Context: Both frailty and multimorbidity are strong predictors of clinical endpoints for older people. In Italy, the interventions targeting chronicity are mainly based on the treatment of diseases: sufficient epidemiological literature is available about these strategies. Less is known about the territorial distribution of the frailty status.Aims: To estimate the prevalence of frailty in older people (65+) and to evaluate the relationship between frailty and multimorbidity.Methods and material: A group of general practitioners working in Veneto (Italy) was enrolled on a voluntary basis. Older individuals were both community dwelling and institutionalized patients, that is, the older people normally followed by Italian general practitioners. A centrally randomized sample was extracted from the pool of physician-assisted elderly. Each doctor evaluated the frailty status through the CSHA Clinical Frailty Scale and the multimorbidity status through the Charlson score (Frailty = CSHA Clinical Frailty Scale’s score >4; serious multimorbidity = Charlson score ≥4). Prevalence and its confidence interval (CI) 95% were evaluated through the Agresti’s method for proportions. The relation between frailty and multimorbidity was studied through a logistic regression model adjusted for age and sex.Results: Fifty-three physicians were enrolled, whose population of elderly individuals (N = 82919) was highly representative of the population of Veneto. The prevalence of frailty in the randomized sample of 2407 older people was 23.18% (CI 95%: 21.53%–24.91%). Sex was shown to be a strong predictor of frailty (female status OR = 1.58 p < .0001) and multimorbidity was shown to be an independent predictor only for individuals <85 years of age.Conclusions: In Veneto, more than 20% of elderly people are frail. Physicians should pay close attention to frailty and multimorbidity because both are important prognostic factors toward clinical endpoints relevant to territorial care. The CSHA Clinical Frailty Scale (easy and quick) should become part of their professional routine.
Federica Braga and coworkers [1] stated recently that hyperuricemia shows to be an independent predictor of coronary heart disease (CHD) risk (RR CHD = 1.206 [1.066-1.364]; RR CHD death = 1.209 [1.003-1.457]), mainly for the results found in women. That message seems to be of great importance: if it is true, the treatment of hyperuricemia should be included in the landscape of the therapeutic strategies to reduce the coronary risk. To ascertain the methodologic validity and robustness of that work, we considered it as a critical appraisal of some methodological aspects.In our approach, (a) we evaluated the overall quality of that systematic review through the AMSTAR checklist [2]; (b) we recovered the nine studies selected by Braga and colleagues [1] in order to repeat the meta-analysis and quantified the heterogeneity through I 2 statistic [3]; (c) we launched new subgroup and sensitivity and metaregression analyses in order to better explore the heterogeneity, considering the following as potential effect modifiers: gender, number of CHD covariates used in the adjustment models (i.e. age, BMI, total cholesterol or LDL-cholesterol or presence of dyslipidemia, blood pressure values or presence of hypertension, smoke, glucose values or presence of diabetes) and lack of nutritional information; (d) we estimated the prevalence of metabolic syndrome in single-trial samples using an Italian epidemiological research as reference sample [4]; (e) we investigated the quality of included trials and their risk of bias through the ACROBAT Cochrane checklist [5]; and (f) we used a generalized least-squares regression model to inspect some dose-response effect [6] both at trial level and with a doseresponse meta-analysis; the goodness of fit was explored with a χ 2 -test [7]. We restricted all our described analyses to the end point 'CHD incidence'; their methodological details are available in the online Supplementary material. What were our results?1. The quality of the meta-analysis assessed with the AMSTAR checklist [2] appears to be medium/low: only 4/11 items were fully satisfied, 3/11 not satisfied and 4/11 uncertain. 2. The metaregression (Figure 1) demonstrates that the number of confounders could be an important cause of heterogeneity, with the risk ratio of CHD associated to hyperuricemia decreasing by 13% for each covariate added to the model (p = 0.056). The subgroup analysis using the number of covariates as effect modifier coherently indicates that the role of hyperuricemia tends to disappear in the best adjusted models (test of interaction, p = 0.056). Notably, the trials that were not adjusted for nutritional status [8][9][10]
The relationship between LDL-C lowering and cardiovascular events has not showed any significant association (and even a tendency toward harm), challenging the "lower the better" theory. A separate meta-analysis of trials recruiting familial hypercholesterolemia patients has showed a tendency to harm for all outcomes with PCSK9 antibodies. Therefore, at the moment, the data available from randomized trials does not clearly support the use of these antibodies.
