Search Results (268)

The COVID-19 pandemic catalyzed the rapid adoption of remote patient monitoring (RPM) technologies such as telemedicine and wearable devices (WDs), significantly transforming healthcare delivery. Telemedicine made virtual consultations possible, reducing in-person visits and infection risks, particularly for the management of chronic diseases. Wearable devices enabled the real-time continuous monitoring of health that assisted in condition prediction and management, such as for COVID-19. This narrative review addresses these transformations by uniquely synthesizing findings from 13 diverse studies (sourced from PubMed and Google Scholar, 2020–2024) to analyze the parallel evolution of telemedicine and WDs as interconnected RPM components. It highlights the pandemic’s dual impact, as follows: accelerating RPM innovation and adoption while simultaneously unmasking systemic challenges such as inequities in access and a need for robust integration approaches; while telemedicine usage soared during the pandemic, consumption post-pandemic, as indicated by the reviewed studies, suggests continued barriers to adoption among older adults. Likewise, wearable devices demonstrated significant potential in early disease detection and long-term health management, with promising applications extending beyond COVID-19, including long COVID conditions. Addressing the identified challenges is crucial for healthcare providers and systems to fully embrace these technologies and this would improve efficiency and patient outcomes. Full article

Total Knee Arthroplasty (TKA) is a well-established surgical intervention for the management of end-stage knee osteoarthritis. While the procedure is generally successful, postoperative rehabilitation remains a key determinant of long-term functional outcomes. Traditional rehabilitation protocols, particularly those requiring in-person clinical visits, often encounter limitations in accessibility, patient adherence, and personalization. In response, emerging sensor technologies have introduced innovative solutions to support and enhance recovery following TKA. This review provides a thematically organized synthesis of the current landscape and future directions of sensor-assisted rehabilitation in TKA. It examines four main categories of technologies: wearable sensors (e.g., IMUs, accelerometers, gyroscopes), smart implants, pressure-sensing systems, and mobile health (mHealth) platforms such as ReHub^® and BPMpathway. Evidence from recent randomized controlled trials and systematic reviews demonstrates their effectiveness in tracking mobility, monitoring range of motion (ROM), detecting gait anomalies, and delivering real-time feedback to both patients and clinicians. Despite these advances, several challenges persist, including measurement accuracy in unsupervised environments, the complexity of clinical data integration, and digital literacy gaps among older adults. Nevertheless, the integration of artificial intelligence (AI), predictive analytics, and remote rehabilitation tools is driving a shift toward more adaptive and individualized care models. This paper concludes that sensor-enhanced rehabilitation is no longer a future aspiration but an active transition toward a smarter, more accessible, and patient-centered paradigm in recovery after TKA. Full article

Bacterial vaginosis (BV) affects 30% of women annually, but many face barriers to in-person care. Here we present real-world outcomes of remote BV diagnosis and management through self-collected vaginal microbiome (VMB) testing and telemedicine visits, focusing on symptom resolution, recurrence, and overall microbial shifts. Among the 1159 study participants, 75.5% experienced symptom resolution at four weeks when managed with our algorithm-guided treatment protocol. At a median follow-up of 4.4 months after the initial visit, 30.0% of patients experienced recurrent BV, which is lower than the typical recurrence rates seen in historical in-person cohorts. Across the entire cohort, metagenomic data demonstrated a significant increase in Lactobacillus abundance (mean of 32.9% to 48.4%, p < 0.0001) and a corresponding decrease in BV-associated taxa such as Gardnerella, Prevotella, and Fannyhessea. A PERMANOVA of pairwise Bray–Curtis distances showed significant separation between pre-and post-treatment samples (pseudo-F = 37.6, p < 0.0001), driven by an increase in Lactobacillus-dominated samples. Treatment adherence was high (a total of 78% reported perfect or near-perfect adherence), and adverse events were generally mild (in total, 22% reported vaginal irritation, and 13% reported abnormal discharge). These results demonstrate that Evvy’s at-home metagenomic platform, paired with telemedicine and a smart treatment algorithm, delivers robust clinical and microbial outcomes. This work offers a novel approach to managing bacterial vaginosis, a challenging condition characterized by persistently high recurrence rates. Full article

