Abstract
Objective
To explore the influence of nutritional status on adverse clinical events in elderly patients with nonvalvular atrial fibrillation.
Methods
This retrospective observational cohort study included 196 patients, 75–102‐years‐old, with nonvalvular atrial fibrillation, hospitalized in our hospital. The nutritional status was assessed using Mini‐Nutritional Assessment—Short Form (MNA‐SF). Patients with MNA‐SF scores of 0–11 and 12–14 were included in the malnutrition and nonmalnutrition groups, respectively.
Results
The average age of the malnutrition group was higher than that of the nonmalnutrition group, and the levels of body mass index (BMI), hemoglobin (HGB), and albumin (ALB) were significantly lower than those of the nonmalnutrition group, with statistical significance (p < .05). The incidence of all‐cause death in the malnutrition group was higher than that in the nonmalnutrition group (p = .007). Kaplan–Meier curve indicated that malnutrition patients have a higher risk of all‐cause death (log‐rank test, p = .001) and major bleeding events (p = .017). Multivariate Cox proportional hazard regression analysis corrected for confounders showed that malnutrition was an independent risk factor of all‐cause death (HR = 1.780, 95%CI:1.039–3.050, p = .036). The malnutrition group had a significantly high incidence of major bleeding than the nonmalnutrition group (p = .026), and there was no significant difference in the proportion of anticoagulation therapy (p = .082) and the incidence of ischemic stroke/systemic embolism (p = .310) between the two groups.
Conclusions
Malnutrition is an independent risk factor of all‐cause death in elderly patients with atrial fibrillation. The incidence of major bleeding in malnourished elderly patients with atrial fibrillation is high, and the benefit of anticoagulation therapy is not obvious.
Keywords: all‐cause death, atrial fibrillation, bleeding, elderly, malnutrition
The incidence of major bleeding in malnourished elderly patients with atrial fibrillation is high, and the benefit of anticoagulation therapy is not obvious. Evaluating the nutritional status of elderly patients with atrial fibrillation can help judge patients' prognosis and choose anticoagulation strategies.
1. INTRODUCTION
Atrial fibrillation is one of the common cardiovascular diseases in the elderly people, most of which is nonvalvular atrial fibrillation. The incidence of atrial fibrillation increases with age (Bencivenga et al., 2020). Reportedly, the prevalence of atrial fibrillation in hospitalized patients aged ≥75 years is 34%, which increases the risk of death by 17% compared with nonatrial fibrillation patients (de Terwangne et al., 2022). Atrial fibrillation can cause ischemic stroke/systemic embolism, myocardial ischemia, heart failure, and other complications, resulting in death and disability. Identifying patients with atrial fibrillation with a high risk of adverse clinical events and actively intervening would improve their prognosis.
The proportion of malnutrition and nutritional risk among hospitalized elderly patients can reach 30–50% (Liu et al., 2022), and the nutritional risk increases with age (Koren‐Hakim et al., 2016). Moreover, malnutrition significantly increases the risk of death in elderly inpatients, raises the readmission rate within 90‐days and prolongs the hospitalization time of patients (Liu et al., 2022). Old patients with atrial fibrillation suffer from malnutrition. Complications, such as cardiac insufficiency and stroke caused by atrial fibrillation, can decline the patients' physical function and activity ability, thus affecting their nutritional intake and leading to malnutrition.
Previous studies have shown that malnutrition is an independent risk factor for adverse clinical events in elderly patients with cardiovascular diseases, such as heart failure and acute myocardial infarction (Keskin et al., 2017; Sze et al., 2018). The study on the nutritional status of elderly patients with atrial fibrillation and its correlation with clinical prognosis is limited, and the nutritional assessment tools used in previous studies are complicated. In this study, a simple tool, Mini‐Nutritional Assessment—Short Form (MNA‐SF), was used to evaluate the nutritional status of elderly patients with atrial fibrillation and explore the influence of nutritional status on adverse clinical events of elderly patients with atrial fibrillation.
