Interactions between patterns of multimorbidity and functional status among hospitalized older patients: a novel approach using cluster analysis and association rule mining.

BACKGROUND: Multimorbidity (MM) is generally defined as the presence of 2 or more chronic diseases in the same patient and seems to be frequently associated with frailty and poor quality of life. However, the complex interplay between MM and functional status in hospitalized older patients has not been fully elucidated so far. Here, we implemented a 2-step approach, combining cluster analysis and association rule mining to explore how patterns of MM and disease associations change as a function of disability. METHODS: This retrospective cohort study included 3366 hospitalized older patients discharged from acute care units of Ancona and Cosenza sites of Italian National Institute on Aging (INRCA-IRCCS) between 2011 and 2017. Cluster analysis and association rule mining (ARM) were used to explore patterns of MM and disease associations in the whole population and after stratifying by dependency in activities of daily living (ADL) at discharge. Sensitivity analyses in men and women were conducted to test for robustness of study findings. RESULTS: Out of 3366 included patients, 78% were multimorbid. According to functional status, 22.2% of patients had no disability in ADL (functionally independent group), 22.7% had 1 ADL dependency (mildly dependent group), and 57.4% 2 or more ADL impaired (moderately-severely dependent group). Two main MM clusters were identified in the whole general population and in single ADL groups. ARM revealed interesting within-cluster disease associations, characterized by high lift and confidence. Specifically, in the functionally independent group, the most significant ones involved atrial fibrillation (AF)-anemia and chronic kidney disease (CKD) (lift = 2.32), followed by coronary artery disease (CAD)-AF and heart failure (HF) (lift = 2.29); in patients with moderate-severe ADL disability, the most significant ARM involved CAD-HF and AF (lift = 1.97), thyroid dysfunction and AF (lift = 1.75), cerebrovascular disease (CVD)-CAD and AF (lift = 1.55), and hypertension-anemia and CKD (lift = 1.43). CONCLUSIONS: Hospitalized older patients have high rates of MM and functional impairment. Combining cluster analysis to ARM may assist physicians in discovering unexpected disease associations in patients with different ADL status. This could be relevant in the view of individuating personalized diagnostic and therapeutic approaches, according to the modern principles of precision medicine.

Biomarkers of chronic kidney disease in older individuals: navigating complexity in diagnosis.

Chronic kidney disease (CKD) in older individuals is a matter of growing concern in the field of public health across the globe. Indeed, prevalence of kidney function impairment increases with advancing age and is often exacerbated by age-induced modifications of kidney function, presence of chronic diseases such as diabetes, hypertension, and cardiovascular disorders, and increased burden related to frailty, cognitive impairment and sarcopenia. Accurate assessment of CKD in older individuals is crucial for timely intervention and management and relies heavily on biomarkers for disease diagnosis and monitoring. However, the interpretation of these biomarkers in older patients may be complex due to interplays between CKD, aging, chronic diseases and geriatric syndromes. Biomarkers such as serum creatinine, estimated glomerular filtration rate (eGFR), and albuminuria can be significantly altered by systemic inflammation, metabolic changes, and medication use commonly seen in this population. To overcome the limitations of traditional biomarkers, several innovative proteins have been investigated as potential, in this review we aimed at consolidating the existing data concerning the geriatric aspects of CKD, describing the challenges and considerations in using traditional and innovative biomarkers to assess CKD in older patients, highlighting the need for integration of the clinical context to improve biomarkers' accuracy.

The emerging links between immunosenescence in innate immune system and neurocryptococcosis.

