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Degree of COVID-19 severity and mortality in stroke: correlation of clinical and laboratory parameters
Abdul Gofir1, Irawan Satriotomo2, Yossy Catarina Budi Nur Syamsah3
1Department of Neurology, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada/ Dr. Sardjito General Hospital, Jalan Farmako Sekip Utara, Sleman, Mlati, Yogyakarta, 55281, Indonesia. gofir@ugm.ac.id.
Insights
Stroke is a serious COVID-19 complication. Loss of consciousness, motor deficits, respiratory distress, and high monocyte counts predict mortality in these patients. The risk increases with multiple coexisting factors.
Area of Science:
- Neurology
- Infectious Diseases
- Critical Care Medicine
Background:
- Stroke is a significant neurological complication of COVID-19, associated with increased morbidity and mortality.
- Understanding predictors of mortality in COVID-19 stroke patients is crucial for clinical management.
- This study investigates clinical and laboratory factors associated with mortality in this patient population.
Purpose of the Study:
- To identify predictors of mortality in patients with acute stroke and confirmed COVID-19.
- To analyze the association between clinical manifestations, laboratory parameters, and mortality.
- To inform clinical decision-making and improve outcomes for COVID-19 stroke patients.
Main Methods:
- A case-control study was conducted at Dr. Sardjito General Hospital, Indonesia (July 2020 - August 2021).
- Clinical and laboratory data from 72 acute stroke patients with COVID-19 were collected and analyzed.
- Bivariate and multivariate analyses, including Hazard Ratio (HR) calculations, were performed to determine mortality predictors.
Main Results:
- The study included 72 COVID-19 stroke patients; most had ischemic stroke and hypertension.
- Significant predictors of mortality included loss of consciousness (HR=2.68), motor deficit (HR=2.34), respiratory distress (HR=81.51), and elevated monocyte count (HR=1.002).
- Severe COVID-19 (52.8%), respiratory distress (56.9%), and high mortality rates (58.3%) were observed.
Conclusions:
- Mortality in COVID-19 patients with stroke is significantly linked to loss of consciousness, motor deficit, respiratory distress, and elevated monocyte count.
- The presence of multiple risk factors amplifies the risk of mortality.
- These findings underscore the importance of monitoring these factors for improved patient outcomes.
Background:
Stroke is one of the neurological manifestations of COVID-19, leading to a significant risk of morbidity and mortality. Clinical manifestations and laboratory parameters were investigated to determine mortality predictors in this case.
Method:
The case control study was conducted at Dr. Sardjito General Hospital,Yogyakarta, Indonesia, with data collected between July 2020 and August 2021. All recorded clinical and laboratory data from acute stroke patients with confirmed COVID-19 were collected. Baseline characteristics, bivariate, and multivariate analyses were assessed to determine significant predictors for mortality.
Result:
This study involved 72 subjects with COVID-19 and stroke. The majority experienced ischemic stroke, with hypertension as the most prevalent comorbidity. Notably, 45.8% of subjects (p < 0.05) loss of consciousness and 72.2% of exhibited motor deficits (p < 0.05). Severe degree of COVID-19 was observed in 52.8% of patients, with respiratory distress and death rates of 56.9% and 58.3%. Comparison of surviving and deceased groups highlighted significant differences in various clinical and laboratory characteristics differences. Hazard ratio (HR) analysis identified loss of consciousness (HR = 2.68; p = 0.01), motor deficit (HR = 2.34; p = 0.03), respiratory distress (HR = 81.51; p < 0.001), and monocyte count (HR:1.002; p = 0.04) as significant predictors of mortality.
Conclusion:
Mortality in COVID-19 patients with stroke was significantly associated with loss of consciousness, motor deficit, respiratory distress, and raised monocyte count. The risk of mortality is heightened when multiple factors coexist.
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