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Controlling Nutritional Status (CONUT) score as a predictive marker for short-term complications following gastrectomy of gastric cancer: a retrospective study

Abstract

Background

It is well established that the controlling nutritional status (CONUT) score was correlated with long-term outcomes in gastric cancer (GC), but the significance of CONUT for postoperative short-term outcomes remains unclear. The study aimed to characterize the relationship between CONUT and short-term complications following gastrectomy of GC.

Methods

We collected data on 1479 consecutive GC patients at Nanjing Drum Tower Hospital between January 2016 and December 2018. Univariate and multivariate analyses of predictive factors for postoperative complications were performed. The cutoff value of the CONUT score was determined by Youden index.

Results

Among all of the patients, 431 (29.3%) patients encountered postoperative complications. Multivariate analyses identified CONUT was an independent predictor for postoperative short-term complications (OR 1.156; 95% CI 1.077–1.240; P < 0.001). Subgroup analysis elucidated that CONUT was related to postoperative complications both in early gastric cancer and advanced gastric cancer. We further explored that patients with high CONUT score had prolonged hospital stay (12.3 ± 6.0 vs 11.1 ± 4.6, P < 0.001) and more total hospital charges (7.6 ± 2.4 vs 7.1 ± 1.6, P < 0.001).

Conclusions

The present study demonstrated that the preoperative CONUT was an independent predictor for short-term complications following gastrectomy of GC.

Peer Review reports

Background

Gastric cancer (GC) is one of the most common digestive tract cancers worldwide [1]. To this day, radical gastrectomy remains the main option for resectable GC. Despite significant advance has been seen in surgical techniques in recent years, the incidence of complications after radical gastrectomy remains at 15%-25% [2, 3]. Therefore, it is necessary to accurately predict postoperative complications to help perioperative management of GC patients.

Malnutrition is common in GC patients because of a decrease in food intake and energy expenditure. The poor nutritional condition was reported to be correlated with postoperative complications and a worse prognosis [4, 5]. Moreover, immunological status was also regarded as a prognostic marker for GC patients [6, 7]. Several nutritional and inflammatory indicators were monitored routinely before GC surgery, including albumin, total cholesterol, total lymphocytes, hemoglobin, C-reactive protein, neutrophils, and platelet [8,9,10]. Furthermore, more reliable combined scoring systems were developed to accurately predict patient prognoses, such as neutrophil to lymphocyte ratio (NLR), Prognostic Nutritional Index (PNI), and platelet to lymphocyte ratio (PLR) [8, 11, 12].

Controlling nutritional status (CONUT) score is another nutritional scoring system, covering serum albumin, cholesterol, and lymphocyte counts [13]. Recently, several studies elucidated that CONUT was correlated with the long-term prognosis of different kinds of cancer [14,15,16,17,18]. However, it remains controversial whether CONUT could predict short-term outcomes following tumor resection [19, 20]. Also, little is known about the connection between CONUT and postoperative complications of GC [21]. Therefore, this study intended to characterize the significance of CONUT on short-term complications following gastrectomy of GC.

Methods

Patients

We collected data on 1479 consecutive GC patients at Nanjing Drum Tower Hospital between January 2016 and December 2018. All patients underwent curative (R0) gastrectomy and were histologically confirmed. Exclusion criteria include (1) incomplete clinical data; (2) Stage 0 cancer; (3) multi-visceral resection; (4) preoperative radiotherapy or chemotherapy; (5) previous stomach surgery.

Data collection

The following three types of parameters were extracted: preoperative, intraoperative, and postoperative characteristics. Preoperative index involved age, sex, body mass index, the American Society of Anesthesiologists (ASA) grade, comorbidities (diabetes mellitus, hypertension, and previous abdominal surgery), and laboratory data (neutrophil count, lymphocyte count, platelet count, serum albumin, C-reactive protein, and total cholesterol). The intraoperative features contained type of resection, surgical approach, operation time, and blood loss. Postoperative characteristics included tumor depth, pTNM stage (7th edition), short-term complications, postoperative stay, and hospital costs. The postoperative short-term complications were defined as morbidity that occurred during hospitalization or within 30 days after surgery. The complications were classified according to the Clavien-Dindo (CD) classification system [22].

