Home 5 Clinical Diagnostics Insider 5 G2 Insider: Automated Urinalysis Underreports Signs of Kidney Damage

G2 Insider: Automated Urinalysis Underreports Signs of Kidney Damage

by | Feb 19, 2015 | Clinical Diagnostics Insider, Diagnostic Testing and Emerging Technologies, G2 Insider-dtet

Manual microscopy outperforms automated urine analysis, according to a small study presented at the National Kidney Foundation’s 2014 Spring Clinical Meetings (Las Vegas; April 23-26). Automated urinalysis underreported the value of granular casts in a cohort of acute kidney injury (AKI) patients, a key determinant of the underlying cause of kidney damage. The researchers compared results in the reported ranges of granular and muddy brown casts using manual microscopy and an automated urine analyzer (IRIS 200 system) for evaluation of 10 samples from patients with acute kidney injury. A single observer analyzed the same urine sample with both technologies, spending an average of 10 minutes per patient specimen. An attending physician validated the first count. Manual counts were divided by 144 to approximate the automated system’s high-power focus (HPF). Results were characterized by number of casts as none, few (0 to 5 casts/HPF) and many (21 to 50 casts/HPF). The researchers found that there were significant differences between the results produced by each modality. Manual microscopy coded no patient as having “none,” while the automated system coded 70 percent as “none.” Manual analysis coded 100 percent of specimens as “few.” The automated system coded two samples as “many,” which manual […]

Manual microscopy outperforms automated urine analysis, according to a small study presented at the National Kidney Foundation’s 2014 Spring Clinical Meetings (Las Vegas; April 23-26). Automated urinalysis underreported the value of granular casts in a cohort of acute kidney injury (AKI) patients, a key determinant of the underlying cause of kidney damage. The researchers compared results in the reported ranges of granular and muddy brown casts using manual microscopy and an automated urine analyzer (IRIS 200 system) for evaluation of 10 samples from patients with acute kidney injury. A single observer analyzed the same urine sample with both technologies, spending an average of 10 minutes per patient specimen. An attending physician validated the first count. Manual counts were divided by 144 to approximate the automated system’s high-power focus (HPF). Results were characterized by number of casts as none, few (0 to 5 casts/HPF) and many (21 to 50 casts/HPF). The researchers found that there were significant differences between the results produced by each modality. Manual microscopy coded no patient as having “none,” while the automated system coded 70 percent as “none.” Manual analysis coded 100 percent of specimens as “few.” The automated system coded two samples as “many,” which manual microscopy characterized as “few.” “Nowadays most hospitals use some form of an automated urinalysis system, and how often the data is actually supplemented with manual microscopy is hard to quantify,” said lead author Natasha Sharda, M.D., of the University of Arizona, in a statement, acknowledging that the automated systems can offer a cost, labor, and efficiency benefit. Manual microscopy can take up to six minutes per sample compared to less than one minute for automated systems. “The automated system still has utility as a screening test, but manual microscopy should be done in all cases of abnormal kidney function, as accurate quantification of casts could have some prognostic benefit to patients,” adds Sharda. Joseph Vassalotti, M.D., the chief medical officer of the National Kidney Foundation, tells DTET that AKI complicates at least 1 percent of hospital admissions in the United States, including especially critically ill patients and those undergoing cardiac surgery. Vassalotti, says that while initial reaction would be to assume that detecting more casts in manual examination is better, he urges further studies to determine if this discrepancy in results has prognostic implications with regard to renal recovery, dialysis dependency, or mortality.

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