D-dimer as a biomarker for assessment of COVID-19 prognosis: D-dimer levels on admission and its role in predicting disease outcome in hospitalized patients with COVID-19.

INTRODUCTION: Coronavirus Disease 2019 is a primarily respiratory illness that can cause thrombotic disorders. Elevation of D-dimer is a potential biomarker for poor prognosis in COVID-19, though optimal cutoff value for D-dimer to predict mortality has not yet been established. This study aims to assess the accuracy of admission D-dimer in the prognosis of COVID-19 and to establish the optimal cutoff D-dimer value to predict hospital mortality. METHODS: Clinical and laboratory parameters and outcomes of confirmed COVID-19 cases admitted to four hospitals in Kathmandu were retrospectively analyzed. Admitted COVID-19 cases with recorded D-dimer and definitive outcomes were included consecutively. D-dimer was measured using immunofluorescence assay and reported in Fibrinogen Equivalent Unit (µg/ml). The receiver operating characteristic curve was used to determine the accuracy of D-dimer in predicting mortality, and to calculate the optimal cutoff value, based on which patients were divided into two groups and predictive value of D-dimer for mortality was measured. RESULTS: 182 patients were included in the study out of which 34(18.7%) died during the hospital stay. The mean admission D-dimer among surviving patients was 1.067 µg/ml (±1.705 µg/ml), whereas that among patients who died was 3.208 µg/ml (±2.613 µg/ml). ROC curve for D-dimer and mortality gave an area under the curve of 0.807 (95% CI 0.728-0.886, p<0.001). Optimal cutoff value for D-dimer was 1.5 µg/ml (sensitivity 70.6%, specificity 78.4%). On Cox proportional hazards regression analysis, the unadjusted hazard ratio for high D-dimer was 6.809 (95% CI 3.249-14.268, p<0.001), and 5.862 (95% CI 2.751-12.489, p<0.001) when adjusted for age. CONCLUSION: D-dimer value on admission is an accurate biomarker for predicting mortality in patients with COVID-19. 1.5 µg/ml is the optimal cutoff value of admission D-dimer for predicting mortality in COVID-19 patients.

Premenstrual Syndrome in Students of a Teaching Hospital.

BACKGROUND: Premenstrual syndrome is group of psychosomatic symptoms which occurs during second half of menstrual cycle. Significant number of reproductive aged females suffer from it with its impact on their daily activities. This study was conducted to assess the prevalence, severity and impacts of Premenstrual syndrome on female students of a teaching hospital of Kathmandu, Nepal. METHODS: This cross-sectional study was conducted among female students of a teaching hospital from Kathmandu over a period of three months. Premenstrual Symptom Screening Tool was used to quantify the symptoms severity and their effect in activities. In addition; patient profile, socioeconomic status were recorded. The obtained information was entered in Statistical Package for Social Sciences and analyzed. Findings were then interpreted using chi-square test. RESULTS: Out of the 285 respondents, 206 (72.3%) reported at least one premenstrual syndrome symptom of moderate to severe intensity among which 74 (25.9%) had at least one severe symptom. Six individuals (2.1%) fulfilled all criteria for Pre-Menstrual Dysphoric Disorder and 49 (17.2%) fulfilled the criteria for moderate to severe premenstrual syndrome and rest (80.7%) were having no or mild premenstrual syndrome with isolated symptoms. PMS was found to have significant association to menstrual bleeding (p?0.001) and severity of dysmenorrhea (p?0.001), family history of premenstrual syndrome (p=0.019) and physical activity (p=0.021). CONCLUSIONS: Premenstrual syndrome is common in female and has a considerable impact on day to day activities activities although its severe form Pre-Menstrual Dysphoric Disorder is less common.