Scoring systems of the general condition

Preoperative immune-nutritional and inflammatory scoring systems, including NLR, PLR, PNI, and CONUT, were examined. The NLR and PLR were brought out by dividing the neutrophil and platelet count by the lymphocyte count, respectively [23]. The PNI was obtained from the following formula: (10 × albumin level [g/dL]) + (0.005 × lymphocyte count [number/mm3]) [24]. The CONUT was calculated using serum albumin, total cholesterol concentrations, and total lymphocyte count (Additional file 1: Table S1) [13].

Statistical analysis

Continuous variables were summarized with means ± SD and compared using Student’s t test or Mann–Whitney U test. Categorical variables were summarized with numbers and compared using the Chi squared test or the Fisher exact test. The correlation between postoperative complications and clinicopathological factors were investigated using univariate and multivariate analysis. Variables that were statistically significant in univariate analysis were selected for further multivariate analysis. Binary logistic regression models (Forward: LR) were performed for multivariate analyses. The cut-off value of the CONUT score was determined by Youden index. All P values were two-sided and statistical differences were termed as P value < 0.05. All statistical analyses were carried out in SPSS 19.0 (Chicago, IL, USA).

Results

Patient characteristics

Details of the patient characteristics were summarized in Table 1. This study enrolled 1479 GC patients, including 1083 (73.2%) male and 396 (26.8%) female. The median age was 60 (range: 21–96 years). Diabetes mellitus and hypertension were present in 130 (8.8%) and 485 (32.8%), respectively. Most patients (n = 1403, 94.9%) underwent open gastrectomy. The number of patients who underwent distal gastrectomy, proximal gastrectomy, total gastrectomy was 613 (41.4%), 162 (11.0%), 704 (47.6%), respectively. The overall incidence of postoperative short-term complications was 29.3% (n = 431).

Table 1 Demographic and clinical features of patients

Risk factors correlated with postoperative short-term complications

As shown in Table 2, univariate analyses elucidated that postoperative short-term complications were associated with age, sex, low serum albumin, low total cholesterol, PLR, PNI, CONUT score, type of resection (proximal gastrectomy vs. total gastrectomy), and operation time. Multivariate analyses further revealed that age, gender, CONUT score, type of resection (proximal gastrectomy vs. total gastrectomy), and operation time were independent risk factors for postoperative short-term complications.

Table 2 Univariate and multivariate analyses of risk factors associated with postoperative complications

We further explored the relationship between postoperative short-term complications and CONUT score in different pathological stages. Based on the Youden index, the appropriate cut-off value was 2 for the CONUT score. Patients were categorized into two groups: high CONUT score (≥ 2), low CONUT score (< 2). As shown in Table 3, Postoperative complications were more frequent in high CONUT group in stage I/II/III. From another perspective, the CONUT score was associated with postoperative complications both in early gastric cancer and advanced gastric cancer.

Table 3 Relationship between postoperative complications and CONUT in different stages

Preoperative CONUT score as a predictor for postoperative complications

Of the 1479 patients, 431 (29.3%) encountered postoperative short-term complications, and 64 (4.3%) encountered major complications (grade III or more). The details of postoperative complications were presented in Table 4. Postoperative complications were more frequent in high CONUT group than low CONUT group (33.9% vs 22.6%; p < 0.001). Major complications were also more frequent in the high CONUT group (5.4% vs 2.9%; p = 0.018). Congruently, patients with high CONUT scores had prolonged hospital stay (12.3 ± 6.0 vs 11.1 ± 4.6, P < 0.001) and more hospital costs (7.6 ± 2.4 vs 7.1 ± 1.6, P < 0.001).

