Application of Smartphone Technologies in Disease Monitoring: A Systematic Review

Digital solutions for migrant and refugee health: a framework for analysis and action

Digital technologies can help support the health of migrants and refugees and facilitate research on their health issues. However, ethical concerns include security and confidentiality of information; informed consent; how to engage migrants in designing, implementing and researching digital tools; inequitable access to mobile devices and the internet; and access to health services for early intervention and follow-up. Digital technical solutions do not necessarily overcome problems that are political, social, or economic. There are major deficits with regard to (1) reliable data on the health needs of migrants and mobile populations and on how they can use digital tools to support their health; (2) evidence on effectiveness of solutions; and (3) a broad framework to guide future work. This article provides a wide socio-technical perspective, as a framework for analysis and developing coherent agendas across global-to-local spaces, with particular attention to the European region.

Issues in Using Four Languages in a Culturally Tailored Technology-Based Intervention Study: Asian American Breast Cancer Survivors With Depressive Symptoms

To provide culturally competent care for racial/ethnic minorities, it is important to provide information and coaching/support in the languages that users can understand. However, issues in using multiple languages, especially in culturally tailored technology-based intervention research among racial/ethnic minority cancer survivors, have rarely been discussed. The purpose of this article is to discuss the issues in using four different languages among Asian American breast cancer survivors with depressive symptoms in a culturally tailored technology-based intervention study for cancer pain management and make suggestions for future technology-based intervention research using multiple languages. Research diaries written by the research team members, the recordings of biweekly research team meetings, and postings on Microsoft Teams were analyzed using content analysis. The issues included: (1) difficulties in recruiting eligible translators for multiple languages; (2) differences in selecting words by translators' traits; (3) difficulties in ensuring conceptual equivalence in measurements; (4) necessary contextual translation based on cultural understanding; (5) avoiding words with stigma; and (6) required multiple repeated steps. These methodological and conceptual issues need to be considered in future culturally tailored technology-based intervention research among racial/ethnic minorities, especially Asian American breast cancer survivors.

Perceptions of healthcare professionals and patients with cardiovascular diseases on mHealth lifestyle apps: A qualitative study

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death globally and is predominantly associated with a cluster of lifestyle risk factors. Mobile health (mHealth) apps offer the potential to overcome traditional barriers by supporting healthy lifestyle behaviours. However, knowledge about perceptions of mHealth lifestyle apps among healthcare professionals and people with CVD is sparse. This study examined barriers and facilitators of using the mHealth apps for healthy lifestyle support among healthcare professionals and CVD patients.

METHODS

We conducted an in-depth qualitative study employing individual semi-structured interviews with 8 CVD healthcare professionals and 4 patients with CVD in Australia. Participants were asked open-ended questions about their perceptions and experiences with mHealth lifestyle apps. A thematic analysis approach was used to establish perceived barriers and facilitators for mHealth lifestyle apps.

RESULTS

Most participants perceived mHealth lifestyle apps as useful. The key perceptions of facilitators included features for tailoring to personal needs, low costs and wide availability of the apps and addressing barriers to use like reminders. Both healthcare professionals and patients identified the strengths and weaknesses regarding the usefulness of mHealth lifestyle apps. Healthcare professionals and patients perceived several barriers to mHealth app use including trustworthiness, scientific validity, language barriers, the capability of using an app or digital literacy, costs for some commercial apps, and accessibility of an app for low-income groups.

CONCLUSION

Lifestyle apps provide an opportunity for better patient and healthcare professional communications, however, several barriers including improving digital health literacy and scientific validations of the apps are required before being recommended in clinical practice. Findings from this study can inform potential mHealth lifestyle app design to meet the demands of users. Addressing these barriers effectively can enhance the adoption and efficacy of mHealth apps, ultimately contributing to improved CVD management and healthier lifestyle behaviours.

Smartphone Application Versus Standard Instruction for Colonoscopic Preparation: A Randomized Controlled Trial

OBJECTIVE

To compare smartphone application (Colonoscopic Preparation) instructions versus paper instructions for bowel preparation for colonoscopy.

BACKGROUND

Adhering to bowel preparation instructions is important to ensure a high-quality colonoscopy.

PATIENTS AND METHODS

This randomized controlled trial included individuals undergoing colonoscopy at a tertiary care hospital. Individuals were randomized (1:1) to receive instructions through a smartphone application or traditional paper instructions. The primary outcome was the quality of the bowel preparation as measured by the Boston Bowel Preparation Score. Secondary outcomes included cecal intubation and polyp detection. Patient satisfaction was assessed using a previously developed questionnaire.

RESULTS

A total of 238 individuals were randomized (n = 119 in each group), with 202 available for the intention-to-treat analysis (N = 97 in the app group and 105 in the paper group). The groups had similar demographics, indications for colonoscopy, and type of bowel preparation. The primary outcome (Boston Bowel Preparation Score) demonstrated no difference between groups (Colonoscopic Preparation app mean: 7.26 vs paper mean: 7.28, P = 0.91). There was no difference in cecal intubation ( P = 0.37), at least one polyp detected ( P = 0.43), or the mean number of polyps removed ( P = 0.11). A higher proportion strongly agreed or agreed that they would use the smartphone app compared with paper instructions (89.4% vs 70.1%, P = 0.001).

CONCLUSIONS

Smartphone instructions performed similarly to traditional paper instructions for those willing to use the application. Local patient preferences need to be considered before making changes in the method of delivery of medical instructions.

Smart Home Technologies for Enhancing Independence of Living and Reducing Care Dependence in Older Adults: A Systematic Review

AIM

To systematically review the potential of smart home technology to enhance the independence of older adults and reduce their dependence on care. Additionally, it sought to examine the positive impacts of such technology on their golden years.

DESIGN

A systematic review based on Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA).

DATA SOURCES

The search was conducted on 8 April 2024. Peer-reviewed studies in PubMed, Embase, Web of Science, IEEE Xplore, Scopus, The Cochrane Library, CINAHL, CNKI, WANFANG DATA and VIP from 1 January 2000 to 8 April 2024 were searched.

METHODS

The methodological quality assessment used the Mixed Methods Appraisal Tool (MMAT). Positive findings relevant to this study were extracted from the literature and analysed using thematic synthesis.

