ABSTRACT
A 55 year old patient of COVID-19, with no known comorbidities presented with fever, myalgia and headache and at presentation had leukopenia and thrombocytopenia, however did not have any bleeding manifestations. The patient's inflammatory markers including ferritin and C-reactive protein were elevated at admission. Later in the course of illness went on to develop severe thrombocytosis and leukocytosis. We discuss the course and outcome of illness in an unusual case of COVID-19 with severe and diametrically opposite haematological abnormalities.
ABSTRACT
Context Due to the wide spectrum of clinical illness in coronavirus disease 2019 (COVID-19) patients, it is important to stratify patients into severe and nonsevere categories. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been evaluated rapidly by a few studies worldwide for its association with severe disease, but practically none have been conducted in the Indian population. This study was undertaken to examine the role of NLR and PLR in predicting severe disease in Indian patients. Objectives The objective was to study the association of NLR and PLR observed at the time of admission with maximum disease severity during hospitalization and to study their role in predicting disease severity. Material and Methods A total of 229 COVID-19 patients were admitted at the center during the study period. After applying inclusion and exclusion criteria, 191 patients were included in the study. The demographic, clinical, and laboratory (complete blood count, NLR, and PLR) data of all patients were obtained at the time of admission. Maximum disease severity of all patients was assessed during hospitalization. Statistical Analysis Chi-square and Mann-Whitney U tests were used to assess statistical significance. Receiver operating characteristic curve (ROC) was plotted for NLR and PLR to estimate the cutoff values and sensitivity and specificity using Youden's index for predicting severe disease. Logistic regression analysis was used to estimate the odds ratios (OR) and 95% confidence intervals. Results Mean NLR and PLR were significantly higher in severe patients (NLR = 7.41; PLR = 204) compared with nonsevere patients (NLR = 3.30; PLR = 121). ROC analysis showed that NLR, in comparison to PLR, had a higher area under the curve (AUC) of 0.779, with a larger OR of 1.237 and cutoff of 4.1, and showed 69% sensitivity and 78% specificity in predicting severe disease. Cut off for PLR was 115.3, which showed 79% sensitivity and 62% specificity in predicting severe disease. Conclusion NLR and PLR, both showing acceptable AUCs, can be used as screening tools to predict disease severity. However, NLR was a better predictor of disease severity.
ABSTRACT
BACKGROUND: Polypharmacy is a significant problem in the elderly. The veteran population is unique in terms of better access to health-care services and higher educational qualifications. However, the studies to assess the burden and effects of polypharmacy in this cohort are rare. Hence, the research was done to find the prevalence of polypharmacy in the veteran population. METHODS: In this cross-sectional observational study, we included veterans with more than 35 years visiting the medical outpatient department. All participants were interviewed about polypharmacy after taking informed consent. RESULTS: Out of 394 patients included in the study, 110 were prescribed five or more medicines for their illnesses (27.91%: 95% confidence interval [CI] 21.1%-30%). More than 95% (377/394) of the study participants were unaware of the concept of polypharmacy. There was high compliance to treatment in veterans (97.46%, 95% CI 95.1%-98.6%). CONCLUSION: This study shows that the prevalence of polypharmacy is significant in veterans, including patients in their fourth and fifth decades of life, despite fewer morbidities.
ABSTRACT
BACKGROUND AND AIMS: Diabetes is a frequent comorbidity in patients with Severe COVID-19 infection associated with a worse prognosis. Hypercoagulability with elevation in D-dimer levels has been demonstrated in patients with COVID-19. This study aims to study D-dimer levels in people with diabetes compared to those without diabetes among patients with COVID-19 infection. METHODS: In this observational study 98 moderate and severely ill patients with COVID-19 infection were included at a dedicated COVID hospital. The study group was divided into patients with diabetes and without diabetes. Peak D-dimer was measured in both the groups and compared using appropriate statistical tests. RESULTS: In our study peak D-dimer levels were 1509 ± 2420 ng/mL (Mean ± SD) in people with diabetes and 515 ± 624 ng/mL (Mean ± SD) in patients without diabetes. Patients with diabetes had higher D-dimer levels which were statistically significant. CONCLUSIONS: This study shows COVID-19 patients with diabetes had significantly higher D-dimer levels. Therefore, it is possible that COVID-19 infection with diabetes is more likely to cause hypercoagulable state with a worse prognosis. However clinical implications of these findings will need to be seen in further studies.
