Register or Submit a manuscript.
Quick Link
OBM Geriatrics

(ISSN 2638-1311)

OBM Geriatrics is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. The journal takes the premise that innovative approaches – including gene therapy, cell therapy, and epigenetic modulation – will result in clinical interventions that alter the fundamental pathology and the clinical course of age-related human diseases. We will give strong preference to papers that emphasize an alteration (or a potential alteration) in the fundamental disease course of Alzheimer’s disease, vascular aging diseases, osteoarthritis, osteoporosis, skin aging, immune senescence, and other age-related diseases.

Geriatric medicine is now entering a unique point in history, where the focus will no longer be on palliative, ameliorative, or social aspects of care for age-related disease, but will be capable of stopping, preventing, and reversing major disease constellations that have heretofore been entirely resistant to interventions based on “small molecular” pharmacological approaches. With the changing emphasis from genetic to epigenetic understandings of pathology (including telomere biology), with the use of gene delivery systems (including viral delivery systems), and with the use of cell-based therapies (including stem cell therapies), a fatalistic view of age-related disease is no longer a reasonable clinical default nor an appropriate clinical research paradigm.

Precedence will be given to papers describing fundamental interventions, including interventions that affect cell senescence, patterns of gene expression, telomere biology, stem cell biology, and other innovative, 21st century interventions, especially if the focus is on clinical applications, ongoing clinical trials, or animal trials preparatory to phase 1 human clinical trials.

Papers must be clear and concise, but detailed data is strongly encouraged. The journal publishes a variety of article types (Original Research, Review, Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, etc.). There is no restriction on the length of the papers and we encourage scientists to publish their results in as much detail as possible.

 
 

Publication Speed (median values for papers published in 2024): Submission to First Decision: 6.3 weeks; Submission to Acceptance: 11.4 weeks; Acceptance to Publication: 7 days (1-2 days of FREE language polishing included)

 
 
Current Issue: 2026  Archive: 2025 2024 2023 2022 2021 2020 2019 2018 2017
Open Access Review

Medical Digital Technologies in Older Patients with Cardiac Disease Achievements and Drawbacks

Giuseppe Cocco 1,*, Hans Peter Hofmann 2, Stefano Pandolfi 3

  1. Cardiology Office, Weiermattstrasse 41, CH 4153 Reinach, BL, Switzerland

  2. Praxis, Museumstrasse 3, CH-6060 Sarnen, Switzerland

  3. Salina Medizin AG, Roberstenstrasse 31, CH-4310 Rheinfelden, Switzerland

* Correspondence: Giuseppe Cocco

Academic Editor: Chiara Mussi

Received: February 17, 2025 | Accepted: August 31, 2025 | Published: September 09, 2025

OBM Geriatrics 2025, Volume 9, Issue 3, doi:10.21926/obm.geriatr.2503323

Recommended citation: Cocco G, Hofmann HP, Pandolfi S. Medical Digital Technologies in Older Patients with Cardiac Disease Achievements and Drawbacks. OBM Geriatrics 2025; 9(3): 323; doi:10.21926/obm.geriatr.2503323.

© 2025 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

Abstract

Older adults are a growing population characterized by a high prevalence of multimorbidity and age-related conditions, such as organ and pharmacokinetic dysfunction. Medical digital technologies have emerged through the combined use of wearable, implantable, and insertable medical devices with digital systems. Gerontology aims to help older patients with disabilities utilize these technologies. These technologies are used in high-tech medical centers, particularly among older cardiac patients. Many cardiac societies support these technologies because of their positive medical effects in older cardiac patients. These technologies are added tools to support better outcomes and experiences of care in older cardiac patients. Medical centers claim that these technologies might enhance patient care, improve health outcomes, and lower medical expenditures. There are, however, some drawbacks. Internet technologies cannot completely replace face-to-face contact among cardiologists and patients. It is too early to assume that these technologies can be adopted without some adverse effects on the outcomes among high-risk cardiac patients with multimorbidity. Furthermore, it remains to be proven that such technologies can currently lower health costs, and one should also consider the significant expenses associated with their effective utilization. Furthermore, most health insurance plans do not cover bills resulting from these technologies. Therefore, family physicians show little interest in these technologies. The purpose of our mini review is to summarize the achievements of available medical digital technologies in geriatric cardiology and outline their drawbacks.

Graphical abstract

Click to view original image

Keywords

Gerotechnology; geriatric cardiology; eHealth; digital health technology

1. Introduction

People aged more than 65 years are a growing population characterized by multimorbidity and age-related organ and pharmacokinetic dysfunction [1,2,3,4].

Death is delayed by better education and income [4]. Ischemic heart diseases (IHDs) are responsible for a third of all deaths globally and are a common cause of mortality in older adults [5,6]. In 2021, the global average life expectancy was 71.3 years, while the lowest death rates worldwide were in Qatar (1.53%) and in the United Arab Emirates (1.97%) [5,6]. Socioeconomic data and quality of life among older adults were published for the USA in 2020 [7] and for Europe in 2022 [8]. They should be similar in most high-income nations.

The purpose of our mini-review is to assess medical device technologies (MDTs) in the context of geriatric cardiology, highlighting their achievements and some of their drawbacks.

2. Medical Devices Technologies

Wearable, insertable, and implantable medical devices monitor biological parameters and transmit collected data via the internet to healthcare centers. MDTs are the combination of collected biological parameters and their delivery via the internet to health centers [7,8,9,10,11,12,13,14,15,16].

