尿常规结果对革兰氏阳性菌或阴性菌引起尿路感染评分预测模型的建立和验证

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Abstract Objective To establishment and validation of urinary tract infection(UTI)score prediction model caused by gram-positive(G+)or gram-negative bacteria(G-),and verify the prediction efficiency of the scoring model.Methods A total of 182 patients with UTI treated in Yangjiang Hospital of Traditional Chinese Medicine,Guangdong Province from January 2019 to May 2021 were retrospectively analyzed.According to random number table method,they were divided into modeling group(91 cases,59 cases of G- bacteria,G+ bacteria 32 cases)and verification group(91 cases,59 cases of G-bacteria,G+bacteria 32 cases).The risk prediction model of G+bacteria infection was constructed by binary logistic regression analysis to screen the relevant influencing factors,and the prediction ability of the model was judged.Results A total of 225 strains were detected,including 138 G- strains,75 G+ strains and 12 fungi.The AUC of G- bacterial infection predicted by bacterial count in the modeling group was 0.793,and the best cut-off value was 320/μl.The AUC of G-bacterial infection predicted by white blood cell(WBC)count was 0.699,and the best cut-off value was 64/μl.Binary logistic regression analysis showed that nitrite(NIT)negative,urinary sediment stained G+bacteria,bacterial count ＜320.00/μl and WBC count ＜64/μl were the influencing factors of G+ bacteria in UTI patients,and 11,4,5 and 4 points were assigned respectively.The AUC of model subjects in the modeling group was 0.874 and that in the validation group was 0.877.The risk of G+bacteria infection was stratified,0-11 points was divided into low G+bacteria risk,13-19 points was medium G+ bacteria risk,and 20-24 points was high G+ bacteria risk.Conclusion The score prediction model has good discrimination and calibration,which is convenient for the prediction of pathogens and clinical medication according to the model.

Key words： Urine routine Urinary tract infection Gram staining Urine sediment detection Urine dry chemical test

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	YANG Kaihong
	ZENG Qingzhan
	FENG Bin

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YANG Kaihong,ZENG Qingzhan,FENG Bin. Establishment and validation of urinary tract infection score prediction model caused by gram-positive or negative bacteria[J]. 中国当代医药, 2022, 29(10): 24-28.

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https://www.dangdaiyiyao.com/EN/ OR https://www.dangdaiyiyao.com/EN/Y2022/V29/I10/24

[1]	Millner R，Becknell B.Urinary Tract Infections[J].Pediatr Clin N Am，2019，66（1）：1-13.
[2]	Keshi L，Weiwei X，Shoulin L，et al.Analysis of drug resistance of extended-spectrum beta-lactamases-producingEscherichia coliandKlebsiella pneumoniaein children with urinary tract infection[J].Saudi Med J，2019，40（11）：1111-1115.
[3]	Yi-Te C，Shigemura K，Nishimoto K，et al.Urinary tract infection pathogens and antimicrobial susceptibilities in Kobe，Japan and Taipei，Taiwan：an international analysis[J].J Int Med Res，2020，48（2）：1120-1142.
[4]	虞培娟，张杲琳，严茹红，等.尿液有形成分分析联合血清降钙素原检测在尿路感染诊断中的应用价值[J].检验医学杂志，2018，33（4）：299-304.
[5]	冯敏亚，史伟峰.UC-3500 与UF-5000 流水线分析系统在诊断尿路感染中的价值[J].检验医学于临床，2019，16（12）：1737-1740.
[6]	尿路感染诊断与治疗中国专家共识编写组.尿路感染诊断与治疗中国专家共识（2015 版）——复杂性尿路感染[J].中华泌尿外科杂志，2015，36（4）：241-244.
[7]	Gao YM，Li D，Cheng H，et al.Derivation and validation of a risk score for contrast-induced nephropathy after cardiac catheterization in Chinese patients[J].Clin Exp Nephrol，2014，18（6）：892-898.
[8]	Rakhra J，Williams G，Marais BJ，et al.Urinary tract infections in febrile children：Changing spectra of pathogenic bacteria and antibiotic susceptibilities?[J].J Paediatr Child Health，2019，55（6）：680-689.
[9]	杜颖，冯景，杨传信，等.尿常规及尿液定量分析参数在早期尿路感染经验性用药中的应用[J].检验医学杂志，2020，35（10）：1046-1048.
[10]	尿路感染诊断与治疗中国专家共识编写组.尿路感染诊断与治疗中国专家共识（2015 版）-尿路感染抗菌药物选择策略及特殊类型尿路感染的治疗建议[J].中华泌尿外科杂志，2015，36（4）：245-248.
[11]	余明主，郑慧杰，曹卫霞，等.银花泌炎灵片联合左氧氟沙星治疗急性尿路感染的临床观察[J].中国医师杂志，2019，21（10）：1571-1574.
[12]	Ganesh R，Shrestha D，Bhattachan B，et al.Epidemiology of urinary tract infection and antimicrobial resistance in a pediatric hospital in Nepal[J].BMC Infect Dis，2019，19（1）：420.
[13]	陈程，郭淑丽，贾海英，等.乌鲁木齐市SLE 患者尿路感染病原菌分布特点及无乳链球菌药敏结果分析[J].中国抗生素杂志，2021，46（1）：87-89.
[14]	李丽华，李丹丹，宋金娜.老年尿路感染者的病原菌分析及大肠埃希菌耐药性研究[J].黑龙江医学，2021，45（9）：923-925.
[15]	吴志农，周汉义，谢丹，等.尿路感染患者病原菌分布特征、免疫功能及相关因子水平检测[J].国际检验医学杂志，2019，40（13）：1621-1623.
[16]	尚红，王毓三，申子瑜.全国临床检验操作规程[M].4 版.北京：人民卫生出版社，2015：478.
[17]	肖楠，周佳，段宁，等.尿干化学和尿流式检测结果快速预测肾结石患者尿路细菌感染模型的建立与评价[J].检验医学杂志，2021，36（1）：75-79.
[18]	BoonHA，StruyfT，BullensD，et al.Diagnostic value of biomarkers for paediatric urinary tract infections in primary care：systematic review and meta-analysis[J].BMC Fam Pract，2021，22（1）：193.
[19]	于峰，王卉媛，孙凤霞.尿常规亚硝酸盐测定与尿沉渣细菌计数对尿路感染的意义[J].中国医药指南，2021，19（14）：132-133.
[20]	Zhang Q，Zong XL，Li P，et al.Performance Evaluation of Four Commercial Point-of-Care Testing Urine Analyzers for Diagnosing Urinary Tract Infection[J].Clin Lab，2021，67（10）：1011-1019.