Impact of Preoperative Nutritional Status on the Outcome of Catheter Ablation for Atrial Fibrillation

Koichi Furui; Itsuro Morishima; Yasuhiro Morita; Yasunori Kanzaki; Kensuke Takagi; Hiroaki Nagai; Naoki Watanabe; Naoki Yoshioka; Ryota Yamauchi; Hiroyuki Miyazawa; Satoshi Yanagisawa; Yasuya Inden; Toyoaki Murohara

doi:10.1253/circj.CJ-21-0218

Abstract

Background: The relationship between nutritional status and the incidence or prognosis of atrial fibrillation (AF) has been reported, but no studies have described the relationship between the outcomes of AF catheter ablation (CA) and nutritional status as assessed by various scoring tools. We aimed to verify the hypothesis that preoperative nutritional status is associated with arrhythmia recurrence after CA for AF.

Methods and Results: We evaluated 913 patients (age, 67±10 years; men, 72%; paroxysmal AF, 56%) who underwent CA for AF between November 2011 and November 2017. Patients were systematically followed with an endpoint of atrial tachyarrhythmia recurrence, the predictive value of which was compared among 3 scoring tools (Controlling Nutritional Status [CONUT] score / Geriatric Nutritional Risk Index [GNRI] / Prognostic Nutritional Index [PNI]). Patients were divided into normal nutrition (CONUT <2 [n=637] / GNRI >98 [n=836] / PNI >38 [n=910]) and undernutrition (CONUT ≥2 [n=276] / GNRI ≤98 [n=77] / PNI ≤3 [n=3]) groups. AF recurred in 274 patients (mean follow-up, 2.3±0.8 years). The AF recurrence rate was higher in patients with undernutrition than in those with normal nutrition (CONUT/GNRI) status. Multivariate Cox regression analysis identified undernutrition status (GNRI ≤98) as an independent predictor of atrial tachyarrhythmia recurrence.

Conclusions: The AF recurrence rate after CA was higher in patients with undernutrition than in those with normal nutrition as stratified by the nutrition scoring tools.

Malnutrition has recently been noted in a broad range of diseases. In the field of cardiology, several studies have shown malnutrition to be an important indicator of poor prognosis and negative outcomes after therapeutic intervention in patients with cardiovascular diseases, such as heart failure (HF), valvular heart disease, and peripheral artery disease.¹^–³

Editorial p 277

Body mass index (BMI) is a typical indicator of nutritional status, and a low BMI is one of the phenotypes of undernutrition. Several scoring tools are often used to perform a more comprehensive assessment of nutritional status as not only BMI but also other components, such as blood examination data, weight loss rate, and dietary intake, are important determinants of malnutrition. Of the various scoring tools that have been reported to be effective, 3 major indices, the Controlling Nutritional Status (CONUT) score,⁴ Geriatric Nutritional Risk Index (GNRI),⁵ and Prognostic Nutritional Index (PNI),⁶ are widely used to assess malnutrition, and are reported to be significant predictors of death in patients with HF.² These scoring methods are simple and objective indicators that do not require complex patient consultations and interviews.

Several reports have shown a relationship between nutritional status and the incidence or prognosis of atrial fibrillation (AF).⁷^,⁸ Regarding BMI and AF recurrence after catheter ablation (CA), some studies concluded that patients with a low BMI have a higher recurrence rate of AF after CA.⁹^,¹⁰ However, to the best of our knowledge, no study has described the relationship between the outcomes of AF after ablation and nutritional status as assessed by the various scoring tools. Therefore, we aimed to verify the hypothesis that preoperative nutritional status is associated with arrhythmia recurrence after CA for AF.

Methods

Study Design and Patient Population

Using the Ogaki Catheter Ablation Database, we retrospectively recruited 917 consecutive patients who underwent index CA for AF at Ogaki Municipal Hospital in Japan (from November 2011 to November 2017). Of these, we excluded 4 patients (2 with no follow-up data and 2 whose index lymphocyte counts were unavailable) and finally included 913 patients. Hematologic data were collected within 1 week prior to AF ablation. Body weight and height were measured the day before the ablation procedure in all patients. The type of AF was determined according to the 2017 Heart Rhythm Society, European Heart Rhythm Association, European Cardiac Arrhythmia Society, Asia Pacific Heart Rhythm Society, and the Sociedad Latinoamericana de Estimulación Cardíaca y Electrofisiología expert consensus statement on catheter and surgical ablation of AF.¹¹ Paroxysmal AF (PAF) was defined as episodes of AF lasting <7 days with subsequent reversion to sinus rhythm. Persistent AF was defined as AF episodes lasting ≥7 days, including episodes that were terminated by cardioversion, by either drugs or direct current cardioversion after ≥7 days. Long-standing persistent AF was defined as AF episodes lasting ≥1 year.

