Chronic heart failure (CHF) leads to an excess of urgent ambulatory visits, recurrent hospital admissions, morbidity, and mortality regardless of medical and non-medical management of the disease. ...This excess of risk may be attributable, at least in part, to comorbid conditions influencing the development and progression of CHF. In this perspective, the authors examined and described the most common endocrine disorders observed in patients with CHF, particularly in individuals with reduced ejection fraction, aiming to qualify the risks, quantify the epidemiological burden and discuss about the potential role of endocrine treatment. Thyroid dysfunction is commonly observed in patients with CHF, and sometimes it could be the consequence of certain medications (e.g., amiodarone). Male and female hypogonadism may also coexist in this clinical context, contributing to deteriorating the prognosis of these patients. Furthermore, growth hormone deficiency may affect the development of adult myocardium and predispose to CHF. Limited recommendation suggests to screen endocrine disorders in CHF patients, but it could be interesting to evaluate possible endocrine dysfunction in this setting, especially when a high suspicion coexists. Data referring to long-term safety and effectiveness of endocrine treatments in patients with CHF are limited, and their impact on several “hard” endpoints (such as hospital admission, all-cause, and cardiovascular mortality) are still poorly understood.
Comprehensive screening for non-alcoholic fatty liver disease (NAFLD) may help prompt clinical management of fatty liver disease. A family history, especially of diabetes, has been little studied as ...a predictor for NAFLD. We characterized the cross-sectional relationship between a family history of type 2 diabetes (FHT2D) and NAFLD probability in 1185 diabetes-free Apulian (Southern-Italy) subjects aged > 20 years with overweight or obesity not receiving any drug or supplementation. Clinical data and routine biochemistry were analysed. NAFLD probability was defined using the fatty liver index (FLI). A first-degree FHT2D was assessed by interviewing subjects and assigning a score of 0, 1, or 2 if none, only one, or both parents were affected by type 2 diabetes mellitus (T2DM). Our study population featured most females (70.9%, N = 840), and 48.4% (N = 574) of the sample had first-degree FHT2D. After dividing the sample by a FHT2D, we found a higher BMI, Waist Circumference (WC), and diastolic blood pressure shared by FHT2D subjects; they also showed altered key markers of glucose homeostasis, higher triglyceride levels, and worse liver function. FLI scores were significantly lower in subjects without a first-degree FHT2D. After running logistic regression models, a FHT2D was significantly associated with the NAFLD probability, even adjusting for major confounders and stratifying by age (under and over 40 years of age). A FHT2D led to an almost twofold higher probability of NAFLD, regardless of confounding factors (OR 2.17, 95% CI 1.63 to 2.89). A first-degree FHT2D acts as an independent determinant of NAFLD in excess weight phenotypes, regardless of the age group (younger or older than 40 years). A NAFLD risk assessment within multidimensional screening might be useful in excess weight subjects reporting FHT2D even in the absence of diabetes.
Aging is often associated with a decline in physical function that eventually leads to loss of autonomy in activities of daily living (ADL). Walking is a very common ADL, important for main ...determinants of quality of life in older age, and it requires the integration of many physiological systems. Gait speed has been described as the ‘sixth vital sign’ because it is a core indicator of health and function in aging and disease. We reviewed original studies up to June 2020 that assessed frailty in both longitudinal and cross‐sectional observational studies, paying particular attention to how gait is measured in older population and how the gait parameter adopted may influence the estimated frailty models and the health‐related outcomes of the various studies (i.e. clinical, cognitive, physical, and nutritional outcomes). Eighty‐five studies met the search strategy and were included in the present systematic review. According to the frailty tools, more than 60% of the studies used the physical phenotype model proposed by Fried and colleagues, while one‐third referred to multi‐domain indexes or models and only 5% referred to other single‐domain frailty models (social or cognitive). The great heterogeneity observed in gait measurements and protocols limited the possibility to directly compare the results of the studies and it could represent an important issue causing variability in the different outcome measures in both clinical‐and population‐based settings. Gait appeared to be an indicator of health and function also in frail older adults, and different gait parameters appeared to predict adverse health‐related outcomes in clinical, cognitive, and physical domains and, to a lesser extent, in nutritional domain. Gait has the potential to elucidate the common basic mechanisms of cognitive and motor decline. Advances in technology may extend the validity of gait in different clinical settings also in frail older adults, and technology‐based assessment should be encouraged. Combining various gait parameters may enhance frailty prediction and classification of different frailty phenotypes.
•We analyzed 71 frailty tools for the inclusion of components/items associated with nutritional status.•Fifty-two tools (73 %) included at least one nutritional-related item and 22 (31 %) two or more ...items.•The assessment of nutritional status was mainly based on anthropometric measurements.•Methods for assessing nutritional status in the frailty context lack consistency.•The definition of nutritional items contributing to a possible operational definition of the nutritional frailty phenotype is needed.