2. MATERIALS AND METHODS
2.1. Research design and subjects
This retrospective, observational, cohort study included elderly patients with nonvalvular atrial fibrillation hospitalized in the Department of Geriatrics, Affiliated Beijing Friendship Hospital, Capital Medical University, Beijing, China, from May 2017 to July 2020. Selection criteria: age ≥75‐years‐old and electrocardiogram or Holter electrocardiogram indicating atrial fibrillation. Exclusion criteria: (1) rheumatic valve disease; (2) artificial valve replacement; (3) mitral valvuloplasty; and (4) in the terminal stage of severe disease, the survival time is <1 month. This study protocol conformed to the tenets of Helsinki Declaration and was approved by the Bioethics Committee of Beijing Friendship Hospital Capital Medical University.
2.2. Data acquisition
2.2.1. Common data
Including gender, age, body mass index (BMI = weight/height2 [kg/m2]), basic diseases (chronic heart failure, prior myocardial infarction, diabetes, hypertension [systolic blood pressure >160 mmHg], malignant tumors, chronic obstructive pulmonary disease [COPD]), and use of anticoagulants (warfarin and non‐vitamin K antagonist oral anticoagulant).
2.2.2. Nutritional status assessment
The patients' nutritional status was assessed using MNA‐SF (Kaiser et al., 2009). There are 6 items, including appetite loss, weight loss, mobility, stress/acute disease, dementia/depression, BMI/calf circumference. The max score is 14 points. The MNA‐SF score of 12–14 is normal, 8–11 is risk of malnutrition, and 0–7 is malnourishment. In this study, patients with MNA‐SF score of 0–11 comprised the malnutrition group, and patients with an MNA‐SF score of 12–14 comprised the nonmalnutrition group.
2.2.3. Atrial fibrillation‐related score
The CHA2DS2‐VASc score (congestive heart failure [1 point], hypertension [1 point], age >75 years [2 points], diabetes [1 point], history of stroke/systemic embolism/transient ischemic attack [2 points], age >65 years [1 point], female sex [1 point], and vascular disease [1 point], total score ≥2 points, anticoagulation therapy is recommended) is used to evaluate the risk of stroke/systemic embolism in patients with atrial fibrillation (Lip et al., 2010). HAS‐BLED score (hypertension [1 point], abnormal renal/liver function [1 point], stroke [1 point], bleeding history or predisposition [1 point], labile international normalized ratio [INR] [1 point], elderly [age >65 years] [1 point], drugs or alcohol concomitantly [1 point], and a total score ≥3 points indicates a high risk of bleeding) was used to assess the bleeding risk of patients (Pisters et al., 2010).
2.2.4. Laboratory examination
Hemoglobin (HGB), albumin (Alb), creatinine (Cr), fasting blood glucose (FPG), glycosylated hemoglobin (HbA1c), total cholesterol (TC), triglyceride (TG), high‐density lipoprotein cholesterol (HDL‐C), and low‐density lipoprotein cholesterol (LDL‐C) were collected. The estimated glomerular filtration rate (eGFR) was calculated using the formula of Chronic Kidney Disease Epidemiology Collaboration (CKD‐EPI).
2.2.5. Clinical outcomes
The endpoints were clinical adverse events, including all‐cause death, ischemic stroke/systemic embolism, major bleeding, acute myocardial infarction, and acute heart failure. Ischemic stroke was confirmed with concomitant imaging studies of the brain, including computed tomography or magnetic resonance imaging. Systemic embolism was defined as thromboembolism outside the brain. Major bleeding was defined as bleeding requiring hospitalization, a transfusion of at least 2 units of packed red cells, or bleeding based on the definition of the International Society on Thrombosis and Hemostasis (Schulman & Kearon, 2005). Clinical adverse events were obtained through telephone follow‐up and medical records, and the follow‐up ended on March 30, 2022.
2.3. Statistical methods
The SPSS 22.0 statistical software (IBM Corp, Armonk, NY, USA) was used for statistical analysis. The measurement data conforming to the normal distribution were expressed by (mean ± standard deviation [SD]), and between two groups were compared by Student's t‐test. The measurement data that did not conform to the normal distribution were represented by (median [P25, P75]), and the Mann–Whitney U test was used for comparison between the two groups. These data were expressed in percentages, and the comparison between the two groups was carried out by chi‐squared test. The survival curve was drawn using Kaplan–Meier method and compared using the log‐rank test. Univariate and multivariate Cox proportional hazard regression was used to analyze the influencing factors of adverse events in elderly patients with atrial fibrillation and determine whether malnutrition was an independent risk factor of adverse events in elderly patients with atrial fibrillation. Differences with a 2‐tailed p‐value of <.05 were considered statistically significant.
