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Guy's结石评分和改良Clavien分级方法预测PCNL术后结石清除率和并发症的研究
引用本文:刘 欢,邓远忠.Guy's结石评分和改良Clavien分级方法预测PCNL术后结石清除率和并发症的研究[J].医学信息,2019,0(9):101-103.
作者姓名:刘 欢  邓远忠
作者单位:(重庆医科大学附属第一医院泌尿外科,重庆 400016)
摘    要:目的 探讨Guy's结石评分(GS)预测经皮肾镜碎石取石术(PCNL)术后结石清除率及利用改良Clavien分级方法(MCC)预测PCNL术后并发症发生的可靠性。方法 选取2015年1月~2016年12月我院收治的155例行PCNL的肾结石患者(160个肾单位),所有患者根据术前泌尿系CT结果应用GS进行肾结石分组,利用术后KUB结果评估患者术后结石清除率,并且通过MCC预测患者术后并发症的发生。结果 160个行PCNL的肾单位中,GS1、GS2、GS3及GS4分别为15、63、73和9个。每个组的结石最大直径:GS1=25 mm,GS2=28 mm,GS3=48 mm,GS4=69 mm,差异具有统计学意义(P<0.05)。根据GS进行数据分析,四组手术时间[GS1=(32.50±14.10)min,GS2=(55.80±29.70)min,GS3=(80.80±35.10)min,GS4=(116.30±54.80)min],通道数[GS1=1个,GS2=(1.10±0.30)个,GS3=(1.20±0.50)个,GS4=(2.00±1.30)个],结石立即清除率(GS1=100.00%,GS2=87.30%,GS3=67.10%,GS4=66.70%),患者术后并发症(GS1=6.70%,GS2=28.60%,GS3=31.50%,GS4=44.40%)比较,组间差异有统计学意义(P<0.05)。首次PCNL失败的患者,无论最终再次PCNL成功与否,患者的结石最终清除率比较,差异无统计学意义(P>0.05)。结论 GS和MCC可精确评估患者经皮肾镜术后结石清除率及有效预测患者术后并发症的发生。

关 键 词:结石评分  成功率  并发症  经皮肾镜碎石取石术  预测

Guy's Stone Score and Modified Clavien Classification Method for Predicting Stone Clearance and Complications after PCNL
LIU Huan,DENG Yuan-zhong.Guy's Stone Score and Modified Clavien Classification Method for Predicting Stone Clearance and Complications after PCNL[J].Medical Information,2019,0(9):101-103.
Authors:LIU Huan  DENG Yuan-zhong
Institution:(Department of Urology,the First Affiliated Hospital of Chongqing Medical University,Chongqing 400016,China)
Abstract:Objective To investigate the accuracy of Gus's stone score (GS) in predicting stone clearance after percutaneous nephrolithotomy (PCNL) and the reliability of postoperative complications of PCNL using modified Clavien classification (MCC). Methods A total of 155 patients with PCNL kidney stones (160 nephrons) admitted to our hospital from January 2015 to December 2016 were enrolled.All patients underwent GS for renal calculus according to preoperative urinary CT findings. Postoperative KUB results were used to evaluate postoperative calculus clearance, and MCC was used to predict postoperative complications. Results Among the 160 nephrons of PCNL, GS1, GS2, GS3 and GS4 were 15, 63, 73 and 9 respectively. The maximum diameter of the stones in each group: GS1=25 mm, GS2=28 mm, GS3=48 mm, GS4=69 mm, the difference was statistically significant (P<0.05). According to GS data analysis, four groups of operation time GS1=(32.50±14.10)min, GS2=(55.80±29.70)min, GS3=(80.80±35.10)min, GS4=(116.30±54.80)min], the number of channels GS1=1, GS2=(1.10±0.30), GS3=(1.20±0.50), GS4=(2.00±1.30)], stone removal rate immediately (GS1=100.00%, GS2=87.30%, GS3 =67.10%, GS4=66.70%), the postoperative complications (GS1=6.70%, GS2=28.60%, GS3=31.50%, GS4=44.40%) were statistically significant (P<0.05).For the first time patients with PCNL failed, no matter whether the final PCNL was successful or not, the final clearance rate of the patients was not statistically significant (P>0.05). Conclusion GS and MCC can accurately assess the rate of stone removal after percutaneous nephrolithotomy and effectively predict the occurrence of postoperative complications.
Keywords:Stone score  Success rate  Complications  Percutaneous nephrolithotomy  Prediction
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