Clinical study on the association between metabolic syndrome, the incidence and severity of adherent perinephric fat
-
摘要: 目的 研究临床工作中肾肿瘤患者肾周脂肪粘连(adherent perinephric fat，APF)发生及粘连程度与代谢综合征(metabolic syndrome，MS)发病率的相关性。方法 纳入2022年1月—2023年4月于南京大学医学院附属鼓楼医院泌尿外科就诊并行机器人辅助腹腔镜下肾部分切除术患者共400例，将其分为无粘连组(197例)及粘连组[轻度(84例)、中度(100例)、重度(19例)]，记录患者年龄、性别、体重指数(body mass index，BMI)、空腹血糖(fasting plasma glucose，FPG)、术前血清甘油三酯(triglyceride，TG)、高密度脂蛋白胆固醇(high-density lipoprotein cholesterol，HDL-C)、吸烟饮酒史、高血压及糖尿病史等资料，按照《中华医学会糖尿病学分会关于代谢综合征的建议》诊断标准进一步评估患者有无MS发生。继而将记录的各变量、MS与术中APF发生及其粘连程度进行相关性回归分析。结果 单因素分析结果显示，术中APF的发生与患者的年龄、性别、BMI、吸烟饮酒史、高血压、糖尿病史及MS有关(P < 0.05)；多因素分析示，BMI：25~30 kg/m2[OR=2.87(95%CI：1.49~5.52)，P=0.002]、>30 kg/m2[OR=4.12(95%CI：1.07~15.91)，P=0.040]、吸烟史[OR=22.12(95%CI：12.72~38.49)，P < 0.001]、饮酒史[OR=12.63(95%CI：6.64~24.01)，P < 0.001]及MS[OR=5.41(95%CI：2.53~12.48)，P < 0.001]是APF发生的独立危险因素。粘连程度与性别、BMI、吸烟、饮酒、高血压、MS相关(P < 0.05)，多因素分析结果示，吸烟史[OR=4.11(95%CI：2.21~7.64)，P < 0.001]、MS[OR=2.01(95%CI：1.12~3.60)，P=0.019]是术中APF程度的独立危险因素。结论 MS与APF的发生率及粘连程度呈正相关，是肾肿瘤患者肾周脂肪发生粘连及不同粘连程度的独立危险因素，可作为肾肿瘤患者术前评估肾周脂肪有无粘连及其粘连程度的预测因子，为手术入路的选择提供指导。Abstract: Objective To investigate the association between the occurrence, severity of adherent perinephric fat (APF) and the incidence of metabolic syndrome (MS) in patients with renal tumors in clinical practice.Methods This study included a total of 400 patients who underwent robot-assisted laparoscopic partial nephrectomy at the Department of Urology, Nanjing Drum Tower Hospital, between January 2022 and April 2023. The patients were divided into two groups: a non-adhesion group(197 cases) and an adhesion group with varying degrees of severity(mild: 84 cases, moderate: 100 cases, severe: 19 cases). Patient information including age, gender, body mass index(BMI), fasting plasma glucose(FPG), triglyceride(TG), high-density lipoprotein cholesterol(HDL-C), smoking and alcohol history, hypertension and diabetes history was recorded. Furthermore, MS was evaluated based on the diagnostic criteria of MS proposed by Chinese Diabetes Society (CDS). Subsequently, a correlation regression analysis was conducted to investigate the association between recorded variables, MS, and the occurrence, severity of APF.Results The results of the univariate analysis showed that the occurrence of APF was associated with patients' age, gender, BMI, smoking and alcohol history, hypertension, diabetes and MS(P < 0.05). The multivariate analysis revealed that BMI: 25-30 kg/m2(OR=2.87[95%CI: 1.49-5.52], P=0.002), BMI>30 kg/m2(OR=4.12[95%CI: 1.07-15.91], P＝0.040), smoking history(OR=22.12[95%CI: 12.72-38.49], P < 0.001), alcohol history(OR=12.63[95%CI: 6.64-24.01], P < 0.001), and MS(OR=5.41[95%CI: 2.53-12.48], P < 0.001) were independent risk factors in the occurrence of APF. The degree of adhesion was correlated with patients' gender, BMI, smoking, alcohol consumption, hypertension, and MS(P < 0.05). According to the multivariate analysis results, smoking history(OR=4.11[95%CI: 2.21-7.64], P < 0.001) and MS(OR=2.01[95%CI: 1.12-3.60], P=0.019) were independent risk factors in the severity of APF.Conclusion The presence and severity of APF in patients diagnosed with renal tumors demonstrate a positive correlation with MS, establishing it as an independent risk factor in the occurrence and severity of APF. Therefore, MS can serve as a predictive factor in preoperative assessment of both the presence and degree of APF in renal tumor patients, providing valuable guidance for selecting appropriate surgical approaches.
