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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.

Early recognition and rapid initiation of high-quality cardiopulmonary resuscitation (CPR) are key to maximising chances of achieving successful return of spontaneous circulation in patients with out-of-hospital cardiac arrests (OHCAs), as well as improving patient outcomes both inside and outside hospital. Mechanical chest compression devices such as the LUCAS-2 have been developed to assist rescuers in providing consistent, high-quality compressions, even during transportation. However, providing uninterrupted and effective compressions with LUCAS-2 during transportation down stairwells and in tight spaces in a non-supine position is relatively impossible. In this study, we proposed adaptations to the LUCAS-2 to allow its use during transportation down stairwells and examined its effectiveness in providing high-quality CPR to simulated OHCA patients. 20 volunteer emergency medical technicians were randomised into 10 pairs, each undergoing 2 simulation runs per experimental arm (LUCAS-2 versus control) with a loaded Resusci Anne First Aid full body manikin weighing 60 kg. Quality of CPR compressions performed was measured using the CPRmeter placed on the sternum of the manikin. The respective times taken for each phase of the simulation protocol were recorded. Fisher’s exact tests were used to analyse categorical variables and median test to analyse continuous variables. The LUCAS-2 group required a longer time (~ 35 s) to prepare the patient prior to transport (p

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 Conclusions The qSOFA score potentially is a useful prognostic predictor for influenza and could be applied in the ED as a risk stratification tool. However, qSOFA may not be a good screening tool for triage because of its poor sensitivity. The SIRS criteria showed poor predictive performance in influenza for mortality as an outcome. Further research is needed to determine the role of these predictive tools in influenza and in other viral infections.

Background Triage plays a crucial role in the emergency department (ED) management of mass casualty incidents (MCIs) when resources are limited. This study aimed to compare the performance of simple triage and rapid treatment (START) with that of the Taiwan Triage and Acuity Scale (TTAS) for the ED triage of victims following an earthquake-related MCI. Methods We retrospectively reviewed the records of victims presenting at our ED with earthquake-related injuries within 24 h of a large-scale earthquake. TTAS was initially used at our ED for this event, and START was performed by retrospectively reviewing the patient records in a blinded manner. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of START and TTAS were determined for predicting ED discharge. Results We enrolled 105 patients (predominantly women, 60.0%; median age, 45.0 years) in this study; most of them presented with traumatic injuries and were initially triaged as TTAS level III (78.1%), followed by TTAS level II (11.4%). Although the majority of the victims (81.0%) were discharged, four deaths occurred. A moderate agreement in differentiating emergency from nonemergency patients was observed between START and TTAS. Furthermore, both the triage systems showed similar predictions for ED disposition (START AUC/sensitivity/specificity: 0.709/82.35%/55.00%; TTAS AUC/sensitivity/specificity: 0.709/90.59%/45.00%). Conclusions The present study demonstrated that START and TTAS have similar triage accuracy and ability to predict ED disposition. Our findings demonstrate that START may be used as an alternative to TTAS for the ED triage of victims following earthquake-related MCIs.

Combination therapy with focused ultrasound (FUS) and a neuroprotective agent, BNG-1, was examined in an acute carotid thrombotic occlusion model using LED irradiation in rat to improve the thrombolytic effect of rt-PA. Seven treatment groups included (A) intravenous bolus injection of 0.45 mg/kg rt-PA, (B) intravenous bolus injection of 0.9 mg/kg, (C) sonothrombolysis with FUS alone, (D) oral administration of 2 g/kg BNG-1 for 7 days alone, (E) A + D, (F) A + C, and (G) A + C + D. Four comparison groups were made including (H) 0.45 mg/kg rt-PA 20% bolus +80% IV fusion + FUS, (I) 0.9 mg/kg rt-PA with 10% bolus + 90% intravenous fusion, (J) B + C, (K) B + D. At 7 days after carotid occlusion, small-animal carotid ultrasound and 7 T MR angiography showed the recanalization rate of ≤50% stenosis was 50% in group B and 83% in group I, but 0% in groups A and C and 17% in group D. Combination therapy improved recanalization rate to 50–63% in groups E and F, to 67–83% in groups J and K, and to 100% in groups G and H. Our study demonstrated combination therapy with different remedies can be a feasible strategy to improve the thrombolytic effect of rt-PA.