Immunosenescence refers to the age-related progressive decline of immune function contributing to the increased susceptibility to infectious diseases in older people. Neurocryptococcosis, an infectious disease of central nervous system (CNS) caused by Cryptococcus neoformans (C. Neoformans) and C. gattii, has been observed with increased frequency in aged people, as result of the reactivation of a latent infection or community acquisition. These opportunistic microorganisms belonging to kingdom of fungi are capable of surviving and replicating within macrophages. Typically, cryptococcus is expelled by vomocytosis, a non-lytic expulsive mechanism also promoted by interferon (IFN)-I, or by cell lysis. However, whereas in a first phase cryptococcal vomocytosis leads to a latent asymptomatic infection confined to the lung, an enhancement in vomocytosis, promoted by IFN-I overproduction, can be deleterious, leading the fungus to reach the blood stream and invade the CNS. Cryptococcus may not be easy to diagnose in older individuals and, if not timely treated, could be potentially lethal. Therefore, this review aims to elucidate the putative causes of the increased incidence of cryptococcal CNS infection in older people discussing in depth the mechanisms of immunosenscence potentially able to predispose to neurocryptococcosis, laying the foundations for future research. A deepest understanding of this relationship could provide new ways to improve the prevention and recognition of neurocryptococcosis in aged frail people, in order to quickly manage pharmacological interventions and to adopt further preventive measures able to reduce the main risk factors.

Falls may trigger body weight decline in nursing home residents.

OBJECTIVES: The effect of falls on changes in body weight is still unknown. This study investigated the extent to which falls can modify the course of body weight in nursing home residents, and aimed to identify the factors that might modulate this effect. METHODS: The sample included 132 residents aged ≥60 y who had experienced at least one fall after nursing home admission. Body weight was measured monthly in the 6 mo after the fall in the entire sample, and also in the 6 mo prefall in a subsample (n = 111). Sociodemographic and health data were obtained from medical records. Linear mixed models were used to estimate the average monthly changes in body weight after the fall in the total sample, and as a function of the sociodemographic and medical factors. RESULTS: Falls modified the course of body weight in the total sample (ß = -0.28, 95% confidence interval, -0.44 to -0.12, for the change in slope before and after fall) in all age classes and especially in individuals with severe cognitive impairment who received less-frequent informal visits (ß = -0.55, 95% confidence interval, -0.87 to -0.22). Individuals aged ≥90 y and those with severe cognitive impairment had a steeper monthly weight decline in the 6 mo postfall, of 0.23 and 0.35 kg greater, respectively, than their younger and cognitively healthier counterparts. CONCLUSIONS: Falls may trigger a body weight loss in nursing home residents, especially in the oldest old people and those with severe cognitive impairment who receive little support from informal caregivers. These findings highlight the importance of monitoring nutritional status of people who live in institutions after falls.

Increase in Frailty in Nursing Home Survivors of Coronavirus Disease 2019: Comparison With Noninfected Residents.

OBJECTIVES: Institutionalized older adults have a high prevalence of frailty and disability, which may make them more vulnerable to the negative consequences of coronavirus disease 2019 (COVID-19). We investigated the impact of COVID-19 on the level of frailty, physical, and cognitive performance in nursing home residents. DESIGN: Nested case-control study. SETTING AND PARTICIPANTS: The study included nursing home residents who were infected with COVID-19 (case group, n = 76), matched by age to a control group (n = 76). METHODS: Participants' sociodemographic and medical data were collected, and they were also assessed for physical function (handgrip and walking speed), cognitive performance (Mini-Mental State Examination) and frailty (Frail-NH scale) before the first wave of the COVID-19 pandemic (October to December 2019, pre-COVID-19) and after (June to July 2020, post-COVID-19). COVID-19 symptoms and clinical course were recorded for the cases. RESULTS: Between the pre- and post-COVID-19 assessments, we found a 19% greater deterioration in handgrip, a 22% greater decrease in walking speed, and a 21% greater increase in Frail-NH scores in cases compared with controls. In both cases and controls, on the other hand, there was a significant 10% decrease in Mini-Mental State Examination scores over the study period. Multivariable logistic regression showed that COVID-19 survivors had a 4-fold increased chance of developing frailty compared with controls (odds ratio 4.95, 95% confidence interval 1.13-21.6, P = .03), but not cognitive decline. CONCLUSIONS AND IMPLICATIONS: COVID-19 can accelerate the aging process of institutionalized older adults in terms of physical performance and frailty by around 20%. However, we found similar levels of decline in cognitive performance in both cases and controls, likely because of the burden of social isolation and containment measures on neuropsychological health.