-
Key words:
- adherent perinephric fat /
- renal tumor /
- metabolic syndrome
-
-
表 1 粘连组与非粘连组临床基线资料比较
例(%)，M(Q1，Q3) 项目 总例数(400例) 无粘连组(197例) 粘连组(203例) Z/χ2 P值 年龄/岁 6.318 0.042 < 50 114(28.50) 65(32.99) 49(24.14) 50~70 229(57.25) 111(56.35) 118(58.13) >70 57(14.25) 21(10.66) 36(17.73) 性别 51.778 < 0.001 男 255(63.75) 91(46.19) 164(80.79) 女 145(36.25) 106(53.81) 39(19.21) BMI/(kg/m2) 90.820 < 0.001 < 25 204(51.00) 148(75.13) 56(27.59) 25~30 170(42.50) 44(22.34) 126(62.07) >30 26(6.50) 5(2.54) 21(10.34) 习惯性吸烟 154.901 < 0.001 无 235(58.75) 177(89.85) 58(28.57) 有 165(41.25) 20(10.15) 145(71.43) 习惯性饮酒 64.791 < 0.001 无 312(78.00) 187(94.92) 125(61.58) 有 88(22.00) 10(5.08) 78(38.42) 高血压病史 64.351 < 0.001 无 228(57.00) 152(77.16) 76(37.44) 有 172(43.00) 45(22.84) 127(62.56) 糖尿病史 24.081 < 0.001 无 327(81.75) 180(91.37) 147(72.41) 有 73(18.25) 17(8.63) 56(27.59) FPG 4.75(4.29，5.47) 4.63(4.23，5.16) 4.81(4.39，5.97) 2.688 0.007 TG 1.23(0.91，1.78) 1.12(0.82，1.67) 1.36(0.99，1.86) 2.769 0.006 HDL-C 1.08(0.89，1.31) 1.19(0.99，1.36) 1.02(0.85，1.23) 3.410 < 0.001 MS 101.223 < 0.001 无 280(70.00) 184(93.40) 96(47.29) 有 120(30.00) 13(6.60) 107(52.71) 
下载: 导出CSV
表 2 不同粘连程度患者临床资料比较
例，X±S 项目 总例数(400例) 无粘连组(197例) 粘连组(203例) F/χ2 P值 轻度粘连(84例) 中度粘连(100例) 重度粘连(19例) 年龄/岁 15.037 0.020 < 50 114(28.50) 65(32.99) 25(29.76) 20(20.00) 4(21.05) 50~70 229(57.25) 111(56.35) 51(60.71) 57(57.00) 10(52.63) >70 57(14.25) 21(10.66) 8(9.53) 23(23.00) 5(26.32) 性别 52.884 < 0.001 男 255(63.75) 91(46.19) 65(77.38) 82(82.00) 17(89.47) 女 145(36.25) 106(53.81) 19(22.62) 18(18.00) 2(10.53) BMI/(kg/m2) 100.975 < 0.001 < 25 204(51.00) 148(75.13) 34(40.48) 19(19.00) 3(15.79) 25~30 170(42.50) 44(22.34) 43(51.19) 70(70.00) 13(68.42) >30 26(6.50) 5(2.54) 7(8.33) 11(11.00) 3(15.79) 习惯性吸烟 164.149 < 0.001 无 235(58.75) 177(89.85) 34(40.48) 22(22.00) 2(10.53) 有 165(41.25) 20(10.15) 50(59.52) 78(78.00) 17(89.47) 习惯性饮酒 107.239 < 0.001 无 312(78.00) 187(94.92) 62(73.81) 62(62.00) 1(5.26) 有 88(22.00) 10(5.08) 22(26.19) 38(38.00) 18(94.74) 高血压病史 79.875 < 0.001 无 228(57.00) 152(77.16) 44(52.38) 30(30.00) 2(10.53) 有 172(43.00) 45(22.84) 40(47.62) 70(70.00) 17(89.47) 糖尿病史 28.088 < 0.001 无 327(81.75) 180(91.37) 66(78.57) 69(69.00) 12(63.16) 有 73(18.25) 17(8.63) 18(21.43) 31(31.00) 7(36.84) FPG 5.13±1.53 4.97±1.49 5.12±1.30 5.41±1.81 5.38±1.17 2.022 0.110 TG 1.51±1.13 1.43±1.04 1.47±0.73 1.72±1.52 1.31±0.62 1.726 0.161 HDL-C 1.13±0.31 1.19±0.31 1.12±0.28 1.00±0.28 1.13±0.29 9.159 < 0.001 MS 130.534 < 0.001 无 280(70.00) 184(93.40) 57(67.86) 34(34.00) 5(26.32) 有 120(30.00) 13(6.60) 27(32.14) 66(66.00) 14(73.68)
下载: 导出CSV
表 3 有无粘连批量单因素回归分析
