Frontiers in medicine
-
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
Transnasal Humidified Rapid Insufflation Ventilatory Exchange With Nasopharyngeal Airway Facilitates Apneic Oxygenation: A Randomized Clinical Noninferiority Trial.
Background: Transnasal humidified rapid insufflation ventilatory exchange (THRIVE) was used to extend the safe apnea time. However, THRIVE is only effective in patients with airway opening. Nasopharyngeal airway (NPA) is a simple device that can help to keep airway opening. ⋯ No patient had a SpO2 < 90% during apnea. Conclusion: When THRIVE was applied during anesthesia-induced apnea, NPA placement kept airway opening and was noninferior to jaw thrust in terms of its effects on PaO2 and PaCO2 at 20 min after apnea. Clinical Trial Registration: ClinicalTrials.gov (NCT03741998).
-
Frontiers in medicine · Jan 2020
Performance of Two Risk-Stratification Models in Hospitalized Patients With Coronavirus Disease.
Background: Despite an increase in the familiarity of the medical community with the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19), there is presently a lack of rapid and effective risk stratification indicators to predict the poor clinical outcomes of COVID-19 especially in severe patients. Methods: In this retrospective single-center study, we included 117 cases confirmed with COVID-19. The clinical, laboratory, and imaging features were collected and analyzed during admission. ⋯ The K-M survival analysis showed that patients with MuLBSTA score ≥ 12 had higher risk of ICU (log-rank, P = 0.001) and high risk of death (log-rank, P = 0.000). Conclusions: The MuLBSTA score is valuable for risk stratification and could effectively screen high-risk patients at admission. The higher score at admission have higher risk of ICU care and death in patients infected with COVID.