3. RESULTS
3.1. Common data
A total of 196 patients aged 75–102 (average: 86.7 ± 6.1 years) were included in this study. The cohort consists of 136 (69.4%) males and 60 (30.6%) females. According to the MNA‐SF score, the patients were divided into two groups: 97 subjects in the malnutrition group (49.5%), including 59 with MNA‐SF score of 8–11 and 38 with MNA‐SF score of 0–7, and 99 subjects in the nonmalnutrition group (50.5%). The follow‐up time was 2–57 (average: 29.3 ± 16.1) months. The age of patients with malnutrition was higher than that of patients without malnutrition (88.80 ± 5.58 vs. 85.0 ± 6.0, p < .001), and HGB, Alb, and BMI were significantly lower than those of patients without malnutrition (p < .05). The CHA2DS2‐VASc score (4.9 vs. 4.7, p = .320) and HAS‐BLED score (3.0 vs. 2.6, p = .065) of the malnutrition group were higher than that of the nonmalnutrition group, and the proportion of anticoagulation treatment was lower than that of the nonmalnutrition group (14.4% vs. 24.2%, p = .082) (Table 1).
TABLE 1.
Comparison of baseline data of patients with and without malnutrition.
| Items | Malnutrition (n = 97) | Nonmalnutrition (n = 99) | p‐Values |
|---|---|---|---|
| Age (years) | 88.8 ± 5.6 | 85.0 ± 6.0 | <.001 |
| Male [n (%)] | 63 (65.0%) | 73 (73.7%) | .182 |
| AF phenotypes | |||
| Paroxysmal [n (%)] | 57 (57.6%) | 73 (75.3%) | .009 |
| Persistent/permanent [n (%)] | 42 (42.4%) | 24 (24.7%) | |
| Hypertension [n (%)] | 76 (78.4%) | 84 (84.9%) | .240 |
| Diabetes [n (%)] | 36 (37.1%) | 50 (50.5%) | .059 |
| Prior myocardial infarction [n (%)] | 22 (22.7%) | 16 (16.2%) | .248 |
| History of heart failure [n (%)] | 32 (33.0%) | 22 (22.2%) | .092 |
| COPD [n (%)] | 30 (30.9%) | 25 (25.3%) | .377 |
| Malignant tumor [n (%)] | 22 (22.7%) | 25 (25.3%) | .673 |
| Anticoagulation therapy [n (%)] | 14 (14.4%) | 24 (24.2%) | .082 |
| BMI (kg/m2) | 22.6 ± 4.2 | 25.4 ± 3.3 | <.001 |
| CHA2DS2‐VASc score [M (P25, P75)] | 4.91 (4.00, 6.00) | 4.68 (4.00, 5.00) | .320 |
| HAS‐BLED score [M (P25, P75)] | 2.99 (2.00, 4.00) | 2.62 (2.00, 3.00) | .065 |
| HGB (g/L) | 112.5 ± 21.9 | 127.6 ± 16.9 | <.001 |
| Alb (g/L) | 32.0 ± 3.9 | 35.4 ± 3.6 | <.001 |
| FPG [M (P25,P75), mmol/L] | 5.92 (4.81, 6.33) | 5.96 (4.72,6.86) | .830 |
| HbA1c [M (P25, P75) %] | 5.97 (5.29, 6.33) | 6.10 (5.46, 6.59) | .259 |
| TC [M (P25, P75), mmol/L] | 3.71 (2.94, 3.97) | 3.53 (2.90, 4.06) | .972 |
| HDL‐C (mmol/L) | 1.0 ± 0.3 | 1.0 ± 0.2 | .748 |
| LDL‐C (mmol/L) | 2.1 ± 0.7 | 2.1 ± 0.6 | .871 |
| TG [M (P25, P75), mmol/L] | 1.09 (0.72, 1.30) | 1.06 (0.73, 1.15) | .930 |
| eGFR [mL/(min·1.73 m2)] | 75.5 ± 35.5 | 75.7 ± 29.8 | .977 |
Abbreviations: AF, atrial fibrillation; Alb, albumin; BMI, body mass index; eGFR, estimated glomerular filtration rate; FPG, fasting blood glucose; HbA1c, glycosylated hemoglobin; HDL‐C, high‐density lipoprotein cholesterol; HGB, hemoglobin; LDL‐C, low‐density lipoprotein cholesterol (LDL‐C); TC, total cholesterol; TG, triglyceride.
