Frontiers in medicine
-
Frontiers in medicine · Jan 2020
Mixed Method Study to Explore Ethical Dilemmas and Health Care Workers' Willingness to Work Amid COVID-19 Pandemic in Palestine.
Background: The high potential risks involved in working in a healthcare setting during a pandemic and the associated fear that may affect health care workers' (HCWs') willingness to work are important to understand to eliminate potential barriers to working. This study aimed to assess Palestinian HCWs' willingness to work and the related factors as well as to explore their ethical dilemmas during the coronavirus disease 2019 (COVID-19) pandemic. Materials and Methods: Quantitative (survey questionnaire) and qualitative (semi-structured interviews) data were collected. ⋯ Conclusion: Physicians and nurses were more likely to comply with a commitment to their professional ethics and the duty or obligation to work. Stress levels could be mitigated in the future with better leadership, adding supports to address mental health and psychosocial challenges to enhance HCWs' well-being and improve quality of care. The realities of the occupation added additional threats and uncertainty.
-
Frontiers in medicine · Jan 2020
Immune-Inflammatory Parameters in COVID-19 Cases: A Systematic Review and Meta-Analysis.
Background: The recent outbreak of coronavirus disease 2019 (COVID-19) has been rapidly spreading on a global scale and poses a great threat to human health. Acute respiratory distress syndrome, characterized by a rapid onset of generalized inflammation, is the leading cause of mortality in patients with COVID-19. We thus aimed to explore the effect of risk factors on the severity of the disease, focusing on immune-inflammatory parameters, which represent the immune status of patients. ⋯ Furthermore, we found that NLR, as a novel marker of systemic inflammatory response, can also help predict clinical severity in patients with COVID-19 (OR = 2.50, 95% CI: 2.04-3.06). Conclusions: Immune-inflammatory parameters, such as WBC, lymphocyte, PCT, CRP, and NLR, could imply the progression of COVID-19. NLR has taken both the levels of neutrophil and lymphocyte into account, indicating a more complete, accurate, and reliable inspection efficiency; surveillance of NLR may help clinicians identify high-risk COVID-19 patients at an early stage.
-
Frontiers in medicine · Jan 2020
A Machine-Learning Approach for Dynamic Prediction of Sepsis-Induced Coagulopathy in Critically Ill Patients With Sepsis.
Background: Sepsis-induced coagulopathy (SIC) denotes an increased mortality rate and poorer prognosis in septic patients. Objectives: Our study aimed to develop and validate machine-learning models to dynamically predict the risk of SIC in critically ill patients with sepsis. Methods: Machine-learning models were developed and validated based on two public databases named Medical Information Mart for Intensive Care (MIMIC)-IV and the eICU Collaborative Research Database (eICU-CRD). ⋯ The AUCs of the full and the compact models in the external validation were 0.842 (95% CI: 0.837-0.846) and 0.803 (95% CI: 0.798-0.809), respectively, which were still larger than those of Logistic Regression (0.660; 95% CI: 0.653-0.667) and SIC scores (0.752; 95% CI: 0.747-0.757). Prediction results were illustrated by SHapley Additive exPlanations (SHAP) values, which made our models clinically interpretable. Conclusions: We developed two models which were able to dynamically predict the risk of SIC in septic patients better than conventional Logistic Regression and SIC scores.
-
Frontiers in medicine · Jan 2020
Skeletal Muscle Mass Index Is Positively Associated With Bone Mineral Density in Hemodialysis Patients.
Background: Patients with chronic kidney disease (CKD) are at risk for bone loss and sarcopenia because of associated mineral and bone disorders (MBD), malnutrition, and chronic inflammation. Both osteoporosis and sarcopenia are associated with a poor prognosis; however, few studies have evaluated the relationship between muscle mass and bone mineral density (BMD) in hemodialysis (HD) patients. The present study examined the association between skeletal muscle mass index (SMI) and BMD in the lumbar spine and femoral neck in HD patients. ⋯ In multivariate analysis, SMI (standardized coefficient: 0.578) was the only independent factor that affected the lumbar spine BMD; the independent factors that affected the femoral neck BMD were SMI (standardized coefficient: 0.468), ucOC (standardized coefficient: -0.366) and sex (standardized coefficient: 0.231). Conclusion: SMI was independently associated with the BMD in the lumbar spine and femoral neck in HD patients. The preservation of skeletal muscle mass could be important to prevent BMD decrease in HD patients, in addition to the management of CKD-MBD.
-
Frontiers in medicine · Jan 2020
Classification of Patients With Sepsis According to Immune Cell Characteristics: A Bioinformatic Analysis of Two Cohort Studies.
Background: Sepsis is well-known to alter innate and adaptive immune responses for sustained periods after initiation by an invading pathogen. Identification of immune cell characteristics may shed light on the immune signature of patients with sepsis and further indicate the appropriate immune-modulatory therapy for distinct populations. Therefore, we aimed to establish an immune model to classify sepsis into different immune endotypes via transcriptomics data analysis of previously published cohort studies. ⋯ External validation further demonstrated that the present model could categorize sepsis into the immunoparalysis and immunocompetent type precisely and efficiently. The percentages of 4 types of immune cells (M0 macrophages, M2 macrophages, naïve B cells, and naïve CD4 T cells) were significantly associated with 28-day cumulative mortality (P < 0.05). Conclusion: The present study developed a comprehensive tool to identify the immunoparalysis endotype and immunocompetent status in hospitalized patients with sepsis and provides novel clues for further targeting of therapeutic approaches.