RESULTS

After meticulously examining 3404 studies, we identified 21 relevant sources for in-depth analysis, including qualitative studies (n = 10), experimental studies (n = 9) and mixed method studies (n = 2). These sources were grouped into five core themes based on the pivotal role of smart home technologies in enabling ageing in place: daily monitoring, assisted living activities, life reminders, functional improvement and emotional companionship. The study found that smart home technology offers numerous benefits to the lives of older adults, including increased independence, psychological support, improved cognitive functioning, enhanced self-management, increased mobility, support for caregivers, promoted social engagement and enhanced quality of life.

CONCLUSION

Smart home technology can enhance the independence of older adults' lives, reduce their dependence on care, alleviate the burden on caregivers and promote home-based elderly care.

IMPACT

This systematic review contributes to understanding the capability of smart home technology to promote elderly care at home and help better utilise smart home technology to benefit older adults. Older adults and their caregivers should be encouraged to adopt this technology to improve older adults' quality of life.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Theranostic Applications of Scaffolds in Current Biomedical Research

Theranostics, a remarkable combination of diagnostics and therapeutics, has given rise to tissue/organ-format theranostic scaffolds that integrate targeted therapy and real-time disease monitoring. The scaffold is a 3D structuring template for cell or tissue attachment and growth. These scaffolds offer unprecedented opportunities for personalized medicine and hold great potential for revolutionizing healthcare. Recent advancements in fabrication techniques have enabled the creation of highly intricate and precisely engineered scaffolds with controllable physical and chemical properties, enhancing their therapeutic potential for tissue engineering and regenerative medicine. This paper proposes a new categorization method for scaffolds in tissue engineering based on the relativity of scaffold design-independent parameters. Five types of scaffolds are defined at different levels, highlighting the importance of understanding and analyzing scaffold types. It possesses the ability to seamlessly integrate diagnostics and therapeutics within a single platform, enhancing the efficacy and precision of personalized medicine. Natural scaffolds derived from biomaterials and synthetic scaffolds fabricated by human intervention are discussed, with synthetic scaffolds offering advantages such as tunable mechanical properties and controlled drug delivery, while natural scaffolds provide inherent biocompatibility and bioactivity, making them ideal for promoting cellular responses. The use of synthetic scaffolds shows great promise in advancing regenerative medicine and improving patient outcomes. The transfer of new technologies and changes in society have accelerated the evolution of health monitoring into the era of personal health monitoring. Using emerging health data, cost-effective analytics, wireless sensor networks, mobile smartphones, and easy internet access, the combination of these technologies is expected to accelerate the transition to personal health monitoring outside of traditional healthcare settings. The main objective of this review article is to provide a comprehensive overview of the theranostic applications of scaffolds in current biomedical research, highlighting their dual role in therapy and diagnostics. The review aims to explore the latest advancements in scaffold design, fabrication, and functionalization, emphasizing how these innovations contribute to improved therapeutic efficacy, targeted drug delivery, and the real-time monitoring of disease progression across various medical fields.

Vaping habits and respiratory symptoms using a smartphone app platform

BACKGROUND

Widespread use of e-cigarette (EC) or vaping products causes respiratory disorders including the nationwide outbreak of e-cigarette or vaping product use-associated lung injury (EVALI) in 2019. Chronic adverse health effects are now being reported as well. To address this important public health issue, an innovative approach of epidemic control and epidemiologic study is required. We aimed to assess the association between short-term and long-term use of EC products and respiratory health in adults using smartphone app data.

METHODS

A population-based, repeated measures, longitudinal smartphone app study that performed 8-day survey participation over 60 days for each participant from August 2020 to March 2021, including 306 participants aged 21 years and older in the US. The participants were asked to complete the respiratory health questionnaire daily, weekly, and monthly on their smartphone app. We analyzed the association between vaping habits and respiratory health using generalized linear mixed models (GLMMs).

RESULTS

EC use in the previous 7 days was associated with frequent cough (OR: 5.15, 95% CI: 2.18, 12.21), chronic cough (OR: 3.92, 95% CI: 1.62, 9.45), frequent phlegm (OR: 3.99, 95% CI: 1.44, 11.10), chronic phlegm (OR: 3.55, 95% CI: 1.41, 8.96), episodes of cough and phlegm (OR: 4.68, 95% CI: 1.94, 11.28), mMRC grade 3-4 dyspnea (OR: 3.32, 95% CI: 1.35 to 8.13), chest cold (OR: 3.07, 95% CI: 1.29, 7.33), eye irritation (OR: 2.94, 95% CI: 1.34, 6.47) and nose irritation (OR : 2.02, 95% CI: 0.95, 4.30). Relatively long-term effects of the past 90 days EC use was associated with an increased risk of wheeze (OR: 3.04, 95% CI: 1.31, 7.03), wheeze attack (OR: 2.78, 95% CI: 1.07, 7.24), mMRC grade 3-4 dyspnea (OR: 2.54, 9% CI: 1.05 to 6.18), eye irritation (OR: 3.16, 95% CI: 1.49, 6.68), and eye irritation during the past month (OR: 3.50, 95% CI: 1.52, 8.04).

CONCLUSIONS

In this smartphone app-based repeated measures study, short-term and relatively long-term use of EC increased the risk of respiratory symptoms.

Advancing Diabetes Self-Management: A Novel Smartphone Application Featuring a Scoring Algorithm for Tailored User Engagement

Background

We developed and evaluated an intelligent diabetes assistant application (Diabetter) for the self-management of diabetes. It suggested that increasing the patient's interest and participation in using smartphone apps is important for the effectiveness of diabetes management apps.

Methods

After evaluating all-encompassing features for diabetes management, we divided the selected factors into sub-factors for use in the application. Then, we created the first high-fidelity prototype using related programs and conducted early user testing to validate and improve Diabetter. To handle the user transaction time and keep them motivated, we designed and implemented a scoring system based on the nudge theory rules within the app.

Results

To evaluate Diabetter's impact on diabetes self-management, we measured HbA1c levels after a prolonged period. The Diabetter prototype was developed and modified in a revised version for better user interaction with the app. The scoring system increased the input of users' information, which resulted in more analysis and recommendations to users. Clinical studies showed that as a result of continuous input of information from users who had been using the application for a longer period of time, their HbA1c levels were within the healthy range.

Conclusions

The results demonstrate that the Diabetter application has been able to play an effective role in diabetes self-management by increasing users' app usage time. However, future study is needed to provide a better interpretation.