3.2. Comparison of clinical adverse events between two groups
Compared with the nonmalnutrition group, the malnutrition group had a higher incidence of all‐cause death (41 cases, 42.3% vs. 24 cases, 24.2%, p = .007) and a higher incidence of major bleeding (14 cases, 14.4% vs. 5 cases, 5.1%, p = .026), with statistical significance. The incidence of ischemic stroke/systemic embolism in the malnutrition group was lower than that in the nonmalnutrition group (10 cases, 10.3% vs.15 cases, 15.2%), and the incidence of acute myocardial infarction and acute heart failure was higher than that in the nonmalnutrition group (19 cases, 19.6% vs.18 cases, 18.2%; 15 cases, 15.5% vs.11 cases, 11.1%), but the difference was not statistically significant (p > .05) (Table 2).
TABLE 2.
Comparison of adverse clinical events between patients with and without malnutrition.
| Items | Malnutrition (n = 97) | Nonmalnutrition (n = 99) | p‐Values |
|---|---|---|---|
| All‐cause death [n (%)] | 41 (42.3%) | 24 (24.2%) | .007 |
| Ischemic stroke/systemic embolism [n (%)] | 10 (10.3%) | 15 (15.2%) | .310 |
| Major bleeding events [n (%)] | 14 (14.4%) | 5 (5.1%) | .026 |
| Acute myocardial infarction [n (%)] | 19 (19.6%) | 18 (18.2%) | .801 |
| Acute heart failure [n (%)] | 15 (15.5%) | 11 (11.1%) | .369 |
3.3. Cox proportional risk regression analysis
Univariate Cox proportional hazard regressions were used to analyze malnutrition influencing clinical adverse events in elderly patients with atrial fibrillation, the results showed that malnutrition (MNA‐SF score ≤11) was correlated with all‐cause death (HR = 2.207, 95%CI: 1.333–3.656, p = .002) and major bleeding events (HR = 3.480, 95% CI: 1.244–9.731, p = .017) (Table 3). Kaplan–Meier curve also showed that malnutrition patients had a high risk of all‐cause death (log‐rank test, p = .001) (Figure 1) and major bleeding events (log‐rank test, p = .011) (Figure 2). Univariate Cox proportional hazard regression was used to analyze the factors influencing all‐cause death in elderly patients with atrial fibrillation. The results showed that the related factors were malnutrition (MNA‐SF score ≤11) (HR = 2.207, 95% CI: 1.333–3.656, p = .002), age ≥85 years (HR = 1.680, 95% CI: 1.041–3.089, p = .035), history of heart failure (HR = 1.914, 95% CI: 1.160–3.158, p = .011), prior myocardial infarction (HR = 1.785, 95% CI: 1.036–3.075, p = .037), HAS‐BLED score ≥3 (HR = 2.554, 95% CI: 1.433–4.550, p = .001), and not receiving anticoagulant therapy (HR = 3.362, 95% CI: 1.350–8.374, p = .009) indicated the risk factors of all‐cause death in elderly patients with atrial fibrillation. Multivariate Cox proportional risk regression analysis after adjusting for age ≥85 years, history of heart failure, prior myocardial infarction, HAS‐BLED score ≥3, and not receiving anticoagulant therapy showed that malnutrition (HR = 1.780,95% CI: 1.039–3.050, p = .036) remained an independent risk factor for all‐cause deaths in elderly patients with atrial fibrillation (Table 4). Univariate Cox proportional hazard regression analysis revealed that malnutrition was identified as an independent risk factor for major bleeding events (HR = 3.480, 95% CI: 1.244–9.731, p = .017). Furthermore, in the multivariate Cox proportional hazard regression analysis, after adjusting for history of prior bleeding, HAS‐BLED score ≥3, and antithrombotic therapy (anticoagulant therapy + antiplatelet therapy), malnutrition (HR = 2.880, 95% CI: 1.011–8.204, p = .048) was found to persist as an independent risk factor for major bleeding events (Table 5).
