The impact of malnutrition on atrial fibrillation recurrence post ablation |
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| Authors: | Shijie Zhu Haiyu Zhao Muhan Zheng Jian Peng |
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| Affiliation: | 1. Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China;2. Department of Rheumatology and Immunology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China;3. Department of Cardiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China;4. Department of Rheumatology and Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong Province, China |
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| Abstract: | Background and aimsBoth malnutrition and atrial fibrillation (AF) are the major health problems in modern society. Only a few studies focused on the relationship between malnutrition and recurrence of atrial arrhythmias post AF ablation (AF recurrence), which used body mass index (BMI) as nutrition assessment tool. However, BMI can't credibly reflect body composition and has limitation in patients with water-sodium retention. In this study, we used controlling nutritional status score (CONUT score) and geriatric nutritional risk index (GNRI) to identify the malnutrition patients and explored the effect of malnutrition on AF recurrence.Methods and resultsThis retrospective study included 246 patients who underwent AF ablation. During a median 11-month follow-up, 77 patients (31.3%) experienced AF recurrence. The recurrence group had higher CONUT score (2.3 ± 1.5 vs. 0.9 ± 1.0, P < 0.001) and lower GNRI (99.9 ± 7.6 vs. 103.9 ± 5.6, P < 0.001). After balancing the traditional risk factors, both CONUT score (OR: 2.614, 95%CI: 1.831–3.731, P < 0.001) and GNRI (OR: 0.884, 95%CI: 0.828–0.944, P < 0.001) were the independent predictors for AF recurrence. Pre-ablation CONUT score ≥1 and GNRI≥95.66 are indicative of AF recurrence. Adding CONUT score or GNRI to the base prediction model for AF recurrence significantly improved the discrimination and calibration. However, adding BMI to the base prediction model did not improve the model performance.ConclusionsCONUT score and GNRI are ideal tools to evaluate the nutrition status of AF patients. Undernourished patients are more likely to suffer from AF recurrence. Improving nutrition status may be a potential target for reducing the postoperative recurrence rate. |
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| Keywords: | Atrial fibrillation Malnutrition Recurrence AF" },{" #name" :" keyword" ," $" :{" id" :" kwrd0030" }," $$" :[{" #name" :" text" ," _" :" atrial fibrillation BMI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0040" }," $$" :[{" #name" :" text" ," _" :" body mass index CONUT score" },{" #name" :" keyword" ," $" :{" id" :" kwrd0050" }," $$" :[{" #name" :" text" ," _" :" Controlling nutritional status score GNRI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0060" }," $$" :[{" #name" :" text" ," _" :" Geriatric nutritional risk index NYHA" },{" #name" :" keyword" ," $" :{" id" :" kwrd0070" }," $$" :[{" #name" :" text" ," _" :" New York Heart Association CHD" },{" #name" :" keyword" ," $" :{" id" :" kwrd0080" }," $$" :[{" #name" :" text" ," _" :" Coronary heart disease OSAHS" },{" #name" :" keyword" ," $" :{" id" :" kwrd0090" }," $$" :[{" #name" :" text" ," _" :" Obstructive sleep apnea-hypopnea syndrome NT-pro BNP" },{" #name" :" keyword" ," $" :{" id" :" kwrd0100" }," $$" :[{" #name" :" text" ," _" :" N-terminal Pro-Brain Natriuretic Peptide LVEF" },{" #name" :" keyword" ," $" :{" id" :" kwrd0110" }," $$" :[{" #name" :" text" ," _" :" Left ventricular ejection fraction PVI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0120" }," $$" :[{" #name" :" text" ," _" :" Pulmonary vein isolation AADs" },{" #name" :" keyword" ," $" :{" id" :" kwrd0130" }," $$" :[{" #name" :" text" ," _" :" Antiarrhythmic drugs ROC" },{" #name" :" keyword" ," $" :{" id" :" kwrd0140" }," $$" :[{" #name" :" text" ," _" :" Receiver operating characteristic AUC" },{" #name" :" keyword" ," $" :{" id" :" kwrd0150" }," $$" :[{" #name" :" text" ," _" :" Area under the curve Harrell's CI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0160" }," $$" :[{" #name" :" text" ," _" :" Harrell's concordance index LLR" },{" #name" :" keyword" ," $" :{" id" :" kwrd0170" }," $$" :[{" #name" :" text" ," _" :" Log likelihood rate NRI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0180" }," $$" :[{" #name" :" text" ," _" :" Net reclassification index IDI" },{" #name" :" keyword" ," $" :{" id" :" kwrd0190" }," $$" :[{" #name" :" text" ," _" :" Integrated discrimination index |
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