Assessing digital health knowledge, attitudes and practices among nurses in Naples: a survey study protocol

INTRODUCTION

Digital competencies are essential for nurses to actively participate in the digitisation of healthcare systems. Therefore, it is important to assess their skill levels to identify strengths and areas for improvement.

METHOD AND ANALYSIS

This study aims to investigate nurses' knowledge, attitudes, behaviours, subjective norms and behavioural control regarding digital health. A knowledge-attitude-practice model guided the development of a structured questionnaire divided into six sections. A sample of 480 registered nurses of Naples will be involved in the study. After conducting a pretest, an invitation will be publicised through the institutional communication channels of Nurses Provincial Order of Naples. Nurses will respond via a unique link or quick response code sent through a PEC email system (a legally valid email system, which guarantees delivery and receipt). They will have 30 days to complete the survey, scheduled between May and July 2024.

ETHICS AND DISSEMINATION

No ethics committee approval was required, as the study does not involve minors, direct or indirect physical or physiological harm to participants, or clinical trials. Anonymity will be guaranteed at all data collection and processing levels. The results will be broadly distributed through conference presentations and peer-reviewed publications. The effective use of digital technologies by healthcare professionals can bring significant improvements to healthcare services and help improve the health of individuals and community health. The study's findings will serve as a foundation for developing and implementing educational programmes related to eHealth and telemedicine, promoting the harmonisation of such programmes.

Accuracy of Apple Watch to Measure Cardiovascular Indices in Patients with Chronic Diseases: A Cross Sectional Study

Background

The validity of the Apple Watch to measure the heart rate (HR) and oxygen saturation (Spo2) for patients with chronic diseases such as diabetes mellitus (DM), dyslipidemia, and hypertension is still unclear. Therefore, this study aims to investigate the accuracy of the Apple Watch in measuring the Spo2 and HR in patients with chronic diseases.

Methods

Forty-one patients with chronic diseases, including 20 with hypertension, 10 with diabetes, and 11 with dyslipidemia, completed a cross-sectional study. All participants used the Apple Watch against the Polar chest strap and the pulse oximeter at rest and during moderate intensity exercise sessions to measure HR and the SpO2 at rest for 5 minutes, during exercise for 16 minutes, and followed by 3 minutes of rest. The HR was measured during all previous periods, but evaluation of the Spo2 included 5 measures, done only before and after exercise, with a minute interval between each measure.

Results

Overall, a strong correlation exists between measuring the SpO2 using the Apple Watch against the pulse oximeter (Contec) at rest (r = 0.92, p < 0.001) and after exercise (r = 0.86, p < 0.001) in all patients. The HR had a very strong correlation between the Apple Watch and the Polar chest strap (r = 0.99, p < 0.001) in all patients. There was no significant difference (p = 0.76) between the twenty-seven white and fourteen brown-skinned patients.

Conclusion

The Apple Watch is valid to measure the HR and SpO2 in patients with chronic diseases.

Clinical Trial Registration No

NCT05271864.

Using Digital Health Technologies to Monitor Pain, Medication Adherence and Physical Activity in Young People with Juvenile Idiopathic Arthritis: A Feasibility Study

Juvenile idiopathic arthritis can be influenced by pain, medication adherence, and physical activity. A new digital health intervention, InteractiveClinics, aims to monitor these modifiable risk factors. Twelve children, aged 10 to 18 years, received daily notifications on a smartwatch to record their pain levels and take their medications, using a customised mobile app synchronised to a secure web-based platform. Daily physical activity levels were automatically recorded by wearing a smartwatch. Using a quantitative descriptive research design, feasibility and user adoption were evaluated. The web-based data revealed the following: Pain: mean app usage: 68% (SD 30, range: 28.6% to 100%); pain score: 2.9 out of 10 (SD 1.8, range: 0.3 to 6.2 out of 10). Medication adherence: mean app usage: 20.7% (SD, range: 0% to 71.4%), recording 39% (71/182) of the expected daily and 37.5% (3/8) of the weekly medications. Pro-re-nata (PRN) medication monitoring: 33.3% (4/12), one to six additional medications (mean 3.5, SD 2.4) for 2-6 days. Physical activity: watch wearing behaviour: 69.7% (439/630), recording low levels of moderate-to-vigorous physical activity (mean: 11.8, SD: 13.5 min, range: 0-47 min). To conclude, remote monitoring of real-time data is feasible. However, further research is needed to increase adoption rates among children.

Fabry App: the value of a portable technology in recording day-to-day patient monitored information in patients with Fabry disease

BACKGROUND

Fabry disease is a rare inherited disorder resulting from deficient α-galactosidase A enzyme activity. Common disease manifestations are sweating abnormalities, neuropathic pain, gastrointestinal symptoms and fatigue. Challenges are faced by health care professionals in evaluating symptom burden in the current clinical setting, and the demand for alternative methods for monitoring disease-specific symptoms has seen an acceleration in recent years. Smartphone technologies offer the potential for continuity of care and surveillance. As a part of a quality improvement project, a disease specific app was developed in collaboration with a software company (Health Touch Ltd) and made available for patient use in May 2018. The Fabry mobile app records five categories: pain, gastrointestinal symptoms, sweating, activity levels, medications. Fabry disease patients with gastrointestinal and pain symptoms attending the Lysosomal Storage Disorders Unit of the Royal Free London NHS Foundation Trust were reviewed to assess eligibility and invited to download the app for recording their symptoms (activity, sweating, pain and gastrointestinal) and medications. Patient-generated data were transmitted to a secure website for clinicians to review.

RESULTS

One-hundred and thirty-nine symptomatic Fabry disease patients who had a smartphone (iPhone or android) were invited to download the app. Sixty-seven patients (26 males and 41 females; median age, 49 years [range, 20-81]) downloaded and tracked the Fabry App at least once. The median frequency of use per patient was 6 (range, 1-629). Pain in the hands and abdominal pain were significantly higher (p = 0.009 and p = 0.007, respectively) in patients with classic phenotype compared with patients with non-classic phenotypes.

CONCLUSIONS

We demonstrated the feasibility and acceptability of a smartphone app to facilitate the remote assessment and monitoring of Fabry disease symptom burden on a daily/weekly basis, as an alternative to the current standard of care that requires patients to recall their symptoms during 6 to 12 monthly annual clinic visits. Patients who were more likely to use the app had greater disease burden. This innovation has the potential to assess disease progression, early therapeutic intervention, thereby decreasing the burden of morbidity and mortality among Fabry patients, and to record long-term effects of Fabry-specific therapies.