TABLE 3.
Univariate Cox proportional hazard analysis of association between malnutrition and clinical adverse events.
| Items | Malnutrition | ||
|---|---|---|---|
| Clinical adverse events | HR value | 95% CI | p‐Values |
| All‐cause death [n (%)] | 2.207 | 1.333–3.656 | .002 |
| Ischemic stroke/systemic embolism | 0.791 | 0.349–1.794 | .574 |
| Major bleeding events | 3.480 | 1.244–9.731 | .017 |
| Acute myocardial infarction | 1.706 | 0.779–3.737 | .182 |
| Acute heart failure | 1.452 | 0.761–2.770 | .257 |
FIGURE 1.
Kaplan–Meier survival curve for all‐cause death.
FIGURE 2.
Kaplan–Meier curve for major bleeding events.
TABLE 4.
Univariate and multivariate Cox proportional hazard analysis of predicting all‐cause death.
| Variables | HR value | 95% CI | p‐Values |
|---|---|---|---|
| Univariate analysis | |||
| Malnutrition | 2.207 | 1.333–3.656 | .002 |
| Age ≥85‐years‐old | 1.680 | 1.041–3.089 | .035 |
| Gender (male) | 1.470 | 0.825–2.618 | .191 |
| History of heart failure | 1.914 | 1.160–3.158 | .011 |
| Prior myocardial infarction | 1.785 | 1.036–3.075 | .037 |
| Hypertension | 0.851 | 0.454–1.594 | .615 |
| Diabetes | 0.827 | 0.505–1.355 | .452 |
| Malignant tumor | 0.962 | 0.540–1.712 | .894 |
| Paroxysmal AF | 1.341 | 0.621–2.899 | .455 |
| HAS‐BLED score ≥3 | 2.554 | 1.433–4.550 | .001 |
| CHA2DS2‐VASc score ≥3 | 2.610 | 0.361–18.857 | .342 |
| Not receiving anticoagulant therapy | 3.362 | 1.350–8.374 | .009 |
| Multivariate analysis | |||
| Malnutrition | 1.780 | 1.039–3.050 | .036 |
| Age ≥85‐years‐old | 1.100 | 0.611–1.982 | .751 |
| History of heart failure | 1.499 | 0.878–2.559 | .138 |
| Prior myocardial infarction | 1.297 | 0.730–2.303 | .375 |
| HAS‐BLED score ≥3 | 2.285 | 1.278–4.086 | .005 |
| Not receiving anticoagulant therapy | 2.986 | 1.185–7.520 | .020 |
Note: Malnutrition is defined as MNA‐SF score ≤11.
Abbreviation: CI, confidence interval.
TABLE 5.
Univariate and multivariate Cox proportional hazard analysis of predicting major bleeding events.
| Variables | HR value | 95% CI | p‐Values |
|---|---|---|---|
| Univariate analysis | |||
| Malnutrition | 3.480 | 1.244–9.731 | 0.017 |
| Age ≥85‐years‐old | 1.146 | 0.449–2.929 | 0.776 |
| Gender (male) | 0.638 | 0.255–1.592 | 0.335 |
| Prior bleeding | 1.910 | 0.768–4.753 | 0.164 |
| Hypertension | 1.206 | 0.331–4.399 | 0.776 |
| Diabetes | 0.856 | 0.344–2.133 | 0.739 |
| Malignant tumor | 0.751 | 0.242–2.329 | 0.619 |
| HAS‐BLED score ≥3 | 1.205 | 0.466–3.114 | 0.700 |
| Anticoagulant therapy | 1.542 | 0.507–4.686 | 0.445 |
| Antithrombotic therapy (anticoagulant therapy + antiplatelet therapy) | 2.683 | 1.085–6.636 | 0.033 |
| Multivariate analysis | |||
| Malnutrition | 2.880 | 1.011–8.204 | 0.048 |
| Prior bleeding | 1.543 | 0.577–4.124 | 0.388 |
| HAS‐BLED score ≥3 | 1.107 | 0.396–3.097 | 0.847 |
| Antithrombotic therapy (anticoagulant therapy + antiplatelet therapy) | 2.225 | 0.878–5.640 | 0.092 |
Note: Malnutrition is defined as MNA‐SF score ≤11.
