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Abstract Background Early diagnosis and treatment of patients with sepsis reduce mortality significantly. In terms of exploring new diagnostic tools of sepsis, monocyte distribution width (MDW), as part of the white blood cell (WBC) differential count, was first reported in 2017. MDW greater than 20 and abnormal WBC count together provided a satisfactory accuracy and was proposed as a novel diagnostic tool of sepsis. This study aimed to compare MDW and procalcitonin (PCT)’s diagnostic accuracy on sepsis in the emergency department. Methods This was a single-center prospective cohort study. Laboratory examinations including complete blood cell and differentiation count (CBC/DC), MDW, PCT were obtained while arriving at the ED. We divided patients into non-infection, infection without systemic inflammatory response syndrome (SIRS), infection with SIRS, and sepsis-3 groups. This study’s primary outcome is the sensitivity and specificity of MDW, PCT, and MDW + WBC in differentiating septic and non-septic patients. In addition, the cut-off value for MDW was established to maximize sensitivity at an optimal level of specificity. Results From May 2019 to September 2020, 402 patients were enrolled for data analysis. Patient number in each group was: non-infection 64 (15.9%), infection without SIRS 82 (20.4%), infection with SIRS 202 (50.2%), sepsis-3 15 (7.6%). The AUC of MDW, PCT, and MDW + WBC to predict infection with SIRS was 0.753, 0.704, and 0.784, respectively (p

Abstract Background Infleunza is a challenging issue in public health. The mortality and morbidity associated with epidemic and pandemic influenza puts a heavy burden on health care system. Most patients with influenza can be treated on an outpatient basis but some required critical care. It is crucial for frontline physicians to stratify influenza patients by level of risk. Therefore, this study aimed to create a prediction model for critical care and in-hospital mortality. Methods This retrospective cohort study extracted data from the Chang Gung Research Database. This study included the patients who were diagnosed with influenza between 2010 and 2016. The primary outcome of this study was critical illness. The secondary analysis was to predict in-hospital mortality. A two-stage-modeling method was developed to predict hospital mortality. We constructed a multiple logistic regression model to predict the outcome of critical illness in the first stage, then S1 score were calculated. In the second stage, we used the S1 score and other data to construct a backward multiple logistic regression model. The area under the receiver operating curve was used to assess the predictive value of the model. Results In the present study, 1680 patients met the inclusion criteria. The overall ICU admission and in-hospital mortality was 10.36% (174 patients) and 4.29% (72 patients), respectively. In stage I analysis, hypothermia (OR = 1.92), tachypnea (OR = 4.94), lower systolic blood pressure (OR = 2.35), diabetes mellitus (OR = 1.87), leukocytosis (OR = 2.22), leukopenia (OR = 2.70), and a high percentage of segmented neutrophils (OR = 2.10) were associated with ICU admission. Bandemia had the highest odds ratio in the Stage I model (OR = 5.43). In stage II analysis, C-reactive protein (OR = 1.01), blood urea nitrogen (OR = 1.02) and stage I model’s S1 score were assocaited with in-hospital mortality. The area under the curve for the stage I and II model was 0.889 and 0.766, respectively. Conclusions The two-stage model is a efficient risk-stratification tool for predicting critical illness and mortailty. The model may be an optional tool other than qSOFA and SIRS criteria.

Abstract Background The seasonal influenza epidemic is an important public health issue worldwide. Early predictive identification of patients with potentially worse outcome is important in the emergency department (ED). Similarly as with bacterial infection, influenza can cause sepsis. This study was conducted to investigate the effectiveness of the Systemic Inflammatory Response Syndrome (SIRS) criteria and the quick Sequential Organ Failure Assessment (qSOFA) score as prognostic predictors for ED patients with influenza. Methods This single-center, retrospective cohort study investigated data that was retrieved from a hospital-based research database. Adult ED patients (age ≥ 18 at admission) with laboratory-proven influenza from 2010 to 2016 were included for data analysis. The initial SIRS and qSOFA scores were both collected. The primary outcome was the utility of each score in the prediction of in-hospital mortality. Results For the study period, 3561 patients met the study inclusion criteria. The overall in-hospital mortality was 2.7% (95 patients). When the qSOFA scores were 0, 1, 2, and 3, the percentages of in-hospital mortality were 0.6, 7.2, 15.9, and 25%, respectively. Accordingly, the odds ratios (ORs) were 7.72, 11.92, and 22.46, respectively. The sensitivity and specificity was 24 and 96.2%, respectively, when the qSOFA score was ≥2. However, the SIRS criteria showed no significant associations with the primary outcome. The area under the receiver operating characteristic curve (AUC) was 0.864, which is significantly higher than that with SIRS, where the AUC was 0.786 (P