Global population is progressively aging (1, 2), and one of the roles that geriatric medicine has is to provide quality care for all these people (3). In fact, even if aging can be slowed down by lifestyle, it cannot be stopped (4, 5). A noble aim could be to early intercept mild deficits, and Comprehensive Geriatric Assessment (CGA) represent the specialistic tool which has the objective of achieving that (3), finding out how much support an elderly person needs for day-to-day living and helping to diagnose any health conditions they may have, by enquiring cognitive impairment, mood deflection, functional and nutritional status, other than comorbidities and quality of life (6–9).

Nowadays, in particular, it is used to assess “frailty”, a common medical word, whose interpretation is yet not univocal (10–12). It continues the literature continues to discuss “phenotypes” rather than “definitions”: the phenotypic model proposed by Fried et al. (13, 14) characterize frailty as a clinical syndrome with 3 or more criteria among weight loss, exhaustion, reduced grip strength, reduced walking speed and physical activity. Anyway, it is known that a categorization of pre-frail and frail people is necessary to stratify different needs for intervention (15). The concept of frailty is led to the concept of multimorbidity, which does not have to be considered as a “long list of illnesses”, but rather an indicator of burden (16), mortality (17), reduced quality of life (18) for elderly people. Anyways, multimorbidity is indeed associated with the most common geriatric syndromes, such as cognitive impairment and sarcopenia, and age-related pathologies (19–21). Among them, in cardiovascular medicine, one of the most represented in elderly is Atrial Fibrillation (AF). This common condition is an arrythmia which can be due to a number of factors including genetics, but also aging and lifestyle (22). It is associated with higher risk of hospitalization and higher mortality in elderly (23, 24).

The study included 1981 people aged 65 years or more. The propensity score model brought a final sample of 660 subjects, divided in two groups (AF and non-AF), of whom 414 women (62.7%), with average age of 81.2 years (SD: 6.5) (Figure 1).

Table 1 summarizes the scores achieved by the two groups in every CGA tests, and the most common co-morbidities and drugs taken.

We found that history of coronary heart disease (22.1 vs. 14.5%, p = 0.0009) and Chronic Obstructive Pulmonary Disease (COPD) (29.4 vs. 18.5%, p = 0.0001) were significantly more common in AF-group, as well as the assumption of Vitamin K Antagonists (VKA) (45.5 vs. 2.4%, p < 0.0001), Direct Oral Anti-Coagulants (DOAC) (26.7 vs. 1.2%, p < 0.0001), Beta Blockers (48.8 vs. 23%, p < 0.0001), and Proton-Pump Inhibitors (PPI) (56.4 vs. 48.2%, p = 0.0239), while antiplatelet drugs were more commonly taken by non-AF group (24.8 vs. 56.4%, p < 0.0001, of whom, respectively, 15 and 58% in secondary prevention). About CGA, CCI (6.6 vs. 6.2, p = 0.0222), FRAIL scores (2.9 vs. 2.6, p = 0.0109), and number of drugs taken (8.3 vs. 7.2, p = 0.0002) were higher in AF than in non-AF group.

Following the aims of the study, we analyzed the data resulting from 647 patients' (98%) follow-up (missing data in 1 patient of AF-group, and 12 patients of non-AF group). The Kaplan-Meier curves (Figure 2) showed a cumulative 58.6% 5-years exitus. According to logrank test, survival probability—calculated at 0, 1, 2, 3, 4, and 5 years—was significantly higher in non-AF than in AF group (χ² = 4.4278, p = 0.0354) (Table 2). Non-AF group showed HR: 1.27 (95% CI: 1.01–1.58) for survival.

In order to explain the clinical significance of what above reported, we divided CCI scores in three groups (mild severity of comorbidities, scores: 1–2; moderate, scores: 3–4; severe, scores: ≥5), and FRAIL scores in three groups (non-frail, scores: 0; pre-frail, scores: 1–2; frail: ≥3).

