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 Table of Contents  
Year : 2019  |  Volume : 3  |  Issue : 3  |  Page : 202-205

Validation and impact of the use of automated urine culture streak system in a diagnostic laboratory on surveillance of catheter-associated urinary tract infections at a tertiary care setting

Section of Microbiology, Department of Pathology and Laboratory Medicine, Aga Khan University Hospital, Karachi, Pakistan

Date of Submission17-May-2019
Date of Decision25-Jun-2019
Date of Acceptance11-Jun-2019
Date of Web Publication10-Sep-2019

Correspondence Address:
Dr. Seema Irfan
Aga Khan University Hospital, Karachi
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/bbrj.bbrj_81_19

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Background: Quantitative urine culture reporting on plates inoculated by automated streaking system (PREVI® Isola) demonstrates maximum growth only equivalent up to 104 colony-forming unit (CFU)\ml, according to the manufacturer's recommendation. Therefore, there is a probability of erroneous catheter-associated urinary tract infection (CAUTI) surveillance data as a count of ≥105 CFU/ml is required according to CAUTI definition. This study aimed to validate automated urine culture streak system for improving the surveillance of hospital-acquired CAUTIs. Materials and Methods: This was a prospective, cross-sectional study. In 1-month duration, urine samples of 1000 consecutive patients reported to the microbiology section for culture and sensitivity were included. Samples were processed simultaneously manually (1 μl loop) and with an automated streaking system. Plates streaked by automated method were arbitrarily divided into eight equally sized segments. After 24 h of incubation at similar conditions, microbial growths in each segment were noted and correlated with its manual colony count. To minimize the error, colony count and morphotype were analyzed by a senior technologist and counterchecked by a consultant. Results were recorded on an Excel sheet. Results: Growth on the 7th and 8th segments corresponded with ≥105 CFU/ml. Growth up to the 4th, 5th, and 6th segments corresponded with 104 CFU/ml, whereas the 3rd segment with >103 but <104 CFU/ml. Any growth in the 1st and 2nd sectors was considered insignificant. Conclusion: Quantitative urine culture analysis inoculated by automated streak system corresponds to the CAUTI surveillance definition. Colony count requires validation with manual method before implementing in laboratory.

Keywords: Automated streaking system, catheter-associated urinary tract infection, CAUTI surveillance

How to cite this article:
Zeeshan M, Farooqi J, Chandio S, Rafiq Z, Roshan R, Irfan S. Validation and impact of the use of automated urine culture streak system in a diagnostic laboratory on surveillance of catheter-associated urinary tract infections at a tertiary care setting. Biomed Biotechnol Res J 2019;3:202-5

How to cite this URL:
Zeeshan M, Farooqi J, Chandio S, Rafiq Z, Roshan R, Irfan S. Validation and impact of the use of automated urine culture streak system in a diagnostic laboratory on surveillance of catheter-associated urinary tract infections at a tertiary care setting. Biomed Biotechnol Res J [serial online] 2019 [cited 2022 May 20];3:202-5. Available from: https://www.bmbtrj.org/text.asp?2019/3/3/202/266564

  Introduction Top

Laboratory confirmation of infectious disease diagnosis is essential not only in assisting clinicians in the disease management but also helping in curtailing its spread and monitoring the surveillance. Reliability of clinical microbiology results is crucial for an infectious disease clinician and infection control practitioner in making right decisions.[1]

Burden of hospital-acquired-urinary tract infections (HA-UTIs) and the associated morbidity in both ingenious and developing world is significant.[2],[3] The risk of developing bacteriuria increases by approximately 3%–10% per day during which a catheter remains in place.[4] This can lead to many complications such as pyelonephritis, prostatitis, epididymitis, orchitis, and sepsis, which can cause prolonged hospital stay and increased financial liabilities.[5]

According to the Centers for Disease Control and Surveillance (CDC), catheter-associated urinary tract infection (CAUTI) is defined as the presence of symptoms with a positive urine culture of no more than two species of organisms in urine culture, at least one of which is a bacterium with a count of ≥105 colony-forming unit (CFU)/mL.[6] Therefore, standardization of laboratory procedures in quantitating microbial count is crucial to delineate between infection and colonization.

Conventionally, urine specimen is inoculated by handheld calibrated Nichrome loop, which is labor intensive and time-consuming. The use of disposable plastic loop reduces time but still requires skilled technologists. Laboratory automation has been gradually replacing the conventional time-consuming manual methods in clinical laboratory practices.[7]

Microbiology section of pathology and laboratory medicine department is one of the busiest and overworked areas of our hospital. It receives clinical specimens round the clock from across the country for infectious disease diagnosis. To overcome heavy workload, we planned to substitute manual or conventional diagnostic method to automation and novel techniques. In view of this consideration, the clinical microbiology section had introduced an automated streaking system (PREVI® Isola, bioMérieux, France) for inoculation of clinical specimens. Urine culture reporting was started based on manufacturer's instruction on which maximum growth was interpreted and reported as equivalent to >104 CFU/mL. This reporting format of microbial count could easily pick clinical cases of urinary tract infection; however, it could not fulfill the microbiological CAUTI surveillance criteria, whereby a growth of ≥105 CFU/mL of an organism from a urine specimen is essential for labeling the infection as CAUTI.[6],[7]

Therefore, the objective of this study was to improve the laboratory-based surveillance of CAUTI by validating automated urine culture streak system for reporting higher pathogen count.