Background and Objectives: To systematically map and evaluate the current literature on the application of artificial intelligence (AI) in teleorthodontics, focusing on clinical use, technological approaches, outcomes, and limitations. Materials and Methods: A scoping review was conducted following a formal and recognized methodological framework. Three databases (PubMed, Scopus, Web of Science) were searched until 30 April 2025. Studies were included if they reported original data on AI applications in orthodontic remote monitoring or virtual care. Data extraction focused on study design, type of AI, clinical setting, reported outcomes, and main findings. Results: Nine studies met the inclusion criteria. Most research focused on the use of the Dental Monitoring™ (DM) system, which employs deep learning algorithms to analyze intraoral scans captured via smartphones. Reported benefits included reduced in-office visits (up to 33%), accurate 3D tracking of tooth movement, improved hygiene compliance, and high patient engagement. However, significant variability was observed in the repeatability and precision of AI decisions, especially in GO/NO-GO aligner progression instructions. One study explored an alternative system, StrojCHECK™, based on a decision tree algorithm, showing improved compliance with personalized feedback. Conclusions: AI-powered teleorthodontic systems show potential to enhance treatment efficiency and patient engagement, particularly in aligner therapy. However, their current clinical application remains narrowly focused on commercial monitoring platforms, with limited validation and transparency. This review highlights the early stage of real-world AI integration in orthodontics, underlining the need for independent validation, broader applications beyond monitoring, and robust ethical frameworks. In this context, AI should be used as a complementary tool, never a substitute, for clinical judgment. Full article

Background/Objectives: Remote telemedical management (RTM) in heart failure (HF) patients with cardiac implantable electronic devices (CIED) is a reliable approach to follow device-specific and heart failure-related parameters. However, while some positive outcome data is available, results are inconclusive. We aimed to assess the benefits of continuous remote telemonitoring (RTM) compared to the in-person visit (IPV) in reducing all-cause mortality, heart failure hospitalizations (HFH), cardiovascular (CV) deaths, and the occurrence of inappropriate therapy. Methods: The study comprised a systematic review and meta-analysis of randomized controlled trials (RCTs) testing RTM (device-related or other non-invasive telemonitoring systems) vs. IPV for the management of HF patients. The main endpoints were all-cause and CV mortality. Risk of bias and level of evidence were assessed. Hazard ratios (HRs), odds ratios (ORs) and 95% confidence intervals (CI) were calculated. CENTRAL, EMBASE and MEDLINE were searched, and only randomized controlled studies were included. Results: Sixteen RCTs were identified, comprising a total of 11,232 enrolled patients. Seven studies evaluated all-cause mortality, resulting in an OR 0.83 (95% CI 0.72 to 0.96). When CV mortality was assessed, the RTM group showed a significant benefit compared to the IPV group (OR 0.81, 95% CI 0.67 to 0.97). The risk of bias ranged from “low” to “some concerns” for most outcomes, and the certainty was low to moderate depending on the specific outcomes. Conclusions: RTM proved to be superior in reducing all-cause and CV mortality compared to IPV; however, there is a clear need to have standardized alert actions to achieve the mortality benefit. Full article

Breast cancer is a leading cause of cancer-related mortality worldwide, requiring efficient diagnostic tools for early detection and monitoring. Human epidermal growth factor receptor 2 (HER2) is a key biomarker for breast cancer classification, typically assessed using immunohistochemistry (IHC). However, IHC requires invasive biopsies and time-intensive laboratory procedures. In this study, we present a biosensor integrated with a reusable printed circuit board (PCB) and functionalized glucose test strips designed for rapid and non-invasive HER2 detection in saliva. The biosensor achieved a limit of detection of 10⁻¹⁵ g/mL, 4 to 5 orders of magnitude more sensitive than the enzyme-linked immunosorbent assay (ELISA), with a sensitivity of 95/dec and a response time of 1 s. In addition to HER2, the biosensor also detects cancer antigen 15-3 (CA15-3), another clinically relevant breast cancer biomarker. The CA15-3 test demonstrated an equally low limit of detection, 10⁻¹⁵ g/mL, and a higher sensitivity, 190/dec, further validated using human saliva samples. Clinical validation using 29 saliva samples confirmed our biosensor’s ability to distinguish between healthy, in situ breast cancer, and invasive breast cancer patients. The system, which integrates a Bluetooth Low-Energy (BLE) module, enables remote monitoring, reduces hospital visits, and enhances accessibility for point-of-care and mobile screening applications. This ultra-sensitive, rapid, and portable biosensor can serve as a promising alternative for breast cancer detection and monitoring, particularly in rural and underserved communities. Full article