Abbreviation: CI, confidence interval.
4. DISCUSSION
This study showed that the incidence of all‐cause death in malnourished elderly patients with atrial fibrillation screened by MNA‐SF score is high, and malnutrition is an independent risk factor of all‐cause death in elderly patients with atrial fibrillation. The incidence of major bleeding in elderly patients with atrial fibrillation in the malnutrition group is higher, while the rate of anticoagulation therapy and the incidence of ischemic stroke/systemic embolism are not significantly different from those in the nonmalnutrition group; thus, the benefit of anticoagulant therapy is not obvious. The evaluation of nutritional status by MNA‐SF score in elderly patients with atrial fibrillation could help in judging the prognosis of patients and choosing anticoagulation strategies.
Herein, we found that malnutrition is an independent risk factor for all‐cause death of elderly patients with atrial fibrillation, which is consistent with previous findings in recent years (Arenas Miquélez et al., 2020; Cheng et al., 2019; Díez‐Manglano & Clemente‐Sarasa, 2019). However, these studies used control nutritional status score (CONUT), prognostic nutritional index (PNI), and geriatric nutritional risk index (GNRI) as nutrition assessment tools, which require the results of blood routine, Alb, blood lipid level, and other laboratory indicators and the height and weight measurements; hence, these tools are relatively inconvenient. In the present study, MNA‐SF score was used to evaluate nutritional status. This tool is simple, convenient, and standard, which does not require laboratory indicators, allowing nonmedical professionals to complete the assessment rapidly. Height and weight cannot be obtained for some reasons, such as a bedridden state; thus, measuring calf circumference can be an alternative approach. The results of this method are in good agreement with objective indexes related to nutrition, such as BMI, triceps skinfold thickness, and upper arm muscle circumference (Sukkriang & Somrak, 2021). Taken together, this study showed that the nutritional indexes, such as HbA1c, HGB, Alb, and BMI in the malnourished group, are lower than those in the nonmalnourished group. This finding confirmed that their nutritional status is worse than that in the nonmalnourished group, indicating that MNA‐SF score could evaluate the nutritional status of elderly patients with atrial fibrillation.
The nutritional status may have a significant influence on the treatment decision of elderly patients with atrial fibrillation. Anticoagulation therapy is a critical part of the treatment of patients with atrial fibrillation that prevents ischemic stroke/systemic embolism. In this study, there is no significant difference in CHA2DS2‐VASc scores between the malnutrition and the nonmalnutrition groups. The proportion of patients and the incidence of ischemic stroke/systemic embolism in the malnutrition group who received anticoagulation therapy was lower than that in the nonmalnutrition group. The HAS‐BLED score of malnutrition group was higher, and the incidence of major bleeding was significantly higher than that of the nonmalnutrition group. The mortality rate of patients with malnutrition was 42.27%, which is much higher than that of ischemic stroke/systemic embolism, suggesting that elderly patients with malnutrition may die from other causes before the occurrence of ischemic stroke/systemic embolism. In summary, malnourished elderly patients with atrial fibrillation have a higher risk of bleeding and a lower incidence of ischemic stroke/systemic embolism than those without malnutrition. Considering malnutrition, the benefits of anticoagulation therapy for elderly patients with atrial fibrillation are not obvious, it should pay more attention to individualized anticoagulant therapy to avoid major bleeding events in malnutrition group. The malnourished patients often show frailty status. Previous studies have shown that the proportion of elderly patients with atrial fibrillation who have frailty status receiving anticoagulation therapy is low (Oqab et al., 2018). Moreover, the degree of frailty is inversely proportional to the ratio of anticoagulant therapy (Lefebvre et al., 2016), suggesting that malnutrition may be involved in causing a frailty status, thereby affecting the choice of treatment strategies for elderly patients with atrial fibrillation.
