KaydedilenlerDerginizi ekleyin

Dergiler / International Journal of Medical Biochemistry / 2022 / Cilt: 5 - Sayı: 2

Performance of a multi-criteria algorithm based on urinalysis in predicting negative urine culture results

Sabahattin MUHTAROĞLU
Didem Barlak KETİ
Pinar SAĞIROĞLU
Sayfa
84–88
Yayın Tarihi
2022-10-19
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Conclusion: This algorithm may reduce unnecessary culture requests and more effective use of time and resources.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Objectives: Urinalysis by automated urine analyzer, including microscopy and dipstick test, is easy, rapid, and inexpensive.
📊
Temel Bulgular & Veri:This study aimed to evaluate the performance of a multi-criteria algorithm by using urinalysis in predicting negative urine cultures.
💡
Sonuç & Katkı:Conclusion: This algorithm may reduce unnecessary culture requests and more effective use of time and resources.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

Objectives: Urinalysis by automated urine analyzer, including microscopy and dipstick test, is easy, rapid, and inexpensive. Among these parameters, leukocyte count (WBC) or leukocyte esterase (LE) has relatively sufficient sensitivity in urinary tract infection (UTI) detection. Urine culture is accepted as the gold standard for the diagnosis of UTI. Unnecessary culture requests constitute the majority of the microbiology laboratory workload. This study aimed to evaluate the performance of a multi-criteria algorithm by using urinalysis in predicting negative urine cultures. Methods: During a 2-week period, randomly selected 600 urine samples that reached the microbiology laboratory for urine culture were subjected to chemical and microscopic urinalysis without waiting. Urinalysis was performed using Iris iQ200 (Iris Diagnostics, Chatsworth, USA). LE >25 μL-1, nitrite positive, and WBC >5 per HPF were accepted as abnormal/positive. The sensitivity and specificity were also calculated by Receiver operating characteristic analysis at alternative threshold values for all small particles. A multi-criteria algorithm based on these urine parameters was developed, and its performance was evaluated by determining specificity, sensitivity, negative predictive value (NPV), and positive predictive value. Results: Multi-criteria algorithm based on urinalysis gave false-negative results for only 3 (0.5%) samples. This algorithm had 98.9% NPV and eliminated 47.4% of urine samples from the culture workflow. Conclusion: This algorithm may reduce unnecessary culture requests and more effective use of time and resources.

🔖

Bu Makaleye Atıf Yap

MUHTAROĞLU, S., KETİ, D. B., SAĞIROĞLU, P. (2022). Performance of a multi-criteria algorithm based on urinalysis in predicting negative urine culture results. International Journal of Medical Biochemistry, Cilt: 5 - Sayı: 2, 84–88. https://ajindex.com/articles/541404

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (13)

  1. Flores-Mireles AL, Walker JN, Caparon MG, Hultgren SJ. Urinary tract infections: Epidemiology, mechanisms of infection and treatment options. Nat Rev Microbiol 2015;13(5):269–84
  2. Williams GJ, Macaskill P, Chan SF, Turner RM, Hodson E, Craig JC. Absolute and relative accuracy of rapid urine tests for urinary tract infection in children: a meta-analysis. Lancet Infect Dis 2010;10(4):240–50
  3. Centres for Disease Control and Prevention (US). Antibiotic resistance threats in the United States, 2013. Available at: https:// www.cdc.gov/drugresistance/pdf/ar-threats-2013-508.pdf. Accessed Apr 13, 2022
  4. Wilson ML, Gaido L. Laboratory diagnosis of urinary tract infections in adult patients. Clin Infect Dis 2004;38(8):1150–8
  5. Whiting P, Westwood M, Watt I, Cooper J, Kleijnen J. Rapid tests and urine sampling techniques for the diagnosis of urinary tract infection (UTI) in children under five years: a systematic review. BMC Pediatr.ü 2005;5(1):4
  6. Semeniuk H, Church D. Evaluation of the leukocyte esterase and nitrite urine dipstick screening tests for detection of bacteriuria in women with suspected uncomplicated urinary tract infections. J Clin Microbiol 1999;37(9):3051–2
  7. Öztürk A, Gınıs Z, Hancı T, Yıldız Z, Taşlıpınar MY, Uçar F, et al. Evaluation of diagnostic performance of routine automated urinalysis and association between urinary tract infection and leukocytosis. Acta Med 2015;46(1):42–7
  8. Gehringer C, Regeniter A, Rentsch K, Tschudin-Sutter S, Bassetti S, Egli A. Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations. BMC Infect Dis 2021;21(1):209
  9. Parta M, Hudson BY, Le TP, Ittmann M, Musher DM, Stager C. IRIS iQ200 workstation as a screen for performing urine culture. Diagn Microbiol Infect Dis 2013;75(1):5–8
  10. Cantey JB, Gaviria-Agudelo C, McElvania TeKippe E, Doern CD. Lack of clinical utility of urine gram stain for suspected urinary tract infection in pediatric patients. J Clin Microbiol 2015;53(4):1282–5
  11. Gülmez D, Hasçelik G. Efficient use of laboratory resources: pre-screening for urine cultures by automated urinalysis and microscopy to allow exclusion of specimens from culture workflow. J Lab Med 2016;40(4):277–82
  12. Kayalp D, Dogan K, Ceylan G, Senes M, Yucel D. Can routine automated urinalysis reduce culture requests? Clin Biochem 2013;46(13–14):1285–9
  13. Ourania M, Hondaa NS, MacDonaldb W, Roberts J. Evaluation of evidence-based urinalysis refl