Other than that the evaluation of urine formed elements that we
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A total of 209 patients who visited our hospital's laboratory were subjected to the research. They were chosen at random from a pool of candidates. Patients were required to provide signed written consent prior to enrollment in the study, and the research was carried out in accordance with the Helsinki Declaration (Ethical Principles for Medical Research Involving Human Subjects).
The collection, transportation, preparation of specimens, and urinalysis of the samples were all completed in accordance with European Urinalysis Guidelines 1. After being collected into primary containers that did not pose a risk of spillage during transport, mid-stream samples (30 mL) were then transferred to secondary containers (three different conical tubes) in the laboratory. The use of translucent secondary tubes was necessary to ensure that the sample could be clearly seen. To begin, each tube received a 10 mL sample of urine analyzer to be analyzed. During the course of less than an hour, each sample was subjected to three different methods. The first tube was centrifuged for 5 minutes at 1500 rpm (400 g) for 400 g before being used for manual microscopic examination. The supernatant was decanted several times until only 0.5 mL urine analyzer remained at the bottom of the tube, at which point it was discarded. To conduct the experiment, one drop of sediment was placed on a microscope slide, which was then covered with a cover slip and examined under bright light using a light microscope. In this study, the evaluation of microscopic urine analysis-formed elements was carried out independently by two biochemistry specialists and one biologist, both of whom worked with the same microscope slide. During the course of the examination, at least ten different microscopic fields were scanned at magnifications of 100 and 400 (per low-power field; LPF) and 400 (per high-power field; HPF) during the course of the examination, with each field being scanned at a magnification of 100 and 400 (per low-power field; LPF). It was decided on the results by taking an average of the elements that had been formed, and they were displayed as cells or particles in a field of data. Should a discrepancy arise between the results of the two evaluators, the analysis was repeated with a new sample in order to resolve the discrepancy between the two evaluators' findings.
Using the Iris iQ200 ELITE (Iris Diagnostics, Chatsworth, CA, USA) and Dirui FUS-200 (DIRUI Industrial Co., Changchun, China) automatic microscopic urine analysis sediment analyzers, the evaluation of urine formed elements in the other two (uncentrifuged) tubes was carried out on the other two (uncentrifuged) tubes. For the calculations based on the instruments' measurements, the average of formed elements per LPF and HPF was used to calculate the results. A flow cell digital imaging and identification technique, achieved through the use of artificial intelligence, forms the basis of the analytical principle of the Dirui FUS-200 analyzer. The analytical principle is based on the Digital Flow Morphology technology used by the Iris iQ200 ELITE analyzer in conjunction with the Auto-Particle Recognition (APR) software, which is provided by the company. A special light source illuminates the urine analyzer as it passes through the flow cell, and the images are captured by a digital camera that is mounted in the microscope's eyepiece and transmitted to the computer via a computer interface as the microscopic urine analysis passes through the flow cell. A classification system is used to classify the images, and then those classifications are displayed on the screen for the operator to see. The operator decides whether or not to accept, modify, or delete the sediment images.
In order to account for the fact that native samples were not stable over the course of 20 days, we calculated the coefficients of variation for between-run imprecision using the results of positive controls (Dirui FUS-200 positive control and Iris iQ200 positive control) rather than native urine samples over the course of 20 days. The imprecision within a run was determined using two different pooled urine specimens containing varying concentrations of erythrocytes, leukocytes, and epithelial cells. Each analyzer ran a total of 20 runs on each specimen, resulting in a total of 240 runs on each specimen. Amounts of particulate matter per high-pressure fluid (HPF) were calculated and reported.
The statistical analyses were carried out using the SPSS Statistics 20.0 (Statistical Package for Social Sciences, IBM Corporation, Armonk, NY) and the Microsoft Excel 2007 (Microsoft Corporation, Seattle, WA) programs. Semi-quantitative classification of erythrocytes, leukocytes, and epithelial cells was carried out (0–5, 6–10, 11–20, >20 cell/HPF) on erythrocytes, leukocytes, and epithelium (0–5, 6–10, 11–20, >20 cell/HPF) on erythrocytes, leukocytes, and epithelium. Positive and negative classifications were assigned to a variety of microorganisms, such as bacteria, yeast, casts, and crystal. It was also possible to categorize semi-quantitative elements as either positive or negative, with positive results being those that exceeded the cutoff values, which were defined as 5/HPF for leukocytes, erythrocytes, and epithelial cells, respectively, with negative results being those that did not exceed the cutoff values.
The Cohen's kappa coefficient was used to determine whether or not the two methods were in agreement with one another. The kappa coefficient values range from 0–0.21 to 0.21–0.40, 0.40–0.60, 0.61–0.80, and 0.81–1.00, and are categorized as poor to fair agreement, moderate to good agreement, good agreement, and very good agreement. They were able to calculate the rates of concordance among students in the same grade level. The researchers compared the analytical sensitivity and specificity of automated analyzers to manual microscopic examination, as well as their positive and negative predictive values, in order to determine which was superior.