Table 4 Comparisons of postoperative complications associated with CONUT

Discussion

In this study, we evaluated the predictive ability of various nutritional and inflammatory parameters for short-term complications following gastrectomy of GC, including NLR, PLR, PNI, and CONUT. Only CONUT was found to be statistically correlated with postoperative complications both in univariate and multivariate analyses. These findings revealed that a high CONUT score was a strong predictor for postoperative short-term complications.

CONUT was initially proposed to assess patients' nutritional conditions in 2005 by Gonzalez and colleagues [13]. It was obtained from serum albumin concentration, total cholesterol concentration, and total lymphocyte count. The easy-to-use index could provide a prompt and accurate preoperative evaluation. It has been well established that preoperative CONUT served as a prognostic factor for long-term outcomes in several cancers, including renal cell cancer, hepatocellular cancer, lung cancer, and colorectal cancer [25,26,27,28,29]. As for GC, recent studies also elucidated that CONUT was significantly related to long-term prognosis [14, 30,31,32]. However, the correlation between CONUT and short-term outcomes remained unclear because the number of relevant studies was small [4, 21]. Ryo et al. recently reported that stage II/III GC patients with high preoperative CONUT scores were more likely to suffer postoperative pneumonia [31]. Li et al. elucidated that high CONUT was related to severe postoperative complications [33]. The present study thoroughly accessed the ability of the preoperative CONUT in predicting short-term outcomes following gastrectomy. Our results suggest that the incidence of postoperative overall complications or major complications was higher in patients with high CONUT scores. Furthermore, prolonged hospital stay and more total hospital charges were also observed in patients with high CONUT scores. Therefore, the current study shed light on that the CONUT score might be a useful predictor, not only for long-term outcomes but also for short-term outcomes in GC patients.

The biological mechanism why CONUT could be a predictor for short-term outcomes in GC has not been clearly understood. Here we tried to explain the reasons from each parameter of CONUT. Firstly, serum albumin, representing protein metabolism, is a strong marker of nutritional status. Low serum albumin is not only correlated with poor prognosis in GC but also reported to be a promising predictor for short-term outcomes following gastrectomy [10, 34, 35]. Gunder et al. recently reported that albumin levels were better to predict both short-term and long-term GC patient outcomes than complex parameters (PNI, NLR, PLR, and SII) [36]. Serum albumin level was so significant that it has twice the weight of the other components in the CONUT score. Multivariate analysis revealed that the CONUT rather that albumin level was correlated with postoperative short-term complications. Secondly, total cholesterol level, representing lipid metabolism, has been found to be related to tumor progression and overall survival in various kinds of cancer [37, 38]. Several studies suggested that a low cholesterol level might affect the antioxidant reserve and inflammatory response [39, 40]. Finally, total lymphocyte, representing host immunocompetence, was also reported to be correlated with the prognosis of GC patients [41]. The combination of these three components into CONUT allows different phases of nutrition to be included, which enhances the accuracy to assess general conditions.

We acknowledged some potential limitations in this study. First, it was a retrospective, single-center study. Patients enrolled were from just one institution and were ethnically homogeneous. Second, the potential factors influencing preoperative immune-nutritional status were not accessed, such as cancer-related inflammation, chronic renal failure, and liver cirrhosis. Third, the suitable cutoff value for the CONUT score was not yet unified. Therefore, more studies are warranted for elucidating the predictive ability of CONUT for postoperative complications of GC patients.

Conclusion

In conclusion, the present study demonstrated that the preoperative CONUT was an independent predictor for short-term complications following gastrectomy of GC.

Availability of data and materials

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

BMI:

Body mass index

CRP:

C-reactive protein

NLR:

Neutrophil-to-lymphocyte ratio

PLR:

Platelet-to-lymphocyte ratio

PNI:

Prognostic Nutritional Index

CONUT:

Controlling Nutritional Status

ASA:

American Society of Anesthesiologists

References

  1. 1.

    Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Ca-a Cancer J Clin. 2018;68(6):394–424.

    Article  Google Scholar 

  2. 2.

    Kim W, Kim H-H, Han S-U, Kim M-C, Hyung WJ, Ryu SW, Cho GS, Kim CY, Yang H-K, Park DJ, et al. Decreased morbidity of laparoscopic distal gastrectomy compared with open distal gastrectomy for stage I gastric cancer short-term outcomes from a multicenter randomized controlled trial (KLASS-01). Ann Surg. 2016;263(1):28–35.

    Article  Google Scholar 

  3. 3.

    Lee K-G, Lee H-J, Yang J-Y, Oh S-Y, Bard S, Suh Y-S, Kong S-H, Yang H-K. Risk factors associated with complication following gastrectomy for gastric cancer: retrospective analysis of prospectively collected data based on the Clavien–Dindo system. J Gastrointest Surg. 2014;18(7):1269–77.

    Article  Google Scholar 

  4. 4.

    Takagi K, Domagala P, Polak WG, Buettner S, Ijzermans JNM. The controlling nutritional status score and postoperative complication risk in gastrointestinal and hepatopancreatobiliary surgical oncology: a systematic review and meta-analysis. Ann Nutr Metab. 2019;74(4):303–12.

    CAS  Article  Google Scholar 

  5. 5.

    Wang S-H, Zhai S-T, Lin H. Role of Prognostic Nutritional Index in patients with gastric cancer: a meta-analysis. Minerva Med. 2016;107(5):322–7.

    PubMed  Google Scholar 

  6. 6.

    Wang SC, Chou JF, Strong VE, Brennan MF, Capanu M, Coit DG. Pretreatment neutrophil to lymphocyte ratio independently predicts disease-specific survival in resectable gastroesophageal junction and gastric adenocarcinoma. Ann Surg. 2016;263(2):292–7.

    Article  Google Scholar 

  7. 7.

    Hsu J-T, Wang C-C, Le P-H, Chen T-H, Kuo C-J, Lin C-J, Chou W-C, Yeh T-S. Lymphocyte-to-monocyte ratios predict gastric cancer surgical outcomes. J Surg Res. 2016;202(2):284–90.

    CAS  Article  Google Scholar 

  8. 8.

    Kubota T, Shoda K, Konishi H, Okamoto K, Otsuji E. Nutrition update in gastric cancer surgery. Ann Gastroenterol Surg. 2020.

  9. 9.

    Ge X, Dai X, Ding C, Tian H, Yang J, Gong J, Zhu W, Li N, Li J. Early postoperative decrease of serum albumin predicts surgical outcome in patients undergoing colorectal resection. Dis Colon Rectum. 2017;60(3):326–34.

    Article  Google Scholar 

  10. 10.

    Liu Z-J, Ge X-L, Ai S-C, Wang H-K, Sun F, Chen L, Guan W-X. Postoperative decrease of serum albumin predicts short-term complications in patients undergoing gastric cancer resection. World J Gastroenterol. 2017;23(27):4978–85.

    CAS  Article  Google Scholar 

  11. 11.

    Luo Z, Zhou L, Balde AI, Li Z, He L, ZhenWei C, Zou Z, Huang S, Han S, Zhou MW, et al. Prognostic impact of preoperative prognostic nutritional index in resected advanced gastric cancer: a multicenter propensity score analysis. Ejso. 2019;45(3):425–31.

    Article  Google Scholar 

  12. 12.

    Zhang X, Chen X, Wu T, Zhang Y, Yan K, Sun X. Modified glasgow prognostic score as a prognostic factor in gastriccancer patients: a systematic review and meta-analysis. Int J Clin Exp Med. 2015;8(9):15222–9.

    PubMed  PubMed Central  Google Scholar 

  13. 13.