因素 Beta S.E Z P值 OR(95%CI) 年龄/岁 < 50 1.00(Reference) 50~70 0.34 0.23 1.49 0.134 1.41(0.90~2.22) >70 0.82 0.33 2.46 0.014 2.27(1.18~4.37) 性别 女 1.00(Reference) 男 -1.59 0.23 -4.96 < 0.001 0.20(0.13~0.32) BMI/(kg/m2) < 25 1.00(Reference) 25~30 2.02 0.24 8.41 < 0.001 7.57(4.77~12.00) >30 2.41 0.52 4.41 < 0.001 11.10(3.99~30.84) 习惯性吸烟 无 1.00(Reference) 有 3.10 0.28 10.94 < 0.001 22.12(12.72~38.49) 习惯性饮酒 无 1.00(Reference) 有 2.46 0.34 4.92 < 0.001 11.47(5.82~23.41) 高血压病史 无 1.00(Reference) 有 1.73 0.22 7.75 < 0.001 5.64(3.64~8.74) 糖尿病史 无 1.00(Reference) 有 1.39 0.30 4.47 < 0.001 4.03(2.25~7.24) FPG 0.15 0.07 2.00 0.046 1.16(1.01~1.34) TG 0.12 0.10 1.27 0.204 1.13(0.94~1.37) HDL-C -1.44 0.35 -4.11 < 0.001 0.24(0.12~0.47) MS 无 1.00(Reference) 有 2.76 0.32 8.63 < 0.001 15.78(8.43~29.51)
下载: 导出CSV
表 4 有无粘连批量多因素回归分析
因素 Beta S.E Z P值 OR(95%CI) BMI/(kg/m2) < 25 1.00(Reference) 25~30 1.05 0.33 3.16 0.002 2.87(1.49~5.52) >30 1.42 0.49 2.05 0.040 4.12(1.07~15.91) 习惯性吸烟 无 1.00(Reference) 有 2.54 0.33 7.73 < 0.001 22.12(12.72~38.49) 习惯性饮酒 无 1.00(Reference) 有 2.46 0.34 4.92 < 0.001 12.63(6.64~24.01) MS 无 1.00(Reference) 有 1.73 0.41 4.23 < 0.001 5.41(2.53~12.48)
下载: 导出CSV
表 5 不同粘连程度批量单因素回归分析
因素 Beta S.E Z P值 OR(95%CI) 年龄/岁 < 50 1.00(Reference) 50~70 0.29 0.32 0.90 0.344 1.34(0.71~2.50) >70 0.38 0.43 0.89 0.375 1.46(0.63~3.41) 性别 女 1.00(Reference) 男 -0.92 0.32 -2.88 0.004 0.40(0.21~0.75) BMI/(kg/m2) < 25 1.00(Reference) 25~30 1.14 0.29 3.86 < 0.001 3.11(1.75~5.54) >30 0.78 0.55 1.42 0.154 2.19(0.74~6.44) 习惯性吸烟 无 1.00(Reference) 有 1.44 0.30 5.56 < 0.001 5.24(2.29~9.40) 习惯性饮酒 无 1.00(Reference) 有 1.15 0.28 4.06 < 0.001 3.17(1.82~5.54) 高血压病史 无 1.00(Reference) 有 1.07 0.28 3.86 < 0.001 2.92(1.70~5.04) 糖尿病史 无 1.00(Reference) 有 0.50 0.32 1.57 0.116 1.64(0.88~3.05) FPG 0.16 0.07 2.18 0.029 1.18(1.02~1.34) TG -0.11 0.14 -0.76 0.444 0.90(0.48~1.19) HDL-C -0.59 0.45 -1.31 0.191 0.55(0.23~1.35) MS 无 1.00(Reference) 有 1.20 0.27 4.38 < 0.001 3.32(1.94~5.68)
下载: 导出CSV
表 6 不同粘连程度批量多因素回归分析
因素 Beta S.E Z P值 OR(95%CI) 习惯性吸烟 无 1.00(Reference) 有 1.41 0.32 4.47 < 0.001 4.11(2.21~7.64) MS 无 1.00(Reference) 有 0.70 0.30 2.35 0.019 2.01(1.12~3.60)
下载: 导出CSV
-
[1] Li X, Xu W, Fan S, et al. Robot-assisted Partial Nephrectomy with the Newly Developed KangDuo Surgical Robot Versus the da Vinci Si Surgical System: A Double-center Prospective Randomized Controlled Noninferiority Trial[J]. Eur Urol Focus, 2023, 9(1): 133-140. doi: 10.1016/j.euf.2022.07.008
[2] Casale P, Lughezzani G, Buffi N, et al. Evolution of Robot-assisted Partial Nephrectomy: Techniques and Outcomes from the Transatlantic Robotic Nephron-sparing Surgery Study Group[J]. Eur Urol, 2019, 76(2): 222-227. doi: 10.1016/j.eururo.2018.11.038
[3] Borregales LD, Adibi M, Thomas AZ, et al. Predicting Adherent Perinephric Fat Using Preoperative Clinical and Radiological Factors in Patients Undergoing Partial Nephrectomy[J]. Eur Urol Focus, 2021, 7(2): 397-403. doi: 10.1016/j.euf.2019.10.007
[4] Turco F, Tucci M, Di Stefano RF, et al. Renal cell carcinoma(RCC): fatter is better? A review on the role of obesity in RCC[J]. Endocr Relat Cancer, 2021, 28(7): R207-R216. doi: 10.1530/ERC-20-0457