2.1 MDTS in Older Cardiac Patients

Currently, various wearable tools are used, including smartwatches and smartphones [9,10,15,16], pulse oximeters and sleep monitors [15,16], activity tracking tools [17], and Holters [18]. In cardiac patients, insertable and implantable cardiac devices are used (pacemakers, defibrillators, and pulmonary artery monitors) [19,20,21,22,23,24,25,26,27,28,29,30].

These tools monitor vital parameters and may send the collected data through the internet to medical centers where medical professionals analyze the information and contact patients and their caregivers.

In past years, these tools were seldom used because they were poorly adapted to the needs of older people, and MDTs altogether were hesitantly accepted by health workers who were accustomed to old methods [8,10,31]. However, at present, MDTs are commonly used because the hardware and software (algorithms and artificial intelligence) of MDTs have been improved [7,8,10,31,32,33,34,35,36,37,38].

2.2 Types of MDTs

Remote patient monitoring is an asynchronous technology because healthcare centers respond to received data via short message service (SMS) or email.

Telemedicine is synchronous because the health center communicates with patients and their caregivers through video encounters (using the internet).

Another type of technology, telehealth, combines clinical and non-clinical services to promote health, provide training, and educate patients.

Remote patient monitoring and telemedicine are used for primary health prevention, treatment, prescription renewals, stabilizing acute medical conditions, and palliative care [7,8,9,10,11,12,13,14,15,16,17,31,32,36,37,38,39,40,41,42,43].

Telemedicine was used in older patients (mean age 80 years) with multiple morbidities, 60% of whom were in rural locations. With appropriate patient instruction, telemedicine could be effectively used, and most participants preferred video encounters over video alone [7]. Currently, in the USA and Europe, nearly 50% of older adults are willing to have video encounters, and more than 20% of them would like to have access to MDTs [7,8]. In 2020, worldwide, there were more than 200 million video encounters, and these figures are steadily increasing [7,8,14,18]. In the future, the number of older patients using MDTs is expected to rise, as younger people become increasingly familiar with digital technologies.

2.3 Gerotechnology

Gerotechnology adapts the hardware and software of MDTs to reduce the negative impact of patients’ limitations [7,8]. E.g., verbal video communication may be impaired by patients’ hearing defects, and earphones and/or volume amplification might be helpful. The devices may not be designed for patients with visual impairment: larger font sizes and bigger icons might be beneficial [7,8,10,11,12,18,22].

2.4 MDTs in Heart Failure

Heart failure (HF) has a ≥10% prevalence among older adults and is associated with poor quality of life and high mortality, mainly due to ischemic heart diseases (IHDs) [1,4,7,8]. Implanted pacemakers and defibrillators are often used in patients with cardiac conditions. These devices check function and battery longevity, and many modern devices also collect parameters such as physical activity and heart rate variability (e.g., at night). Some devices may record heart sounds and intrathoracic impedance [8,11,14,16,22,23,30,32]. The CardioMEMS device, developed by Abbott, may be used to monitor pulmonary artery pressure [28,29]. Complex algorithms are part of the devices’ software and analyze the collected information saved in home monitors, immediately wirelessly sending it to the cardiology center [22,23,24]. Cardiologists review the data and contact patients and caregivers offering diagnostic and therapeutic suggestions [7,8,9,10,11,12,13,14,15,16,17,18,32]. The contact may be made through inexpensive SMS or e-mails, and may require video encounters. Indeed, MDTs are frequently used in patients with implanted devices [28,29,30,44,45,46,47,48,49,50,51,52,53,54].

2.5 MDTs in Cardiac Arrhythmias

Atrial fibrillation (AFib) is prevalent in older adults [26,55,56,57,58]. Screening for detecting undiagnosed AFib is essential because identifying an undiagnosed AFib may indicate the need for oral anticoagulation (OAC) in patients at increased risk of cerebral stroke [15,22,25,26,27,59,60]. The 2020 ESC Atrial Fibrillation Guidelines [26] state that a) systematic electrocardiographic screening should be considered for ≥75-year-old adults, or for at high risk patients (Class IIa Level B), b) Electrocardiogram (ECG) documentation is needed to establish the diagnosis of AFib, c) in screen-positive cases, the diagnosis is established only after a physician reviews the single-lead ECG recording of ≥30 seconds or a 12-lead ECG and confirms that it shows AFib (Class I Level B). Different modalities for detecting AFib are used in different settings [18,19,20,21,22,23,24,25,26,27,59,60,61,62,63,64]. The specificity of screening tools ranges from 70% to 100%, and the sensitivity ranges from 87% to 99% [20,21,25,26,27,59,60,61,62,63,64]. Holter monitors (some devices can also be used underwater) record the ECG continuously and are used for screening and follow-up of arrhythmias. The chances of detecting paroxysmal arrhythmia depend on its frequency, presence or absence of symptoms, duration (some patients tolerate poorly the long application of electrodes on their skin), and quality of recording (reduced by motion artifacts due to poor skin-electrodes’ contact by sweating or during physical activity) [5].

Implantable pacemakers and defibrillators (sometimes external, but more frequently implanted) are not screening tools for normal adults; however, they are used in selected cardiac pathologies. The LUX-Dx [19] and the Jot Dx [20] record continuously the ECG, adjust device settings, and review collected data. Their apps send all information via the internet to the cardiology center.

