Geriatrics Service, Getafe University Hospital, Getafe, Spain.
Intelligent Robotics Lab, Universidad Rey Juan Carlos, Fuenlabrada, Spain.
J Med Internet Res. 2024 Oct 22;26:e58312. doi: 10.2196/58312.
Frailty represents a state of susceptibility to stressors and constitutes a dynamic process. Untreated, this state can progress to disability. Hence, timely detection of alterations in patients' frailty status is imperative to institute prompt clinical interventions and impede frailty progression. With this aim, the FACET (Frailty Care and Well Function) technological ecosystem was developed to provide clinically gathered data from the home to a medical team for early intervention.
The aim of this study was to assess whether the FACET technological ecosystem prevents frailty progression and improves frailty status, according to the frailty phenotype criteria and Frailty Trait Scale-5 items (FTS-5) at 3 and 6 months of follow-up.
This randomized clinical trial involved 90 older adults aged ≥70 years meeting 2 or more Fried frailty phenotype criteria, having 4 or more comorbidities, and having supervision at home. This study was conducted between August 2018 and June 2019 at the geriatrics outpatient clinics in Getafe University Hospital and Albacete University Hospital. Participants were randomized into a control group receiving standard treatment and the intervention group receiving standard treatment along with the FACET home monitoring system. The system monitored functional tests at home (gait speed, chair stand test, frailty status, and weight). Outcomes were assessed using multivariate linear regression models for continuous response and multivariate logistic models for dichotomous response. P values less than .05 were considered statistically significant.
The mean age of the participants was 82.33 years, with 28% (25/90) being males. Participants allocated to the intervention group showed a 74% reduction in the risk of deterioration in the FTS-5 score (P=.04) and 92% lower likelihood of worsening by 1 point according to Fried frailty phenotype criteria compared to the control group (P=.02) at 6 months of follow-up. Frailty status, when assessed through FTS-5, improved in the intervention group at 3 months (P=.004) and 6 months (P=.047), while when the frailty phenotype criteria were used, benefits were shown at 3 months of follow-up (P=.03) but not at 6 months.
The FACET technological ecosystem helps in the early identification of changes in the functional status of prefrail and frail older adults, facilitating prompt clinical interventions, thereby improving health outcomes in terms of frailty and functional status and potentially preventing disability and dependency.
ClinicalTrials.gov NCT03707145; https://clinicaltrials.gov/study/NCT03707145.
衰弱代表一种易受压力源影响的状态,是一个动态的过程。如果不加以治疗,这种状态可能会发展为残疾。因此,及时发现患者衰弱状态的变化对于及时进行临床干预和阻止衰弱进展至关重要。为此,开发了 FACET(虚弱护理和功能良好)技术生态系统,以便将家庭中临床收集的数据提供给医疗团队,以便进行早期干预。
本研究旨在评估 FACET 技术生态系统是否能根据虚弱表型标准和 Frailty Trait Scale-5 项(FTS-5),在 3 个月和 6 个月的随访中,预防虚弱进展并改善虚弱状态。
这是一项随机临床试验,纳入了 90 名年龄≥70 岁、符合 2 项或以上 Fried 虚弱表型标准、患有 4 种或以上合并症且在家中接受监护的老年人。该研究于 2018 年 8 月至 2019 年 6 月在 Getafe 大学医院和 Albacete 大学医院的老年病门诊进行。参与者被随机分配到对照组(接受标准治疗)和干预组(接受标准治疗和 FACET 家庭监测系统)。该系统监测家庭中的功能测试(步态速度、椅子站立测试、虚弱状态和体重)。使用多变量线性回归模型评估连续反应,使用多变量逻辑模型评估二分类反应。P 值小于 0.05 被认为具有统计学意义。
参与者的平均年龄为 82.33 岁,28%(25/90)为男性。与对照组相比,干预组在 6 个月的随访中,FTS-5 评分恶化的风险降低了 74%(P=.04),根据 Fried 虚弱表型标准恶化 1 分的可能性降低了 92%(P=.02)。与对照组相比,干预组在 3 个月(P=.004)和 6 个月(P=.047)时 FTS-5 评估的虚弱状态得到改善,而根据虚弱表型标准,在 3 个月时(P=.03),但在 6 个月时(P=.06),益处得到了显示。
FACET 技术生态系统有助于早期识别虚弱和虚弱前期老年人的功能状态变化,从而促进及时的临床干预,从而改善虚弱和功能状态方面的健康结果,并有可能预防残疾和依赖。
ClinicalTrials.gov NCT03707145;https://clinicaltrials.gov/study/NCT03707145。