ABSTRACT
Introduction With the spread of the Covid-19 pandemic and its overwhelming impact on health systems in several countries, the importance of identifying predictors of severity is of paramount importance. The objective of this study is to determine the relationship between death and the biological parameters of patients with Covid-19. Materials and methods This is an analytical retrospective cohort study conducted on 326 patients admitted to the Mohammed VI University Hospital in Oujda, Morocco. The statistical analysis concerned the biological parameters carried out on the admission of the patients, in addition to age and sex. The comparison between the two surviving and non-surviving groups was made by a simple analysis than a multivariate analysis by logistic regression. Next, a survival analysis was performed by the Kaplan-Meier method and then by Cox regression. Results A total of 326 patients were included in the study, including 108 fatal cases. The mean age was 64.66 ± 15.51 and the sex ratio was 1.08:1 (M:F). Age, procalcitonin, liver enzymes, and coagulation factors were significantly higher in patients who died of Covid-19 and are therefore considered to be the main prognostic factors identified in this study. Conclusion Knowledge and monitoring of predictive biomarkers of poor prognosis in patients with Covid-19 could be of great help in the identification of patients at risk and in the implementation of an effective diagnostic and therapeutic strategy to predict severe disease forms.
ABSTRACT
Background: Coronavirus disease (COVID-19), caused by a betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly evolved into a pandemic since it was first reported in December 2019. thus, SARS-CoV-2 has become a major global public health issue. Objective: The objective of this work is to compare demographics, comorbidities, clinical symptoms, biology and imaging findings between severe and non-severe COVID-19 patients and to identify clinical and biological risk factors and biomarkers for the development of severe COVID-19 as well as predictive thresholds for severity in order to best rationalize management and decrease the morbidity and mortality caused by this condition. Patients and methods: This is a single-center retrospective study, from June 25 to December 31, 2021, on 521 patients at the level of the unit COVID-19 of the central laboratory of the Mohammed VI University Hospital Center Oujda, then classified into two groups according to the severity of the disease. Results: Out of a total of 521 patients, a severe group including 336 cases (64.5%) and a non-severe group with 185 cases (35.5%). Hypertension, diabetes and obesity were noted in the majority of patients. Severe COVID-19 cases had higher C-reactive protein, procalcitonin, D-dimer, ferritin, elevated white blood cell count, and lower lymphocyte count than non-severe cases with a significant difference between the two groups. The areas under the curve (AUC) for C-reactive protein, procalcitonin and D-dimer were 0.886, 0.708, and 0.736 respectively. The optimal thresholds predictive of severity were 105 mg/l for C-reactive protein, 0.13 ng/ml for procalcitonin, 7420/µl for white blood cell count, and 0.55 mg/l for D-dimer. Conclusion: Comparison of the proportion of clinical, biological and radiological data between severe and non-severe cases of COVID-19, as well as identification of biomarkers for the development of severe form in the present study, will allow optimal streamlining of management with rapid triage of patients.