Data from: Prospective, observational study comparing automated and visual point-of-care urinalysis in general practice

Objective Point-of-care testing (POCT) urinalysis might reduce errors in (subjective) reading, registration and communication of test results, and might also improve diagnostic outcome and optimise patient management. Evidence is lacking. In the present study, we have studied the analytical performance of automated urinalysis and visual urinalysis compared with a reference standard in routine general practice.

Setting The study was performed in six general practitioner (GP) group practices in the Netherlands. Automated urinalysis was compared with visual urinalysis in these practices. Reference testing was performed in a primary care laboratory (Saltro, Utrecht, The Netherlands).

Primary and secondary outcome measures Analytical performance of automated and visual urinalysis compared with the reference laboratory method was the primary outcome measure, analysed by calculating sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) and Cohen's κ coefficient for agreement. Secondary outcome measure was the user-friendliness of the POCT analyser.

Results Automated urinalysis by experienced and routinely trained practice assistants in general practice performs as good as visual urinalysis for nitrite, leucocytes and erythrocytes. Agreement for nitrite is high for automated and visual urinalysis. κ's are 0.824 and 0.803 (ranked as very good and good, respectively). Agreement with the central laboratory reference standard for automated and visual urinalysis for leucocytes is rather poor (0.256 for POCT and 0.197 for visual, respectively, ranked as fair and poor). κ's for erythrocytes are higher: 0.517 (automated) and 0.416 (visual), both ranked as moderate. The Urisys 1100 analyser was easy to use and considered to be not prone to flaws.

Conclusions Automated urinalysis performed as good as traditional visual urinalysis on reading of nitrite, leucocytes and erythrocytes in routine general practice. Implementation of automated urinalysis in general practice is justified as automation is expected to reduce human errors in patient identification and transcribing of results.

【研究目的】床旁检测（Point-of-care testing, POCT）尿液分析或可降低检验结果的主观判读、登记及沟通环节的误差，同时有望改善诊断结局、优化患者管理，但目前相关研究证据仍存在缺口。本研究以参考标准为对照，评估常规全科医疗场景中自动化尿液分析与手工视觉尿液分析的分析性能。
【研究场景】本研究在荷兰6家全科医生（General Practitioner, GP）集团诊所开展，在上述诊疗场景中对比自动化尿液分析与手工视觉尿液分析的效果；参考检测由荷兰乌得勒支市基层医疗实验室Saltro完成。
【主要与次要结局指标】以参考实验室方法为金标准，评估自动化与手工视觉尿液分析的分析性能，此为本研究的主要结局指标，通过计算灵敏度、特异度、阳性预测值（Positive Predictive Value, PPV）、阴性预测值（Negative Predictive Value, NPV）以及一致性检验的科恩κ系数（Cohen's κ coefficient）进行统计分析。次要结局指标为床旁检测分析仪的易用性。
【研究结果】在常规全科医疗场景中，由接受过常规培训的资深诊所助理开展的自动化尿液分析，在亚硝酸盐、白细胞与红细胞的检测性能上与手工视觉尿液分析相当。二者针对亚硝酸盐的检测一致性均较高，科恩κ值分别为0.824与0.803，分别被评定为“极佳”与“良好”。针对白细胞的检测结果，二者与中心实验室参考标准的一致性均较差：床旁检测的κ值为0.256（评定为“尚可”），手工视觉检测的κ值为0.197（评定为“较差”）。针对红细胞的检测一致性则有所提升：自动化检测为0.517，手工视觉检测为0.416，二者均被评定为“中等”。Urisys 1100分析仪操作简便，且不易出现操作偏差。
【研究结论】在常规全科医疗场景中，自动化尿液分析在亚硝酸盐、白细胞与红细胞的判读性能上与传统手工视觉尿液分析相当。鉴于自动化技术有望减少患者身份识别与结果转录环节的人为误差，因此在全科医疗场景中推广自动化尿液分析具备合理性。