Currently, wearable smartwatches and smartphones are frequently used for screening purposes. They record ECG snapshots and, therefore, are not ideal for detecting infrequent paroxysmal arrhythmia. Nonetheless, these devices utilize algorithmics, and consequently, the detection of undiagnosed paroxysmal AFib is significantly improved with their use compared to classic office ECG recordings [15,26,27]. The wearables monitor the regularity of pulse rate through plethysmography sensors and, in the event of irregularity, record the ECG rhythm [15,25,26,27]. The Apple Heart Study [61] described the accuracy of this technology. The detection of paroxysmal AFib was very low when patients did not report symptoms; however, when patients reported symptoms (e.g., palpitations), the algorithm worked efficiently and detected paroxysmal AFib in 84% of recorded ECG strips.

Altogether, the presence of risk factors increases the chances of detecting undiagnosed AFib. Ancient age is a high-risk factor [15,26,27,55,58,63,64,65,66,67,68,69]. A meta-analysis [63] of 141 220 screened adults found that undiagnosed AFib was detected in only 0, 34% among those <60 years old and in 2.73% among those ≥85 years old. Other risk factors are HF [50,51,53,56,57,58,60], left ventricular hypertrophy [65], and higher CHA2DS2-VASc scores [15,50,53,56,59]. Undetected AFib was found in 3% of screened individuals without risk factors and in 7.4% among those with additional risk factors [8]. Age also had a significant effect on the need for OAC. The number of screened individuals who need OAC was 1089 among <65-year-old individuals and 83 for those ≥65-year-old [63]. OAC reduces the risk of stroke in high-risk AFib patients, and the CHA2DS2-VASc scoring system is used for prescribing OAC [59,63]. In older HF patients, the need for OAC should be clear. Unfortunately, we have few valid data in this population. Indeed, the CHA2DS2-VASc scoring system was neither specifically developed nor validated for the use of OAC in older patients and has many limitations when applied to very old cardiac patients with comorbidities [1,25,26,63,64]. Consequently, there is debate about the necessary duration of AFib that would be associated with a heightened risk of stroke, warranting OAC therapy, especially in the very old patients. It has been suggested that OAC should not be ordered using a single cutoff, and that it would be safer to consider AFib duration in relation to the CHA2DS2-VASc score: OAC should be given to patients with CHA2DS2-VASc score ≥3 with an AFib duration ≥6 minutes per day and also to patients with CHA2DS2-VASc score 2 with an AFib and a duration ≥23.5 hours per day [59].

2.6 MDTs in Some Diseases that are Cardiovascular Risk Factors

Centers using MDTs in the treatment of arterial hypertension [35,39,40,41,42,43,66,67,68,69] claim that their use contributes to better blood pressure control by increasing adherence to the therapy [35,39,40,41,42,43,66,67,68,69]. Also, in patients with poorly controlled hypertension, MDTs reduced blood pressure significantly more than conventional treatment [41]. However, the hypotensive effect was larger in <65-year-old patients, possibly because older patients had more problems than the young ones with MDTs.

Nonetheless, there are currently no specific recommendations on the role of MDTs in general hypertension management.

2.6.1 Diabetes Mellitus

Diabetes mellitus is associated with considerable morbidity and mortality. Bluetooth-enabled glucose meters are available and send recorded values to physicians via SMS or web-based services [38,47,70,71,72]. The 2019 ESC guidelines on diabetes and cardiovascular diseases [72] recommend self-management with MDTs. However, a meta-analysis [70] reports a modest effect, as mobile phone interventions for self-management reduced HbA1c by up to 0.5% over a median follow-up of 6 months, and the reduction was larger in patients with type 2 diabetes than in those with type 1 diabetes.

2.7 Positive Aspects, Claims and Drawbacks of MDTs

One beneficial aspect of telemedicine is reducing the need for frequent physical contact between health centers and patients who have difficulty visiting the center.

Additionally, telemedicine facilitates collaboration among specialized medical centers and geographically distant, less specialized healthcare centers. Immediate digital reception of data enables a rapid and effective response, which appears to reduce mortality in older HF patients [13,16,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43]. Indeed, the 2021 ESC HF-guidelines [60] state that MDTs may be considered' for the use of home-based telemonitoring.

One fascinating aspect of telemedicine is the feasibility of remote surgery. In 2001, Prof. Jacques Marescaux performed the world’s first remote surgery, known as “Operation Lindbergh”. Located in New York (USA), he performed a complete tele-surgical cholecystectomy on a patient in Strasbourg (France) [71]. In 2024, a team located in Shanghai (China) performed successful remote surgery on a patient in Morocco, using the Chinese-made Toumai Robot, covering a 12,000-kilometer distance [72]. Also, in 2024, located in Strasbourg (France), using the “hinotori™” Surgical Robot System, he successfully performed a prostatectomy on a patient from a robotic training center based in Kobe (Japan), over a one-way distance of approximately 23,000 kilometers, spanning both the Pacific and Atlantic Oceans [73]. The results of these demonstrations have shown that safe remote surgery may be performed over the internet at extremely great geographic distances and might improve global access to medical care in countries lacking high-tech medicine.

Centers using MDTs outline their positive aspects [7,8,9,10,11,12,13,14,15,16,17,18,30,36,39,40,41,42,43]. They claim that a) MDTs would give better results than the usual in-clinic follow-up and would increase adherence to the therapy, b) MDTs would improve the cooperation among specialists and home caregivers (relatives and medical personnel), and c) MDTs would lower medical expenditure.

