Related Experiment Video
Updated: Jul 15, 2026
Detection of microRNA Expression in Peritoneal Membrane of Rats Using Quantitative Real-time PCR
Published on: June 27, 2017
Flow cytometric analysis of peritoneal dialysis fluid in suspected peritonitis: diagnostic performance and
Lea Tybirk1, Helle Pilgaard Kristiansen1, Mie Samson1,2
1Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark.
Objectives:
Peritonitis is a feared complication to peritoneal dialysis (PD), requiring empirical broad-spectrum antibiotics. A rapid method to predict culture positivity and bacterial Gram classification could enable earlier targeted therapy and reduce unnecessary antibiotic exposure. This study evaluated the diagnostic performance of the automated flow cytometer Sysmex UF-5000 for cell counts and Gram classification in suspected PD-related peritonitis.
Methods:
Adults (>18 years) with suspected PD-associated peritonitis admitted to Aarhus University Hospital were included. Peritoneal dialysis fluid (PDF) was analysed using the UF-5000. Cell counts, bacterial counts, and Gram classification were compared with culture results. White blood cell (WBC) counts were additionally compared with Sysmex XN-9000.
Results:
Fifty-two episodes in 39 patients were analysed; 71 % were culture-positive. Bacterial and WBC counts on the UF-5000 were strongly correlated. WBC count in urine mode was the only parameter significantly associated with culture positivity (AUC 0.79), but several culture-negative cases had high WBC and bacterial counts. Gram classification was unreliable with 65 % of culture-positive samples unclassified and 31 % of the remainder misclassified. Agreement between the UF and XN WBC counts in body fluid mode was good (bias 7.6 %), whereas UF urine mode showed substantial negative bias for both WBC and bacterial counts compared with body fluid mode.
Conclusions:
WBC count was the best predictor of culture positivity. Gram classification by UF-5000 urine mode was unreliable in PDF. The body fluid mode on the UF or XN is recommended for PDF analysis due to apparent interference in UF urine mode.
Insights
Automated flow cytometry can predict peritonitis culture positivity using white blood cell counts. However, Gram classification in peritoneal dialysis fluid is unreliable with the Sysmex UF-5000.
Area of Science:
- Nephrology
- Clinical Diagnostics
- Microbiology
Background:
- Peritonitis is a serious complication of peritoneal dialysis (PD), often necessitating broad-spectrum antibiotics.
- Rapid diagnostics for peritonitis can guide targeted therapy and reduce antibiotic overuse.
Purpose of the Study:
- To assess the Sysmex UF-5000's diagnostic performance for cell counts and Gram classification in suspected PD-related peritonitis.
- To evaluate the UF-5000's ability to predict culture positivity and guide antibiotic therapy.
Main Methods:
- Analysis of peritoneal dialysis fluid (PDF) from adult patients with suspected peritonitis using the Sysmex UF-5000.
- Comparison of UF-5000 cell and bacterial counts, and Gram classification with culture results.
- Validation of white blood cell (WBC) counts against the Sysmex XN-9000.
Main Results:
- 71% of peritonitis episodes were culture-positive.
- WBC count in UF-5000 urine mode showed moderate accuracy (AUC 0.79) for predicting culture positivity.
- Gram classification by UF-5000 was unreliable, with high rates of unclassified and misclassified samples.
- Good agreement for WBC counts between UF-5000 and XN-9000 in body fluid mode, but significant negative bias in UF-5000 urine mode.
Conclusions:
- WBC count is the most reliable indicator for predicting culture positivity in PD peritonitis.
- The UF-5000's Gram classification in urine mode is not suitable for PDF analysis.
- PDF analysis using the UF-5000 or XN-9000 in body fluid mode is recommended.
Related Concept Videos
01:25Peritoneal Dialysis II: Peritoneal Dialysis Systems and Complications
01:23Flow Cytometry
In...
01:30Peritoneal Dialysis I: Introduction and Procedure
01:25Peritoneal Dialysis III: Nursing Management