[5] Davidiuk AJ, Parker AS, Thomas CS, et al. Mayo adhesive probability score: an accurate image-based scoring system to predict adherent perinephric fat in partial nephrectomy[J]. Eur Urol, 2014, 66(6): 1165-1171. doi: 10.1016/j.eururo.2014.08.054
[6] Masenga SK, Kabwe LS, Chakulya M, et al. Mechanisms of Oxidative Stress in Metabolic Syndrome[J]. Int J Mol Sci, 2023, 24(9): 7898. doi: 10.3390/ijms24097898
[7] Silva-Ochoa AD, Velasteguí E, Falconí IB, et al. Metabolic syndrome: Nutri-epigenetic cause or consequence?[J]. Heliyon, 2023, 9(11): e21106. doi: 10.1016/j.heliyon.2023.e21106
[8] Zhang QH, Chen LH, An Q, et al. Quantification of the renal sinus fat and exploration of its relationship with ectopic fat deposition in normal subjects using MRI fat fraction mapping[J]. Front Endocrinol(Lausanne), 2023, 14: 1187781. doi: 10.3389/fendo.2023.1187781
[9] 中华医学会糖尿病学分会代谢综合征研究协作组. 中华医学会糖尿病学分会关于代谢综合征的建议[J]. 中华糖尿病杂志, 2004, 12(3): 156-161. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTL200403001.htm
[10] 周嘉乐, 吴小荣, 陈勇辉, 等. 腹腔镜下肾部分切除术在cT1期完全内生型肾肿瘤治疗中的临床应用与疗效分析[J]. 临床泌尿外科杂志, 2022, 37(9): 665-668. https://lcmw.whuhzzs.com/article/doi/10.13201/j.issn.1001-1420.2022.09.004
[11] Tian Q, Lee PR, Yang Q, et al. The mediation roles of intermuscular fat and inflammation in muscle mitochondrial associations with cognition and mobility[J]. J Cachexia Sarcopenia Muscle, 2024, 15(1): 138-148. doi: 10.1002/jcsm.13413
[12] Roccatello D, Lan HY, Sciascia S, et al. From inflammation to renal fibrosis: A one-way road in autoimmunity?[J]. Autoimmun Rev, 2023, 23(4): 103466.
[13] Wang L, Chen L, Liu Z, et al. PAI-1 Exacerbates White Adipose Tissue Dysfunction and Metabolic Dysregulation in High Fat Diet-Induced Obesity[J]. Front Pharmacol, 2018, 9: 1087. doi: 10.3389/fphar.2018.01087
[14] Liu Y, Wang L, Luo M, et al. Inhibition of PAI-1 attenuates perirenal fat inflammation and the associated nephropathy in high-fat diet-induced obese mice[J]. Am J Physiol Endocrinol Metab, 2019, 316(2): E260-E267. doi: 10.1152/ajpendo.00387.2018
[15] Chen L, Chen G, Guo Y, et al. Ketanserin, a serotonin 2A receptor antagonist, alleviates ischemia-related biliary fibrosis following donation after cardiac death liver transplantation in rats[J]. Liver Transpl, 2014, 20(11): 1317-1326. doi: 10.1002/lt.23947
[16] Afonso-Alí A, Porrini E, Teixido-Trujillo S, et al. The Role of Gender Differences and Menopause in Obesity-Related Renal Disease, Renal Inflammation and Lipotoxicity[J]. Int J Mol Sci, 2023, 24(16): 12984. doi: 10.3390/ijms241612984
[17] Avequin T, Lau KH, Waldhart AN, et al. Differential effects of sugar and fat on adipose tissue inflammation[J]. iScience, 2023, 26(7): 107163. doi: 10.1016/j.isci.2023.107163
-