New Prognostic Parameter of West Nile Virus: Platelet Distribution Width

Background: West Nile virus (WNV) infection is a viral disease caused by arboviruses. It can cause epidemics of febrile diseases and meningoencephalitis, especially at the end of the summer season. In this study, we aimed to determine the risk factors of WNV encephalitis with a case-control study of the patients followed in our clinic. Materials and Methods: Among the patients who applied to our hospital with sudden onset fever, headache, myalgia, nausea, vomiting, maculopapular rash, viral meningitis, or encephalitis findings in late summer and early autumn, those diagnosed with positive WNV PCR and antibody tests were defined as WNV cases. In the same date range, patients with clinically compatible but negative serological and PCR tests for WNV in our hospital were considered as the control group. Results: WNV infection was diagnosed in 26 of 48 patients who were examined with a preliminary diagnosis of WNV infection, and the other 22 patients were considered as the control group. A statistically significant difference was found between the two groups in C-reactive protein, procalcitonin, 1-h erythrocyte sedimentation rate, alkaline phosphatase, platelet, and platelet distribution width (PDW). PDW >17.85% indicated WNV infection with 82% sensitivity and 91% specificity. PDW percentage >17.85 increased the risk of WNV infection by 6.1 times. The power of the study was calculated as 83%. Conclusion: The most common findings in WNV cases were fever and confusion. WNV infection should be considered in the differential diagnosis in patients with fever and confusion in September and October in settlements on the migration route of birds. The percentage of PDW in whole blood examination can guide the differential diagnosis of WNV cases.

Effect of a combination of gliptin and metformin on serum vitamin B12, folic acid, and ferritin levels

OBJECTIVE

The primary objective of this study was to explore the impact of metformin and metformin/gliptin combination therapy on the serum concentrations of vitamin B12, ferritin, and folic acid in individuals diagnosed with type 2 diabetes.

METHODS

This study included 118 patients, classified into two groups: 59 patients using only metformin and 59 patients using a combination of metformin/gliptin. Among the latter group, 35 patients used vildagliptin/metformin, and 24 used sitagliptin/metformin. The study recorded the demographic data such as the age and gender of the patients, as well as their initial and 1-year follow-up blood parameters.

RESULTS

Folic acid decreased significantly in the metformin group but not in the metformin/gliptin group. Vitamin B12 and ferritin decreased significantly in both groups. The decrease in vitamin B12 and ferritin was not significantly different between the two groups. The decrease in fasting plasma glucose was more significant in the metformin/gliptin group than in the metformin group.

CONCLUSION

After 1 year, both groups taking metformin and metformin/gliptin showed low serum ferritin and vitamin B12 levels. Therefore, vitamin B12 levels in patients using these drugs should be closely monitored. Ferritin levels can be used to indicate whether glycemic control has been achieved.

Can artificial intelligence predict COVID-19 mortality?

OBJECTIVE

COVID-19 infection rapidly spread across the globe and evolved into a pandemic. Artificial intelligence (AI) has been used to predict the spread of the virus and diagnose and treat the disease. In this study, we aimed to predict whether patients admitted to the intensive care unit (ICU) due to COVID-19 infection will result in mortality.

PATIENTS AND METHODS

Ninety parameters were used for each 589 ICU patient. The nine parameters with the highest effect on mortality were determined. Four hundred seventy-one patients were used to train the AI with these nine parameters. AI was tested with 118 patient data.

RESULTS

AI estimated mortality with 83% sensitivity, 84% specificity, 84% accuracy, and 0.81 F1 score. Therefore, the area under the curve was calculated as 0.91. The results indicate that mortality among COVID-19 patients admitted to the ICU can be predicted based on their laboratory parameters on the first day.

CONCLUSIONS

These findings underscore the potential benefits of utilizing AI in managing pandemics.

Is the COVID-19 disease associated with de novo nephritic syndrome?

INTRODUCTION

This study aims to determine the incidence of de novo nephritic syndrome (NS) in COVID-19 patients and identify its associated factors.

METHODS

All ward patients with COVID-19 pneumonia were investigated. After determining the inclusion and exclusion criteria, the study population was identified. The urine dipstick test and urine protein creatinine ratio (UPCR) measurements were performed. Patients with de novo NS findings, nasopharyngeal swab, and urine RT-PCR tests were performed simultaneously.

RESULTS

This descriptive cross-sectional study was conducted with 21 patients with COVID-19. The mean age of the patients was 42.2±8.8 years, and 71.4% of them were male. The mean duration of follow-up was 28.4±9.3 days. The urine RT-PCR test was positive in one patient (4.8%). Improvements were observed in hematuria by 71.4%, and proteinuria by 85.7% at the end of the follow-up. A significant decrease in the measured UPCR was found in comparison to the baseline(P=0.000). Also, improvements were recorded in the complete blood counts, inflammatory parameters, ferritin, and coagulation tests, compared to the baseline. There was a positive correlation between baseline UPCR and ferritin, and a negative correlation between baseline UPCR and sodium values.

CONCLUSION

COVID-19-induced de novo nephritic syndrome may occur mainly due to tubulointerstitial involvement and often results in spontaneous remission. However, why these findings were not present in all patients who had no comorbidities is not clear.