Scoring Tools for Nutritional Status Assessment

Three major score calculating indices (CONUT, GNRI, and PNI) were used to evaluate nutritional status in this study. The CONUT score involves assessing the serum albumin levels, total cholesterol levels, and total lymphocyte count. It is calculated using a predetermined point according to the serum levels, with the total score ranging from 0 to 12.⁴ The GNRI is calculated using the formula: 14.89 × serum albumin (g/dL) + 41.7 × (body weight [kg] / ideal body weight [kg]).⁵ The PNI is calculated using the formula: 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (mm³).⁶ We used these scores to assess nutritional status prior to the ablation procedure in all patients.

With the original CONUT, a score of 0–1 is considered normal, and scores of 2–4, 5–8, and 9–12 reflect mild, moderate, and severe malnutrition, respectively.⁴ In this study, we defined a score of 0–1 as “normal nutrition” and scores ≥2 as “undernutrition.” For the GNRI, a score >98 is considered normal, and scores of 92–98, 82–91, and <82 reflect mild, moderate, and severe malnutrition, respectively.⁵ In this study, we defined a score >98 as “normal nutrition” and scores ≤98 as “undernutrition.” A PNI score >38 is considered normal, and scores of 35–38 and <35 reflect moderate and severe malnutrition, respectively.⁶ Because there is no “mild” category for the PNI, we defined a score >38 as “normal nutrition” and scores ≤38 as “undernutrition.”

Ablation Protocol

All patients were effectively anticoagulated for >3 weeks, and transesophageal echocardiography was performed to exclude any left atrial (LA) thrombi prior to CA. Before the procedure, all antiarrhythmic drugs were discontinued for ≥5 half-lives (except amiodarone). The ablation procedure was performed under local anesthesia with mild conscious sedation. Radiofrequency (RF) and balloon ablations using a 3D mapping system (NavX system: St. Jude Medical, Saint Paul, MN, USA; or CARTO system: Biosense Webster, Diamond Bar, CA, USA) were performed in all cases. Most patients underwent circumferential pulmonary vein (PV) isolation with point-by-point applications using an irrigated-tip RF catheter to create contiguous lesions. The remaining patients underwent individual PV isolation, either using a 2nd-generation cryoballoon ablation catheter (Arctic Front Advance Cardiac Cryoablation Catheter; Medtronic, Minneapolis, MN, USA) or the SATAKE Hot Balloon catheter (Toray Industries, Inc., Tokyo, Japan). The electrophysiological endpoint of PV isolation was the creation of a bidirectional conduction block between the LA and PVs. The decision to perform additional ablations (i.e., cavotricuspid isthmus ablation, superior vena cava isolation, non-PV foci ablation, or LA linear ablation) was at the discretion of the operator.

Follow-up

Patients underwent periodic follow-up in the outpatient clinic at 1, 3, 6, and 12 months, and annually thereafter, following the initial ablation procedure, as described previously.¹² Discontinuation of antiarrhythmic drugs was encouraged at 3 months after the procedure. When patients developed any arrhythmia-related symptoms, a 1-channel ECG was recorded using an ambulatory recorder (HCG-801; Omron Healthcare, Kyoto, Japan) to correlate its findings with the symptoms. At each follow-up, the medical history and physical examination findings were reviewed, and a 12-lead ECG and 24-hour Holter monitor recording were performed. Missing follow-up data were obtained by contacting either the physicians in charge or the patients themselves.

Study Endpoint

The primary endpoint was defined as the recurrence of atrial tachyarrhythmia beyond a blanking period of 90 days. However, if repeat ablation was performed within the blanking period after the session, the patient was considered to have recurrent arrhythmia on day 91. Recurrence was defined as atrial arrhythmias lasting >30 s (as revealed by examination data) requiring repeat ablation.