Background/Objectives: Despite the recent advances in glucose-lowering therapy, achieving diabetes control remains challenging. With the advancing progress of innovative digital health technologies, management of diabetes is taking advantage from telehealth and telemedicine, which allow for remote assistance, virtual visits, and monitoring of diabetes-related parameters, and facilitate the exchange of documents and reports to support clinical decisions. We aim to provide an overview of the impact of telehealth and digital technologies on the care of people with diabetes, from therapeutic management to the assessment of complications. Methods: A comprehensive literature search was conducted using PubMed to assess the impact of digital technologies and telemedicine on diabetes care. Results: From the comprehensive PubMed search, 86 peer-reviewed studies were selected based on relevance, clinical significance, and methodological quality. The selected literature addressed digital health tools such as continuous glucose monitoring, connected insulin pens, automatic insulin delivery systems, mobile applications, and telemedicine systems. These interventions were associated with improved glycemic control (e.g., reduced HbA1c, increased time in range), better adherence to therapy, enhanced patient engagement, and more efficient management of complications such as neuropathy, retinopathy, and cardiovascular risk. Conclusions: Telehealth may offer a fully patient-centered approach to disease management through a tailored individual management plan. This may lead to an improvement in adherence to proper therapy and lifestyle, resulting in a subsequent increase in the quality of life. Full article

Background: Remote symptom monitoring via electronic platforms may identify patients at risk for unplanned acute care visits after surgery. Since 2016, the Memorial Sloan Kettering Cancer Center (MSKCC) has employed the Recovery Tracker (RT), a patient-reported outcome (PRO) system, for symptom monitoring after ambulatory procedures. In 2021, RT was extended to patients undergoing inpatient colorectal surgery. Objective: To evaluate the impact of RT implementation on urgent care utilization and readmission rates in patients undergoing elective inpatient colorectal surgery and to determine whether patient engagement with RT influences these outcomes. Methods: In this retrospective observational study at MSKCC, we compared patients undergoing elective colorectal surgery during the RT implementation period (March 2021–December 2022) to a historical control cohort (February 2019–February 2020). The primary outcome was a potentially unnecessary urgent care center (UCC) visits—defined as a visit not requiring inpatient admission. Secondary outcomes included 30-day readmission and survey engagement. Multivariable logistic regression was used for adjusted comparisons. Results: A total of 1941 patients in the RT cohort and 1206 in the control group met the inclusion criteria. The RT cohort had higher rates of UCC visits without admission (4.43% vs. 1.6%) and 30-day readmissions (9.74% vs. 6.88%). RT period surgery was independently associated with increased odds of UCC visits (OR 2.80, 95% CI 1.71–4.58, p < 0.0001) and readmissions (OR 1.43, 95% CI 1.09–1.88, p = 0.0098). Notably, RT users who completed at least one survey (70.2%) had significantly lower odds of readmission (OR 0.56, 95% CI 0.41–0.77, p = 0.0003) compared to non-responders. Discussion: Engagement with the RT system was associated with a 44% reduction in readmission risk, identifying non-responders as a vulnerable subgroup. While the overall rates of post-discharge care utilization increased after RT implementation, active participation in PRO reporting emerged as a protective factor. Conclusions: These findings highlight the need for strategies to promote engagement and support patients less likely to interact with remote monitoring tools. Non-response may signal barriers such as technological challenges or increased vulnerability, warranting proactive engagement strategies. Full article

Background/Objectives: Potassium-competitive acid blockers (P-CABs) offer rapid gastric acid inhibition and lower toxicity compared to proton pump inhibitors (PPIs). This study investigates the drug–drug interaction between P-CABs and immunosuppressants tacrolimus and mycophenolate in kidney transplant recipients (KTRs). Methods: Sixty-two KTRs were randomized to receive either 50 mg of tegoprazan or 20 mg of pantoprazole. Patients were monitored using a smart clinical trial platform incorporating remote monitoring and safety management systems, which tracked drug adherence and vital signs. General and gastrointestinal (GI) symptoms were surveyed via a self-developed app on patients’ phones. Trough levels of tacrolimus and mycophenolate were measured every 4 weeks over 12 weeks. Results: Medication adherence was 100% in both groups. A total of 13,726 biometric data points and 5031 questionnaire responses were collected, with 5704 feedback messages and 56 video visits conducted. At 12 weeks, the mean trough levels of tacrolimus and mycophenolate were similar between the tegoprazan and pantoprazole groups (5.5 ± 1.6 vs. 5.8 ± 2.0 ng/mL, p = 0.50 and 2.7 ± 1.4 vs. 2.6 ± 1.4 µg/mL, p = 0.57, respectively). The intragroup difference in trough levels from baseline to week 12 was not significant in either group. GI symptoms scores, vital signs, and allograft function remained stable and comparable between groups. Conclusions: Tegoprazan does not alter the blood trough levels of tacrolimus and mycophenolate during the 12-week follow-up in KTRs and has a similar impact on GI symptoms as pantoprazole. This study confirms the feasibility and safety of using a smart clinical trial system with remote monitoring for randomized trials. Full article