Non-invasive blood glucose monitoring technology in diabetes management: review

Diabetes is one of the leading non-communicable diseases globally, adversely impacting an individual's quality of life and adding a considerable burden to the healthcare systems. The necessity for frequent blood glucose (BG) monitoring and the inconveniences associated with self-monitoring of BG, such as pain and discomfort, has motivated the development of non-invasive BG approaches. However, the current research progress is slow, and only a few BG self-monitoring devices have made considerable progress. Hence, we evaluate the available non-invasive glucose monitoring technologies validated against BG recordings to provide future research direction to design, develop, and deploy self-monitoring of BG with integrated emerging technologies. We searched five databases, Embase, MEDLINE, Proquest, Scopus, and Web of Science, to assess the non-invasive technology's scope in the diabetes management paradigm published from 2000 to 2020. A total of three approaches to non-invasive screening, including saliva, skin, and breath, were identified and discussed. We observed a statistical relationship between BG measurements obtained from non-invasive methods and standard clinical measures. Opportunities exist for future research to advance research progress and facilitate early technology adoption for healthcare practice. The results promise clinical validity; however, formulating regulatory guidelines could foresee the deployment of approved non-invasive BG monitoring technologies in healthcare practice. Further, research prospects are there to design, develop, and deploy integrated diabetes management systems with mobile technologies, data analytics, and the internet of things (IoT) to deliver a personalised monitoring system.

Mobile-Based Application Interventions to Enhance Cancer Control and Care in Low- and Middle-Income Countries: A Systematic Review

Objective: To identify and appraise mobile-based application (mAPP) interventions that have been used to support cancer control and care in low- and middle-income countries (LMICs). Methods: Four electronic databases were systematically searched for studies that reported primary research findings related to mAPP interventions applied in oncology settings in LMICs. A narrative synthesis was performed using the Mhealth Index and Navigation Database as an analytical framework. Results: Twenty studies reporting 18 cancer control and care mAPPs were included in this review. Among these mAPPs, ten focused on prevention, screening and early detection of cancer, five provided information to optimise supportive and palliative care, two provided support to assist treatment-shared decision-making and one covered information for follow-up and survivorship care. Conclusion: Cancer mAPP interventions are gradually gaining attention in LMICs as they provide unique resources for empowering and strengthening the role of people with cancer in their own care. To enhance cancer control, a focus on prevention and early detection is important; however, more mAPP interventions related to cancer treatment, follow-up and survivorship are also needed to enable more cost-effective cancer care.

The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials

AIMS

Type 2 diabetes (T2D) is rising worldwide. Self-care prevents diabetic complications. Lack of knowledge is one reason patients fail at self-care. Intelligent digital health (IDH) solutions have a promising role in training self-care behaviors based on patients' needs. This study reviews the effects of RCTs offering individualized self-care training systems for T2D patients.

METHODS

PubMed, Web of Science, Scopus, Cochrane Library, and Science Direct databases were searched. The included RCTs provided data-driven, individualized self-care training advice for T2D patients. Due to the repeated studies measurements, an all-time-points meta-analysis was conducted to analyze the trends over time. The revised Cochrane risk-of-bias tool (RoB 2.0) was used for quality assessment.

RESULTS

In total, 22 trials met the inclusion criteria, and 19 studies with 3071 participants were included in the meta-analysis. IDH interventions led to a significant reduction of HbA1c level in the intervention group at short-term (in the third month: SMD = - 0.224 with 95% CI - 0.319 to - 0.129, p value < 0.0; in the sixth month: SMD = - 0.548 with 95% CI - 0.860 to - 0.237, p value < 0.05). The difference in HbA1c reduction between groups varied based on patients' age and technological forms of IDH services delivery. The descriptive results confirmed the impact of M-Health technologies in improving HbA1c levels.

CONCLUSIONS

IDH systems had significant and small effects on HbA1c reduction in T2D patients. IDH interventions' impact needs long-term RCTs. This review will help diabetic clinicians, self-care training system developers, and researchers interested in using IDH solutions to empower T2D patients.

Self-management program and Black women with hypertension: Randomized controlled trial substudy

The prevalence of hypertension (HTN) among Black women in the United States has increased over the past 10 years with a decline in levels of HTN awareness, treatment, and control. Higher death rates occur in Black women from HTN-related diseases when compared with women of other racial/ethnic groups. Although interventions aimed at self-care/self-management are vital to adults becoming the cornerstone of their own health and well-being, there is a paucity of research in Black women. This randomized controlled pilot trial substudy examined the influence of a Chronic Disease Self-Management Program (CDSMP) with tailored coaching versus the CDSMP alone on blood pressure (BP), weight, and scores on self-care questionnaires and medication adherence for Black women with HTN over 9 months. Eighty-three women who had completed the CDSMP were randomly assigned to coaching or no coaching. Median age was 54 years and the time since the HTN diagnosis was 9 years. Significant differences were noted in self-care maintenance and management over time with better self-care in the treatment group. Though not significant, both groups denoted a trend toward better medication adherence. Almost 60% of the participants in both groups showed improvements in their systolic and/or diastolic BP. However, there was no significant difference between the study groups' BP and weight variables. The CDSMP was effective in decreasing BP and improving medication adherence. Further research is needed to evaluate effective coaching strategies that motivate Black women with HTN toward self-care management.

Evaluation of a smartphone-based colorimetric method for urinalysis dipstick readings in cats

OBJECTIVES

The aim of the study was to compare the diagnostic performances of a smartphone-based colorimetric method (SBCM) for urinalysis with a semi-automated point-of-care (POC) analyser using standardised solutions and cat urine.

METHODS

Artificial solutions (negative and positive quality controls, and purposely designed artificial urine) and natural urine from 216 cats were used. Two urine reagent strips were simultaneously dipped in each sample. One dipstick was read by the SBCM and the other by the POC analyser at the same time. Results for pH, proteins, bilirubin, 'blood', glucose and ketones were considered. Overall agreement and sensitivity, specificity and accuracy of the SBCM were determined based on selected cut-offs.