However, some consideration is needed. Many older patients refuse MDTs [8,10,12,14,15,49,50,52,53]. Additionally, video encounters do not permit a physical examination of elderly, symptomatic patients with comorbidities. The electronic medical data at the center may be either unavailable or outdated. Thus, the health center’s reaction to a “problem” might lead to unnecessary diagnostic tests or an avoidable emergency hospitalization. Moreover, frequent video encounters may have adverse effects on the interaction between home physicians and patients, as health centers may order medical changes and inform them later, potentially affecting home care physicians. Useless to say, the wishful “good cooperation” among medical centers and home physicians may suffer.

The financial aspect is probably the most critical drawback. Centers using MDTs require expensive high-tech equipment, a large staff comprising specialists in digital technologies, nurses, physicians, and several office employees. Also, the system must function 24/hours daily for rapid reaction in case of alerts, and technicians must be permanently active due to the safety problems related to the use of internet, the system must operate 24 hours a day to facilitate rapid reaction in the event of alerts, and technicians must be available at all times due to the safety concerns associated with internet use, to prevent attacks from hackers. Moreover, older patients often have poor memory for retention of medical information and are at risk for poor communication with the medical staff [7,8,47,48,49,74,75,76,77,78,79]; thus, the centers must provide instructions in various ways, often resorting to special mHealth Apps [7,8,12,13]. This situation is cumbersome, time-consuming, and requires good interaction among health centers, patients, and their caregivers. It is needless to say, all this is expensive. It is unproven that MDTs may reduce medical expenditure.

Last, but not least, other financial drawbacks must be considered. Many older adults have insufficient income and cannot afford a personal computer, a tablet, or a wearable device [4,7]. More importantly, health insurance companies generally pay for a limited amount of time that physicians may dedicate to patients’ care, and either do not refund or reimburse insufficient medical bills generated from the utilization of MDTs. While these financial restrictions are not necessarily prohibitive for health centers, as they are located in teaching institutions and receive tax benefits, as well as financial grants from the government and companies that sell the MDTs, they are significantly detrimental for home practitioners and their elderly patients.

Positive aspects and drawbacks of MDTs are summarized in Table 1.

Table 1 MDTs in cardiology. Positive Claims and Drawbacks.

3. Discussion

MDTs are used in medicine and are valuable tools, especially in older and frail cardiac patients. Their use is rapidly increasing due to advancements in hardware, software, and the price of the devices. Since young people grow up with the internet and smartphones, it is most likely that they will use MDTs when the need arises in the future. The rapid acquisition of data allows a fast intervention in case of the occurrence of acute problems and reduces the need for frequent contact between cardiologists and patients who need regular check-ups and who have difficulties in coming to the center. MDTs might also enhance cooperation among specialized centers and geographically distant, less specialized health centers. Extraordinary demonstrations have proven that remote surgery can be successfully performed over 23,000 kilometers and are expected to contribute to the social implementation of safe and precise remote surgery, as well as significantly improve global access to medical care.

However, MDTs have some drawbacks. Telemedicine cannot replace physical contact with patients and should not discredit the home physicians. It is too early to assume that MDTs can be generally used in high-risk, older cardiac patients with multimorbidity. While medical centers claim that MDTs might lower health expenditures, this has yet to be proven. Even recognizing their important medical positive qualities, their high costs must also be considered.

Finally, currently, MDTs are almost exclusively used in specialized teaching medical centers, but office-based family physicians show less interest and knowledge about MDTs. The reason for this attitude may appear unclear. Still, it is essentially a consequence of health insurance companies that do not refund or reimburse medical bills related to the use of MDTs sufficiently. There is a long and arduous road to the legitimacy of MDTs.

List of Abbreviations

Author Contributions

Stefano Pandolfi found almost 300 references. He checked the manuscript and the reviewers’ comments. Giuseppe Cocco and Hans Peter Hofmann selected the used references, wrote the manuscript and answered the reviewers’ comments.

Competing Interests

The authors have declared that no competing interests exist.

AI-Assisted Technologies Statement

The authors have used Windows Copilot for spelling and grammar. All scientific content, data interpretation, and conclusions were developed independently by the author. The authors have thoroughly reviewed and edited the AI-assisted text to ensure its accuracy and accept full responsibility for the content of the manuscript.