Background/Objectives: Patients recovering from COVID-19 often experience persistent respiratory symptoms, necessitating pulmonary function monitoring. While clinical spirometry is the gold standard, home spirometry offers a remote alternative. This study evaluated the validity of an ultrasonic home-based spirometer for monitoring lung function in post-COVID-19 pneumonia patients over 12 weeks. Methods: This prospective study included 30 post-COVID pneumonia patients who underwent clinical spirometry at weeks 4, 8 and 12. Participants performed weekly home spirometry using the SpiroHome Personal^® device. Agreement between home and clinical spirometry was assessed using a Bland–Altman analysis, intraclass correlation coefficients (ICCs), and Pearson correlation coefficients. Pulmonary function changes over time were analyzed using repeated measures ANOVA. Results: Home spirometry showed strong agreement with clinical spirometry for forced vital capacity (FVC) and forced expiratory volume in the first second (FEV1), with ICC values exceeding 0.92. The Bland–Altman analysis demonstrated minimal bias, though limits of agreement exceeded the clinically accepted threshold of ±150 mL. FEV1/FVC ratios showed greater variability. Pulmonary function improved significantly over 12 weeks for both methods (p < 0.002). Patient adherence to home spirometry remained high, with a median of 18.50 sessions [IQR: 15.00–26.00] and an overall compliance rate of 98.33% ± 9.13%. Conclusions: Home spirometry provides reliable pulmonary function measurements, particularly for FVC and FEV1, supporting its role as a remote monitoring tool. Despite minor variability in FEV1/FVC, home spirometry enables frequent assessment of lung function recovery, potentially reducing hospital visits and improving patient management. Full article

Urban vegetation plays a key role in promoting health and environmental balance in cities. This study analyzed the relationship between green areas and human well-being in the Alvorada neighborhood of Guanambi, Bahia, Brazil. Using an ecological study design, vegetation was assessed through the Vegetation Coverage Index (VCI), percentage of vegetation coverage (PVC), aerial and satellite imagery, and population density data. Field visits were also conducted to validate remote observations. The results revealed that the VCI in the study area was significantly below the levels recommended by the World Health Organization (12 m²/inhabitant), indicating a scarcity of green areas. This deficiency is associated with reduced thermal comfort and potential negative impacts on residents’ physical and mental health. The findings reinforce the urgent need for sustainable urban planning in alignment with Sustainable Development Goals (SDGs) 3, 11, and 13, highlighting vegetation as a determinant of urban quality of life. Full article

(1) Aims: In our study, we evaluated the effectiveness of a telemonitoring program based on a nursing clinic, supported by a physician who remotely monitors patients via a dedicated application (TreC Cardiology), in reducing visits and hospitalizations for HF in patients affected by HF living in Trentino in Italy. (2) Methods and Results: The TreC Heart Failure (TreC HF) study prospectively enrolled consecutive patients diagnosed with HF who attended our outpatient clinic and who were provided with the TreC Cardiology application. We analyzed primarily the number of visits and hospitalizations, comparing the year before and after the enrollment. From March 2021 to June 2023, we enrolled 211 patients, predominantly male (70.1%) and with a mean age of 71.5 ± 12.6 years. At baseline, 43.6% of patients were diagnosed with HFrEF, 28% with HFmrEF, and 28.4% with HFpEF. The mean left-ventricular ejection fraction (LV-EF) was 43.2 ± 11.9%. Outpatient visits in the year before the enrollment were on average 2.0 ± 1.2 vs. 1.6 ± 1.3 (p = 0.002) in the same following period. The percentage of patients who were hospitalized for heart failure went from 25.6% to 4.7% (p < 0.001). Analyzing HF categories separately, we found that, in the HFrEF population, after the enrollment, hospitalization for HF significantly decreased (32.6% vs. 7.6%, p < 0.001), while the number of outpatient visits did not vary (2.1 ± 1.4 vs. 2.1 ± 1.3, p = 0.795). In HFmrEF patients, both hospitalization for HF and outpatient visits significantly decreased (respectively, 30.5% vs. 1.7%, p < 0.001 and 2.0 ± 1.0 vs. 1.5 ± 1.3, p = 0.025). Finally, in the HFpEF population, only the number of outpatient visits significantly decreased after the enrollment (2.0 ± 1.1 vs. 1.0 ± 0.8, p < 0.001). (3) Conclusions: Our results confirm the enormous potential of telemonitoring, since in a real-world population affected by heart failure, it resulted in a significant reduction in hospitalization for HF and the number of outpatient visits. Full article