RESULTS

For the artificial solutions, 80 comparisons were obtained for each analyte and each expected concentration. The overall agreement (exactly the same result) between the two methods was 78.4%. SBCM sensitivity, specificity and accuracy were 99.0%, 100% and 99.3%, respectively. The correlation between the two methods was almost perfect (Cohen's kappa coefficient = 0.9851). For natural urine samples, the overall agreement (including pH) was 68.6%. Using optimal cut-offs for the SBCM determined from the results of analysis of artificial solutions, the sensitivity, specificity and accuracy of the SBCM were 100%, 76.02% and 80.5%, respectively. In this situation, the correlation between the two methods was moderate (Cohen's kappa coefficient = 0.5401). This was mostly due to a high rate of false-positive results for bilirubin (61.1%).

CONCLUSIONS AND RELEVANCE

With proper cut-off use (ie, considering positive or negative results) the SBCM evaluated here has a perfect sensitivity and appropriate diagnostic performances for proteins, 'blood', glucose and ketones. Based on these experimental data, this method appears suitable for dipstick urinalysis but positive results for bilirubin and proteins have to be confirmed.

A roadmap for the digital management of long-lasting insecticide-treated mosquito nets (LLINs) distribution campaigns in the Democratic Republic of Congo

The use of the long-lasting insecticide-treated mosquito net (LLIN) is one of the basic interventions recommended by the Global technical strategy for Malaria 2016-2030. Since the start of the LLIN distribution campaigns in 2006 in Democratic Republic of Congo (DRC), it was based on paper tools leading to poor quality data. The first digital campaigns date back to 2014 through "Interchurch medical assistance" (IMA), which used the ODK collect application for recording household count data and LLIN distribution data. In 2020 "Soins de santé primaire en milieu Rurale" (SANRU) developed both household registration and LLIN distribution data recording forms as well as additional modules for supervision, monitoring and training. This article briefly describes the status of the implementation process of this digital-based management of LIIN mass distribution. During the first half of 2020, a roadmap was developed between Sanru and the Global fund to fight Tuberculosis, AIDS and Malaria (GFTAM) on the objectives of digitization, the data to be digitized, and the timelines for implementing the changes. In the last quarter of 2021, an internal Sanru team composed of some members of its technical management, and staff in charge of the digitization of LLIN mass distribution campaign data participated in a document review of the deliverables in comparison with the roadmap and in group discussions. For recording household enumeration data and distribution data, forms configured on smartphones allow data recording and uploading without going through manual calculations and previously necessary transcriptions with management based on paper tools, thus removing sources of errors. Online data delivery and automated production of dashboards allow real-time sharing of information to all stakeholders and shorten data validation times. Feedback to actors in the field is possible thanks to access to information and maps generated on the basis of geolocation data from households. ODK forms for supervision and monitoring have been put in place to ensure that these activities are effectively deployed in the field in accordance with the standards set by geolocating the actors and using the data transmitted online for interactive feedback. The next step is to develop a material flow management module to improve the traceability of inputs.

Luminescent Guests Encapsulated in Metal-Organic Frameworks for Portable Fluorescence Sensor and Visual Detection Applications: A Review

Metal-organic frameworks (MOFs) have excellent applicability in several fields and have significant structural advantages, due to their open pore structure, high porosity, large specific surface area, and easily modifiable and functionalized porous surface. In addition, a variety of luminescent guest (LG) species can be encapsulated in the pores of MOFs, giving MOFs a broader luminescent capability. The applications of a variety of LG@MOF sensors, constructed by doping MOFs with LGs such as lanthanide ions, carbon quantum dots, luminescent complexes, organic dyes, and metal nanoclusters, for fluorescence detection of various target analyses such as ions, biomarkers, pesticides, and preservatives are systematically introduced in this review. The development of these sensors for portable visual fluorescence sensing applications is then covered. Finally, the challenges that these sectors currently face, as well as the potential for future growth, are briefly discussed.

Transformation of chronic disease management: Before and after the COVID-19 outbreak

Adults with chronic diseases often experience a decline in their quality of life along with frequent exacerbations. These diseases can cause anxiety and impose a significant economic burden. Self-management is a crucial aspect of treatment outside of the hospital and can improve quality of life and reduce the financial burden resulting from unexpected hospitalizations. With the COVID-19 pandemic, telehealth has become a vital tool for both medical professionals and patients; many in-person appointments have been canceled due to the pandemic, leading to increased reliance on online resources. This article aimed to discuss various methods of chronic disease management, both traditional self-management and modern telehealth strategies, comparing before and after the COVID-19 outbreak and highlighting challenges that have emerged.

The electronic medical record management systems may improve monitoring and control of disease activity in patients with ankylosing spondylitis

To investigate the impact of an electronic medical record management system (EMRMS) on disease activity and the frequency of outpatient visits among patients with ankylosing spondylitis (AS). We identified 652 patients with AS who were followed up for at least 1 year before and after the first Ankylosing Spondylitis Disease Activity Score (ASDAS) assessment and compared the number of outpatient visits and average visit time within 1 year before and after the initial ASDAS assessment. Finally, we analyzed 201 patients with AS who had complete data and received ≥ 3 continuous ASDAS assessments at an interval of 3 months, and we compared the results of the second and third ASDAS assessments with those of the first. The number of annual outpatient visits increased after ASDAS assessment (4.0 (4.0, 7.0) vs. 4.0 (4.0, 8.0), p < 0.001), particularly among those with a high initial disease activity. The average visit time was reduced within 1 year after ASDAS assessment (6.4 (8.5, 11.2) vs. 6.3 (8.3, 10.8) min, p = 0.073), especially among patients whose with an inactive disease activity was < 1.3 (ASDAS C-reactive protein (CRP) 6.7 (8.8, 11.1) vs. 6.1 (8.0, 10.3) min, p = 0.033; ASDAS erythrocyte sedimentation rate (ESR) 6.4 (8.7, 11.1) vs. 6.1 (8.1, 10.0) min, p = 0.027). Among patients who received at least three ASDAS assessments, the third ASDAS-CRP tended to be lower than the first (1.5 (0.9, 2.1) vs. 1.4 (0.8, 1.9), p = 0.058). The use of an EMRMS increased the frequency of ambulatory visits among AS patients with high and very high disease activity and reduced the visit time among those with an inactive disease. Continual ASDAS assessments may help control the disease activity of patients with AS.