Subanalyses

Because cholesterol level is 1 of the 3 elements of the CONUT score, we further divided patients into those taking lipid-lowering agents (statins, fibrates, ezetimibe, and polyunsaturated fatty acids) and those not taking lipid-lowering agents. Additional analyses were performed in each group for the same endpoint.

Statistical Analysis

Continuous variables are expressed as mean±standard deviation or median and interquartile range (25–75%). Discrete variables are presented as absolute values, percentages, or both. Student’s t-test and the Mann–Whitney U test were used to compare the trends for normally distributed and non-normally distributed continuous variables, respectively. For comparison of trends between categorical variables, the χ² test was performed. Comparisons of AF-free survival were performed by plotting Kaplan-Meier curves using the log-rank test. The Cox proportional hazards model was used for univariate and multivariate analyses to identify independent predictors of outcomes. Variables demonstrating an association with atrial tachyarrhythmia recurrence in the univariate analysis (P<0.1), and other important variables (age, sex, left ventricular ejection fraction (LVEF), and the prevalence of HF and coronary artery disease), were included in the multivariate model using the backward stepwise selection method. For all tests, P<0.05 was considered significant. Statistical analyses were performed using SPSS software version 23.0 (SPSS Inc., Chicago, IL, USA) and R version 3.5.2 (The R Project for Statistical Computing; http://www.R-project.org/).

Results

Classification and Distribution of Patients

Figure 1 is a flowchart of the study method and population. The total population was stratified according to the CONUT, GNRI, and PNI scores. The CONUT scores revealed that 637 (69.8%) patients had normal nutrition, and 276 (30.2%) patients were undernourished. Using the GNRI, 836 (91.6%) patients were included in the normal nutrition group and 77 (8.4%) in the undernutrition group. In contrast, according to the PNI scores, of 913 patients, only 3 (0.3%) were undernourished with a PNI ≤38. Figure 2 demonstrates the distribution of the CONUT and GNRI scores in all patients. The median CONUT and GNRI scores were 1 (0–2) and 106 (103–110), respectively. The agreement of the nutritional grades among the patients divided by the CONUT, the GNRI, and the PNI are shown in Supplementary Table 1.

Figure 1.

Study population and nutritional status assessed using the scoring tools: the Controlling Nutritional Status (CONUT) score, Geriatric Nutritional Risk Index (GNRI), and Prognostic Nutritional Index (PNI). AF, atrial fibrillation.

Figure 2.

Distribution of patients’ score values assessed using the Controlling Nutritional Status (CONUT) score and Geriatric Nutritional Risk Index (GNRI).

Patients’ Characteristics

The baseline characteristics and examination data of all patients are summarized in Table 1. The mean age was 66.9±9.9 years, 656 (72%) patients were men, and 56% had PAF. On dividing the population into undernutrition (CONUT ≥2) and normal nutrition (CONUT <2) groups, the patients in the undernutrition group were significantly older (69.3±9.5 vs. 65.9±9.9 years; P<0.001), had a lower BMI (23.1±3.5 vs. 24.3±3.6 kg/m²; P<0.001), higher prevalence of HF (25% vs. 17%; P=0.004) and coronary artery disease (19% vs. 4.9%; P<0.001), higher CHADS2 (Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, Stroke) score (1.5±1.1 vs. 1.3±1.1; P=0.004), larger LA dimension (Lad: 40.6±7.0 vs. 39.7±6.5 mm; P=0.038), lower estimated glomerular filtration rate (eGFR: 63.6±18.0 vs. 68.4±17.7 mL/min/1.73 m²; P=0.003), lower serum albumin (4.3±0.4 vs. 4.4±0.3 g/dL; P<0.001), lower total cholesterol (166±32 vs. 196±28 mg/dL; P<0.001), lower total lymphocyte count (1,309±432 vs. 1,955±521 mg/dL; P<0.001), and lower LVEF (61.2±12.4 vs. 64.0±8.7%; P=0.032) than those in the normal nutrition group. A comparison of the undernutrition and normal nutrition groups according to GNRI revealed several significant differences in baseline characteristics, including age, sex ratio, BMI, history of hypertension, HF rates, eGFR, serum albumin, total cholesterol, total lymphocyte count, and LVEF, between the 2 groups (Table 1).