  Materials and Methods Top


This was a prospective, cross-sectional study conducted at the microbiology section of a pathology and laboratory medicine department.


Catheter-associated urinary tract infection

CAUTI is defined as the presence of symptoms with a positive urine culture (and significant urine detail report (DR) in cases of low colony counts) in patients with an indwelling urinary catheter at the time of or within 48 h before the onset of the event.

Standardized infection ratio

The standardized infection ratio (SIR) is calculated by dividing the number of CAUTI by the expected number of CAUTI.

Cumulative hospital rates are compared with the reference range reported by the National Healthcare Safety Network of CDC, using the SIR. An SIR greater than 1 indicates that infection rates are higher than expected (provided the 95% confidence interval [CI] does not cross 1).

Hospital catheter-associated urinary tract infection surveillance

In our hospital, the infection control committee oversees all infection prevention- and control-related activities including device-related infections. A policy has been developed and implemented for the prevention and surveillance of CAUTI only in critical care units. This policy states the CAUTI prevention bundles and surveillance criteria in accordance with the CDC.[8]

Steps to improve catheter-associated urinary tract infection surveillance

Since the introduction of CAUTI surveillance using SIR, the rate was noticed to be very low. In March 2017, to evaluate the reasons for this, a meeting was conducted between infection control persons and microbiology section in which new changes in microbiology sections regarding urine culture specimen inoculation were evaluated. As per manufacturer's guideline, the automated streaking system (PREVI® Isola) reports maximum growth only equivalent to >104 CFU/mL; therefore, there was a chance that cases with urine culture growth of ≥105 CFU/mL might be reported as >104 CFU/mL and not accomplishing the CAUTI surveillance criteria. We validated the automated streaking system to report higher colony counts in urine culture. Finally, urine culture reporting to include counts of >105 CFU/ml was changed from the quarter 3 of 2017.

Automated streaking system (PREVI® Isola)

A plastic comb with 16 needles, moving in a circular fashion on agar surface was used to inoculate 10 μl of urine. The inoculated culture plate, divided into arbitrary equal sectors [Figure 1]a, was then used to quantitate microbial growth by enumerating colonies in each sector.
Figure 1: (a) Arbitrary division of 90-mm plate inoculated by the automated streaking system into eight sectors. (b) Growth of lactose fermenter up to the 8th sector on cysteine, lactose electrolyte-deficient agar plate streaked by automated system which correlated with a colony count of ≥105 CFU/mL when processed manually

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Manual method

Using calibrated loop, 1μl volume of urine sample was inoculated on the agar plate. To evenly disperse the urine across the agar, firstly, with help of this loop a single streak was made down the plate and then streaking was made perpendicularly across the primary inoculum.[9]

Sample size

We reviewed 1140 urine cultures over 4 days to calculate the expected frequency of growth in sectors 1–2 (0.3 ± 0.1%), 3–4 (1.2 ± 0.5%), and 5–8 (31.3 ± 5%). The minimum sample size required to ensure the detection of least frequent growth (0.3 ± 0.1%), at 95% CI, was calculated to be 1038. The first ninety samples from each shift were selected daily for 1 month and run in parallel for the purpose of bacterial count evaluation.


Each sample was inoculated in parallel on the automated streaking system (PREVI® Isola) and manually on Cysteine, Lactose Electrolyte Deficient (CLED) agar. After the first 24–48 h of incubation at 35°C ± 2°C, interpretation [Figure 1]b was performed by a bench technologist. Colonies of up to two morphotypes were included, whereas mixed peri-urethral and perineal flora were excluded from the sample size. Results were entered and analyzed in Microsoft Excel.

To determine if there was an improved detection of CAUTI cases, surveillance data of 2016, 2017, and 2018 (1st and 2nd quarters only) were evaluated, and the mean number of CAUTI cases and SIRs of the time before and after the improved reporting was compared using two-sample t-test with unequal variances using STATA software version 12.0 (StataCorp LP, College Station, Texas, USA).

  Results Top

[Table 1] shows the comparison of results of 1000 urine culture specimens. In case of a single morphotype, analysis of comparative results showed 100% agreement with the corresponding sections. Out of 19 samples growing two morphotypes of uropathogens, four showed disagreement in colony count between two methods and therefore, the percentage agreement reduced to 80%.
Table 1: Comparison of observed growth of inoculated by both methods for single morphotype of growing organism

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The effect on catheter-associated urinary tract infection surveillance