    Ignacio de Ulibarri J, Gonzalez-Madrono A, de Villar NGP, Gonzalez P, Gonzalez B, Mancha A, Rodriguez F, Fernandez G. CONUT: a tool for controlling nutritional status First validation in a hospital population. Nutr Hosp. 2005;20(1):38–45.

    CAS  PubMed  Google Scholar 

  14. 14.

    Kuroda D, Sawayama H, Kurashige J, Iwatsuki M, Eto T, Tokunaga R, Kitano Y, Yamamura K, Ouchi M, Nakamura K, et al. Controlling Nutritional Status (CONUT) score is a prognostic marker for gastric cancer patients after curative resection. Gastric Cancer. 2018;21(2):204–12.

    Article  Google Scholar 

  15. 15.

    Takagi K, Buettner S, Ijzermans JNM. Prognostic significance of the controlling nutritional status (CONUT) score in patients with colorectal cancer: a systematic review and meta-analysis. Int J Surg. 2020;78:91–6.

    Article  Google Scholar 

  16. 16.

    Li W, Li M, Wang T, Ma GZ, Deng YF, Pu D, Liu ZK, Wu Q, Liu XJ, Zhou QH. Controlling Nutritional Status (CONUT) score is a prognostic factor in patients with resected breast cancer. Sci Rep. 2020;10(1):1–10.

    Article  Google Scholar 

  17. 17.

    Shimose S, Kawaguchi T, Iwamoto H, Tanaka M, Miyazaki K, Ono M, Niizeki T, Shirono T, Okamura S, Nakano M, et al. Controlling Nutritional Status (CONUT) score is associated with overall survival in patients with unresectable hepatocellular carcinoma treated with lenvatinib: a multicenter cohort study. Nutrients. 2020;12(4):1076.

    CAS  Article  Google Scholar 

  18. 18.

    Suzuki H, Ito M, Takemura K, Nakanishi Y, Kataoka M, Sakamoto K, Tobisu KI, Koga F. Prognostic significance of the controlling nutritional status (CONUT) score in advanced urothelial carcinoma patients. Urol Oncol Semin Orig Investig. 2020;38(3):76-e11.

    Google Scholar 

  19. 19.

    Yoshida N, Baba Y, Shigaki H, Harada K, Iwatsuki M, Kurashige J, Sakamoto Y, Miyamoto Y, Ishimoto T, Kosumi K, et al. Preoperative nutritional assessment by Controlling Nutritional Status (CONUT) is useful to estimate postoperative morbidity after esophagectomy for esophageal cancer. World J Surg. 2016;40(8):1910–7.

    Article  Google Scholar 

  20. 20.

    Miyata T, Yamashita Y, Higashi T, Taki K, Izumi D, Kosumi K, Tokunaga R, Nakagawa S, Okabe H, Imai K, et al. The prognostic impact of Controlling Nutritional Status (CONUT) in intrahepatic cholangiocarcinoma following curative hepatectomy: a retrospective single institution study. World J Surg. 2018;42(4):1085–91.

    Article  Google Scholar 

  21. 21.

    Takagi K, Domagala P, Polak WG, Buettner S, Wijnhoven BPL, Ijzermans JNM. Prognostic significance of the controlling nutritional status (CONUT) score in patients undergoing gastrectomy for gastric cancer: a systematic review and meta-analysis. BMC Surg. 2019;19(1):129.

    Article  Google Scholar 

  22. 22.

    Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13.

    Article  Google Scholar 

  23. 23.

    Sun X, Liu X, Liu J, Chen S, Xu D, Li W, Zhan Y, Li Y, Chen Y, Zhou Z. Preoperative neutrophil-to-lymphocyte ratio plus platelet-to-lymphocyte ratio in predicting survival for patients with stage I–II gastric cancer. Chin J Cancer. 2016;35:1–7.

    CAS  Article  Google Scholar 

  24. 24.

