Smart-Home Concept for Remote Monitoring of Instrumental Activities of Daily Living (IADL) in Older Adults with Cognitive Impairment: A Proof of Concept and Feasibility Study.

Assessment of instrumental activities of daily living (IADL) is essential for the diagnosis and staging of dementia. However, current IADL assessments are subjective and cannot be administered remotely. We proposed a smart-home design, called IADLSys, for remote monitoring of IADL. IADLSys consists of three major components: (1) wireless physical tags (pTAG) attached to objects of interest, (2) a pendant-sensor to monitor physical activities and detect interaction with pTAGs, and (3) an interactive tablet as a gateway to transfer data to a secured cloud. Four studies, including an exploratory clinical study with five older adults with clinically confirmed cognitive impairment, who used IADLSys for 24 h/7 days, were performed to confirm IADLSys feasibility, acceptability, adherence, and validity of detecting IADLs of interest and physical activity. Exploratory tests in two cases with severe and mild cognitive impairment, respectively, revealed that a case with severe cognitive impairment either overestimated or underestimated the frequency of performed IADLs, whereas self-reporting and objective IADL were comparable for the case with mild cognitive impairment. This feasibility and acceptability study may pave the way to implement the smart-home concept to remotely monitor IADL, which in turn may assist in providing personalized support to people with cognitive impairment, while tracking the decline in both physical and cognitive function.

Potential applications of artificial intelligence and machine learning on diagnosis, treatment, and outcome prediction to address health care disparities of chronic limb-threatening ischemia.

Chronic limb-threatening ischemia (CLTI) is the most advanced form of peripheral artery disease. CLTI has an extremely poor prognosis and is associated with considerable risk of major amputation, cardiac morbidity, mortality, and poor quality of life. Early diagnosis and targeted treatment of CLTI is critical for improving patient's prognosis. However, this objective has proven elusive, time-consuming, and challenging due to existing health care disparities among patients. In this article, we reviewed how artificial intelligence (AI) and machine learning (ML) can be helpful to accurately diagnose, improve outcome prediction, and identify disparities in the treatment of CLTI. We demonstrate the importance of AI/ML approaches for management of these patients and how available data could be used for computer-guided interventions. Although AI/ML applications to mitigate health care disparities in CLTI are in their infancy, we also highlighted specific AI/ML methods that show potential for addressing health care disparities in CLTI.

Electrical stimulation to regain lower extremity muscle perfusion and endurance in patients with post-acute sequelae of SARS CoV-2: A randomized controlled trial.

Muscle deconditioning and impaired vascular function in the lower extremities (LE) are among the long-term symptoms experienced by COVID-19 patients with a history of severe illness. These symptoms are part of the post-acute sequelae of Sars-CoV-2 (PASC) and currently lack evidence-based treatment. To investigate the efficacy of lower extremity electrical stimulation (E-Stim) in addressing PASC-related muscle deconditioning, we conducted a double-blinded randomized controlled trial. Eighteen (n = 18) patients with LE muscle deconditioning were randomly assigned to either the intervention (IG) or the control (CG) group, resulting in 36 LE being assessed. Both groups received daily 1 h E-Stim on both gastrocnemius muscles for 4 weeks, with the device functional in the IG and nonfunctional in the CG. Changes in plantar oxyhemoglobin (OxyHb) and gastrocnemius muscle endurance (GNMe) in response to 4 weeks of daily 1 h E-Stim were assessed. At each study visit, outcomes were measured at onset (t0 ), 60 min (t60 ), and 10 min after E-Stim therapy (t70 ) by recording ΔOxyHb with near-infrared spectroscopy. ΔGNMe was measured with surface electromyography at two time intervals: 0-5 min (Intv1 ) and: 55-60 min (Intv2 ). Baseline OxyHb decreased in both groups at t60 (IG: p = 0.046; CG: p = 0.026) and t70 (IG = p = 0.021; CG: p = 0.060) from t0 . At 4 weeks, the IG's OxyHb increased from t60 to t70 (p < 0.001), while the CG's decreased (p = 0.003). The IG had higher ΔOxyHb values than the CG at t70 (p = 0.004). Baseline GNMe did not increase in either group from Intv1 to Intv2 . At 4 weeks, the IG's GNMe increased (p = 0.031), whereas the CG did not change. There was a significant association between ΔOxyHb and ΔGNMe (r = 0.628, p = 0.003) at 4 weeks in the IG. In conclusion, E-Stim can improve muscle perfusion and muscle endurance in individuals with PASC experiencing LE muscle deconditioning.

