Association between Initial Fibrinogen Levels and the Need for Massive Transfusion in Emergency Department Patients with Primary Postpartum Hemorrhage: A Retrospective Study from a Single Center in Korea.

BACKGROUND: This study aimed to evaluate the association between initial fibrinogen levels and massive transfusion (MT) in emergency department (ED) patients with primary postpartum hemorrhage (PPH). METHODS: This retrospective study was conducted in the ED of a university-affiliated, tertiary referral center from January 2004 to August 2023. Patients were divided into two groups: the MT group, which included those who received a transfusion of 10 or more units of packed red blood cells within the first 24 h, and the Non-MT group. RESULTS: Out of the 364 patients included in the study, 97 (26.6%) required MT. Fibrinogen, shock index, and lactate were independently associated with MT (odds ratio [OR] 0.987; 95% confidence interval [CI] 0.983-0.991; p < 0.001, OR 7.277; 95% CI 1.856-28.535; p = 0.004, and OR 1.261; 95% CI 1.021-1.557; p = 0.031, respectively). The area under the receiver operating characteristic curve for fibrinogen, shock index, and lactate in predicting MT was 0.871 (95% CI 0.832-0.904; p < 0.001), 0.821 (95% CI 0.778-0.859; p < 0.001), and 0.784 (95% CI 0.738-0.825; p < 0.001), respectively. When the cutoff value of fibrinogen was 400 mg/dL, both the sensitivity and negative predictive values for predicting MT were 100.0%. When the cutoff value of fibrinogen was 100 mg/dL, the specificity and positive predictive values were 91.8% and 70.7%, respectively. CONCLUSION: The initial fibrinogen levels were independently associated with the need for MT in ED patients with primary PPH.

Prediction of Neurologically Intact Survival in Cardiac Arrest Patients without Pre-Hospital Return of Spontaneous Circulation: Machine Learning Approach.

Current multimodal approaches for the prognostication of out-of-hospital cardiac arrest (OHCA) are based mainly on the prediction of poor neurological outcomes; however, it is challenging to identify patients expected to have a favorable outcome, especially before the return of spontaneous circulation (ROSC). We developed and validated a machine learning-based system to predict good outcome in OHCA patients before ROSC. This prospective, multicenter, registry-based study analyzed non-traumatic OHCA data collected between October 2015 and June 2017. We used information available before ROSC as predictor variables, and the primary outcome was neurologically intact survival at discharge, defined as cerebral performance category 1 or 2. The developed models' robustness were evaluated and compared with various score metrics to confirm their performance. The model using a voting classifier had the best performance in predicting good neurological outcome (area under the curve = 0.926). We confirmed that the six top-weighted variables predicting neurological outcomes, such as several duration variables after the instant of OHCA and several electrocardiogram variables in the voting classifier model, showed significant differences between the two neurological outcome groups. These findings demonstrate the potential utility of a machine learning model to predict good neurological outcome of OHCA patients before ROSC.

Model for end-stage liver disease score as a predictor of short-term outcome in patients with drug-induced liver injury.

OBJECTIVES: The purposes of this study were to investigate the clinical presentation, cause and outcome of drug-induced liver injury (DILI) and to evaluate the predictive value of the model for end-stage liver disease (MELD) score in DILI. METHODS: Patients diagnosed with DILI between January 1, 2010 and December 31, 2012 in the Emergency Department at Asan Medical Center in Seoul, Korea were analyzed retrospectively. The primary end point was poor outcome, defined as liver transplantation or death within 30 days of the initial hospital visit. RESULTS: Of 213 patients, 13.1% had a 30-day poor outcome. Folk remedies were the most common cause of DILI in 147 patients (69%). Univariate logistic regression analysis showed that multiple drugs (odds ratio [OR] 2.30, 95% confidence interval [CI]: 1.03-5.15), concurrent alcohol consumption (OR 3.69, 95% CI: 1.03-13.18), white blood cell (WBC) count (OR 1.17, 95% CI: 1.07-1.28), hemoglobin (Hb) (OR 0.60, 95% CI: 0.49-0.74), platelet count (OR 0.993, 95% CI: 0.987-0.998), total bilirubin (OR 1.09, 95% CI: 1.06-1.13) and MELD (OR 1.23, 95% CI: 1.15-1.32) were significantly associated with 30-day poor outcomes. Multivariate analysis showed that the MELD (OR 1.21, 95% CI: 1.12-1.30) and Hb (OR 0.77, 95% CI: 0.61-0.98) were independent predictors of poor outcome. For 30-day mortality, the c-statistics for MELD alone and for combination of MELD and Hb were 0.93 (95% CI: 0.89-0.97) and 0.94 (95% CI: 0.90-0.97), respectively. CONCLUSION: The outcome of patients with DILI was poor. MELD score and Hb were reliable predictors of short-term outcome in patients with DILI.