Table 1. Baseline Clinical Characteristics and Examination Results of the Study Population

Variable	Total 913 patients	CONUT score		P value	GNRI score		P value
Variable	Total 913 patients	CONUT <2 637 patients	CONUT ≥2 276 patients	P value	GNRI >98 836 patients	GNRI ≤98 77 patients	P value
Age, years	66.9±9.9	65.9±9.9	69.3±9.5	<0.001	66.5±9.8	71.3±9.5	<0.001
Sex, male, n (%)	656 (72)	458 (72)	198 (72)	0.96	617 (74)	39 (51)	<0.001
BMI, kg/m²	23.9±3.6	24.3±3.6	23.1±3.5	<0.001	24.3±3.4	20.1±3.2	<0.001
Underlying diseases, n (%)
Hypertension	541 (59)	378 (59)	163 (59)	0.94	507 (61)	34 (44)	0.005
Diabetes mellitus	176 (19)	127 (20)	49 (18)	0.44	162 (19)	14 (18)	0.80
History of HF	173 (19)	105 (17)	68 (25)	0.004	148 (18)	25 (33)	0.002
Systemic embolism/TIA	75 (8.2)	51 (8.0)	24 (8.7)	0.73	68 (8.1)	7 (9.1)	0.77
Coronary artery disease	82 (8.9)	31 (4.9)	51 (19)	<0.001	73 (8.7)	9 (12)	0.39
CHADS2 score	1.4±1.1	1.3±1.1	1.5±1.1	0.005	1.3±1.1	1.6±1.1	0.12
No. of AADs failed	0.5±0.7	0.5±0.7	0.5±0.7	0.67	0.5±0.7	0.5±0.7	0.93
eGFR, mL/min/1.73 m²	66.9±17.9	68.4±17.7	63.6±18.0	0.003	67.5±17.3	60.7±22.7	0.013
Serum albumin, g/dL	4.4±0.3	4.4±0.3	4.3±0.4	<0.001	4.4±0.3	3.8±0.3	<0.001
Total cholesterol, mg/dL	187±33	196±28	166±32	<0.001	189±32	172±37	<0.001
Total lymphocyte count, mm³	1,760±578	1,955±521	1,309±432	<0.001	1,784±575	1,502±541	<0.001
LAD, mm	40.0±6.7	39.7±6.5	40.6±7.0	0.038	40.0±6.6	39.8±6.6	0.81
LVEF, %	63.2±10.0	64.0±8.7	61.2±12.4	0.032	63.7±8.9	58.5±14.4	<0.001
Total sessions	1.3±0.5	1.3±0.5	1.3±0.5	0.79	1.3±0.5	1.3±0.5	0.43
Mean follow-up period, years	2.3±0.8	2.3±0.7	2.3±0.8	0.42	2.3±0.7	2.2±0.8	0.18
AF type, n (%)
Paroxysmal	513 (56)	356 (55)	157 (57)	0.08	470 (56)	43 (56)	0.84
Persistent	228 (25)	150 (24)	78 (28)		207 (25)	21 (27)
Long-standing persistent	172 (19)	131 (21)	41 (15)		159 (19.0)	13 (17)
OAC type, n (%)
Warfarin	138 (15)	93 (15)	45 (16)	0.51	154 (18)	19 (25)	0.18
DOAC	775 (85)	544 (85)	231 (84)	0.51	682 (82)	58 (75)	0.18

Data are presented as mean±SD unless specified otherwise. AAD, antiarrhythmic drugs; AF, atrial fibrillation; BMI, body mass index; CHADS2, Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, Stroke; CONUT, Controlling Nutritional Status; DOAC, direct oral anticoagulant; eGFR, estimated glomerular filtration rate; GNRI, Geriatric Nutritional Risk Index; HF, heart failure; LAD, left atrial dimension; LVEF, left ventricular ejection fraction; OAC, oral anticoagulant; SD, standard deviation; TIA, transient ischemic attack.

Table 2 shows the procedural outcomes in patients stratified according to the CONUT and GNRI scores. RF ablation was performed in 83% of the patients. PV isolation was achieved in all patients in combination with cavotricuspid isthmus ablation (n=803; 88%) and LA posterior wall isolation (n=131; 14%). There were no significant differences in the procedural parameters between the normal nutrition and undernutrition groups classified according to the CONUT and GNRI scores.