Specifications and feasibility of technology-based self-management of COPD: An exploratory qualitative study with patients and providers

This article outlines the findings of a study that looked at the self-management needs of Chronic Obstructive Pulmonary Disease (COPD) patients and the feasibility of an eHealth intervention. This study found that patient self-monitoring is sub-optimal. Patients want the technology to include record keeping, feedback, the integration of biomedical and environmental data, exacerbation detection, and the ability to connect with providers. Health leaders could benefit from this information by working with their suppliers to eliminate system and technology barriers, and ensuring that technology is interactive, personalized and easy to use.

Measuring adherence to inhaled control medication in patients with asthma: Comparison among an asthma app, patient self-report and physician assessment

BACKGROUND

Previous studies have demonstrated the feasibility of using an asthma app to support medication management and adherence but failed to compare with other measures currently used in clinical practice. However, in a clinical setting, any additional adherence measurement must be evaluated in the context of both the patient and physician perspectives so that it can also help improve the process of shared decision making. Thus, we aimed to compare different measures of adherence to asthma control inhalers in clinical practice, namely through an app, patient self-report and physician assessment.

METHODS

This study is a secondary analysis of three prospective multicentre observational studies with patients (≥13 years old) with persistent asthma recruited from 61 primary and secondary care centres in Portugal. Patients were invited to use the InspirerMundi app and register their inhaled medication. Adherence was measured by the app as the number of doses taken divided by the number of doses scheduled each day and two time points were considered for analysis: 1-week and 1-month. At baseline, patients and physicians independently assessed adherence to asthma control inhalers during the previous week using a Visual Analogue Scale (VAS 0-100).

RESULTS

A total of 193 patients (72% female; median [P25-P75] age 28 [19-41] years old) were included in the analysis. Adherence measured by the app was lower (1 week: 31 [0-71]%; 1 month: 18 [0-48]%) than patient self-report (80 [60-95]) and physician assessment (82 [51-94]) (p < 0.001). A negligible non-significant correlation was found between the app and subjective measurements (ρ 0.118-0.156, p > 0.05). There was a moderate correlation between patient self-report and physician assessment (ρ = 0.596, p < 0.001).

CONCLUSIONS

Adherence measured by the app was lower than that reported by the patient or the physician. This was expected as objective measurements are commonly lower than subjective evaluations, which tend to overestimate adherence. Nevertheless, the low adherence measured by the app may also be influenced by the use of the app itself and this needs to be considered in future studies.

Assessing the Usability of an Instagram Filter in Monitoring Essential Tremor: A Proof-of-Concept Study

Background

Spiral drawing is an important test in monitoring essential tremor (ET). With the rise of telemedicine amid the coronavirus disease 2019 pandemic, a contactless tool for monitoring tremors was required. We aimed to assess the validity of a novel smartphone technology using a video-based social media platform for rapid and objective monitoring of ET.

Methods

A prospective pilot study evaluated patients with ET in 2 clinic visits. Videos of tremors were recorded using a publicly available Instagram filter and were visually compared with spirals drawn by the patients. The level of agreement among the raters was evaluated.

Results

A total of 12 patients with ET were recruited. A consensus between both raters was achieved for 11 patients (91.6%) for both spirals and videos with good interrater agreement (κ value, 0.755 ± 0.332).

Conclusion

This novel method was found to be valid and easy to use in measuring ET in real-world settings. Further research in a larger cohort is needed to suggest its use as a home-based or clinic-based monitoring tool.

Digital Health Marketing and Its Applications: A Neglected Priority in Iran’s Healthcare System

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Using Social Media to Collect Dietary Information for Public Health Policy

There is no regular, routine measurement of food and nutrient intake regionally in the UK. Our goal was to identify a method to support policy makers tracking the local population food intakes. The aim of this study was to test the feasibility of using social media to obtain a large sample in a short time, with a regional focus; collecting dietary information using online tools. A Facebook (FB) boost approach was used to recruit a regional (Yorkshire and Humberside) sample of adults to complete a brief online survey followed by a detailed measure of food and nutrient intakes for the previous day using myfood24®. The FB posts were boosted for 21 days and reached 76.9 k individuals. 1428 participants completed the main questionnaire and 673 participants completed the diet diary. The majority of respondents were older women. 22% of respondents reported experiencing moderate food insecurity during 2021. Overall nutrient values recorded were similar to national survey data. Intakes of fibre and iron were low. Despite some challenges, this study has demonstrated the potential to use social media, in this case Facebook, to recruit a large sample in a short timeframe. Participants were able to use online tools to report food and nutrient intakes. This data is relevant to local and national policy makers to monitor and evaluate public health programmes.

Factors Associated with Willingness to Receive a COVID-19 Vaccine in Adult Polish Population-A Cross-Sectional Survey

Vaccinations are proven to be the most efficient in preventing COVID-19 disease. Nonetheless, some people are skeptical and hesitant. The study aimed to determine factors associated with willingness to receive a COVID-19 vaccine in the Polish adult population. An online survey consisting of questions regarding (1) demographic information and (2) health issues (the status of vaccination, comorbidities, receiving the flu vaccine and usage of health monitoring apps) was distributed between 13 January and 14 February 2022. Of the 7018 participants who met the study conditions, 76.89% (n = 5396) were females, 22.44% (n = 1575) were males and 0.67% (n = 47) did not specify gender. The median age was 31 years. Among them, 81.82% (n = 5742) were vaccinated and 18.18% (n = 1276) were not. 46.87% (n = 3289) had no chronic co-morbidities. Factors associated with lower odds to receive the vaccine were: being men (p = 0.02; OR = 0.83), having lower education status (p = 0.001, OR = 0.56−0.77), living in a smaller residence area (p < 0.001, OR = 0.47−0.73.), not receiving flu vaccination (p < 0.001, OR = 24.51) and not using health monitoring applications (p < 0.001, OR = 1.56). Health education and communication strategies are needed to achieve large-scale vaccine acceptability and finally herd immunity.

Trends in the prevalence and associated factors of prediabetes and diabetes in Bangladesh: Evidence from population-based cross-sectional surveys

AIMS

Diabetes is a major health problem in Bangladesh, but nationally representative studies on its trends and associated factors are scarce to guide policy formulation. Therefore, the study aims to determine trends in the prevalence and associated factors of prediabetes and diabetes in Bangladesh.

METHODS

The study included two population-based cross-sectional surveys from Bangladesh Demographic and Health Survey (n = 7,505 in 2011 and n = 11,959 in 2017-18). Chi-square association tests were performed to determine the associated factors. Logistic regression models (univariate and multivariable) were used to estimate unadjusted and adjusted relative risks of having diabetes, reported with odds ratios. Age-adjusted prevalence was also reported for both surveys.

