Material and Method: The retrospective study included 516 patients who had CTO on coronary angiography. The nutritional status of the patients was evaluated with PNI and CONUT scores, and categorical groups were formed according to these results and compared.

Results: All-cause mortality occurred in 127 (24.6%) patients during median follow-up period of 48 months. At the end of the follow-up period, the patients were divided into two groups as survival and non-survival. In terms of all-cause mortality, mean PNI score (47,87±6,31 vs. 42,41±6,57) and median CONUT score (1(2) vs. 3(3)) differed significantly between the surviving and non-surviving groups (p <0.001). Kaplan-Meier analysis showed a significant difference in survival between the PNI and CONUT scores cathegorical groups (p <0.001).

Conclusion: Higher CONUT scores and lower PNI scores were found to be associated with poor outcomes in CTO patients. Evaluation and monitoring of nutritional status in CTO patients by these nutritional scores may provide additional prognostic information.

Assessment of nutritional status is highly important in cardiac conditions, as in all diseases. The development or presence of cachexia is corraleted with a worse prognosis as in most diseases. To date, various methods and indices have been proposed for the assessment of nutritional situation and have been used to predict poor prognosis in various clinical conditions ^2,3.

Serum parameters such as albumin level and lymphocyte count are commonly used in nutritional indices. Moreover, admission hypoalbuminemia has been shown to be an independent predictor of long-term mortality and the development of advanced heart failure in patients who undergoing primary percutaneous coronary intervention (PCI) with ST segment elevation myocardial infarction (STEMI) ⁴. In a recent study, serum albumin levels at admission were found to be statistically lower in the massive pulmonary embolism group than in the submassive and nonmassive groups ⁵. On the other hand, a relationship has been reported among a single nutritional parameter, such as albumin, and coronary collateral circulation (CCC), which is a predictor of mortality in patients with CTO ⁶. Prognostic Nutritional Index (PNI) is calculated by total lymphocyte count and serum albumin and reflects immunonutritional status and the risk of developing postoperative complications ⁷. Controlling Nutritional Status (CONUT) is an effective instrument for early finding and continuous check of hospital malnutrition, calculated based on serum albumin level, lymphocyte count and total cholesterol level ⁸.

The aim of this study was to examine the effect of nutritional situation determined by objective nutritional indices on the development of all-cause mortality and prognosis in patients with CTO.

Laboratory parameters and nutritional indices
Blood samples were routinely obtained from venous blood during hospital admission. Complete blood count (CBC) was performed using an Abbott Analyzer system and hematological indices were calculated for each patient. Total cholesterol, highdensity lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride, and other biochemical levels were measured using an Abbott system. Left ventricular ejection fraction (LVEF) was measured using transthoracic 2D echocardiography during hospitalization. Table 1 presents the calculation methods of PNI and CONUT scores and the risk classifications performed according to total scores ⁹.

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Table 1: Methods for calculating nutritional indexes and the formation of nutritional status groups.

Based on PNI scores, patients were categorized as follows: (i) <35; severe malnutrition, (ii) 35-38; moderate malnutrition, and (iii) >38; no malnutrition. Based on CONUT scores, patients were categorized as follows: (I) <2; no malnutrition, (II) 2-4; mild malnutrition, (III) 5-8; moderate malnutrition, and (IV) >8; severe malnutrition. Since the number of patients in the severe malnutrition group was remarkably low, the moderate and severe malnutrition groups were grouped together as a single group.

Statistical analysis
We analyzed our data using SPSS for Windows version 25.0. First, we analyzed the normality of the distribution of our data with the Shapiro-Wilk tests or Kolmogorov-Smirnov. We expressed abnormally distributed variables as IQR (interquartile range). Continuous variables were expressed as mean ± standard deviation (SD) or first and third percentiles (Q1-Q3) and median based on the distribution patterns of the data. Continuous variables were compared using Mann-Whitney U test or student t-test as appropriate. We used Chi-square test/Fischer's Exact tests to analyze categorical variables and expressed the variables as percentages (%). In the case of more than one group, we compared groups using one-way analysis of variance (ANOVA) or the Kruskal-Wallis test as appropriate. We used univariate and multivariate analyzes with logistic regression models to identify predictors of all caused mortality. We then performed multivariate logistic regression analyzes to identify independent predictors of all caused mortality. Survival rates in the groups formed based on PNI and CONUT scores were analyzed using the Kaplan-Meier method. A p value of <0.05 was considered significant.