    Nozoe T, Ninomiya M, Maeda T, Matsukuma A, Nakashima H, Ezaki T. Prognostic nutritional Index: A tool to predict the biological aggressiveness of gastric carcinoma. Surg Today. 2010;40(5):440–3.

    Article  Google Scholar 

  25. 25.

    Elghiaty A, Kim J, Jang WS, Park JS, Heo JE, Rha KH, Choi YD, Ham WS. Preoperative controlling nutritional status (CONUT) score as a novel immune-nutritional predictor of survival in non-metastatic clear cell renal cell carcinoma of 7cm on preoperative imaging. J Cancer Res Clin Oncol. 2019;145(4):957–65.

    Article  Google Scholar 

  26. 26.

    Ohba T, Takamori S, Toyozawa R, Nosaki K, Umeyama Y, Haratake N, Miura N, Yamaguchi M, Taguchi K, Seto T, et al. Prognostic impact of the Controlling Nutritional Status score in patients with non-small cell lung cancer treated with pembrolizumab. J Thorac Dis. 2019;11(9):3757–68.

    Article  Google Scholar 

  27. 27.

    Wang XB, Chen J, Xiang BD, Wu FX, Li LQ. High CONUT score predicts poor survival and postoperative HBV reactivation in HBV-related hepatocellular carcinoma patients with low HBV-DNA levels. Ejso. 2019;45(5):782–7.

    Article  Google Scholar 

  28. 28.

    Hirahara N, Tajima Y, Fujii Y, Kaji S, Kawabata Y, Hyakudomi R, Yamamoto T, Taniura T. Controlling Nutritional Status (CONUT) as a prognostic immunonutritional biomarker for gastric cancer after curative gastrectomy: a propensity score-matched analysis. Surg Endosc. 2019;33(12):4143–52.

    Article  Google Scholar 

  29. 29.

    Ahiko Y, Shida D, Horie T, Tanabe T, Takamizawa Y, Sakamoto R, Moritani K, Tsukamoto S, Kanemitsu Y. Controlling nutritional status (CONUT) score as a preoperative risk assessment index for older patients with colorectal cancer. BMC Cancer. 2019;19(1):1–8.

    Article  Google Scholar 

  30. 30.

    Liu X, Zhang D, Lin E, Chen Y, Li W, Chen Y, Sun X, Zhou Z. Preoperative controlling nutritional status (CONUT) score as a predictor of long-term outcome after curative resection followed by adjuvant chemotherapy in stage II–III gastric Cancer. BMC Cancer. 2018;18(1):699.

    Article  Google Scholar 

  31. 31.

    Ryo S, Kanda M, Ito S, Mochizuki Y, Teramoto H, Ishigure K, Murai T, Asada T, Ishiyama A, Matsushita H, et al. The Controlling Nutritional Status score serves as a predictor of short- and long-term outcomes for patients with stage 2 or 3 gastric cancer: analysis of a multi-institutional data set. Ann Surg Oncol. 2019;26(2):456–64.

    Article  Google Scholar 

  32. 32.

    Suzuki S, Kanaji S, Yamamoto M, Oshikiri T, Nakamura T, Kakeji Y. Controlling Nutritional Status (CONUT) score predicts outcomes of curative resection for gastric cancer in the elderly. World J Surg. 2019;43(4):1076–84.

    Article  Google Scholar 

  33. 33.

    Lin J-X, Lin L-Z, Tang Y-H, Wang J-B, Lu J, Chen Q-Y, Cao L-L, Lin M, Tu R-H, Huang C-M, et al. Which nutritional scoring system is more suitable for evaluating the short- or long-term prognosis of patients with gastric cancer who underwent radical gastrectomy? J Gastrointest Surg. 2020;24(9):1969–77.

    Article  Google Scholar 

  34. 34.