RESULTS

The overall age-adjusted prevalence of prediabetes and diabetes decreased from 52.77% (95% CI: 52.61-52.92) and 10.43% (95% CI: 10.33-10.53) in 2011 to 34.10% (95% CI: 33.43-34.78) and 8.50% (95% CI: 8.11-8.90) in 2017-18. Compared to males, females had a higher odds of diabetes in 2011, but in 2017-18 a significant inverse result was observed. In both surveys, the odds of prediabetes and diabetes increased with advancing age, obesity, better wealth status, and hypertension.

CONCLUSION

The study shows that the prevalence of prediabetes and diabetes is high in Bangladesh despite decreasing trends. Therefore, the study recommends promoting healthy lifestyles and regular screening for non-communicable diseases.

covidscreen: a web app and R Package for assessing asymptomatic COVID-19 testing strategies

Background

COVID-19 has caused over 305 million infections and nearly 5.5 million deaths globally. With complete eradication unlikely, organizations will need to evaluate their risk and the benefits of mitigation strategies, including the effects of regular asymptomatic testing. We developed a web application and R package that provides estimates and visualizations to aid the assessment of organizational infection risk and testing benefits to facilitate decision-making, which combines internal and community information with malleable assumptions.

Results

Our web application, covidscreen, presents estimated values of risk metrics in an intuitive graphical format. It shows the current expected number of active, primarily community-acquired infections among employees in an organization. It calculates and explains the absolute and relative risk reduction of an intervention, relative to the baseline scenario, and shows the value of testing vaccinated and unvaccinated employees. In addition, the web interface allows users to profile risk over a chosen range of input values. The performance and output are illustrated using simulations and a real-world example from the employee testing program of a pediatric oncology specialty hospital.

Conclusions

As the COVID-19 pandemic continues to evolve, covidscreen can assist organizations in making informed decisions about whether to incorporate covid test based screening as part of their on-campus risk-mitigation strategy. The web application, R package, and source code are freely available online (see “Availability of data and materials”).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13718-4.

Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study

Background

Diabetic mellitus (DM) and cardiovascular diseases (CVD) cause significant healthcare burden globally and often co-exists. Current approaches often fail to identify many people with co-occurrence of DM and CVD, leading to delay in healthcare seeking, increased complications and morbidity. In this paper, we aimed to develop and evaluate a two-stage machine learning (ML) model to predict the co-occurrence of DM and CVD.

Methods

We used the diabetes complications screening research initiative (DiScRi) dataset containing >200 variables from >2000 participants. In the first stage, we used two ML models (logistic regression and Evimp functions) implemented in multivariate adaptive regression splines model to infer the significant common risk factors for DM and CVD and applied the correlation matrix to reduce redundancy. In the second stage, we used classification and regression algorithm to develop our model. We evaluated the prediction models using prediction accuracy, sensitivity and specificity as performance metrics.

Results

Common risk factors for DM and CVD co-occurrence was family history of the diseases, gender, deep breathing heart rate change, lying to standing blood pressure change, HbA1c, HDL and TC\HDL ratio. The predictive model showed that the participants with HbA1c >6.45 and TC\HDL ratio > 5.5 were at risk of developing both diseases (97.9% probability). In contrast, participants with HbA1c >6.45 and TC\HDL ratio ≤ 5.5 were more likely to have only DM (84.5% probability) and those with HbA1c ≤5.45 and HDL >1.45 were likely to be healthy (82.4%. probability). Further, participants with HbA1c ≤5.45 and HDL <1.45 were at risk of only CVD (100% probability). The predictive accuracy of the ML model to detect co-occurrence of DM and CVD is 94.09%, sensitivity 93.5%, and specificity 95.8%.

Conclusions

Our ML model can significantly predict with high accuracy the co-occurrence of DM and CVD in people attending a screening program. This might help in early detection of patients with DM and CVD who could benefit from preventive treatment and reduce future healthcare burden.

Smart Home Technology Solutions for Cardiovascular Diseases: A Systematic Review

Cardiovascular diseases (CVD) are the leading cause of mortality globally. Despite improvement in therapies, people with CVD lack support for monitoring and managing their condition at home and out of hospital settings. Smart Home Technologies have potential to monitor health status and support people with CVD in their homes. We explored the Smart Home Technologies available for CVD monitoring and management in people with CVD and acceptance of the available technologies to end-users. We systematically searched four databases, namely Medline, Web of Science, Embase, and IEEE, from 1990 to 2020 (search date 18 March 2020). “Smart-Home” was defined as a system using integrated sensor technologies. We included studies using sensors, such as wearable and non-wearable devices, to capture vital signs relevant to CVD at home settings and to transfer the data using communication systems, including the gateway. We categorised the articles for parameters monitored, communication systems and data sharing, end-user applications, regulations, and user acceptance. The initial search yielded 2462 articles, and the elimination of duplicates resulted in 1760 articles. Of the 36 articles eligible for full-text screening, we selected five Smart Home Technology studies for CVD management with sensor devices connected to a gateway and having a web-based user interface. We observed that the participants of all the studies were people with heart failure. A total of three main categories—Smart Home Technology for CVD management, user acceptance, and the role of regulatory agencies—were developed and discussed. There is an imperative need to monitor CVD patients’ vital parameters regularly. However, limited Smart Home Technology is available to address CVD patients’ needs and monitor health risks. Our review suggests the need to develop and test Smart Home Technology for people with CVD. Our findings provide insights and guidelines into critical issues, including Smart Home Technology for CVD management, user acceptance, and regulatory agency’s role to be followed when designing, developing, and deploying Smart Home Technology for CVD.