References

  1. Cocco G, Amiet P. Known-unknowns in geriatric cardiology. OBM Geriatr. 2020; 4: 111. [CrossRef] [Google scholar]
  2. Cocco G, Pandolfi S. Age-related pathologies and life span. OBM Geriatr. 2023; 7: 253. [CrossRef] [Google scholar]
  3. Cocco G, Amiet P. Epigenetics and medicine. OBM Genet. 2021; 5: 133. [CrossRef] [Google scholar]
  4. Cocco G, Hofmann HP, Pandolfi S. Impact of sex and gender differences on heart failure, especially in elderly patients. OBM Geriatr. 2024; 8: 273. [CrossRef] [Google scholar]
  5. World Health Organization. Global health estimates: Leading causes of death [Internet]. Geneva, Switzerland: World Health Organization; 2021. Available from: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death. [PubMed]
  6. World Atlas. Lowest death rates worldwide [Internet]. Quebec, Canada: World Atlas; 2017. Available from: https://www.worldatlas.com/articles/the-countries-with-the-lowest-death-rates.html.
  7. Krishnaswami A, Beavers C, Dorsch MP, Dodson JA, Masterson Creber R, Kitsiou S, et al. Gerotechnology for older adults with cardiovascular diseases: JACC state-of-the-art review. J Am Coll Cardiol. 2020; 76: 2650-2670. [CrossRef] [Google scholar] [PubMed]
  8. Guasti L, Dilaveris P, Mamas MA, Richter D, Christodorescu R, Lumens J, et al. Digital health in older adults for the prevention and management of cardiovascular diseases and frailty. A clinical consensus statement from the ESC council for cardiology practice/taskforce on geriatric cardiology, the ESC digital health committee and the ESC working group on e-cardiology. ESC Heart Fail. 2022; 9: 2808-2822. [CrossRef] [Google scholar] [PubMed]
  9. Kim BY, Lee J. Smart devices for older adults managing chronic disease: A scoping review. JMIR Mhealth Uhealth. 2017; 5: e69. [CrossRef] [Google scholar] [PubMed]
  10. Lyons JP, Watson K, Massacci A. The evolution of elderly telehealth and health informatics. Recent advances in digital system diagnosis and management of healthcare. London, UK: IntechOpen; 2019. [Google scholar]
  11. Brunetti ND, Molinari G, Acquistapace F, Zimotti T, Parati G, Indolfi C, et al. 2019 Italian society of cardiology census on telemedicine in cardiovascular disease: A report from the working group on telecardiology and informatics. Open Heart. 2020; 7: e001157. [CrossRef] [Google scholar] [PubMed]
  12. Kraef C, van der Meirschen M, Free C. Digital telemedicine interventions for patients with multimorbidity: A systematic review and meta-analysis. BMJ Open. 2020; 10: e036904. [CrossRef] [Google scholar] [PubMed]
  13. Chen AT, Chu F, Teng AK, Han S, Lin SY, Demiris G, et al. Promoting problem solving about health management: A mixed-methods pilot evaluation of a digital health intervention for older adults with pre-frailty and frailty. Gerontol Geriatr Med. 2021; 7. doi: 10.1177/2333721420985684. [CrossRef] [Google scholar] [PubMed]
  14. El Jamal N, Abi-Saleh B, Isma’eel H. Advances in telemedicine for the management of the elderly cardiac patient. J Geriatr Cardiol. 2021; 18: 759-767. [Google scholar]
  15. Jensen MT, Treskes RW, Caiani EG, Casado-Arroyo R, Cowie MR, Dilaveris P, et al. ESC working group on e-cardiology position paper: Use of commercially available wearable technology for heart rate and activity tracking in primary and secondary cardiovascular prevention—in collaboration with the European heart rhythm association, European association of preventive cardiology, association of cardiovascular nursing and allied professionals, patient forum, and the digital health committee. Eur Heart J Digit Health. 2021; 2: 49-59. [CrossRef] [Google scholar] [PubMed]
  16. Osipov VS, Skryl TV. Impact of digital technologies on the efficiency of healthcare delivery. In: IoT in healthcare and ambient assisted living. Singapore: Springer Singapore; 2021. pp. 243-261. [CrossRef] [Google scholar]
  17. Quisel T, Foschini L, Zbikowski SM, Juusola JL. The association between medication adherence for chronic conditions and digital health activity tracking: Retrospective analysis. J Med Internet Res. 2019; 21: e11486. [CrossRef] [Google scholar] [PubMed]
  18. Kim JY, Oh IY, Lee H, Lee JH, Cho Y, Gil Y, et al. The efficacy of detecting arrhythmia is higher with 7‐day continuous electrocardiographic patch monitoring than with 24‐h Holter monitoring. J Arrhythm. 2023; 39: 422-429. [CrossRef] [Google scholar] [PubMed]
  19. Boston Scientific. LUX-Dx™ ICM System [Internet]. Marlborough, MA: Boston Scientific; 2025. Available from: https://www.bostonscientific.com/en-EU/products/remote-patient-monitoring/LUX-Dx-ICM-System/implant-procedure.html?utm_medium=search&utm_source=google&utm_campaign=rm-cdx-emea-all-icm-workflow-main-en-dtc-24q4&utm_content=txt-adgroup2&gad_source=1&gclid=CjwKCAiAtsa9BhAKEiwAUZAszSjky1WkWmIFtBFMX9CHvVJqoAplrJebVKBmPykvc4qqkl4iqcReoBoCTzYQAvD_BwE.
  20. Abbott. Jot Dx ICM [Internet]. Tokyo, Japan: Abbott; 2025. Available from: https://www.cardiovascular.abbott/int/en/hcp/products/cardiac-rhythm-management/insertable-cardiac-monitors/jot-dx/why.html.
  21. Varma N, Stambler B, Chun S. Detection of atrial fibrillation by implanted devices with wireless data transmission capability. Pacing Clin Electrophysiol. 2005; 28: S133-S136. [CrossRef] [Google scholar] [PubMed]