Table 2. Index Ablation Procedural Characteristics of Patients

Procedure, n (%)	Total 913 patients	CONUT score		P value	GNRI score		P value
Procedure, n (%)	Total 913 patients	CONUT <2 637 patients	CONUT ≥2 276 patients	P value	GNRI >98 836 patients	GNRI ≤98 77 patients	P value
Ablation device
RF	754 (83)	521 (82)	233 (84)	0.16	689 (82)	65 (84)	0.22
Cryoballoon	156 (17)	115 (18)	41 (15)		145 (17)	11 (14)
Hot balloon	3 (0.3)	1 (0.2)	2 (0.7)		2 (0.2)	1 (1.3)
PV isolation	913 (100)	637 (100)	276 (100)	–	836 (100)	77 (100)	–
Posterior wall isolation	131 (14)	91 (14)	40 (15)	0.94	123 (15)	8 (10)	0.30
LA linear ablations	18 (20)	11 (17)	7 (25)	0.42	14 (17)	4 (5.2)	0.06
SVC isolation	67 (7.3)	51 (8.0)	16 (5.8)	0.24	61 (7.3)	6 (7.8)	0.87
Non-PV foci ablation	12 (1.3)	9 (1.4)	3 (1.1)	0.49	11 (1.3)	1 (1.3)	1.00
Ganglionated plexi ablation	13 (1.4)	11 (1.7)	2 (0.7)	0.20	13 (1.6)	0 (0)	0.62
CTI linear ablation	803 (88)	565 (89)	238 (86)	0.29	740 (89)	63 (82)	0.08

Data are presented as absolute numbers (percentages). CONUT, Controlling Nutritional Status; CTI, cavotricuspid isthmus; GNRI, Geriatric Nutritional Risk Index; LA, left atrium; PV, pulmonary vein; RF, radiofrequency; SVC, superior vena cava.

Ablation Outcomes

During a mean follow-up of 2.3±0.8 years, atrial arrhythmia recurred in 274 patients (30%), consisting of 138 PAF patients (15%) and 136 non-PAF patients (15%). The Kaplan-Meier survival curves revealed that the atrial tachyarrhythmia recurrence-free survival rates were significantly higher in the normal nutrition groups than in the undernutrition groups stratified according to the CONUT (P=0.029; Figure 3A), as well as the GNRI (P=0.006; Figure 3B) scores. The patients with higher malnutrition status were at a higher risk of atrial tachyarrhythmia recurrence when stratified by either the CONUT or GNRI score (Supplementary Table 2).

Figure 3.

Kaplan-Meier survival curves for freedom from atrial tachyarrhythmia after atrial fibrillation catheter ablation. Comparison between the undernutrition and normal nutritional groups assessed using (A) the Controlling Nutritional Status (CONUT) score and (B) the Geriatric Nutritional Risk Index (GNRI).

Clinical Predictors of Atrial Tachyarrhythmia Recurrence

Univariate Cox proportional hazards analysis showed that a GNRI score ≤98, a CONUT score ≥2, LAD, and PAF were significantly associated with atrial arrhythmia recurrence after ablation (Table 3). The subsequent multivariate analysis demonstrated that malnutrition (as indicated by GNRI ≤98) (adjusted hazard ratio [HR], 1.66; 95% confidence interval [CI]: 1.15–2.42; P=0.008) and LAD (adjusted HR, 1.03; 95% CI: 1.01–1.05; P=0.009) were independent predictors of atrial tachyarrhythmia recurrence (Table 3).

Table 3. Predictors of Atrial Tachyarrhythmia Recurrence After AF Catheter Ablation

