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Abstract: SA-PO1110

The Automated Urinalysis in Proliferative Glomerulonephritis

Session Information

Category: Pathology and Lab Medicine

  • 1502 Pathology and Lab Medicine: Clinical


  • Palsson, Ragnar, Harvard Medical School, Boston, Massachusetts, United States
  • Srivastava, Anand, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
  • Waikar, Sushrut S., Harvard Medical School, Boston, Massachusetts, United States

Since the introduction of automated urine analyzers, manual examination of the urine sediment has rapidly fallen out of favor. Limited data are available on the test performance characteristics of the modern automated urinalysis (UA).


We studied whether features on an automated UA distinguish proliferative glomerulonephritis (PGN) from other forms of kidney disease using a prospective observational cohort of adult patients undergoing native kidney biopsies at 3 tertiary care hospitals in Boston, MA. We included individuals who had an automated UA within 30 days of kidney biopsy along with an adjudicated clinicopathologic diagnosis. We excluded individuals who were on immunosuppression at the time of the biopsy.


134 of 512 patients had PGN. The mean age was 53.9±15.9 years, 46.3% were female, and 68.6% were white. The mean estimated glomerular filtration rate was 53±34 mL/min/1.73m2 and median proteinuria was 2.0 (interquartile range 0.63-4.97) g/g creatinine. Table 1 shows the sensitivity and specificity of automated urine RBC counts for diagnosis of PGN at different levels of dipstick proteinuria. The automated urine RBC count identified PGN with an area under the receiver operating characteristic curve of 0.75. At a threshold of >2 RBCs per high-power field (HPF), the positive predictive value was 38% and the negative predictive value was 91% for PGN. Among those with ≤1+ proteinuria, the negative predictive value rose to 97%. RBC casts and dysmorphic RBCs were rarely reported (1 and 3 cases of PGN, respectively).


Hematuria and proteinuria from the automated UA had modest ability to differentiate PGN from other kidney diseases. The diagnostic performance characteristics of the manual sediment exam should be investigated and compared directly to those of the automated UA.

Table 1. Sensitivity and specificity of automated UA RBC counts and dipstick protein for diagnosis of PGN.
 RBCs ≥0/HPF
RBCs >10/HPF
RBCs >15/HPF
Dipstick protein ≥ 0100% / 0.0%86.2% / 51.0%77.1% / 61.9%61.5% / 75.0%51.4% / 80.8%
Dipstick protein ≥ Trace94.7% / 14.7%82.6% / 57.3%73.4% / 68.0%58.7% / 78.0%48.6% / 82.9%
Dipstick protein ≥ 1+85.7% / 24.3%74.3% / 59.2%67.0% / 69.3%%52.3% / 78.6%43.1% / 83.5%
Dipstick protein ≥ 2+73.7% / 36.0%64.2% / 65.1%57.8% / 73.8%45.0% / 82.2%36.7% / 86.7%
Dipstick protein ≥ 3+39.1% / 61.3%35.8% / 77.4%33.0% / 83.2%25.7% / 89.0%18.4% / 91.9%

RBC, red blood cell; HPF, high-power field; UA, urinalysis.


  • NIDDK Support