Malnutrition in elderly patients with atrial fibrillation might exhibit the following phenomena: long‐term atrial fibrillation may lead to cardiac insufficiency, stroke/systemic embolism, and other complications, resulting in the decline of patients' physical function and activities. These factors affect their nutritional intake, leading to frailty and malnutrition. Some studies have shown that the increase in BMI in underweight patients with heart failure can reduce the risk of mortality (Clark et al., 2012). It is speculated that strengthening nutritional support and improving nutritional status reduces all‐cause death in elderly patients with atrial fibrillation, although additional studies are required for substantiation. Chronic inflammatory state may be a critical link between atrial fibrillation and malnutrition; various chronic diseases can put the body in a chronic inflammatory state, releasing various inflammatory factors, such as C‐reactive protein (CRP), interleukin (IL)‐6, and tumor necrosis factor‐alpha (TNF‐α). These inflammatory factors can directly or indirectly affect the functions of the whole body and various organ systems, increase the decomposition of body fat and protein, reduce fat synthesis, and lead to metabolic disorders, which in turn lead to malnutrition (Li et al., 2019). These inflammatory factors also play a critical role in the occurrence and development of atrial fibrillation (Korantzopoulos et al., 2018; Van Wagoner & Chung, 2018). In some nutrition‐related studies on tumor patients, appetite stimulants synthetic progesterone derivatives, such as megesterol acetate (MA) and medroxyprogesterone acetate (MPA) (Aoyagi et al., 2015) and anabolic hormones (such as testosterone (Wright et al., 2018) and ghrelin (Garcia et al., 2015)) can improve the nutritional status of patients and inhibit the inflammatory factors (Rahman et al., 2016). However, whether these drugs can improve the nutritional status and have any influence on atrial fibrillation (such as whether it is possible to trigger atrial fibrillation and its influence on heart rate and coagulation function) need an in‐depth investigation.
This study included patients with malignant tumors and infections, and such patients are mostly excluded in previous similar studies; this study may be closer to the real clinical situation. Nevertheless, the present study also has some limitations. This is a single‐center retrospective study for hospitalized patients, and the sample size is small, which might not fully reflect the situation of all elderly patients with atrial fibrillation. There is no dynamic assessment of changes in the nutritional status during follow‐up, and whether improving the nutritional status of patients can enhance their prognosis is yet to be clarified.
In conclusion, nutritional status is significant in judging the prognosis of elderly patients with atrial fibrillation, which might greatly impact the decision‐making of anticoagulant therapy in elderly patients with atrial fibrillation. The evaluation of nutritional status should be used as a critical indicator of admission evaluation in elderly patients with atrial fibrillation. The application of MNA‐SF score as a nutrition assessment tool to elderly patients with atrial fibrillation predicts the occurrence of all‐cause death and high bleeding risk, identifies those at risk of malnutrition, and actively conducts nutritional intervention at the earliest, which has great application value. Thus, finding effective ways of nutritional intervention for elderly patients with AF may be the direction of future research.
AUTHORS CONTRIBUTIONS
Kan Zhang designed the experiments. Ying Sun, Jiancao Ding and Qing Ma performed the experiments. Dai Zhang and Wei Huang collected and analyzed the data. Wei Huang and Yunli Xing drafted manuscript. All authors read and approved the final manuscript.
CONFLICT OF INTEREST STATEMENT
No competing interest.
ETHICS STATEMENT
All patients were informed and signed informed consent voluntarily. The current study was approved by the Ethics Committee of Affiliated Beijing Friendship Hospital, Capital Medical University (2022‐P2‐295‐01), and complied with the guidelines outlined in the declaration of Helsinki were followed. The written consent was received from all participants.
Zhang, K. , Sun, Y. , Ding, J. , Ma, Q. , Zhang, D. , Huang, W. , & Xing, Y. (2024). Effect of nutritional status on adverse clinical events in elderly patients with nonvalvular atrial fibrillation: A retrospective cohort study. Annals of Noninvasive Electrocardiology, 29, e13130. 10.1111/anec.13130
DATA AVAILABILITY STATEMENT
The datasets used and/or analyzed during this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during this study are available from the corresponding author upon reasonable request.