performance in differentiating between PD patients and healthy controls. Similarly, advancements in facial expression analysis through tools have demonstrated significant potential in detecting emotional changes in ND patients, with some models reaching an accuracy of 0.89 and a precision of 0.85. This review follows a structured approach to article selection, starting with a comprehensive database search and culminating in a rigorous quality assessment and meaning for NDs of the different methods. The process is visualized in 10 tables with 54 parameters describing different approaches and their consequences for understanding various mechanisms in ND changes. However, these methods also face challenges related to data accuracy and privacy concerns. To address these issues, this review proposes strategies that emphasize the need for rigorous validation and rapid integration into clinical practice. Such integration could transform ND diagnostics, making early detection tools more cost-effective and globally accessible. In conclusion, this review underscores the urgent need to incorporate validated digital health tools into mainstream medical practice. This integration could indicate a new era in the early diagnosis of neurodegenerative diseases, potentially altering the trajectory of these conditions for millions worldwide. Thus, by highlighting specific and statistically significant findings, this review demonstrates the current progress in this field and the potential impact of these advancements on the global management of NDs.

Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement

Osteoarthritis (OA) poses a growing challenge for the aging population, especially in the hip and knee joints, contributing significantly to disability and societal costs. Exploring the integration of wearable technology, this study addresses the limitations of traditional rehabilitation assessments in capturing real-world experiences and dynamic variations. Specifically, it focuses on continuously monitoring physical activity in hip and knee OA patients using automated unsupervised evaluations within the rehabilitation process. We analyzed data from 1144 patients who used a mobile health application after surgery; the activity data were collected using the Garmin Vivofit 4. Several parameters, such as the total number of steps per day, the peak 6-minute consecutive cadence (P6MC) and peak 1-minute cadence (P1M), were computed and analyzed on a daily basis. The results indicated that cadence-based measurements can effectively, and earlier, differ among patients with hip and knee conditions, as well as in the recovery process. Comparisons based on recovery status and type of surgery reveal distinctive trajectories, emphasizing the effectiveness of P6MC and P1M in detecting variations earlier than total steps per day. Furthermore, cadence-based measurements showed a lower inter-day variability (40%) compared to the total number of steps per day (80%). Automated assessments, including P1M and P6MC, offer nuanced insights into the patients' dynamic activity profiles.

An Introduction to Smart Home Ward-Based Hospital-at-Home Care in China

Hospital-at-home has been gaining increased attention as a potential remedy for the current shortcomings of our health care system, allowing for essential health services to be provided to patients in the comfort of their own homes. The advent of digital technology has revolutionized the way we provide medical and health care, leading to the emergence of a “hospital without walls.” The rapid adoption of novel digital health care technologies is revolutionizing remote health care provision, effectively dismantling the conventional boundary separating hospitals from the comfort of patients’ homes. The Guangdong Second Provincial General Hospital has developed a 5G-powered Smart Home Ward (SHW) that extends medical care services to the home setting and is tailored to meet the needs and settings of each patient’s household. The SHW was initially tested for its suitability for treating 4 specialized diseases, including cardiovascular disease, stroke, Parkinson disease, and Alzheimer disease. Understanding and addressing the potential challenges and risks associated with SHWs is essential for the successful implementation and maintenance of safe and effective home hospitalization.

Methods for the Clinical Validation of Digital Endpoints: Protocol for a Scoping Review Abstract

BACKGROUND

Clinical trials often use digital technologies to collect data continuously outside the clinic and use the derived digital endpoints as trial endpoints. Digital endpoints are also being developed to support diagnosis, monitoring, or therapeutic interventions in clinical care. However, clinical validation stands as a significant challenge, as there are no specific guidelines orienting the validation of digital endpoints.

OBJECTIVE

This paper presents the protocol for a scoping review that aims to map the existing methods for the clinical validation of digital endpoints.

METHODS

The scoping review will comprise searches from the electronic literature databases MEDLINE (PubMed), Scopus (including conference proceedings), Embase, IEEE (Institute of Electrical and Electronics Engineers) Xplore, ACM (Association for Computing Machinery) Digital Library, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science Core Collection (including conference proceedings), and Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports. We will also include various sources of gray literature with search terms related to digital endpoints. The methodology will adhere to the Joanna Briggs Institute Scoping Review and the Guidance for Conducting Systematic Scoping Reviews.

