Andrea Tessari Microbiology Unit, Hospital of Rovigo, ULSS 18 Rovigo (Italy)

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1 URINARY SEDIMENT: STILL AN IMPORTANT DIAGNOSTIC TOOL International Symposium Rome, December The Application in Microbiology Andrea Tessari Microbiology Unit, Hospital of Rovigo, ULSS 18 Rovigo (Italy)

2 Urinary tract infections are among the most common bacterial infections and are a frequent clinical indication for empirical antibiotic treatment. Urine samples constitute a large proportion of the specimens processed in clinical microbiology laboratories with considerable impact in term of human resources and costs. However, up to 80% could result negatives. A rapid negative test report reduces unnecessary cultures and could avoid inappropriate empirical antimicrobial treatment. Automatic instruments for the screening of urines submitted for culture represent a valid approach for the optimisation of Turn Around Time and costs.

3 Digital microscopy for the screening of urinary tract infections Falbo et al. Journal of Clinical Microbiology. 2012;50: Bacteriuria Screening by Automated Whole Field Image Based Microscopy Reduces the Number of Necessary Urine Cultures. Sensitivity: 98.3% 952 midstream clean catch and catheter urine samples Algorithm: 10 bacteria/hpf or 4 WBC/HPF Specificity: 59.0% PPV: 34.9% NPV: 99.4% Karakukcu et al. Clinical Laboratory. 2012;58: Analytic performance of bacteriuria and leukocyturia obtained by UriSed in culture positive urinary tract infections. 965 midstream clean catch urine samples Algorithm 1: 85.2 bacteria/hpf Sensitivity 96.5% Specificity 82.1% Algorithm 2: 19.3 bacteria/hpf or 3 WBC/HPF Sensitivity 99.8% Specificity 52% Martinez et al. Clin Chim Acta. 2013;425:77 9. UriSed as a screening tool for presumptive diagnosis of urinary tract infection. Sensitivity: 97% 1379 midstream clean catch urine samples Specificity: 59% Algorithm: >12.6 bacteria/hpf or >6 WBC/HPF PPV: 27% NPV: 99%

4 Screening for urinary tract infections with the sedimax automated image analyser: Rovigo experience Semi quantitative culture was performed inoculating 10 µl of urines by a calibrate loop on a chromogenic urine agar media. Plates were analysed after 24 hours incubation on air at 37 C Urinary sample was considered positive when a significant colony concentration was observed* *According to European Urinalysis Guidelines

5 3443 midstream clean catch and catheter urine samples 2429 Outpatients % % 1014 Inpatients Positive Negative % % Female Male Outpatients Outpatients Female Inpatients Male Inpatients (26%) positive samples 200 Inpatients 150 Outpatients

6 Analytical performances of sedimax compared to urine culture 96 4% 96.4% 98 4% 98.4% 75.4% 57 8% 57.8% Sensitivity CI 95% CI 95% Cut off 95% to 97.5% to 97 5% Specificity 73.7% 73 7% to 77.0% to 77 0% WBC/HPF e / BAC/HPF / >2.5 and >13 PPV 55.3% to 60.4% 55 3% to 60 4% WBC/HPF / >29 NPV 97.7% to 98.9% 97 7% to 98 9% BAC/HPF / >39 YST/HPF / >2

7 Evaluation of performances among different patient groups 100,0% 99,2% 98,9% 96,9% 93,8% 91,1% 94,4% 90,0% 97,8% 94,4% 95,3% 80,0% 70,0% 60,0% 50,0% 0% 56,6% 74,1% 48,8% 59,4% 59,5% 51,4% 69,7% Sensitivity Specificity PPV 40,0% NPV 30,0% 20,0% 10,0% 00% 0,0% Male Outpatients (n=868) Female Outpatients (n=1561) Male Inpatients (n=418) Female Inpatients (n=596) Sensitivity 93.8% (86.9% to 97.7%) 7%) 96.9% 9% (94.3% to 98.5%) 94.4% 4% (89.7% to 97.4%) 97.8% (95.5% 5% to 99.1%) Specificity 91.1% (88.8% to 93.0%) 74.1% (71.6% to 76.5%) 59.4% (53.1% to 65.5%) 51.4% (45.4% to 57.5%) PPV 56.6% 6% (48.5% to 64.4%) 4%) 48.8% 8% (44.8% to 52.8%) 59.5% 5% (53.3% 3% to 65.6%) 6%) 69.7% (65.2% to 74.0%) NPV 99.2% (98.2% to 99.7%) 98.9%(98.0% to 99.5%) 94.4% (89.7% to 97.4%) 95.3% (90.6% to 98.1%)