As in Figure 3, a moderate severity of comorbidities was found in 53 AF-patients, and 77 non-AF-patients, and severe in 277 AF-patients and 250 non-AF-patients (χ²: 8.814, p = 0.0122); eighty-one AF-patients and 108 non-AF-patients were pre-frail, and 219 AF-patients and 189 non-AF-patients were frail (χ²: 6.206, p = 0.0449). Moreover, CCI and FRAIL scores were mutually weakly correlated (r = 0.31, p < 0.0001), and very weakly correlated with AF (CCI-AF r = 0.108, p = 0.0005; FRAIL-AF r = 0.088, p = 0.0231). The collinearity among the other variables (CGA domains, co-morbidities, drugs taken) was also assessed, the large part of which was not significant, and, among the significant ones, only one showed r > 0.8 (PPT-POMA, r = 0.813, p < 0.0001) and two > 0.7 (ADL-PPT, r = 0.73, p < 0.0001; ADL-POMA, r = 0.725, p < 0.0001).

AF was then considered as dependent variable in a multivariate logistic regression; CGA domains (cognitive status, mood, autonomy, physical performances, nutritional status, comorbidity burden, and frailty), co-morbidities and drugs taken were considered independent variables (Table 3). The Area Under the ROC Curve (AUC) was 0.808, with a standard error of 0.0203 and a 95% C.I. from 0.769 to 0.844. The regression model demonstrated that the presence of AF was independently associated with a history of coronary heart disease (OR: 2.12, C.I.: 1.13–3.96) and cerebrovascular disease (OR: 1.64, C.I.: 1.01–2.67), with the assumption of Beta Blockers (OR: 3.39, C.I.: 2.09–5.52), and antiplatelets (OR: 0.09, C.I.: 0.05–0.15), and with the amount of drugs taken (OR: 1.12, C.I.: 1.05–1.19).

The increasing elderly population is often frail and multimorbid (10), and CGA (6) can early recognize and categorize such common conditions. Among age-related pathologies, one of the most represented is AF, associated with higher risk of hospitalization and mortality (23, 24).

The primary aim of our study was to compare the frailty status and the comorbidity burden with the presence/absence of AF in a population of subjects aged 65 years or older. The secondary aim was to consider which domains, comorbidities and drugs were independently associated with AF.

Our data demonstrated that severe comorbidity burden (p = 0.01) and frailty status (p = 0.04) were significantly more common in patients with AF than without AF, although their poor collinearity, and such difference did not depend on gender and age, according to the case-control matching performed in our sample. Moreover, non-AF patients were more likely to survive (HR: 1.27) than AFs. These results are consistent with the literature (33–36), and show AF being a disease of serious impact on global health status in elderly patients. In our sample, overall mortality was higher compared to the literature (37), in accordance with our inclusion criteria, and the ensuing abovementioned burden.

Then, we performed a multivariate analysis to characterize the weight of different co-variates on AF. We did not include anticoagulant drugs assumption because of the obvious association with AF, as can be also seen by χ² analysis (p < 0.0001). The regression model showed an independent association with coronary and cerebrovascular diseases (ORs: 2.12 and 1.64, respectively), consistently with the literature and with AF's pathophysiology, likewise to Beta Blockers intake (OR: 3.39). A data so far never emerged in the scientific literature (38, 39) was the inverse association between AF and antiplatelets: our data showed that patients without AF have 91% more chance of taking such drugs. To deepen this result, we must consider that, in AF group, 34% of the patients with a history of coronary or cerebrovascular disease did not take any antiplatelet drugs, while only 9.5% of non-AF group did not take them. Moreover, 10% of AF group and 23.5% of non-AF group was taking antiplatelets in primary prevention (40). We can thus highlight the possible tendency to overprescribe (41, 42) such drugs in primary prevention slightly more in absence than in presence of AF, and, on the other hand, the reduced tendency to prescribe them in presence of AF, because of the known increased risk of bleeding (43, 44).

Our study demonstrates that elderly people with AF are frailer, have more severe comorbidities, and take more drugs, in particular beta blockers, and besides have a higher probability to die. Furthermore, it denounces a dangerous antiplatelets underprescription, that might be carefully considered in such population with additional thrombotic risk factors (45).

Obviously, we recognize the study presents some limitation: firstly, its design did not allow to explore causality among the outcomes and the independent variables; moreover, it is monocentric, and it did not take into account potential geographical differences on FA management; lastly, it did not consider the causes of death, which would have been useful in order to enrich the strength of the results.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by Institutional Review Board (or Ethics Committee) of the University of Cagliari. The patients/participants provided their written informed consent to participate in this study.

FS, AP, and AM were principal investigators and contributed to the study design and data analyses. FS, AP, GD, and MS contributed to data collection. FS and AM contributed to the interpretation of the findings and wrote the manuscript. All authors read and approved the final version of the manuscript.