Variable	Recurrence		Univariate analysis			Multivariate analysis
Variable	(+) 274 patients	(−) 639 patients	HR	95% CI	P value	HR	95% CI	P value
Age, years	66.6±10.2	67.0±9.7	1.00	(0.98–1.01)	0.52	–	–	–
Male sex, n (%)	189 (69)	467 (73)	0.85	(0.65–1.09)	0.20	–	–	–
BMI, kg/m²	23.7±3.5	24.1±3.6	0.97	(0.94–1.01)	0.13	–	–	–
CONUT ≥2, n (%)	96 (35)	180 (28)	1.32	(1.03–1.69)	0.029	1.25	(0.97–1.61)	0.087
GNRI ≤98, n (%)	33 (12)	44 (6.9)	1.66	(1.15–2.39)	0.006	1.66	(1.15–2.42)	0.008
eGFR, mL/min/1.73 m²	65.7±18.6	67.5±17.6	0.99	(0.99–1.01)	0.09	–	–	–
LAD, mm	40.7±7.4	39.7±6.3	1.02	(1.01–1.04)	0.02	1.03	(1.01–1.05)	0.009
LVEF, %	61.2±12.4	63.0±9.6	1.01	(0.99–1.02)	0.62	1.01	(0.99–1.03)	0.083
PAF, n (%)	138 (50)	375 (59)	0.78	(0.61–0.98)	0.036	–	–	–
Hypertension, n (%)	159 (58)	382 (60)	1.08	(0.85–1.37)	0.56	–	–	–
Diabetes mellitus, n (%)	53 (19)	123 (19)	1.01	(0.75–1.37)	0.93	–	–	–
Coronary artery disease, n (%)	23 (8.4)	59 (9.2)	1.10	(0.72–1.68)	0.68	–	–	–
History of HF, n (%)	58 (21)	115 (18)	1.18	(0.88–1.58)	0.26	–	–	–
Cerebral infarction/TIA, n (%)	18 (6.6)	57 (8.9)	1.40	(0.87–2.26)	0.17	–	–	–

Data are presented as means±SD unless specified otherwise. Covariates introduced into the multivariate model were age, sex, CONUT ≥2, GNRI ≤98, eGFR, LAD, LVEF, PAF, coronary artery disease, and history of HF. CI, confidence interval; HR, hazard ratio; PAF, paroxysmal AF. Other abbreviations as in Table 1.

Subanalyses According to Lipid-Lowering Agent Use

Of the total 913 patients, 604 did not use lipid-lowering agents and 309 patients were taking lipid-lowering agents at baseline. The lipid-lowering agents included statins (n=286), fibrates (n=16), ezetimibe (n=10), and polyunsaturated fatty acids (n=7). Among those not taking lipid-lowering agents, the tachyarrhythmia-free survival was significantly worse in the undernutrition group (CONUT ≥2; n=160) than in the normal nutrition group (CONUT <2; n=444) (P=0.010; Figure 4A). Multivariate analysis revealed that malnutrition (as indicated by CONUT ≥2) (adjusted HR, 1.44; 95% CI: 1.05–1.97; P=0.024) and PAF (adjusted HR 0.67; 95% CI: 0.50–0.91; P=0.010) were independent predictors of atrial tachyarrhythmia recurrence (Table 4). In contrast, among the patients taking lipid-lowering agents, the rates of atrial tachyarrhythmia-free survival were not significantly different between the undernutrition and normal nutrition groups based on the CONUT score (P=0.73; Figure 4B).

Figure 4.

Kaplan-Meier survival curves for freedom from atrial tachyarrhythmia after atrial fibrillation catheter ablation in patients with undernutrition and normal nutrition assessed using the Controlling Nutritional Status (CONUT) score among patients not taking (A) and taking (B) lipid-lowering agents.

Table 4. Predictors of Atrial Tachyarrhythmia Recurrence After Catheter Ablation for AF in Patients Not Taking Lipid-Lowering Agents

Variable	Recurrence		Univariate analysis			Multivariate analysis
Variable	(+) 183 patients	(−) 421 patients	HR	95% CI	P value	HR	95% CI	P value
Age, years	65.4±10.7	66.0±10.1	1.00	(0.98–1.01)	0.51	0.99	(0.97–1.00)	0.066
Male sex, n (%)	141 (77)	327 (78)	0.97	(0.69–1.37)	0.88	–	–	–
BMI, kg/m²	23.3±3.3	23.7±3.5	0.97	(0.93–1.02)	0.22	–	–	–
CONUT ≥2, n (%)	61 (33)	91 (24)	1.50	(1.10–2.04)	0.010	1.44	(1.05–1.97)	0.024
GNRI ≤98, n (%)	22 (12)	31 (7.4)	1.61	(1.03–2.52)	0.036	1.53	(0.97–2.41)	0.070
eGFR, mL/min/1.73 m²	67.5±18.2	69.5±17.5	0.99	(0.99–1.01)	0.10	0.99	(0.98–1.00)	0.066
LAD, mm	40.3±6.8	39.0±6.1	1.03	(1.01–1.05)	0.017	–	–	–
LVEF, %	64.3±8.7	63.5±9.1	1.01	(0.99–1.02)	0.45	1.02	(1.00–1.04)	0.055
PAF, n (%)	97 (53)	176 (42)	0.70	(0.52–0.93)	0.014	0.67	(0.50–0.91)	0.010
Hypertension, n (%)	98 (54)	230 (55)	1.06	(0.79–1.42)	0.69	–	–	–
Diabetes mellitus, n (%)	26 (14)	58 (13)	1.02	(0.67–1.54)	0.93	–	–	–
Coronary artery disease, n (%)	5 (2.7)	12 (2.9)	1.07	(0.44–2.61)	0.88	–	–	–
History of HF, n (%)	36 (20)	69 (16)	1.25	(0.87–1.80)	0.23	–	–	–
Cerebral infarction/TIA, n (%)	8 (4.4)	26 (6.2)	1.46	(0.72–2.97)	0.30	–	–	–