Context: A recent meta-analysis (Bonora and coll.) reports benefits on death-risk for Italian diabetic patients mainly followed by the diabetic clinics of the National Health Service. Aims: A) to do a critical appraisal of the meta-analysis by Bonora and coll. B) to verify its results conducting a controlled cohort study based on clinical records of a primary care setting. Methods: (A) We evaluated the meta-analysis by Bonora through AMSTAR II checklist and the trials recruited in the review through ROBINS-I tool. (B) We analysed a cohort of diabetes 2 patients living in Veneto (Italy) and followed from 1/1/2009 to 12/31/2017 to compare the risk of death of a control group (i.e. never followed by specialists) with that of another two groups (i.e. respectively, followed by one specialist visit or by at least two visits in the last three years). We used a time-to-event approach (Cox model) for the main analysis; complementary designs were also tested (Restricted design and Matched design). Statistical adjustments were made both through Multivariate Cox regression and Propensity score. For the adjustments, the covariates considered were: age, sex, severity of diabetes, comorbidity, laboratory values, duration of diabetes and drugs use. Results: (A) The meta-analysis by Bonora shows to be affected by serious pitfalls (B) A cohort of 6530 diabetic patients (none visit: n=3441; one visit: n=947; two or more visits: n=2142) was followed for a mean of 7.32y. Main multivariate analysis was not able to demonstrate any difference in mortality between groups exposed or not exposed to specialist advice: one visit HR=1.01 (0.98-1.03); two or more visits HR=1.12 (0.88-1.43). These results were confirmed by all other analytical approaches. Conclusion: Mortality in diabetes2 is not influenced by specialist consultant. Our results differ by those reported by the meta-analysis because of our better adjustment for prognostic and confounding factors. Most of diabetes 2 patients should be entrusted with confidence to primary care facilities.
Context: In Italy, little is known about the territorial distribution of the frailty status. Aims: To compare frailty- and multimorbidity-prevalence in the elderly population of two Italian regions. Methods: This study examined randomized samples of elderly (both community dwelling and institutionalized) assisted by general practitioners. Frailty was evaluated through the CSHA-Scale, multimorbidity through the Charlson-Score. The relation between frailty and multimorbidity was studied through a logistic model. Both crude and standardized prevalences were calculated. Results: One hundred and sixteen physicians assisted 176,503 patients highly representative of Italian people. In a randomized sample of 4,531 older people, the sex–age-standardized prevalence of Frailty (standard population: Italy) was 25.74% (24.63–26.85%). Age-standardized prevalence for males was 20.08% (18.46–21.71%) and 30.00% (28.54–31.57%) for females. Using the sex–age-standardization pooled sample, the prevalence of frailty was significantly higher in Sicily than Veneto (28.74% [27.03–30.46%] vs 22.30% [20.94–23.67%]. This study did not find differences in the prevalence of multimorbidity: Veneto 20.76% (19.21–22.31%); Sicily 22.05% (20.33–23.77%). Both “to be female” and “to live in Sicily” were shown to be predictors of frailty OR for being female = 1.64 (1.42–1.88); OR for living in Sicily = 1.27 (1.11–1.46). Multimorbidity was an independent frailty-predictor only for those aged < 85: OR of Charlson Index ≥ 4 for ages < 85 = 3.44 (2.88–4.11), OR for ages ≥ 85 = 1.44 (0.97–2.12). Limitations: (1) This study considered patients assisted by doctors, not a random sample of the general population. (2) The cross-sectional nature of the study limits the interpretation of the relationships between frailty and multi-morbidity. (3) Few covariates were available for our multivariate models. Conclusions: More than 1/4 of elderly persons are shown to be frail (1/5 of males and 1/3 of females). Frailty is more frequent in Sicily, while multimorbidity does not differ between the two regions. This could be due to regional differences in the organization of care networks dedicated to elderly patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.