8 Evaluation of the discriminatory power of sedimax AUC Bacteria ( ) AUC Leukocytes ( ) P<

9 100 Male patients AUC (BAC): AUC (WBC): 0.89 P= Female patients AUC (BAC): 0.90 AUC (WBC): P=< Sensitivity Bacteria WBC Sensitivity Bacteria WBC Specificity Specificity Male OUTpatients AUC (BAC): 0.91 AUC (WBC): 0.93 P= UC INpatients AUC (BAC): 0.86 AUC (WBC): 0.75 P=< Sensitivity S batt S wbc Sensitivity S batt S wbc Specificity Specificity WBC/HPF and BAC/HPF WBC/HPF BAC/HPF YST/HPF Algorithm A >2.5 and >13 >29 >39 >2 Algorithm B >3 and >5 >29 >25 >2 Algorithm C >8.5 >2

10 Evaluation of performances among different groups adopting patient specific algorithms Patients Samples Sensitivity Specificity PPV NPV Uncultured Outpatients 2429 Hospitalised CC Hospitalised UC Females 1561 Males Females 346 Males Females 250 Males ( ) 78.4 ( ) 48.0 ( ) 99.3 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 98.7 ( ) 60.8 ( ) 61.9 ( ) 98.6 ( ) ( ) ( ) 62 ( ) 6 69 ( ) ( ) ( ) ( ) ( ) , ( ) ( ) ( ) ( ) ,2 82,8 ( ) ( ) ( ) ( ) ,1 94,3 ( ) ( ) ( ) ( ) 66% 60% 76% 37% 32% 46% 14% 12% 18%

11 Optimisation of instrument performances False Negative samples Not optimised focusing process Bacteria with altered morphology Post analysis image editing Patients with leukopenia Patient specific cut offs False Positive samples Contamination during sample collection Erroneous classification by AIEM Concomitant antimicrobial treatment Post analysis image editing Screening not to be performed Sample should be cultured

12 Multiparameter approach for the screening of approach for the screening of urines urines submitted for culture submitted for submitted for culture 1126 midstream clean catch urine samples % % Outpatients 18% hospitalised patients % P iti Positive 300 Negative % % 0 Female Male Outpatients Outpatients n=587 n=332 Female Inpatients n=132 Male Inpatients n= (20%) 225 (20%) Positive samples

13 68% 16% 5% 5% 2% 1% 1% 1% 1% 2% Microbial pathogens isolated from urine samples collected from outpatients. (n=152) Microbial pathogens isolated from urine samples collected from hospitalized patients. (n=73) 51% 19% 8% 4% 4% 1% 12%

14 HPF: High Power Field. 1 HPF = 4,4 elements/µl

15 Evaluation of the discriminatory power and selection of cut off values Bacteria. AUC: 0.94 ( ) 0.95) Sensitivity Specificity Criterion (p/hpf) > > > >10.9 WBC. AUC: 0.88 ( ) 0.91) Specificity Sensitivity Criterion (p/hpf) > > > >67.2 Comparison of ROC curves Difference between areas Standard Error Significance level P =

16 Algorithm adopted for microbiological screening of urine samples Parameter Cut off Score Bacteria 13 elements/hpf 2 points Leucocyte 10.5 elements/hpf 1 point Squamous Epithelial cells 4 elements/hpf 1 point Leukocyte Esterase =500 Leu/μl 1 point Nitrites 1+ 2 points All results bl below these cut offs were scored with zero point. Five parameter summation score Urine sample Action 2 Positive Submitted to culture <2 Negative Referred as negative

