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Objectives: Several hematological and immunological markers, particularly neutrophil count, predict the severity of COVID-19. This study aimed at assessing hematological and coagulation parameters at different time points, to predict the complications or outcomes of patients with COVID-19 admitted to the intensive care unit (ICU). Methods: We conducted a prospective observational multicenter study in ICU departments. A total of 118 patients with COVID-19 admitted to the ICU were included. Clinical data and blood samples from routine hematology and coagulation tests were collected at admission, and on days 3, 7, and 14. The main outcome measures were high-flow-O2 requirement, thrombosis, and 30-day mortality. Results: The venous thromboembolism score increased from a mean of 5.10 ± 2 on day 0 to 6.40 ± 2.80 on day 14 (P = 0.0002). The disseminated intravascular coagulation (DIC) score significantly correlated with thrombosis (P = 0.031). A total of 41.20% of patients in the ICU had a DIC score ≥4, and 11.40% had a score <4. Mortality was negatively associated with patients on high-flow O2, 9 patients (10.80%) (P = 0.040), and positively associated with patients receiving ventilation, 16 patients (27.50%) (P < 0.001). An increase in white blood cell count (subdistribution hazard ratio (SHR): 0.91; 95% CI: 0.80-1) and neutrophil count (SHR: 1; 95% CI: 1.01-1.05) was associated with greater disease severity and D-dimer level (SHR: 1.60; 95% CI: 1.10-2.5). Conclusion: The venous thromboembolism score was significantly higher for patients who died than those who recovered. Furthermore, mechanical ventilation was associated with high mortality, whereas the risk of thrombosis and ICU admission correlated with high D-dimer values and DIC scores. Therefore, D-dimer levels and DIC scores are prognostic markers that may predict disease severity in patients with COVID-19.
RESUMO
The Internet of Things (IoT) has penetrated many aspects of everyday human life. The use of IoT in healthcare has been expanding over the past few years. In this review, we highlighted the current applications of IoT in the medical literature, along with the challenges and opportunities. IoT use mainly involves sensors and wearables, with potential applications in improving the quality of life, personal health monitoring, and diagnosis of diseases. Our literature review highlights that the current main application studied in the literature is physical activity tracking. In addition, we discuss the current technologies that would help IoT-enabled devices achieve safe, quick, and meaningful data transfer. These technologies include machine learning/artificial intelligence, 5G, and blockchain. Data on current IoT-enabled devices are still limited, and future research should address these devices' effect on patients' outcomes and the methods by which their integration in healthcare will avoid increasing costs.