Biomarkers to Predict Multiorgan Distress Syndrome and Acute Kidney Injury in Critically Ill Surgical Patients.

Background and Objectives: Critically ill surgical patients are susceptible to various postoperative complications, including acute kidney injury (AKI) and multiorgan distress syndrome (MODS). These complications intensify patient suffering and significantly increase morbidity and mortality rates. This study aimed to identify the biomarkers for predicting AKI and MODS in critically ill surgical patients. Materials and Methods: We prospectively enrolled critically ill surgical patients admitted to the intensive care unit via the emergency department between July 2022 and July 2023. A total of 83 patients were recruited, and their data were used to analyze MODS. Three patients who showed decreased creatinine clearance at the initial presentation were excluded from the analysis for AKI. Patient characteristics and laboratory parameters including white blood cell (WBC) count, neutrophil count, delta neutrophil index, urine and serum ß2-microglobulin, and urine serum mitochondrial DNA copy number (mtDNAcn) were analyzed to determine the reliable biomarker to predict AKI and MODS. Results: The following parameters were independently correlated with MODS: systolic blood pressure (SBP), initial neutrophil count, and platelet count, according to a logistic regression model. The optimal cut-off values for SBP, initial neutrophil count, and platelet count were 113 mmHg (sensitivity 66.7%; specificity 73.9%), 8.65 (X3) (109/L) (sensitivity 72.2%; specificity 64.6%), and 195.0 (X3) (109/L) (sensitivity 66.7%; specificity 81.5%), respectively. According to the logistic regression model, diastolic blood pressure (DBP) and initial urine mtDNAcn were independently correlated with AKI. The optimal cut-off value for DBP and initial urine mtDNAcn were 68.5 mmHg (sensitivity 61.1%; specificity 79.5%) and 1225.6 copies/µL (sensitivity 55.6%; specificity 95.5%), respectively. Conclusions: SBP, initial neutrophil count, and platelet count were independent predictors of MODS in critically ill patients undergoing surgery. DBP and initial urine mtDNAcn levels were independent predictors of AKI in critically ill surgical patients. Large-scale multicenter prospective studies are needed to confirm our results.

Effective Control of COVID-19 in South Korea: Cross-Sectional Study of Epidemiological Data.

BACKGROUND: South Korea is one of the few countries that has succeeded in flattening the curve of new COVID-19 cases and avoiding a second outbreak by implementing multiple strategies, ranging from an individual level to the population level. OBJECTIVE: We aim to discuss the unique strategies and epidemiological characteristics of COVID-19 in South Korea and present a summary of policies implemented by the Korean government during the COVID-19 pandemic. METHODS: We designed a cross-sectional study of epidemiological data published by the Korea Centers for Disease Control and Prevention on October 1, 2020. We analyzed detailed epidemiological information of COVID-19 cases, including the number of confirmed cases and resulting deaths. RESULTS: As of October 1, 2020, a total of 23,889 confirmed COVID-19 cases and 415 deaths were reported in South Korea. In this paper, we present data on the epidemiological characteristics and transmission of the disease and discuss how the South Korean government, health care providers, and society responded to the COVID-19 outbreak. CONCLUSIONS: Understanding the epidemiological characteristics of COVID-19 in South Korea and the government's successful efforts in managing the spread of the disease can provide important insights to other countries dealing with the ongoing pandemic.

Correlations of Clinical and Laboratory Characteristics of COVID-19: A Systematic Review and Meta-Analysis.

(1) Background: The global threat of Coronavirus disease 2019 (COVID-19) continues. The diversity of clinical characteristics and progress are reported in many countries as the duration of the pandemic is prolonged. We aimed to perform a novel systematic review and meta-analysis focusing on findings about correlations between clinical characteristics and laboratory features of patients with COVID-19. (2) Methods: We analyzed cases of COVID-19 in different countries by searching PubMed, Embase, Web of Science databases and Google Scholar, from the early stage of the outbreak to late March. Clinical characteristics, laboratory findings, and treatment strategies were retrospectively reviewed for the analysis. (3) Results: Thirty-seven (n = 5196 participants) COVID-19-related studies were eligible for this systematic review and meta-analysis. Fever, cough and fatigue/myalgia were the most common symptoms of COVID-19, followed by some gastrointestinal symptoms which are also reported frequently. Laboratory markers of inflammation and infection including C-reactive protein (CRP) (65% (95% confidence interval (CI) 56-81%)) were elevated, while lymphocyte counts were decreased (63% (95% CI 47-78%)). Meta-analysis of treatment approaches indicated that three modalities of treatment were predominantly used in the majority of patients with a similar prevalence, including antiviral agents (79%), antibiotics (78%), and oxygen therapy (77%). Age was negatively correlated with number of lymphocytes, but positively correlated with dyspnea, number of white blood cells, neutrophils, and D-dimer. Chills had been proved to be positively correlated with chest tightness, lung abnormalities on computed tomography (CT) scans, neutrophil/lymphocyte/platelets count, D-dimer and CRP, cough was positively correlated with sputum production, and pulmonary abnormalities were positively correlated with CRP. White blood cell (WBC) count was also positively correlated with platelet counts, dyspnea, and neutrophil counts with the respective correlations of 0.668, 0.728, and 0.696. (4) Conclusions: This paper is the first systematic review and meta-analysis to reveal the relationship between various variables of clinical characteristics, symptoms and laboratory results with the largest number of papers and patients until now. In elderly patients, laboratory and clinical characteristics indicate a more severe disease course. Moreover, treatments such as antiviral agents, antibiotics, and oxygen therapy which are used in over three quarters of patients are also analyzed. The results will provide "evidence-based hope" on how to manage this unanticipated and overwhelming pandemic.