Safety and efficacy of electrical stimulation for lower-extremity muscle weakness in intensive care unit 2019 Novel Coronavirus patients: A phase I double-blinded randomized controlled trial.

Background: Intensive care unit (ICU) prolonged immobilization may lead to lower-extremity muscle deconditioning among critically ill patients, particularly more accentuated in those with 2019 Novel Coronavirus (COVID-19) infection. Electrical stimulation (E-Stim) is known to improve musculoskeletal outcomes. This phase I double-blinded randomized controlled trial examined the safety and efficacy of lower-extremity E-Stim to prevent muscle deconditioning. Methods: Critically ill COVID-19 patients admitted to the ICU were randomly assigned to control (CG) or intervention (IG) groups. Both groups received daily E-Stim (1 h) for up to 14 days on both gastrocnemius muscles (GNMs). The device was functional in the IG and non-functional in the CG. Primary outcomes included ankle strength (Ankles) measured by an ankle-dynamometer, and GNM endurance (GNMe) in response to E-Stim assessed with surface electromyography (sEMG). Outcomes were measured at baseline, 3 and 9 days. Results: Thirty-two (IG = 16, CG = 16) lower extremities in 16 patients were independently assessed. The mean time between ICU admission and E-Stim therapy delivery was 1.8 ± 1.9 days (p = 0.29). At 3 days, the IG showed an improvement compared to the CG with medium effect sizes for Ankles (p = 0.06, Cohen's d = 0.77) and GNMe (p = 0.06, d = 0.69). At 9 days, the IG GNMe was significantly higher than the CG (p = 0.04, d = 0.97) with a 6.3% improvement from baseline (p = 0.029). E-Stim did not alter vital signs (i.e., heart/respiratory rate, blood saturation of oxygen), showed no adverse events (i.e., pain, skin damage, discomfort), nor interfere with ICU standard of care procedures (i.e., mechanical ventilation, prone rotation). Conclusion: This study supports the safety and efficacy of early E-Stim therapy to potentially prevent deterioration of lower-extremity muscle conditions in critically ill COVID-19 patients recently admitted to the ICU. If confirmed in a larger sample, E-Stim may be used as a practical adjunctive therapy. Clinical trial registration: [https://clinicaltrials.gov/], identifier [NCT04685213].

Mortality risk factors in kidney-transplanted patients with COVID-19: A systematic review and regression analysis.

BACKGROUND AND AIMS: The kidney transplant patients who receive immunosuppressive and specific medication may lead to different mortality risk factors between kidney transplant patients with COVID-19 and the general population. We aimed to provide a model predictor and a risk analysis of mortality in kidney transplant COVID-19 positive patients. METHODS: We performed our search using PubMed, MEDLINE, Web of Science, Scopus, and Google Scholar to identify English articles published from the beginning of December 2019 through August 2020. Excluded manuscripts had no full text, lacked information, were not the original article, or consisted of less than three cases. We gathered information about demographic information, comorbidities, COVID-19 symptoms, lung radiographic findings, history of medication therapy, and changes in the kidney maintenance therapy after confirming their COVID-19 on the data extraction forms. RESULTS: We found a total of 31 eligible articles. We set a 10% mortality rate as our cutoff point. The most common sign and symptoms were cough (53.22 [29.42]), dyspnea (50.80 [24.55]). In the bivariate analysis, fatigue (P = .04, OR of 0.92; 95% CI: 0.85-1.00), hypertension (P = .07, OR of 1.03; 95% CI: 1.00-1.07), and dyspnea (P = .08, OR of 1.04; 95% CI: 1.00-1.09) showed a statistically significant relationship with increases in mortality.In multivariate regression analysis, an independent association was only found between hypertension and mortality (P = .035; AOR of 1.064; CL: 1.004-1.127). CONCLUSION: Clinicians should pay special attention to modifiable risk factors for COVID-19 infection mortality, such as hypertension among kidney transplant patients, because it may be possible to decrease mortality by controlling these factors.