Search

Background: Recent studies suggested an expected survival benefit associated with anticoagulant therapies for sepsis in patients with disseminated intravascular coagulation (DIC). However, anticoagulant therapies for overt DIC are no longer assumed to regulate pathologic progression as overt DIC is a late-phase coagulation disorder. Therefore, methods for early prediction of sepsis-induced DIC before its progression to an overt stage are strongly required. Objectives: We aimed to develop a prediction model for overt DIC using machine learning. Methods: This retrospective, observational study included adult septic patients without overt DIC. The objective variable was binary classification of whether patients developed overt DIC based on International Society on Thrombosis and Haemostasis (ISTH) overt DIC criteria. Explanatory variables were the baseline and time series data within 7 days from sepsis diagnosis. Light Gradient Boosted Machine method was used to construct the prediction model. For controls, we assessed sensitivity and specificity of Japanese Association for Acute Medicine DIC criteria and ISTH sepsis-induced coagulopathy criteria for subsequent onset of overt DIC. Results: Among 912 patients with sepsis, 139 patients developed overt DIC within 7 days from diagnosis of sepsis. Sensitivity, specificity, and area under the receiver operating characteristic curve for predicting onset of overt DIC within 7 days were 84.4%, 87.5%, and 0.867 in the test cohort and 95.0%, 75.9%, and 0.851 in the validation cohort, respectively. Sensitivity and specificity by the diagnostic thresholds were 54.7% and 74.9% for Japanese Association for Acute Medicine DIC criteria and 63.3% and 71.9% for ISTH sepsis-induced coagulopathy criteria, respectively. Conclusion: Compared with conventional DIC scoring systems, a machine learning model might exhibit higher prediction accuracy.

Background: The effect of hospital spending on the mortality rate of patients with sepsis has not yet been fully elucidated. We hypothesized that hospitals that consume more medical resources would have lower mortality rates among patients with sepsis. Methods: This retrospective study used administrative data from 2010 to 2017. The enrolled hospitals were divided into quartiles based on average daily medical cost per sepsis case. The primary and secondary outcomes were the average in-hospital mortality rate of patients with sepsis and the effective cost per survivor among the enrolled hospitals, respectively. A multiple regression model was used to determine the significance of the differences among hospital categories to adjust for baseline imbalances. Results: Among 997 hospitals enrolled in this study, the crude in-hospital mortality rates were 15.7% and 13.2% in the lowest and highest quartiles of hospital spending, respectively. After adjusting for confounding factors, the highest hospital spending group demonstrated a significantly lower in-hospital mortality rate than the lowest hospital spending group (coefficient = −0.025, 95% confidence interval [CI] −0.034 to −0.015; p

ABSTRACT: Introduction: The rapid increase of extended-spectrum beta-lactamase (ESBL)-producing pathogens makes it difficult to choose appropriate antimicrobials in patients with Gram-negative bacterial infection. The Cica-beta reagent (Kanto Chemical, Tokyo, Japan) is a chromogenic test that detects ESBLs from bacterial colonies. This study aimed to reveal whether Cica-beta reagent could detect ESBLs directly from urine samples to facilitate rapid diagnosis of antibiotic susceptibility. Methods: A prospective study was conducted from July 2019 to November 2019. Patients in whom urine culture tests were performed were eligible. Each urine sample was centrifuged, and the pellet was mixed with Cica-beta reagent. The test was considered positive when the enzymatic reaction turned from yellow to red or orange. Results: In total, 350 urine samples were analysed. Urinary tract infection (UTI) was diagnosed in 214 patients. ESBL-producing Enterobacterales were isolated from 79 samples. The Cica-beta test showed sensitivity of 79.8% and specificity of 99.3% in patients with Gram-negative bacteriuria. Sensitivity and specificity improved to 90.2% and 100%, respectively, in patients with UTI. Conclusion: The Cica-beta test could be an efficient test for the detection of ESBL-producing pathogens in urine. By providing immediate information about ESBLs, it might be a useful point-of-care test to guide appropriate antimicrobial use in patients with UTI.

Objectives: One of the most significant features of poor prognosis in COVID-19 is pulmonary fibrosis. Nintedanib is a new antifibrotic agent that interferes with processes of pulmonary fibrosis. This study aimed to investigate the efficacy and safety of nintedanib in COVID-19. Methods: This was an interventional study in which adult patients with COVID-19 requiring mechanical ventilation were consecutively enrolled. The primary endpoint was 28-day mortality after the initiation of mechanical ventilation. The secondary endpoints were length of mechanical ventilation, volume of lung injury, and the incidence of gastrointestinal adverse events and acute liver failure. Results: Thirty patients with COVID-19 underwent nintedanib therapy. We included 30 patients not receiving nintedanib as the historical control group. There were no significant differences in 28-day mortality between the groups (23.3% vs 20%, P = 0.834). Lengths of mechanical ventilation were significantly shorter in the nintedanib group (P = 0.046). Computed tomography volumetry showed that the percentages of high-attenuation areas were significantly lower in the nintedanib group at liberation from mechanical ventilation (38.7% vs 25.7%, P = 0.027). There were no significant differences in the adverse events. Conclusions: The administration of nintedanib may offer potential benefits for minimizing lung injury in COVID-19.

Background: There is no one-size-fits-all empiric antimicrobial therapy for sepsis because the pathogens vary according to the site of infection and have changed over time. Therefore, updating knowledge on the spectrum of pathogens is necessary for the rapid administration of appropriate antimicrobials. Objective: The aim of this study was to elucidate the current spectrum of pathogens and its variation by site of infection in sepsis. Methods: This was a prospective nationwide cohort study of consecutive adult patients with sepsis in 59 intensive care units in Japan. The spectrum of pathogens was evaluated in all patients and in subgroups by site of infection. Regression analyses were conducted to evaluate the associations between the pathogens and mortality. Results: The study cohort comprised 1184 patients. The most common pathogen was Escherichia coli (21.5%), followed by Klebsiella pneumoniae (9.0%). However, the pattern varied widely by site of infection; for example, gram-positive bacteria were the dominant pathogen in bone/soft tissue infection (55.7%) and cardiovascular infection (52.6%), but were rarely identified in urinary tract infection (6.4%). In contrast, gram-negative bacteria were the predominant pathogens in abdominal infection (38.4%) and urinary tract infection (72.0%). The highest mortality of 47.5% was observed in patients infected with methicillin-resistant Staphylococcus aureus, which was significantly associated with an increased risk of death (odds ratio 1.88, 95% confidence interval 1.22–2.91). Conclusions: This study revealed the current spectrum of pathogens and its variation based on the site of infection, which is essential for empiric antimicrobial therapy against sepsis.