Different methods have been proposed for the assessment of the nutritional status in frailty phenotypes. In the present narrative review article, we have summarized the number and specifications of nutritional items in existing frailty tools, in order to develop a possible means of assessment and operational definition of the nutritional frailty phenotype. In six different databases until December 2019, we searched for original articles regarding frailty tools (i.e., scales, indexes, scores, questionnaires, instruments, evaluations, screening, indicators), analyzing each tool regarding nutritional items. We identified 160 articles describing 71 frailty tools. Among the selected frailty tools, 54 were community-based (70 %), 17 hospital-based (22 %), 4 validated in long-term care institutions for older adults (LTCIOA) (5.1 %) and 2 validated in both community- and hospital-based settings, including LTCIOA (2.5 %). Fifty-two of these tools (73 %) included at least one nutritional item. Twenty-two (42 %) reported two or more nutritional items. The items were grouped in the following categories: A) anthropometric measurements, B) laboratory measurements, and C) other nutritional-related measurements. Anthropometric measurements stood out compared to all other items. Nutritional items are included in the majority of frailty tools, strengthening the concept that they may have a direct implication on an increased risk of adverse health-related outcomes in frail subjects. This supports the development of the concept of nutritional frailty as an independent frailty phenotype. Subsequent steps will be to assess the contribution of each nutritional item to a possible operational definition of nutritional frailty and define the items that may best identify this new frailty phenotype.
Introduction
Preventive nutritional management of frailty, a multidimensional intermediate status in the ageing process, may reduce the risk of adverse health‐related outcomes. We investigated the ...ability of a measure combining physical frailty with nutritional imbalance, defined as nutritional frailty, to predict all‐cause mortality over a period of up to 8 years.
Methods
We analysed data on 1,943 older adults from the population‐based ‘Salus in Apulia Study’. Physical frailty was operationalized using Cardiovascular Health Study criteria and cognitive frailty by combining physical frailty with cognitive impairment. A novel five‐item construct was built to assess the extent of nutritional imbalance identified with a machine learning algorithm. Cox models and Kaplan–Meier survival probability analyses of physical frailty, nutritional imbalance (two or more of the following: low body mass index, low skeletal muscle index, ≥2.3 g/day sodium intake, <3.35 g/day potassium intake and <9.9 g/day iron intake), cognitive frailty and the novel nutritional frailty phenotype (physical frailty plus nutritional imbalance) were applied to assess all‐cause mortality risk, adjusted for age, sex, education and multimorbidity.
Results
The overall prevalence of nutritional frailty was 4.52% (95% confidence interval, CI:3.55–5.44), being more frequent in males. Subjects with nutritional frailty were at higher risk for all‐cause mortality hazard ratio (HR):2.31; 95%CI:1.41–3.79 than those with physical frailty (HR:1.45,95% CI:1.0–2.02), nutritional imbalance (HR:1.39; 95%CI:1.05–1.83) and cognitive frailty (HR:1.06; 95%CI:0.56–2.01).
Conclusions
Efforts to identify, manage and prevent frailty should include the nutritional domain. The nutritional frailty phenotype may highlight major nutritional determinants that could drive survival and health trajectories in older adults.
Poor oral health is common among older adults and can impair essential activities of daily living and contribute to frailty. We did a systematic review of studies on the relationship between oral ...health factors and frailty among older adults (>60 years), consulting six different electronic databases for studies published from database inception to March 20, 2021. In total, 39 articles met the eligibility requirements, including 12 different indicators of poor oral health related to frailty, which we grouped in four different categories: oral health status deterioration; deterioration of oral motor skills; chewing, swallowing, and saliva disorders; and oral pain. Factors of oral health status deterioration (52%), in particular few remaining teeth (29%), were most frequently associated with frailty. Reduced oral motor skills (27%), especially masticatory function (9%), oral diadochokinesis (5%), occlusal force (7%), and chewing, swallowing, and saliva disorders (20%), especially chewing difficulties 11%), were less frequent but were similarly considered to be associated with frailty. Our findings could help to assess the contribution of each oral health item to a possible operational definition of this novel frailty phenotype, defined as an age-related gradual loss of oral function together with a decline in cognitive and physical functions.
The association between age-related hearing loss (ARHL) and physical or cognitive frailty has been poorly explored. These associations could define new perspectives for delaying frailty-related ...processes in older age.
To examine whether peripheral ARHL and age-related central auditory processing disorder (CAPD) are independently associated with physical or cognitive frailty.
This cross-sectional study analyzed registry data from December 31, 2014, on 1929 older (≥65 years) participants of the Salus in Apulia Study (Southern Italy) who underwent audiologic, physical, and neuropsychological assessment. Data analysis was performed from December 12, 2019, to January 4, 2020.
Prevalence of peripheral ARHL in older individuals with physical and/or cognitive frailty and those without frailty assessed using the Fried criteria (physical) and the Mini-Mental State Examination (cognitive). Multivariable logistic regression models were used to assess associations of audiologic variables with frailty phenotype.