The scarcity of information on agricultural development in the semi-arid region of Alagoas limits the spatial understanding of this activity. Government data are generally numerical and lack spatial detail. Remote sensing emerges as an efficient alternative, providing accessible visualization of agricultural areas. This study evaluates the performance of MapBiomas in monitoring agricultural areas in the semi-arid region of Alagoas, comparing it to a Random Forest model adjusted for the region using higher-resolution images. The first methodology is based on land use and land cover (LULC) data from MapBiomas, an initiative that provides information on land use and land cover in Brazil. The second method employs the Random Forest model, calibrated for the region’s dry season, addressing cloud cover issues and allowing for the identification of irrigated agriculture. LULC data were subjected to a precision analysis using 200 points generated within the study areas, extracting LULC information for each coordinate. These points were overlaid on high-resolution images to assess model accuracy. Additionally, field visits were conducted to validate the identification of agriculture. The irrigated area data from the Random Forest model were correlated with irrigation records from SEMARH. MapBiomas presented a Kappa index of 0.74, with precision exceeding 90% for classes such as forest, natural pasture, non-vegetated area, and water bodies. However, the agriculture class obtained an F1 score of 0.56. The Random Forest model achieved a Kappa index of 0.82, with an F1 score of 0.79 for agriculture. The correlation between the total annual irrigated area data from Random Forest and SEMARH records was high (R = 0.85). The Random Forest model yielded better results in classifying agriculture in the semi-arid region of Alagoas compared to MapBiomas. However, classification limitations were observed in lowland areas due to spectral confusion caused by soil moisture accumulation. Full article

Teledentistry enhances access to oral healthcare by enabling remote consultations, diagnosis, and patient management. This paper explores its applications, benefits, challenges, and impact on modern dentistry. A comprehensive review of existing literature and case studies was conducted to examine the effectiveness of teledentistry. Key aspects analyzed include digital imaging, AI (artificial intelligence)-assisted diagnostics, and cloud-based patient records, which facilitate early disease detection, reduce wait times, and minimize unnecessary visits. The review also highlights how teledentistry improves collaboration among dental professionals for better treatment planning. Challenges include legal barriers, data security concerns, and limited digital infrastructure. Standardized protocols and professional training are essential for effective implementation. Future advancements in AI and telecommunication technologies will further integrate teledentistry into standard practice, improving accessibility and efficiency in oral healthcare. Full article

Artificial Intelligence (AI) is rapidly transforming orthodontic care by providing personalized treatment plans that enhance precision and efficiency. This narrative review explores the current applications of AI in orthodontics, particularly its role in predicting tooth movement, fabricating custom aligners, optimizing treatment times, and offering real-time patient monitoring. AI’s ability to analyze large datasets of dental records, X-rays, and 3D scans allows for highly individualized treatment plans, improving both clinical outcomes and patient satisfaction. AI-driven aligners and braces are designed to apply optimal forces to teeth, reducing treatment time and discomfort. Additionally, AI-powered remote monitoring tools enable patients to check their progress from home, decreasing the need for in-person visits and making orthodontic care more accessible. The review also highlights future prospects, such as the integration of AI with robotics for performing orthodontic procedures, predictive orthodontics for early intervention, and the use of 3D printing technologies to fabricate orthodontic devices in real-time. While AI offers tremendous potential, challenges remain in areas such as data privacy, algorithmic bias, and the cost of adopting AI technologies. However, as AI continues to evolve, its capacity to revolutionize orthodontic care will likely lead to more streamlined, patient-centered, and effective treatments. This review underscores the transformative role of AI in modern orthodontics and its promising future in advancing dental care. Full article