Automation offers urinalysis upgrades

Nov. 1, 2009

Over the last few decades, the progress of automated
sample analysis by various clinical laboratory disciplines has been
remarkable. Hematology laboratories began automating red cell and white cell
counts in the late 1960s. In the 1970s, white cell differentials
transitioned from 3- and 5-part diffs based on histogram data to highly
accurate automated differentials that today report 20 or more red and white
cell parameters without technologist intervention.

Why has microscopic urine analysis lagged so far behind?
Automated microscopic urinalysis systems are available today and are proving
themselves in use. The same technologies that were brought to bear on
blood-cell analysis have now been adapted to provide fully automated,
complete urine screening studies: the ability to evaluate large numbers of
formed elements using laser light scatter, volumetric impedance, and
differential staining in flow cytometry-based systems. Microscopic
urinalysis can take four minutes or more, depending on the findings.
Automated analysis offers results in less than one minute and avoids
variables that can be introduced by centrifugation and
technologist-to-technologist variation.

A study, conducted at the Medical University of South
Carolina,1 concluded that automated urine microscopy “provides
more sensitive detection of leukocytes and bacteria,” compared to other
detection methods.

In 1982, Szwed and Schaust reported that more than 30% of
urines studied in their laboratory with normal macroscopic findings had
abnormal findings on microscopic analysis of urine sediment.2 The
most common microscopic findings were white blood cells, bacteria, and
casts. They also followed 353 consecutive urine samples showing that 67%
(238/353) had positive microscopic results independent of the macroscopic
tests.

Diane Gaspari, SH(ASCP), core laboratory manager at York
Hospital in Pennsylvania, was an early adopter of automated urine
microscopy. Initially looking for ways to improve productivity and
efficiency, she has also demonstrated the clinical benefits:
standardization, the reduction of analytical variables, and the elimination
of technologist-to-technologist variability, which she has observed to be
even greater in urine microscopy than hematology differentials.

According to Gaspari, “What you need to do, just like was
done in hematology, is challenge the flags and set your own sensitivity
limits based on your lab’s clinical sensitivity studies. The numerical count
results are quite good, but it is the flags in which you need to have
confidence.”

Prior to automation at York Hospital, two to three
technologists were fully occupied performing microscopic urinalysis all day.
Now that urines are automated, 1.5 FTE-technologists can manage the
urinalysis workload and have time to do other things. The new system
analyzes 4 mL of urine in an automated mode and 1 mL of urine in a manual
mode, and aspirates 1,200 uL (automated mode) and 800 uL (manual mode) for
microscopic scrutiny, using two channels, one for bacteria detection and one
for the enumeration of RBC, WBC, epithelial cells, hyaline casts, and the
flagging parameters. This is the equivalent of 38 high-powered fields (HPFs)
or the equivalent of 10 HPFs of 2.5 mL of sediment using a fluorescent flow
cell in less than three minutes/sample.

York Hospital has a significant urine microscopy workload
due, in part, to the ordering options given to physicians. For example,
physicians are able to reflex to urine culture with a microscopic finding of
>28 WBCs/uL, >358.0/uL bacteria positive leukocyte esterase and nitrite, and
85% of the urinalysis requests are ordered that way. Many laboratories
perform no microscopic analysis if the dipstick results are normal.

The clinical benefits of being able to conduct
microscopic analyses on all urine samples are clear, particularly
considering the data that shows that 30% of macroscopically urine samples
with normal chemistry results on the dipsticks, may have abnormal findings
microscopically.

In addition to better patient care, there are economic
reasons for the adoption of microscopic screening of admission urines.
Because hospital-acquired infections, or HAIs, will no longer be reimbursed
by Centers for Medicare and Medicaid Services, a microscopic evaluation of
urine can allow for the identification of patients with pre-existing
bacterial infections to be flagged upon admission. According to the Agency
for Healthcare Research and Quality, “Hospital-acquired catheter-associated
urinary-tract infection is one of the first six conditions Medicare is
targeting to reduce payment associated with hospital-acquired conditions
under Congressional mandate.”3 In a related report, also from the
AHRQ, some of the same authors suggest the “addition of a
present-on-admission code (to identify patients with urinary tract
infections at the time of hospital admission) in Medicare claims in October
2007could boost the positive predictive value (of Medicare claims data) up
to 86%.”4

Urine microscopic analysis is time-consuming and fraught
with variables ranging from sample size to specimen mixing to centrifugation
and others.5 As proven with other laboratory disciplines,
automation provides for standardized, high-quality results that can be
reported in a timely fashion for urine samples as well.

Carl Trippiedi is senior product manager for U.S.
Marketing at Sysmex America Inc. in Mundelein, IL.

References

  1. Szwed JJ, Schaust C. “The Importance of Microscopic
    examination of the Urinary Sediment,” American Journal of Medical
    Technology
    . 1982;48(2):141-143.
  2. Young JL, Soper DE. Infect Dis Obstet Gynecol.
    2001;9(4):249-255.
  3. Zhan C, Elixhauser A, Richards CL Jr, Wang Y, Baine
    WB, Pineau M, Verzier N, Kliman R, Hunt D. “Identification of
    hospital-acquired catheter-associated urinary tract infections from
    Medicare claims: Sensitivity and positive predictive value,” Agency for
    Healthcare Research and Quality, Department of Health and Human
    Services, Rockville, MD. Med Care. 2009;47(3):364-369.
  4. Zhan C, Elixhauser A, Baine WB, et al. “Patient
    Safety and Quality: Medicare claims data identify hospital-acquired
    catheter-associated urinary tract infections with limited accuracy.”
    Agency for Healthcare Research and Quality, Research Activities, August
    2009. http://www.ahrq.gov/research/aug09/0809RA5.htm . Accessed October
    26, 2009.
  5. Dotson JA. An Examination of Urine Microscopic Sediment Analysis.
    ADVANCE
    . May 2001.