RESULTS

A search for reviews on the existing evidence related to this topic was conducted and has shown that no such review was previously undertaken. This review will provide a systematic assessment of the literature on methods for the clinical validation of digital endpoints and highlight any potential need for harmonization or reporting of methods. The results will include the methods for the clinical validation of digital endpoints according to device, digital endpoint, and clinical application goal of digital endpoints. The study started in January 2023 and is expected to end by December 2023, with results to be published in a peer-reviewed journal.

CONCLUSIONS

A scoping review of methodologies that validate digital endpoints is necessary. This review will be unique in its breadth since it will comprise digital endpoints collected from several devices and not focus on a specific disease area. The results of our work should help guide researchers in choosing validation methods, identify potential gaps in the literature, or inform the development of novel methods to optimize the clinical validation of digital endpoints. Resolving these gaps is the key to presenting evidence in a consistent way to regulators and other parties and obtaining regulatory acceptance of digital endpoints for patient benefit.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/47119.

User experience of applying AMSTAR 2 to appraise systematic reviews of healthcare interventions: a commentary

BACKGROUND

'A Measurement Tool to Assess Systematic Reviews, version 2' (AMSTAR 2) is a validated 16-item scale designed to appraise systematic reviews (SRs) of healthcare interventions and to rate the overall confidence in their results. This commentary aims to describe the challenges with rating of the individual items and the application of AMSTAR 2 from the user perspective.

DISCUSSION

A group of six experienced users (methodologists working in different clinical fields for at least 10 years) identified and discussed the challenges in rating of each item and the general use of AMSTAR 2 to appraise SRs. A group discussion was used to develop recommendations on how users could deal with the identified challenges. We identified various challenges with the content of items 2-16 and with the derivation of the overall confidence ratings on AMSTAR 2. These challenges include the need (1) to provide additional definitions (e.g., what constitutes major deviations from SR protocol on item 2), (2) to choose a rating strategy for multiple conditions on single items (e.g., how to rate item 5 if studies were selected in duplicate, but consensus between two authors was not reported), and (3) to determine rules for deriving the confidence ratings (e.g., what items are critical for such ratings). Based on these challenges we formulated specific recommendations for items 2-16 that AMSTAR 2 users could consider before applying the tool. Our commentary adds to the existing literature by providing the first in-depth examination of the AMSTAR 2 tool from the user perspective. The identified challenges could be addressed by additional decision rules including definitions for ambiguous items and guidance for rating of complex items and derivation of confidence ratings. We recommend that a team consensus regarding such decision rules is required before appraisal procedure begins.

TRIAL REGISTRATION

Not applicable.

Different Approaches to Appraising Systematic Reviews of Digital Interventions for Physical Activity Promotion Using AMSTAR 2 Tool: Cross-Sectional Study

High-quality systematic reviews (SRs) can strengthen the evidence base for prevention and health promotion. A 16-item AMSTAR 2 tool allows the appraisal of SRs by deriving a confidence rating in their results. In this cross-sectional study, we aimed to assess and compare two approaches to appraising 30 SRs of digital interventions for physical activity (PA) promotion using AMSTAR 2. Approach 1 (appraisals with 2/16 items) was used to identify SRs with critically low confidence ratings. Approach 2 (appraisals with all 16 items) was used (1) to derive the confidence ratings, (2) to identify SR strengths and weaknesses, and (3) to compare SR strengths among subgroups of SRs. The appraisal outcomes were summarized and compared using descriptive statistics. Approach 1 was quick (mean of 5 min/SR) at identifying SRs with critically low confidence ratings. Approach 2 was slower (mean of 20 min/SR), but allowed to identify SR strengths and weaknesses. Approach 2 showed that confidence ratings were low to critically low in 29/30 SRs. More strengths were identified in SRs with review protocols relative to SRs without review protocols and in newer SRs (published after AMSTAR 2 release) relative to older SRs. Only two items on AMSTAR 2 can quickly identify SRs with critical weaknesses. Although most SRs received low to critically low confidence ratings, SRs with review protocols and newer SRs tended to have more strengths. Future SRs require review protocols and better adherence to reporting guidelines to improve the confidence in their results.