Baseline demographic characteristics
Median follow-up period was 48 months. Patients comprised 368 (71.3%) men and 148 (28.7%) women with a mean age of 63.2 ± 11.1 years. Total mortality occurred in 127 (24.6%) patients within a median period of 35 months after the procedure (Table 2).

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Table 2: Baseline demographic characteristics and biochemical variables and nutritional indices at admission.

Non-surviving group, compared to the surviving group, had a higher prevalence of previous hypertension (47.2% vs. 30.8%), previous chronic kidney disease (11.8% vs. 3.3%), previous heart failure (21.3% vs. 6.2%), and previous cerebrovascular events (7.9 vs. 1.0%).

Three different treatment methods including medical treatment (n= 180; 34.9%), coronary artery bypass graft (CABG) (n= 74; 14.3%) and PCI (n= 262; 50.8%) were used for CTO treatment. Mortality was significantly lower in the PCI group (p <0.001).

Admission Biochemical variables and nutritional indices at admission
Table 2 presents admission biochemical variables and nutritional indices in the surviving and non-surviving groups. Accordingly, LVEF (43.63% vs. 50.92%), hemoglobin (Hgb) (12.94% vs. 13.79%), hematocrit (HCT) (38.94% vs. 41.58%), lymphocyte count (1890.1±777.7 vs. 2241.8±757.8), and albumin level (3.29±0.47 vs. 3.66±0.42 g/dl) were significantly lower in the non-surviving group compared to the surviving group (p <0.001 for all). In terms of all-cause mortality, mean PNI score (47,87±6,31 vs. 42,41±6,57) and median CONUT score (1(2) vs. 3(3)) differed significantly between the surviving and non-surviving groups (p <0.001).

As seen in Figure 1, according to Kaplan-Meier analysis, a significant difference was observed between the categorical groups of PNI and CONUT score in terms of survival time. (p <0.001). However, it is noteworthy that this difference started from the first stages of the follow-up period.

Table 3 presents the results of univariate and multivariate regression analysis that was performed to determine the effect of parameters on mortality.

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Table 3: Predictors of mortality in univariate and multivariate regression analysis.

The analysis indicated that advanced age, heart failure, high glucose level, low PNI score and high CONUT score at admission were independent predictors of mortality. When the groups with nutritional status indicators are compared among themselves, it is note-worthy that the prognosis worsens as the nutritional group worsens.

Successful recanalization of CTO has been shown to result in improved LVEF and regional wall motion ⁹. In our study, a significant relationship was found between low LVEF and the mortality risk and heart failure was found to be an independent predictor of mortality. These findings suggest that LVEF should be monitored closely since it may be useful in the prediction of the prognosis.

Studies investigating CTO and stable coronary artery disease (SCAD) have shown that successful interventional therapy has a positive effect on survival in patients with increased myocardial ischemia ¹². This benefit is often considered to result from a reduction in ischemic burden with successful PCI in patients with greater ischemic burden ¹³. The present study evaluated 516 CTO patients and revealed that successful PCI reduced the risk of all-cause mortality over a median follow-up period of 48 months. Nonetheless, the criteria used in the selection of the intervention methods administered in our patients were not clearly examined, and thus it may be inappropriate to consider that PCI is superior to CABG in intervention therapy.

A previous study followed up 1092 CTO patients for medium period of 39 months and reported that the presence of chronic kidney disease increased the frequency of events and all-cause death. The authors also noted that all the patients, regardless of the presence of chronic kidney disease, benefited from revascularization, although this benefit was lower in patients with chronic kidney disease ¹⁴. Similarly, in our study, a significant relationship was found between the presence of chronic kidney disease and mortality in favor of poor prognosis.

In the presence of severe coronary artery stenosis, good CCC may improve myocardial ischemia, preserve myocardial contractility, improve clinical symptoms, reduce the incidence of myocardial infarction, and reduce myocardial infarct size, thereby leading to reduced mortality from ischemic events ^15,16. A recent study evaluated 128 CTO patients and found a positive correlation between increased serum albumin level and good CCC development and also found a negative correlation between diabetes and CCC devel-opment ¹⁷. In our study, low serum albumin level and high blood glucose level were found to have a significant relationship with all-cause mortality. Based on these findings, we consider that the close relationship between these parameter changes and CCC development is a clear indication of the importance of CCC development in coronary artery diseases.

