Assessing Concordance of Results: A Comparative Study of the Manual and Automated Urinalysis Methods.

Introduction: An accurate urine analysis is a good indicator of the status of the renal and genitourinary system. However, limited studies have been done on comparing the diagnostic performance of the fully automated analyser and manual urinalysis especially in Ghana. This study evaluated the concordance of results of the fully automated urine analyser (Sysmex UN series) and the manual method urinalysis at the Komfo Anokye Teaching Hospital in Kumasi, Ghana. Methodology. Sixty-seven (67) freshly voided urine samples were analysed by the automated urine analyser Sysmex UN series and by manual examination at Komfo Anokye Teaching Hospital, Ghana. Kappa and Bland-Altman plot analyses were used to evaluate the degree of concordance and correlation of both methods, respectively. Results: Substantial (κ = 0.711, p < 0.01), slight (κ = 0.193, p = 0.004), and slight (κ = 0.109, p < 0.001) agreements were found for urine colour, appearance, and pH, respectively, between the manual and automated methods. A strong and significant correlation (r = 0.593, p < 0.001) was found between both methods for specific gravity with a strong positive linear correlation observed for red blood cell count (r = 0.951, R2 = 0.904, p < 0.001), white blood cell count (r = 0.907, R2 = 0.822, p < 0.001), and epithelial cell count (r = 0.729, R2 = 0.532, p < 0.001). A perfect agreement of urine chemistry results in both methods was observed for nitrite 67 (100%) (κ = 1.000, p < 0.001) with a fair agreement for protein 46 (68.7%) (κ = 0.395, p < 0.001). A strong agreement was found in both methods for the presence of cast 65 (97.0%) (κ = 0.734, p < 0.001) with no concordance observed for the presence of crystals (κ = 0.115, p = 0.326) and yeast-like cells (YLC) (κ = 0.171, p = 0.116). Conclusion: The automated and manual methods showed similar performances and good correlation, especially for physical and chemical examination. However, manual microscopy remains necessary to classify urine sediments, particularly for bacteria and yeast-like cells. Future research with larger samples could help validate automated urinalysis for wider clinical use and identify areas requiring improved automated detection capabilities.

Health-related quality of life of type 2 diabetes mellitus patients: A cross-sectional study in the cape coast metropolis.

Background and Aim: Type 2 diabetes mellitus (DM) has in recent decades become a global pandemic, accounting for over 90% of DM cases. The study evaluated the health-related quality of life (HrQoL) and identified its determinants among type 2 DM patients at the University of Cape Coast Hospital. Methods: We conducted our study at the University of Cape Coast Hospital from January to March 2022. The EQ-5D-5L questionnaire was administered to 68 type 2 DM patients. Data were then inputted into Microsoft Excel and analyzed accordingly using IBM SPSS statistical software version 26 and GraphPad Prism 8. Results: The mean age of the participants was 60.71 ± 12.18 with 55.9% being females. The average systolic, diastolic blood pressure and fasting blood glucose (FBG) of participants were 140.99 ± 22.27, 85 ± 11.14 and 7.97 ± 2.66 respectively. With the EQ-5D-5L scale, participants reported severe to extreme problems mainly in pain/discomfort (19.1%) and mobility (8.8%) dimensions. Approximately 21% (14/68) of patients reported themselves as being in perfect health based on the EQ-5D index score with no significant difference between males and females (p ≥ 0.05). On a scale of 0 to 100, most (26.5%) of the participants rated their general health state at 80. Age was significantly associated with all five dimensions while patients with comorbidities had higher odds of experiencing pain/discomfort and anxiety/depression. Conclusion: The study reveals that pain/discomfort and anxiety/depression are the most experienced problems among patients with type 2 DM. The HrQoL of type 2 DM patients was also found to be affected by age, comorbidities, systolic and diastolic blood pressure. Therefore, identifying these factors and developing appropriate interventions is crucial for improving patient outcomes and enhancing treatment outcomes.