痛风频繁发作影响因素分析的单中心回顾性队列研究

A single-center retrospective cohort study on influencing factors of frequent attacks in gout patients

目的回顾性研究分析痛风频繁发作的影响因素,以助于痛风病情监测和管理。方法收集2015年5月—2020年11月在同济大学附属第十人民医院就诊的172例痛风患者的一般人口学特征、个人史、伴随疾病、痛风病程、过去1年痛风急性发作次数、实验室检查、影像学检查等临床资料。根据过去1年内痛风急性发作的次数是否≥3次,分为频繁发作组和非频繁发作组,比较两组之间的临床特征差异。通过Spearman等级相关分析评估痛风发作次数的相关因素,二元Logistic回归分析探讨痛风频繁发作的独立危险因素。采用受试者工作特征(ROC)曲线评估主要影响因素对于判断痛风频繁发作的诊断性能。结果痛风急性发作次数与饮酒史(r_(s)=0.182,P=0.017)、痛风病程(r_(s)=0.438,P<0.001)、血尿酸水平(r_(s)=0.185,P=0.015)、血尿酸分级(r_(s)=0.233,P=0.002)、双能量CT(dual-energy CT,DECT)阳性(r_(s)=0.197,P=0.010)及尿酸盐体积(r_(s)=0.299,P<0.001)呈正相关。与炎症指标的相关性分析显示,痛风发作次数与中性粒细胞百分比(r s=0.198,P=0.009)、中性粒细胞和淋巴细胞比值(r_(s)=0.219,P=0.004)、单核细胞和淋巴细胞比值(r_(s)=0.240,P=0.001)、血小板和淋巴细胞比值(r_(s)=0.261,P=0.001)、C反应蛋白(r s=0.160,P=0.036)呈正相关,而与淋巴细胞数(r s=-0.196,P=0.010)、淋巴细胞百分比(r_(s)=-0.234,P=0.002)呈负相关。二元Logistic回归分析显示,饮酒史、痛风病程、血尿酸分级、DECT阳性、中性粒细胞和淋巴细胞比值等5项临床因素是痛风频繁发作的危险因素。ROC曲线提示:5项临床因素联合评估痛风频繁发作的ROC曲线下面积(AUC)为0.834,95%CI为0.7730.894(P<0.001),灵敏度为0.623,特异度为0.874。结论饮酒史、痛风病程、血尿酸分级、DECT阳性、中性粒细胞和淋巴细胞比值是痛风频繁发作的独立危险因素;5项临床因素联合预测痛风频繁发作,具有较高的诊断效能。

Objective To analyze the influencing factors of frequent attacks in gout patients.Methods The clinical data of 172 patients with gout treated in Shanghai Tenth People s Hospital affiliated to Tongji University from May 2015 to November 2020 were retrospectively analyzed.According to the frequency of acute attack in the past year≥3 or<3,patients were assigned in the frequent attack group(n=61)or the infrequent attack group(n=111).The clinical characteristics of the two groups were compared.Spearman rank correlation analysis was used to evaluate the related factors of gout acute attack,and binary Logistic regression analysis was used to explore the independent risk factors of frequent gout attacks.Receiver operating characteristic(ROC)curve analysis was used to evaluate the performance of the main influencing factors for the prediction of frequent gout attacks.Results The frequency of gout attack was positively correlated with drinking history(r_(s)=0.182,P=0.017),course of gout(r_(s)=0.438,P<0.001),serum uric acid(r_(s)=0.185,P=0.015),serum uric acid grade(r_(s)=0.233,P=0.002),positive dual-energy CT(DECT)(r_(s)=0.197,P=0.010),urate volume(r_(s)=0.299,P<0.001),the percentage of neutrophil(r_(s)=0.198,P=0.009),neutrophil to lymphocyte ratio(r_(s)=0.219,P=0.004),monocyte to lymphocyte ratio(r s=0.240,P=0.001),platelet to lymphocyte ratio(r_(s)=.261,P=0.001),and C-reactive protein(r_(s)=0.160,P=0.036);and negatively correlated with the number of lymphocyte(r_(s)=-0.196,P=0.010)and the percentage of lymphocyte(r_(s)=-0.234,P=0.002).Binary Logistic regression analysis showed that drinking history,course of gout,serum uric acid grade,positive DECT and neutrophil to lymphocyte ratio were risk factors for frequent gout attacks.The area under the ROC(AUC)of the combination of 5 risk factors for predicting frequent gout attacks was 0.834(95%CI:0.7730.894,P<0.001)with a sensitivity of 0.623 and specificity of 0.874.Conclusion Drinking history,course of gout,serum uric acid grade,positive DECT,and neutrophil to lymphocyte ratio were independent risk factors for frequent gout attacks.The combined detection of five clinical factors may be used for predicting frequent attacks in gout patients.