17 Analytical performances of sedimax Aution MAX system compared to urine culture. n= 1126 urine samples True Positives (TP) 223 True Negatives (TN) 647 False Positives (FP) 254 False Negatives (FN) 2 Sensitivity 99.1% (96.8% 99.9%) 95% CI Specificity 71.8% (68.8% 74.7%) 95% CI Positive Predictive Value (PPV) 46.8% (42.2% 51.3%) 95% CI Negative PredictiveValue (NPV) 99.7% (98.9% 100%) 9% 100%) 95% CI Disease Prevalence 20.0% Uncultured samples 57%

18 Evaluation of performances among different patient groups P=0.947 P< P=0.829 P< % 99.7% 98.4% 99.7% 98.7% 99.7% 100% 100% 65.6% 45.5% 81.9% 75.9% 50.4% 44.8% 48.5% 51.4% Female patients (n=719) Male patients (n=407) Outpatients (n=919) Inpatients (n=207) Sensitivity Specificity PPV NPV Sensitivity Specificity PPV NPV Samples not submitted to culture: Female patients: 51% Male patients: 69% Samples not submitted to culture: Outpatients: 64% Inpatients: 31%

19 Post analysis manual editing One sample with underestimated bacterial count was reclassified as positive after manual post analysis editing and then submitted to culture. Analytical performances after post analysis editing: Sensitivity 99.6% Negative Predictive Value 99.9% Small debris can erroneously classified as bacteria. These samples can be reclassified as negative.

20 Importance of cytological analysis of urine sediment in clinical microbiology Plate culture is really the cornerstone for the diagnosis of Urinary Tract Infection?

21 Female 42 years old Outpatient

22 Female 42 years old Outpatient

23 Female 34 years old Outpatient

24 Female 34 years old Outpatient

25 Male 55 years old Inpatient

26 Male 55 years old Inpatient ph 8.5 GLU 0 mg/dl Proteine 300 mg/dl Emoglobina mg/dl KET 0 mg/dl BIL 0 mg/dl URO 3.0 mg/dl NIT Esterasi Leuc. 500 Leu/ul Peso Specifico 1.028

27 Corynebacterium urealyticum

28 Multicentre evaluation of sedimax and Aution Max for the microbiological i lscreening of urines

29 Performances evaluation on 7600 midstream clean catch and catheter urinesamples All parameters were collected in order to optimise i decisional i algorithms Images collected during analysis were stored and are consultable for re evaluation In the case of discordant d results between microscopy and culture, pictures it of agar plates lt were taken for further evaluation

30 Distribution of Age Estimated mean = 57,114 ± 0,556 56,558 57,671

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32 AUTOMATION IN CLINICAL LABORATORY Urinalysis work cell Urine chemistry and particle analysis and Microbiological screening are performed with the same instrument by a single Laboratory Technician Clinical Pathology Laboratory Microbiology Laboratory

33 Fully automated microbiology laboratory SAMPLE AUTOMATED AST PRE ANALITICAL PHASE Plate image MALDI TOFF DIGITAL MICROSCOPIC ANALYSER MALDI TOF spectra DIGITAL PLATE READING AUTOMATED INOCULATION AUTOMATED INCUBATION Digital Microscopy WORKING AREA READING AREA

34 Conclusions Very high sensitivity and NPV values recorded in several studies demonstrated that sedimax, alone or coupled with Aution Max, could be extremely performing for screening of urinary tract infections. The system was able to prevent a lot amount of unnecessary cultures, reducing Turn Around Time and costs. Post analysis manual editing further increases the analytical performances, dropping the number of false positives and false negatives caused by an uncorrected software classification. The adoption of patient specific cut off seems to be important to improve and optimize the system performances. Further studies are needed to set up dedicated algorithms for different patient groups. SediMAX coupled with Aution Max could be easily adopted in an integrated laboratory area where urine chemistry with particle analysis and microbiological screening were performed with the same instrument. The system could also be proficiencyintegrated i i din a fullyautomated microbiology lb laboratory.

35 Thank You For Your Attention