Data are presented means±SD unless specified otherwise. Covariates introduced into the multivariate model were age, sex, CONUT ≥2, GNRI ≤98, eGFR, LAD, LVEF, PAF, coronary artery disease, and history of HF. Abbreviations as in Tables 1,3.

Discussion

To the best of our knowledge, this study is the first to examine the effect of nutritional status, assessed using various nutrition scoring tools, on the long-term outcomes of AF after CA in a large sample size. The main findings were as follows: (1) patients with preoperative undernutrition status, assessed using both the CONUT and GNRI scores, were at a higher risk of AF recurrence after CA than those with normal preoperative nutritional status; (2) among the 3 nutrition assessment tools, the GNRI was the most useful for predicting recurrence in patients undergoing CA for AF; and (3) malnutrition, assessed using the CONUT score, was an independent predictor of AF recurrence, after excluding patients using lipid-lowering drugs.

Obesity has been implicated in the development and progression of AF.¹³ Furthermore, the probability of being free from AF after CA is lower in obese patients than in nonobese patients.¹⁴ However, it has also been demonstrated that BMI has a “U-shaped” relationship with the risk of AF occurrence and its recurrence after CA; not only a high BMI but also a low BMI poses an increased risk of AF occurrence and recurrence after CA, as observed in previous studies.⁸^,¹⁰ A low BMI is an indicator of undernutrition, and the results of our study are similar to those of the previous reports. However, although there seems to be a strong relationship between a low BMI and undernutrition, these 2 conditions are somewhat different. Nutrition scoring tools evaluate various aspects of nutritional status, including lipid, protein, and immune metabolism, compared with the simple evaluation of BMI, which considers only body weight and height.

The prevalence of undernutrition in this study varied among the 3 scoring tools: 0.3%, 8.4%, and 30.2% using the PNI, GNRI, and CONUT scores, respectively. Several large-scale studies have performed nutritional screening using scoring tools in patients with HF. According to a previous study, undernutrition was reported in 8%, 19%, and 54% of patients with HF using PNI, GNRI, and CONUT scores, respectively.² Compared with the nutritional status of HF patients, the AF patients undergoing CA in our study seemed to have a relatively good nutritional status. The PNI could only identify undernutrition in 0.3% of the total study population because it can only detect moderate-to-severe malnutrition, which is rarely observed in AF patients undergoing CA. Therefore, based on the results of this study we conclude that it would be difficult to analyze whether there is an association between undernourished patients evaluated using the PNI and atrial tachycardia recurrence after CA.

In contrast, the CONUT score identified 30% of patients as being undernourished. According to this classification, there was a significant difference in atrial tachyarrhythmia recurrence between the undernutrition and normal nutrition groups. However, in this study, undernutrition status determined by the CONUT score was not as effective for predicting atrial tachyarrhythmia recurrence as that determined by the GNRI score. This result may be explained by the fact that 34% of all eligible patients in this study were administered lipid-lowering agents. Because the CONUT score includes serum cholesterol levels as 1 of its 3 elements, the score may not accurately reflect the nutritional status of patients treated with lipid-lowering drugs. In fact, the subanalyses revealed that undernutrition status determined by the CONUT score failed to identify patients at risk of AF recurrence among those taking lipid-lowering drugs (Figure 4). Conversely, malnutrition assessed using the CONUT score was an independent predictor of AF recurrence among patients not taking lipid-lowering drugs (Table 4). Therefore, undernutrition determined by the CONUT score may be a sensitive predictor of AF recurrence in the group limited to patients not taking lipid-lowering drugs.