Limitations
Our study was limited since it had a retrospective design and thus did not evaluate the changes in laboratory parameters during the follow-up period. Additionally, it also could not assess other parameters associated with malnutrition during blood sampling, such as body mass index (BMI), and thus could not evaluate malnutrition thoroughly.

Acknowledgements
We thank the editors and anonymous reviewers for their outstanding feedback. I would like to express my sincere thanks to Dr. Hasan Akkoç from the Department of Pharmacology of our university, who kindly helped during the statistical evaluation.

1) Puma JA, Sketch MH Jr, Tcheng JE et al. Percutaneous revascularization of chronic coronary occlusions: an overview. J Am Coll Cardiol 1995; 26: 1-11.

2) Satomura H, Wada H, Sakakura K et al. Congestive heart failure in the elderly: comparison between reduced ejection fraction and preserved ejection fraction. J Cardiol 2012; 59: 215-9.

3) Blondé-Cynober F, Morineau G, Estrugo B, Fillie E, Aussel C, Vincent JP. Diagnostic and prognostic value of brain natriuretic peptide (BNP) con-centrations in very elderly heart disease patients: specific geriatric cut-off and impacts of age, gender, renal dysfunction, and nutritional status. Arch Gerontol Geriatr 2011; 52: 106-10.

4) Oduncu V, Erkol A, Karabay CY et al. The prognostic value of serum albumin levels on admission in patients with acute ST-segment elevation myocardial infarction undergoing a primary percutaneous coronary intervention. Coron Artery Dis 2013; 24: 88-94.

5) Telo S, Kuluozturk M. The Relationship Between Serum Albumin Levels and Clinical Forms of Acute Pulmonary Embolism. Firat Med J 2021; 26: 160-4. 6. Chen X, Lin Y, Tian L, Wang Z. Correlation between ischemia-modified albumin level and coronary collateral circulation. BMC Cardiovasc Disord 2020; 20: 326.

7) Sagawa M, Yoshimatsu K, Yokomizo H et al. Assessment of host status in patients treated with mFOLFOX6 adjuvant chemotherapy after colorectal cancer surgery. Gan To Kagaku Ryoho 2013; 40: 1587-9.

8) Fukushima K, Ueno Y, Kawagishi N et al. The nutritional index 'CONUT' is useful for predicting long-term prognosis of patients with endstage liver diseases. Tohoku J Exp Med 2011; 224: 215-9. 9. Chadid P, Markovic S, Bernhardt P, Hombach V, Rottbauer W, Wöhrle J. Improvement of regional and global left ventricular function in magnetic resonance imaging after recanalization of true coronary chronic total occlusions. Cardiovasc Revasc Med 2015; 16: 228-32.

10) Basta G, Chatzianagnostou K, Paradossi U,et al. The prognostic impact of objective nutritional indices in elderly patients with ST-elevation myo-cardial infarction undergoing primary coronary intervention. Int J Cardiol 2016; 221: 987-92.

11) Narumi T, Arimoto T, Funayama A et al. Prognostic importance of objective nutritional indexes in patients with chronic heart failure. J Cardiol 2013; 62: 307-13.

12) Jang WJ, Yang JH, Choi SH et al. Long-term survival benefit of revascularization compared with medical therapy in patients with coronary chronic total occlusion and well-developed collateral circulation. JACC Cardiovasc Interv 2015; 8: 271-9.

13) Safley DM, Koshy S, Grantham JA et al. Changes in myocardial ischemic burden following percutaneous coronary intervention of chronic total occlusions. Catheter Cardiovasc Interv 2011; 78: 337-43.

14) Zhang QB, Chen LM, Li M, Cui YQ, Zhao CY, Cui LQ. Influence of chronic kidney disease on the outcome of patients with chronic total occlusion. Am J Transl Res 2016; 8: 196-208.

15) Seiler C, Stoller M, Pitt B, Meier P. The human coronary collateral circulation: development and clinical importance. Eur Heart J 2013; 34: 2674-82.

16) Jamaiyar A, Juguilon C, Dong F et al. Cardioprotection during ischemia by coronary collateral growth. Am J Physiol Heart Circ Physiol 2019; 316: H1-9.