  22. Wilkoff BL, Auricchio A, Brugada J, Cowie M, Ellenbogen KA, Gillis AM, et al. HRS/EHRA expert consensus on the monitoring of cardiovascular implantable electronic devices (CIEDs): Description of techniques, indications, personnel, frequency and ethical considerations. Heart Rhythm. 2008; 5: 907-925. [CrossRef] [Google scholar] [PubMed]
  23. Varma N, Epstein AE, Irimpen A, Schweikert R, Love C. Efficacy and safety of automatic remote monitoring for implantable cardioverter-defibrillator follow-up: The Lumos-T safely reduces routine office device follow-up (TRUST) trial. Circulation. 2010; 122: 325-332. [CrossRef] [Google scholar] [PubMed]
  24. Hernandez-Madrid A, Lewalter T, Proclemer A, Pison L, Lip GY, Blomstrom-Lundqvist C. Remote monitoring of cardiac implantable electronic devices in Europe: Results of the European heart rhythm association survey. Europace. 2014; 16: 129-132. [CrossRef] [Google scholar] [PubMed]
  25. Amiet PR, Cocco G. Diagnosis and therapy of atrial fibrillation in geriatric patients. OBM Geriatr. 2021; 5: 178. [Google scholar]
  26. Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C, et al. 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European association for cardio-thoracic surgery (EACTS): The task force for the diagnosis and management of atrial fibrillation of the European society of cardiology (ESC) developed with the special contribution of the European heart rhythm association (EHRA) of the ESC. Eur Heart J. 2021; 42: 373-498. [CrossRef] [Google scholar] [PubMed]
  27. Varma N, Cygankiewicz I, Turakhia M, Heidbuchel H. Hu Y, Chen LY et al. 2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in arrhythmia management: Digital medical tools for heart rhythm professionals: From the international society for Holter and noninvasive electrocardiology/heart rhythm society/European heart rhythm association/Asia pacific heart rhythm society. Ann Noninvasice Electrocardiol. 2021; 26: e12795. [CrossRef] [Google scholar] [PubMed]
  28. Adamson PB, Gold MR, Bennett T, Bourge RC, Stevenson LW, Trupp R, et al. Continuous hemodynamic monitoring in patients with mild to moderate heart failure: Results of the reducing decompensation events utilizing intracardiac pressures in patients with chronic heart failure (REDUCEhf) trial. Congest Heart Fail. 2011; 17: 248-254. [CrossRef] [Google scholar] [PubMed]
  29. Abraham WT, Stevenson LW, Bourge RC, Lindenfeld JA, Bauman JG, Adamson PB. Sustained efficacy of pulmonary artery pressure to guide adjustment of chronic heart failure therapy: Complete follow-up results from the CHAMPION randomised trial. Lancet. 2016; 387: 453-461. [CrossRef] [Google scholar] [PubMed]
  30. Ong MK, Romano PS, Edgington S, Aronow HU, Auerbach AD, Black JT, et al. Effectiveness of remote patient monitoring after discharge of hospitalized patients with heart failure: The better effectiveness after transition-heart failure (BEAT-HF) randomized clinical trial. JAMA Intern Med. 2016; 176: 310-318. [CrossRef] [Google scholar] [PubMed]
  31. Asteggiano R, Cowie MR, Richter D, Christodorescu R, Guasti L, Ferrini M. Survey on e-health knowledge and usage in general cardiology of the council of cardiology practice and the digital health committee. Eur Heart J Digit Health. 2021; 2: 342-347. [CrossRef] [Google scholar] [PubMed]
  32. Cowie MR, Lam CS. Remote monitoring and digital health tools in CVD management. Nat Rev Cardiol. 2021; 18: 457-458. [CrossRef] [Google scholar] [PubMed]
  33. Győrffy Z, Boros J, Döbrössy B, Girasek E. Older adults in the digital health era: Insights on the digital health related knowledge, habits and attitudes of the 65 year and older population. BMC Geriatr. 2023; 23: 779. [CrossRef] [Google scholar] [PubMed]
  34. Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, et al. Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Med Educ. 2023; 23: 689. [CrossRef] [Google scholar] [PubMed]
  35. Tsoi K, Yiu K, Lee H, Cheng HM, Wang TD, Tay JC, et al. Applications of artificial intelligence for hypertension management. J Clin Hypertens. 2021; 23: 568-574. [CrossRef] [Google scholar] [PubMed]
  36. Czaja SJ, Charness N, Fisk AD, Hertzog C, Nair SN, Rogers WA, et al. Factors predicting the use of technology: Findings from the Center for research and education on aging and technology enhancement (CREATE). Psychol Aging. 2006; 21: 333-352. [CrossRef] [Google scholar] [PubMed]
  37. Myers KD, Knowles JW, Staszak D, Shapiro MD, Howard W, Yadava M, et al. Precision screening for familial hypercholesterolaemia: A machine learning study applied to electronic health encounter data. Lancet Digit Health. 2019; 1: e393-e402. [CrossRef] [Google scholar] [PubMed]
  38. Andrès E, Meyer L, Zulfiqar AA, Hajjam M, Talha S, Bahougne T, et al. Telemonitoring in diabetes: Evolution of concepts and technologies, with a focus on results of the more recent studies. J Med Life. 2019; 12: 203-214. [CrossRef] [Google scholar] [PubMed]
  39. Omboni S, McManus RJ, Bosworth HB, Chappell LC, Green BB, Kario K, et al. Evidence and recommendations on the use of telemedicine for the management of arterial hypertension: An international expert position paper. Hypertension. 2020; 76: 1368-1383. [CrossRef] [Google scholar] [PubMed]