    Toiyama Y, Yasuda H, Ohi M, Yoshiyama S, Araki T, Tanaka K, Inoue Y, Mohri Y, Kusunoki M. Clinical impact of preoperative albumin to globulin ratio in gastric cancer patients with curative intent. Am J Surg. 2017;213(1):120–6.

    Article  Google Scholar 

  35. 35.

    Huang Q-X, Ma J, Wang Y-S. Significance of preoperative ischemia-modified albumin in operable and advanced gastric cancer. Cancer Biomark. 2018;22(3):477–85.

    CAS  Article  Google Scholar 

  36. 36.

    Guner A, Kim SY, Yu JE, Min IK, Roh YH, Roh C, Seo WJ, Cho M, Choi S, Choi YY, et al. Parameters for predicting surgical outcomes for gastric cancer patients: simple is better than complex. Ann Surg Oncol. 2018;25(11):3239–47.

    Article  Google Scholar 

  37. 37.

    Sun HL, Huang XQ, Wang ZM, Zhang GX, Mei YP, Wang YS, Nie ZL, Wang SK. Triglyceride-to-high density lipoprotein cholesterol ratio predicts clinical outcomes in patients with gastric cancer. Journal of Cancer. 2019;10(27):6829–36.

    CAS  Article  Google Scholar 

  38. 38.

    Li B, Huang DL, Zheng HL, Cai Q, Guo ZL, Wang SS. Preoperative serum total cholesterol is a predictor of prognosis in patients with renal cell carcinoma: a meta- analysis of observational studies. Int Braz J Urol. 2020;46(2):158–68.

    CAS  Article  Google Scholar 

  39. 39.

    Wang Q, Lau WY, Zhang B, Zhang Z, Huang Z, Luo H, Chen X. Preoperative total cholesterol predicts postoperative outcomes after partial hepatectomy in patients with chronic hepatitis B- or C-related hepatocellular carcinoma. Surgery. 2014;155(2):263–70.

    Article  Google Scholar 

  40. 40.

    Oh TK, Kim HH, Park DJ, Ahn SH, Do SH, Hwang JW, Kim JH, Oh AY, Jeon YT, Song IA. Association of preoperative serum total cholesterol level with postoperative pain outcomes after laparoscopic surgery for gastric cancer. Pain Pract. 2018;18(6):729–35.

    Article  Google Scholar 

  41. 41.

    Perez JID, Fernandez G, Salvanes FR, Lopez AMD. Nutritional screening; control of clinical undernutrition with analytical parameters. Nutr Hosp. 2014;29(4):797–811.

    Google Scholar 

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Acknowledgements

The authors gratefully acknowledge all of the investigators for their contributions to the trial.

Funding

This work was supported by the Natural Science Foundation of Jiangsu Province (BK20200052).

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Contributions

FS and CZ worked on the study design, collected data, and drafted the manuscript. ZL helped data collection and extraction. SA contributed to data collection. WG and SL were responsible for study design and manuscript revision. All authors have read and approved the manuscript.

Corresponding authors

Correspondence to Wenxian Guan or Song Liu.

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This study was approved by the ethics committee of Nanjing Drum Tower Hospital, Medial School of Nanjing University. Due to the retrospective nature, the requirement for informed consent was waived by the IRBs from Nanjing Drum Tower Hospital, Medial School of Nanjing University. All the experiment protocol for involving human data was in accordance to guidelines of Nanjing Drum Tower Hospital, Medial School of Nanjing University.

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The authors declare that they have no competing interests.

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Supplementary Information

Additional file 1

. Definition of CONUT.

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Sun, F., Zhang, C., Liu, Z. et al. Controlling Nutritional Status (CONUT) score as a predictive marker for short-term complications following gastrectomy of gastric cancer: a retrospective study. BMC Gastroenterol 21, 107 (2021). https://doi.org/10.1186/s12876-021-01682-z

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Keywords

  • CONUT
  • Postoperative complications
  • Gastric cancer