Undernutrition status determined using the GNRI score appeared to be the most applicable predictor of postoperative AF recurrence in patients undergoing CA for AF. The GNRI is a nutritional index calculated using the ratio of body weight to the ideal body weight and serum albumin levels, and unlike the CONUT score it is not affected by cholesterol levels. The association between a low BMI and high AF recurrence after CA has been demonstrated in previous studies.⁹^,¹⁰ Thus, the GNRI score, which consists of not only serum markers but also anthropometric factors, may be advantageous in predicting AF recurrence after CA over the scores derived only from blood chemistry or BMI.

Although the pathophysiological mechanism has not been fully elucidated, several hypotheses have been proposed regarding the association between the prevalence of AF and undernutrition. One theory is that the high adiponectin levels observed in underweight individuals are associated with an increased risk of AF.⁸ Another theory is that the loss of expression of myostatin, which is an important mediator of sarcopenia, may act as a substrate for AF.⁸ Some studies have linked AF development to a deficiency of trace elements or vitamins.⁸^,¹⁵ Thus, theoretically, undernutrition may promote the occurrence of AF. The results of this study are in line with those previous findings. In addition, in this study the undernourished patients tended to have a lower LVEF, lower eGFR, larger LAD, and higher prevalence of HF and coronary artery disease at baseline than those with normal nutrition (Table 1). Some reports have revealed an association between these factors and the post-ablation AF recurrence rate.¹¹^,¹⁶^–¹⁸ Therefore, this clinical aspect may be one of the explanations for a higher AF recurrence rate after CA in patients with undernutrition than in those with normal nutrition.

Future Directions

Nutritional status may be taken into consideration when making a shared decision with the patients regarding CA for AF. Patients who are preoperatively identified as malnourished and at a high risk of tachyarrhythmia recurrence after CA for AF may require careful postoperative observation and follow-up. This may prevent AF recurrence or reduce the AF burden via appropriate therapeutic interventions (i.e., additional CA for the substrate or administration of antiarrhythmic drugs) in such patients. In addition, intervening on factors responsible for AF substrate development has been reported to reduce the recurrence of AF after AF ablation.¹⁹^,²⁰ Identifying the causes of undernutrition and subsequent appropriate nutritional intervention may improve post-CA outcomes in patients with AF and malnutrition. Further prospective studies are warranted to clarify the association of nutritional status with AF recurrence after CA, as well as the benefit of nutritional intervention in patients with preprocedural malnutrition.

Study Limitations

Several limitations of this study must be addressed. First, this was a retrospective study conducted at a single center, although the registration and systematic follow-up after CA at our hospital was the basis for the analysis. The total study population consisted of patients who were scheduled to undergo ablation for AF and had relatively well-preserved nutritional status, and most were classified as having normal or mildly impaired nutrition. Second, the nutritional status was assessed only once, based on the examination conducted 1 week prior to CA, and the status may have changed during the post-CA period. Finally, some patients may have had underlying diseases that remained undetected, and these may have been responsible for the undernutrition.

Conclusions

Assessment of preoperative malnutrition using nutrition scoring tools was useful in predicting the prognosis of AF after CA. Patients with undernutrition status classified as per the CONUT and GNRI scores had a significantly higher atrial tachyarrhythmia recurrence rate after CA for AF than those with normal nutrition status. The GNRI may be the most suitable nutrition scoring tool for predicting arrhythmia recurrence in patients undergoing CA for AF, whereas undernutrition status determined using the CONUT score may be predictive of AF recurrence in those not taking lipid-lowering drugs.

Disclosures

S.Y. is affiliated with a department sponsored by Medtronic Japan. T.M. is a member of Circulation Journal’s Editorial Team. All other authors declare no conflicts of interest.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

IRB Information

Research involving human participants was conducted in accordance with the Declaration of Helsinki and the ethical standards of the responsible committee on human experimentation (institutional or regional). The study design was approved by the Institutional Review Board of Ogaki Municipal Hospital (approval no. 20181025-2). All participants were notified that they would be included in the study, and we explained to them that they were free to opt out at any time.

Data Availability

The deidentified participant data will not be shared.

Supplementary Files

Please find supplementary file(s);

http://dx.doi.org/10.1253/circj.CJ-21-0218

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