  40. Steinberg DM, Kay MC, Svetkey LP, Askew S, Christy J, Burroughs J, et al. Feasibility of a digital health intervention to improve diet quality among women with high blood pressure: Randomized controlled feasibility trial. JMIR Mhealth Uhealth. 2020; 8: e17536. [CrossRef] [Google scholar] [PubMed]
  41. McManus RJ, Little P, Stuart B, Morton K, Raftery J, Kelly J, et al. Home and online management and evaluation of blood pressure (HOME BP) using a digital intervention in poorly controlled hypertension: Randomised controlled trial. BMJ. 2021; 372: m4858. [CrossRef] [Google scholar] [PubMed]
  42. Milani RV, Lavie CJ, Ventura HO. New aspects in the management of hypertension in the digital era. Curr Opin Cardiol. 2021; 36: 398-404. [CrossRef] [Google scholar] [PubMed]
  43. Yatabe J, Yatabe MS, Ichihara A. The current state and future of internet technology-based hypertension management in Japan. Hypertens Res. 2021; 44: 276-285. [CrossRef] [Google scholar] [PubMed]
  44. Chaudhry SI, Mattera JA, Curtis JP, Spertus JA, Herrin J, Lin Z, et al. Telemonitoring in patients with heart failure. N Engl J Med. 2010; 363: 2301-2309. [CrossRef] [Google scholar] [PubMed]
  45. Boyne JJ, Vrijhoef HJ, Crijns HJ, De Weerd G, Kragten J, Gorgels AP, et al. Tailored telemonitoring in patients with heart failure: Results of a multicentre randomized controlled trial. Eur J Heart Fail. 2012; 14: 791-801. [CrossRef] [Google scholar] [PubMed]
  46. Inglis SC, Clark RA, Dierckx R, Prieto‐Merino D, Cleland JG. Structured telephone support or non‐invasive telemonitoring for patients with heart failure. Cochrane Database Syst Rev. 2015. doi: 10.1002/14651858.CD007228.pub3. [CrossRef] [Google scholar] [PubMed]
  47. Karhula T, Vuorinen AL, Rääpysjärvi K, Pakanen M, Itkonen P, Tepponen M, et al. Telemonitoring and mobile phone-based health coaching among Finnish diabetic and heart disease patients: Randomized controlled trial. J Med Internet Res. 2015; 17: e153. [CrossRef] [Google scholar] [PubMed]
  48. Dierckx R, Inglis SC, Clark RA, Prieto-Merino D, Cleland JG. Telemedicine in heart failure: New insights from the Cochrane meta-analyses. Eur J Heart Fail. 2017; 19: 304-306. [CrossRef] [Google scholar] [PubMed]
  49. Koehler F, Koehler K, Deckwart O, Prescher S, Wegscheider K, Kirwan BA, et al. Efficacy of telemedical interventional management in patients with heart failure (TIM-HF2): A randomised, controlled, parallel-group, unmasked trial. Lancet. 2018; 392: 1047-1057. [CrossRef] [Google scholar] [PubMed]
  50. Vitale C, Jankowska E, Hill L, Piepoli M, Doehner W, Anker SD, et al. Heart failure association of the European society of cardiology position paper on frailty in patients with heart failure. Eur J Heart Fail. 2019; 21: 1299-1305. [CrossRef] [Google scholar] [PubMed]
  51. Angermann CE, Assmus B, Anker SD, Asselbergs FW, Brachmann J, Brett ME, et al. Pulmonary artery pressure‐guided therapy in ambulatory patients with symptomatic heart failure: The Cardio MEMS European monitoring study for heart failure (MEMS‐HF). Eur J Heart Fail. 2020; 22: 1891-1901. [CrossRef] [Google scholar] [PubMed]
  52. Zhu Y, Gu X, Xu C. Effectiveness of telemedicine systems for adults with heart failure: A meta-analysis of randomized controlled trials. Heart Fail Rev. 2020; 25: 231-243. [CrossRef] [Google scholar] [PubMed]
  53. McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M, et al. 2021 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the task force for the diagnosis and treatment of acute and chronic heart failure of the European society of cardiology (ESC) with the special contribution of the heart failure association (HFA) of the ESC. Eur Heart J. 2021; 42: 3599-3726. [CrossRef] [Google scholar] [PubMed]
  54. Singhal A, Cowie MR. Digital health: Implications for heart failure management. Card Fail Rev. 2021; 7: e08. [CrossRef] [Google scholar] [PubMed]
  55. Engdahl J, Andersson L, Mirskaya M, Rosenqvist M. Stepwise screening of atrial fibrillation in a 75-year-old population: Implications for stroke prevention. Circulation. 2013; 127: 930-937. [CrossRef] [Google scholar] [PubMed]
  56. Nielsen PB, Larsen TB, Skjøth F, Overvad TF, Lip GY. Stroke and thromboembolic event rates in atrial fibrillation according to different guideline treatment thresholds: A nationwide cohort study. Sci Rep. 2016; 6: 27410. [CrossRef] [Google scholar] [PubMed]
  57. Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al. Heart disease and stroke statistics-2017 update: A report from the American heart association. Circulation. 2017; 135: e146-e603. [CrossRef] [Google scholar] [PubMed]
  58. Chen LY, Chung MK, Allen LA, Ezekowitz M, Furie KL, McCabe P, et al. Atrial fibrillation burden: Moving beyond atrial fibrillation as a binary entity: A scientific statement from the American heart association. Circulation. 2018; 137: e623-e644. [CrossRef] [Google scholar] [PubMed]
  59. Kaplan RM, Koehler J, Ziegler PD, Sarkar S, Zweibel S, Passman RS. Stroke risk as a function of atrial fibrillation duration and CHA2DS2-VASc score. Circulation. 2019; 140: 1639-1646. [CrossRef] [Google scholar] [PubMed]