The surveillance data are shown in [Figure 2]. The reporting policy of urine cultures changed to include higher counts from the third quarter of 2017. The mean SIR from 2016 quarter-1 till 2017 quarter-2 was 0.196 (95% CI: −0.08–0.48), whereas that from 2017 quarter-3 till 2018 quarter-2 was 0.585 (95% CI: −0.02–1.19), not reaching a statistically significant increase (P = 0.0675). Nevertheless, there was a statistically significant increase (P = 0.0350) in the number of CAUTI cases during the two periods: 1.17 (95% CI: −0.38–2.71) before the change in reporting policy versus 3.25 (95% CI: 0.86–5.64) after it.
Figure 2: Quarterly report of standard infection ratio for surveillance of catheter-associated urinary tract infections in critical care areas of Aga Khan University Hospital, Karachi (quarter 1-2016 to quarter 2-2018)

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  Discussion Top

This study was planned not only to reduce the preanalytical errors in processing urine culture especially when handling large volume of clinical samples daily, but also to overcome the aforementioned issue of disease surveillance by validating the microbial count using this novel method in laboratory. In this era of health sciences, the impact of laboratory-generated data has effect on 70% of clinical decisions.[10] In view of the microbiology laboratory results, infectious diseases' diagnostic, therapeutic, and preventive guidelines are being developed which are followed nationally or internationally. With the advents of laboratory medicine modernization and evolution ofin vitro diagnostic techniques, the quality of patient care has improved not only by producing reliable results in reduced turnaround time but also by minimizing human input errors in the entire process. The pre-analytical phase of specimen processing for culture and sensitivity is crucial for adequate microbial growth.[11] Those clinical specimens in which microbes are unevenly distributed have high probability of contamination with normal flora of surrounding tissue, for example, urine and broncho-alveolar lavage are processed as quantitative culture.[12] Although the clinical diagnosis and surveillance definition of CAUTI includes specific symptoms and positive urine culture of count ≥105 CFU/mL, the maximum colony count recommended by the manufacturer of new automated streak system (PREVI® Isola) is up to 104 CFU/mL. In literature search, we did not find any relevant work in which laboratory equipment was validated to improve the disease surveillance within hospital. This is the first study in which we have tried to develop an agreement between colony count in urine culture specimen inoculated simultaneously by automated and conventional method for improving the laboratory-based disease surveillance.

We found the automated streaking system to be a reliable method to replace manual urine culture inoculation as it is a closed system which also maintains specimen sterility during the process. It also minimizes error in sample processing as it uses barcode reader and is faster than manual inoculation due to repeated heating of wire loop. In this way, it could prove to be cost-effective; however, cost analysis was not performed as it was not the objective of our study.

However, to switch from manual conventional inoculation method to automation, the inoculation volume needs proper validation for the precision and accuracy of quantitative results.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Janda JM. Clinical decisions: How relevant is modern bacterial taxonomy for clinical microbiologists? Clin Microbiol Newsl 2018;40:51-7.  Back to cited text no. 1
Saint S, Greene MT, Krein SL, Rogers MA, Ratz D, Fowler KE, et al. Aprogram to prevent catheter-associated urinary tract infection in acute care. N Engl J Med 2016;374:2111-9.  Back to cited text no. 2
Rosenthal VD. Health-care-associated infections in developing countries. Lancet 2011;377:186-8.  Back to cited text no. 3
Elvy J, Colville A. Catheter associated urinary tract infection: What is it, what causes it and how can we prevent it? J Infect Prev 2009;10:36-41.  Back to cited text no. 4
Zimlichman E, Henderson D, Tamir O, Franz C, Song P, Yamin CK, et al. Health care-associated infections: A meta-analysis of costs and financial impact on the US health care system. JAMA Intern Med 2013;173:2039-46.  Back to cited text no. 5
Weiner LM, Webb AK, Limbago B, Dudeck MA, Patel J, Kallen AJ, et al. Antimicrobial-resistant pathogens associated with healthcare-associated infections: Summary of data reported to the national healthcare safety network at the centers for disease control and prevention, 2011-2014. Infect Control Hosp Epidemiol 2016;37:1288-301.  Back to cited text no. 6
Dauwalder O, Landrieve L, Laurent F, de Montclos M, Vandenesch F, Lina G. Does bacteriology laboratory automation reduce time to results and increase quality management? Clin Microbiol Infect 2016;22:236-43.  Back to cited text no. 7
Hospital AKU. Surveillance of Health Care Associated Infections (HAIs) and Multi Drug Resistant Organism (MDRO). Catheter Associated Urinary Tract Infection (CAUTI); 2018. p. 1-4.  Back to cited text no. 8
Marie Pezzlo MK. Clinical Microbiology Procedures Handbook. 3rd ed. Washington, DC: American Society for Microbiology Press; 2010.  Back to cited text no. 9
Hallworth M. The '70% claim': What is the evidence base? Ann Clin Biochem 2011;48:487-8.  Back to cited text no. 10
Gary W, Elmer W. Color Atlas and Textbook of Diagnostic Microbiology. Vol. 184. Philadelphia: J.B. Lippincott Company; 2016. p. 200-1.  Back to cited text no. 11
Ojanen T, Kiiskinen S, Björkman Y. Use of external quality assessment to evaluate the reliability of quantitative urine culture. Arch Clin Microbiol 2016;7:2.  Back to cited text no. 12


  [Figure 1], [Figure 2]

  [Table 1]


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