Data from 1929 participants (mean SD age, 73.6 6.3 years; 974 male 50.5%) were eligible for the analyses. The prevalence of peripheral ARHL was higher in the physical frailty group (96 26.6%) than in the nonfrail group (329 21.0%) (difference, 5.61 percentage points; 95% CI, 0.63-10.59 percentage points) and in the cognitive frailty group (40 38.8%) than in the nonfrail group (385 21.1%) (difference, 17.75 percentage points; 95% CI, 8.2-27.3 percentage points). Age-related CAPD was more prevalent in the physical frailty group (62 17.2%) than in the nonfrail group (219 14.0%) (difference, 3.21 percentage points; 95% CI, -1.04 to 7.46 percentage points) and in the cognitive frailty group (28 27.2%) than in the nonfrail group (253 13.9%) (difference, 13.33 percentage points; 95% CI, 4.10-22.21 percentage points). In the multivariable models, age-related CAPD was associated with cognitive frailty in the fully adjusted model (odds ratio OR, 1.889; 95% CI, 1.094-3.311). There was also an inverse association between the unitary increase in Synthetic Sentence Identification With the Ipsilateral Competitive Message scores, indicating a lower likelihood of this disorder, and cognitive frailty (OR, 0.989; 95% CI, 0.988-0.999). Peripheral ARHL was associated with cognitive frailty only in the partially adjusted model (OR, 1.725; 95% CI, 1.008-2.937).
In this cross-sectional study of 1929 participants, age-related CAPD was independently associated with cognitive frailty. Whether the management of ARHL may help prevent the development of different frailty phenotypes or improve their clinical consequences should be addressed in longitudinal studies and, eventually, well-designed randomized clinical trials.
In subjects with nonalcoholic fatty liver disease (NAFLD), advanced fibrosis (AF) carries the highest risk of adverse liver-related events. To reduce the number of unnecessary biopsies, several ...noninvasive tools (NITs) for the risk stratification of fibrosis have been developed. We conducted this meta-analysis to assess the performance of the fibrosis-4 index (FIB-4) and NAFLD fibrosis scores (NFS), the 2 most common NITs, for the appropriate selection of subjects with AF for biopsy.
Four databases were searched until December 2020 (CRD42021224766). Original articles reporting data on the performance of FIB-4 and NFS, interpreted according to standard cutoffs in subjects with biopsy-proven NAFLD, were included. Separate data extractions were performed according to the lower cutoff, the higher cutoff, and the dual threshold approach. The numbers of subjects classified as true-negative, true-positive, false-negative, and false-positive were extracted. Summary operating points were estimated using a random-effects model.
Eighteen studies evaluating 12,604 subjects were included. Participants were adult outpatients with biopsy-proven NAFLD or nonalcoholic steatohepatitis. Overall, a weak-to-moderate performance was found for both scores. The head-to-head comparison showed FIB-4 to be associated with a higher performance in ruling in and NFS in ruling out AF in the single threshold approach, whereas, with the dual threshold approach, a lower prevalence of indeterminate findings was found for FIB-4.
This meta-analysis suggested that currently available NITs have a limited performance in identifying AF among subjects with NAFLD. Further studies are needed to optimize existing thresholds or develop new NITs.
Very low-calorie ketogenic diets (VLCKD) are widely employed in successful weight-loss strategies. Herein, we evaluated the efficacy and safety of a VLCKD on non-alcoholic fatty liver disease (NAFLD) ...and parameters commonly associated with this condition in overweight and obese subjects who did not take any drugs. This prospective, real-life study included thirty-three participants who followed a VLCKD for 8 weeks. NAFLD was diagnosed using transient elastography (FibroScan). Data on anthropometric measurements, bioimpedance analysis, and biochemical assays were gathered both before and after the dietary intervention. BMI (kg/m
) (from 33.84 ± 6.55 to 30.89 ± 6.38,
< 0.01), waist circumference (cm) (from 106.67 ± 15.51 to 98.64 ± 16.21,
< 0.01), and fat mass (Kg) (from 38.47 ± 12.59 to 30.98 ± 12.39,
< 0.01) were significantly lower after VLCKD. CAP (db/m), the FibroScan parameter quantifying fatty liver accumulation, showed a significant reduction after VLCKD (from 266.61 ± 67.96 to 223 ± 64.19,
< 0.01). After VLCKD, the fatty liver index (FLI), a benchmark of steatosis, also revealed a significant decline (from 62.82 ± 27.46 to 44.09 ± 31.24,
< 0.01). Moreover, fasting blood glucose, insulin, triglycerides, total cholesterol, LDL-cholesterol, ALT, γGT, and FT3 blood concentrations, as well as insulin resistance (quantified by HOMAIR) and systolic and diastolic blood pressure levels, were significantly lower after VLCKD (
< 0.01 for all the parameters). By contrast, HDL-cholesterol, 25 (OH) vitamin D, and FT4 blood concentrations were higher after VLCKD (
< 0.01 for all parameters). The variation (δ) of CAP after VLCKD did not show a correlation with the δ of any other parameter investigated in this study. We conclude that VLCKD is a helpful approach for NAFLD independent of changes in factors commonly associated with NAFLD (obesity, fat mass, insulin resistance, lipids, and blood pressure) as well as vitamin D and thyroid hormone levels.
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