  60. Richter D, Guasti L, Walker D, Lambrinou E, Lionis C, Abreu A, et al. Frailty in cardiology: Definition, assessment and clinical implications for general cardiology. A consensus document of the council for cardiology practice (CCP), association for acute cardio vascular care (ACVC), association of cardiovascular nursing and allied professions (ACNAP), European association of preventive cardiology (EAPC), European heart rhythm association (EHRA), council on valvular heart diseases (VHD), council on hypertension (CHT), council of cardio-oncology (CCO), working group (WG), aorta and peripheral vascular diseases, WG e-cardiology, WG thrombosis, of the European society of cardiology, European primary care cardiology society (EPCCS). Eur J Prev Cardiol. 2022; 29: 216-227. [CrossRef] [Google scholar] [PubMed]
  61. Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, et al. Large-scale assessment of a smartwatch to identify atrial fibrillation. N Engl J Med. 2019; 381: 1909-1917. [CrossRef] [Google scholar] [PubMed]
  62. Svennberg E, Engdahl J, Al-Khalili F, Friberg L, Frykman V, Rosenqvist M. Mass screening for untreated atrial fibrillation: The STROKESTOP study. Circulation. 2015; 131: 2176-2184. [CrossRef] [Google scholar] [PubMed]
  63. Lowres N, Olivier J, Chao TF, Chen SA, Chen Y, Diederichsen A, et al. Estimated stroke risk, yield, and number needed to screen for atrial fibrillation detected through single time screening: A multicountry patient-level meta-analysis of 141,220 screened individuals. PLoS Med. 2019; 16: e1002903. [CrossRef] [Google scholar] [PubMed]
  64. Kemp Gudmundsdottir K, Fredriksson T, Svennberg E, Al-Khalili F, Friberg L, Frykman V, et al. Stepwise mass screening for atrial fibrillation using N-terminal B-type natriuretic peptide: The STROKESTOP II study. Europace. 2020; 22: 24-32. [CrossRef] [Google scholar] [PubMed]
  65. Proietti M, Marra AM, Tassone EJ, De Vuono S, Corrao S, Gobbi P, et al. Frequency of left ventricular hypertrophy in non-valvular atrial fibrillation. Am J Cardiol. 2015; 116: 877-882. [CrossRef] [Google scholar] [PubMed]
  66. Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al. List of authors/task force members. 2018 practice guidelines for the management of arterial hypertension of the European society of hypertension and the European society of cardiology: ESH/ESC task force for the management of arterial hypertension. J Hypertens. 2018; 36: 2284-2309. [CrossRef] [Google scholar] [PubMed]
  67. Kario K. Management of hypertension in the digital era: Small wearable monitoring devices for remote blood pressure monitoring. Hypertension. 2020; 76: 640-650. [CrossRef] [Google scholar] [PubMed]
  68. Xu H, Long H. The effect of smartphone app-based interventions for patients with hypertension: Systematic review and meta-analysis. JMIR Mhealth Uhealth. 2020; 8: e21759. [CrossRef] [Google scholar] [PubMed]
  69. Padwal R, Wood PW. Digital health approaches for the assessment and optimisation of hypertension care provision. Can J Cardiol. 2021; 37: 711-721. [CrossRef] [Google scholar] [PubMed]
  70. Pal K, Eastwood SV, Michie S, Farmer A, Barnard ML, Peacock R, et al. Computer-based interventions to improve self-management in adults with type 2 diabetes: A systematic review and meta-analysis. Diabetes Care. 2014; 37: 1759-1766. [CrossRef] [Google scholar] [PubMed]
  71. Garabedian LF, Ross-Degnan D, Wharam JF. Mobile phone and smartphone technologies for diabetes care and self-management. Curr Diab Rep. 2015; 15: 109. [CrossRef] [Google scholar] [PubMed]
  72. Cosentino F, Grant PJ, Aboyans V, Bailey CJ, Ceriello A, Delgado V, et al. 2019 ESC guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: The task force for diabetes, pre-diabetes, and cardiovascular diseases of the European society of cardiology (ESC) and the European association for the study of diabetes (EASD). Eur Heart J. 2020; 41: 255-323. [CrossRef] [Google scholar] [PubMed]
  73. IRCAD. Lindbergh Operation: A World’s First Across the Atlantic! [Internet]. Strasbourg, France: IRCAD; 2021. Available from: https://www.ircad.fr/le-geste-chirurgical-a-traverse-latlantique/.
  74. Zheng J, Wang Y, Zhang J, Guo W, Yang X, Luo L, et al. 5G ultra-remote robot-assisted laparoscopic surgery in China. Surg Endosc. 2020; 34: 5172-5180. [CrossRef] [Google scholar] [PubMed]
  75. Medicaroid. Hinotori Robotic Assisted Surgery System [Internet]. San Jose, CA: Medicaroid; 2025. Available from: https://www.medicaroid.com/en/product/hinotori/.
  76. Lind L, Karlsson D. Telehealth for “the digital illiterate”-elderly heart failure patients experiences. In: e-Health–For Continuity of Care. Amsterdam, The Netherlands: IOS Press; 2014. pp. 353-357. [Google scholar]
  77. Vaportzis E, Giatsi Clausen M, Gow AJ. Older adults perceptions of technology and barriers to interacting with tablet computers: A focus group study. Frontiers in psychology. 2017; 8: 1687. [CrossRef] [Google scholar] [PubMed]
  78. Mcguire LC. Remembering what the doctor said: Organization and adults' memory for medical information. Exp Aging Res. 1996; 22: 403-428. [CrossRef] [Google scholar] [PubMed]
  79. Flocke SA, Stange KC. Direct observation and patient recall of health behavior advice. Prev Med. 2004; 38: 343-349. [CrossRef] [Google scholar] [PubMed]
Newsletter
Download PDF Download Full-Text XML Download Citation
0 0
Newsletter  

TOP