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Background and Aims: Central nervous system (CNS) infection is one of the most common causes of morbidity, mortality, and hospital admission worldwide. The natural history of CNS infection is quite fatal. Early diagnosis and treatment have been proven to have a crucial role in patients' survival. The aim of this study was to identify the epidemiological and clinical patterns of patients diagnosed with CNS infections. Methods: This study is a retrospective study conducted in a tertiary level hospital in Nepal in which patient diagnosed with CNS infections (September 2019 to 2021) were included. Data were collected and analyzed in SPSS. Results: The mean age of the 95 patients included in the study was 45.18 ± 19.56. Meningoencephalitis (n = 44, 46.30%) was the most common infection diagnosed. Patients belonging to the age group 30-60 years had a higher frequency of focal neurological deficit, and other classical clinical features. All the patients who died during the treatment had associated comorbidities but no concurrent infections. Altered sensorium, fever, and headache were the common presenting symptoms in all the recovered patients. Conclusion: To ensure optimum disease outcome, early diagnosis and prompt management are crucial. For this, recognizing the local disease patterns in terms of disease distribution, commonly implicated aetiologies, presenting symptoms, and prognostic factors is of utmost importance.
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PURPOSE: We tried to investigate the diagnostic accuracy of glycogen phosphorylase BB as a cardiac marker for myocardial infarction. METHODS: We searched through different electronic databases (PubMed, Google-scholar, Embase, and Cochrane Library) to locate relevant articles. Studies, with sufficient data to reconstruct a 2 × 2 contingency table, met our inclusion criteria were included. Three reviewers independently screened the articles. Discrepancies were resolved by other reviewers. Unpublished data were requested from the authors of the study via email. Subsequently, data extraction was done using a standardized form and quality assessment of studies using the QUADAS-2 tool. Meta-analysis was done using a bivariate model using R software. RESULTS: Fourteen studies were selected for the final evaluation, which yielded the summary points: pooled sensitivity 87.77% (77.52%-93.72%, I2 = 86%), pooled specificity 88.45% (75.59%-94.99%, I2 = 88%), pooled DOR 49.37(14.53-167.72, I2 = 89%), and AUC of SROC was 0.923. The lambda value of the HSROC curve was 3.670. The Fagan plot showed that GPBB increases the pretest probability of myocardial infarction from 46% to 81% when positive, and it lowers the same probability to 12% when negative. CONCLUSION: With these results, we can conclude that GPBB has modest accuracy in screening myocardial infarction, but the limitations of the study warrant further high-quality studies to confirm its usefulness in predicting myocardial infarction (MI).