Smartphone as a Disease Screening Tool: A Systematic Review

Disease screening identifies a disease in an individual/community early to effectively prevent or treat the condition. COVID-19 has restricted hospital visits for screening and other healthcare services resulting in the disruption of screening for cancer, diabetes, and cardiovascular diseases. Smartphone technologies, coupled with built-in sensors and wireless technologies, enable the smartphone to function as a disease-screening and monitoring device with negligible additional costs and potentially higher quality results. Thus, we sought to evaluate the use of smartphone applications for disease screening and the acceptability of this technology in the medical and healthcare sectors. We followed a systematic review process using four databases, including Medline Complete, Web of Science, Embase, and Proquest. We included articles published in English examining smartphone application utilisation in disease screening. Further, we presented and discussed the primary outcomes of the research articles and their statistically significant value. The initial search yielded 1046 studies for the initial title and abstract screening. Of the 105 articles eligible for full-text screening, we selected nine studies and discussed them in detail under four main categories: an overview of the literature reviewed, participant characteristics, disease screening, and technology acceptance. According to our objective, we further evaluated the disease-screening approaches and classified them as clinically administered screening (33%, n = 3), health-worker-administered screening (33%, n = 3), and home-based screening (33%, n = 3). Finally, we analysed the technology acceptance among the users and healthcare practitioners. We observed a significant statistical relationship between smartphone applications and standard clinical screening. We also reviewed user acceptance of these smartphone applications. Hence, we set out critical considerations to provide equitable healthcare solutions without barriers when designing, developing, and deploying smartphone solutions. The findings may increase research opportunities for the evaluation of smartphone solutions as valid and reliable screening solutions.

Prediction of cardiac autonomic neuropathy using a machine learning model in patients with diabetes

Background

Cardiac autonomic neuropathy (CAN) is a diabetes-related complication with increasing prevalence and remains challenging to detect in clinical settings. Machine learning (ML) approaches have the potential to predict CAN using clinical data. In this study, we aimed to develop and evaluate the performance of an ML model to predict early CAN occurrence in patients with diabetes.

Methods

We used the diabetes complications screening research initiative data set containing 200 CAN-related tests on more than 2000 participants with type 2 diabetes in Australia. Data were collected on peripheral nerve functions, Ewing's tests, blood biochemistry, demographics, and medical history. The ML model was validated using 10-fold cross-validation, of which 90% were used in training the model and the remaining 10% was used in evaluating the performance of the model. Predictive accuracy was assessed by area under the receiver operating curve, and sensitivity, specificity, positive predictive value, and negative predictive value.

Results

Of the 237 patients included, 105 were diagnosed with an early stage of CAN while the remaining 132 were healthy. The ML model showed outstanding performance for CAN prediction with receiver operating characteristic curve of 0.962 [95% confidence interval (CI) = 0.939-0.984], 87.34% accuracy, and 87.12% sensitivity. There was a significant and positive association between the ML model and CAN occurrence (p < 0.001).

Conclusion

Our ML model has the potential to detect CAN at an early stage using Ewing's tests. This model might be useful for healthcare providers for predicting the occurrence of CAN in patients with diabetes, monitoring the progression, and providing timely intervention.

Towards a Connected Mobile Cataract Screening System: A Future Approach

Advances in computing and AI technology have promoted the development of connected health systems, indirectly influencing approaches to cataract treatment. In addition, thanks to the development of methods for cataract detection and grading using different imaging modalities, ophthalmologists can make diagnoses with significant objectivity. This paper aims to review the development and limitations of published methods for cataract detection and grading using different imaging modalities. Over the years, the proposed methods have shown significant improvement and reasonable effort towards automated cataract detection and grading systems that utilise various imaging modalities, such as optical coherence tomography (OCT), fundus, and slit-lamp images. However, more robust and fully automated cataract detection and grading systems are still needed. In addition, imaging modalities such as fundus, slit-lamps, and OCT images require medical equipment that is expensive and not portable. Therefore, the use of digital images from a smartphone as the future of cataract screening tools could be a practical and helpful solution for ophthalmologists, especially in rural areas with limited healthcare facilities.

Evaluating the robustness of a contact-less mHealth solution for personal and remote monitoring of blood oxygen saturation

MHealth technologies play a fundamental role in epidemiological situations such as the ongoing outbreak of COVID-19 because they allow people to self-monitor their health status (e.g. vital parameters) at any time and place, without necessarily having to physically go to a medical clinic. Among vital parameters, special care should be given to monitor blood oxygen saturation (SpO2), whose abnormal values are a warning sign for potential COVID-19 infection. SpO2 is commonly measured through the pulse oximeter that requires skin contact and hence could be a potential way of spreading contagious infections. To overcome this problem, we have recently developed a contact-less mHealth solution that can measure blood oxygen saturation without any contact device but simply processing short facial videos acquired by any common mobile device equipped with a camera. Facial video frames are processed in real-time to extract the remote photoplethysmographic signal useful to estimate the SpO2 value. Such a solution promises to be an easy-to-use tool for both personal and remote monitoring of SpO2. However, the use of mobile devices in daily situations holds some challenges in comparison to the controlled laboratory scenarios. One main issue is the frequent change of perspective viewpoint due to head movements, which makes it more difficult to identify the face and measure SpO2. The focus of this work is to assess the robustness of our mHealth solution to head movements. To this aim, we carry out a pilot study on the benchmark PURE dataset that takes into account different head movements during the measurement. Experimental results show that the SpO2 values obtained by our solution are not only reliable, since they are comparable with those obtained with a pulse oximeter, but are also insensitive to head motion, thus allowing a natural interaction with the mobile acquisition device.

Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh

Diabetes and chronic kidney disease (CKD) are a major public health burden in low- and middle-income countries. This study aimed to explore factors associated with CKD in patients with type 2 diabetes (T2D) in Bangladesh. A cross-sectional study was conducted among 315 adults with T2D presenting at the outpatient department of Bangladesh Institute of Health Sciences (BIHS) hospital between July 2013 to December 2013. CKD was diagnosed based on the estimated glomerular filtration rate using the ‘Modification of Diet in Renal Disease’ equations and the presence of albuminuria estimated by the albumin-to-creatinine ratio. Multivariate logistic regression analysis was used to determine the factors associated with CKD. The overall prevalence of CKD among patients with T2D was 21.3%. In the unadjusted model, factors associated with CKD included age 40–49 years (OR: 5.7, 95% CI: 1.3–25.4), age 50–59 years (7.0, 1.6–39), age ≥60 years (7.6, 1.7–34), being female (2.2, 1.2–3.8), being hypertensive (1.9, 1.1–3.5), and household income between 10,001 and 20,000 Bangladeshi taka, BDT (2.9, 1.0–8.2) compared with income ≤10,000 BDT. However, after adjustment of other covariates, only the duration of hypertension and household income (10,001–20,000 BDT) remained statistically significant. There is a need to implement policies and programs for early detection and management of hypertension and CKD in T2D patients in Bangladesh.