中田 孝明

BACKGROUND: It is important to determine the prevalence and prognosis of community-acquired infection (CAI) and nosocomial infection (NI) to develop treatment strategies and appropriate medical policies in aging society. METHODS: Patients hospitalized between January 2010 and December 2019, for whom culture tests were performed and antibiotics were administered, were selected using a national claims-based database. The annual trends in incidence and in-hospital mortality were calculated and evaluated by dividing the patients into four age groups. RESULTS: Of the 73,962,409 inpatients registered in the database, 9.7% and 4.7% had CAI and NI, respectively. These incidences tended to increase across the years in both the groups. Among the patients hospitalized with infectious diseases, there was a significant increase in patients aged ≥ 85 years (CAI: + 1.04%/year and NI: + 0.94%/year, P < 0.001), while there was a significant decrease in hospitalization of patients aged ≤ 64 years (CAI: -1.63%/year and NI: -0.94%/year, P < 0.001). In-hospital mortality was significantly higher in the NI than in the CAI group (CAI: 8.3%; NI: 14.5%, adjusted mean difference 4.7%). The NI group had higher organ support, medical cost per patient, and longer duration of hospital stay. A decreasing trend in mortality was observed in both the groups (CAI: -0.53%/year and NI: -0.72%/year, P < 0.001). CONCLUSION: The present analysis of a large Japanese claims database showed that NI is a significant burden on hospitalized patients in aging societies, emphasizing the need to address particularly on NI.

OBJECTIVES: We aimed to describe empiric antimicrobial options for patients with community-onset sepsis using nationwide real-world data from Japan. METHODS: This retrospective cohort study used nationwide Japanese data from a medical reimbursement system database. Patients aged ≥20 years with both presumed infections and acute organ dysfunction who were admitted to hospitals from the outpatient department or emergency department between 2010 and 2017 were enrolled. We described the initial choices of antimicrobials for patients with sepsis stratified by intensive care unit (ICU) or ward. RESULTS: There were 1,195,741 patients with community-onset sepsis; of these, 1,068,719 and 127,022 patients were admitted to the wards and ICU, respectively. Third-generation cephalosporins and carbapenem were most commonly used for patients with community-onset sepsis. We found that 1.7% and 6.0% of patients initially used antimicrobials for methicillin-resistant Staphylococcus aureus coverage in the wards and ICU, respectively. Although half of the patients initially used antipseudomonal agents, only a few patients used a combination of antipseudomonal agents. Moreover, few patients initially used a combination of antimicrobials to treat methicillin-resistant Staphylococcus aureus and Pseudomonas sp. CONCLUSION: Third-generation cephalosporins and carbapenem were most frequently used for patients with sepsis. A combination therapy of antimicrobials for drug-resistant bacteria coverage was rarely provided to these patients.

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 < 0.0001). Similarly, the highest hospital spending group was associated with a significantly higher effective cost per survivor than the lowest hospital spending group (coefficient = 77.7, 95% CI 73.1 to 82.3; p < 0.0001). In subgroup analyses, hospitals with a small or medium number of beds demonstrated a consistent pattern with the primary test, whereas those with a large number of beds or academic affiliations displayed no association. CONCLUSIONS: Using a nationwide Japanese medical claims database, this study indicated that hospitals with greater expenditures were associated with a superior survival rate and a higher effective cost per survivor in patients with sepsis than those with lower expenditures. In contrast, no correlations between hospital spending and mortality were observed in hospitals with a large number of beds or academic affiliations.

This retrospective cohort study aimed to develop and evaluate a machine-learning algorithm for predicting oliguria, a sign of acute kidney injury (AKI). To this end, electronic health record data from consecutive patients admitted to the intensive care unit (ICU) between 2010 and 2019 were used and oliguria was defined as a urine output of less than 0.5 mL/kg/h. Furthermore, a light-gradient boosting machine was used for model development. Among the 9,241 patients who participated in the study, the proportions of patients with urine output < 0.5 mL/kg/h for 6 h and with AKI during the ICU stay were 27.4% and 30.2%, respectively. The area under the curve (AUC) values provided by the prediction algorithm for the onset of oliguria at 6 h and 72 h using 28 clinically relevant variables were 0.964 (a 95% confidence interval (CI) of 0.963-0.965) and 0.916 (a 95% CI of 0.914-0.918), respectively. The Shapley additive explanation analysis for predicting oliguria at 6 h identified urine values, severity scores, serum creatinine, oxygen partial pressure, fibrinogen/fibrin degradation products, interleukin-6, and peripheral temperature as important variables. Thus, this study demonstrates that a machine-learning algorithm can accurately predict oliguria onset in ICU patients, suggesting the importance of oliguria in the early diagnosis and optimal management of AKI.

INTRODUCTION: The neurologic prognosis of out-of-hospital cardiac arrest (OHCA) patients in whom return of spontaneous circulation (ROSC) is achieved remains poor. The aim of this study was to externally and prospectively validate two scoring systems developed by us: the CAST score, a scoring system to predict the neurological prognosis of OHCA patients undergoing targeted temperature management (TTM), and a simplified version of the same score developed for improved ease of use in clinical settings, the revised CAST (rCAST) score. METHODS: This study was a prospective, multicenter, observational study conducted using the SOS KANTO 2017 registry, an OHCA registry involving hospitals in the Kanto region (including Tokyo) of Japan. The primary outcome was favorable neurological outcome (defined as Cerebral Performance Category score of 1 or 2) at 30 days and the secondary outcomes were favorable neurological outcome at 90 days and survival at 30 and 90 days. The predictive accuracies of the original CAST (oCAST) and rCAST scores were evaluated by using area under the receiver operating characteristic curve (AUC). RESULTS: Of 9909 OHCA patients, 565 showed ROSC and received TTM. Of these, we analyzed the data of 259 patients in this study. The areas under the receiver operating characteristic curve (AUCs) of the oCAST and rCAST scores for predicting a favorable neurological outcome at 30 days were 0.86 and 0.87, respectively, and those for predicting a favorable neurological outcome at 90 days were 0.87 and 0.88, respectively. The rCAST showed a higher predictive accuracy for the neurological outcome as compared with the NULL-PLEASE score. The patients with a favorable neurological outcome who had been classified into the high severity group based on the rCAST tended to have hypothermia at hospital arrival and to not show any signs of loss of gray-white matter differentiation on brain CT. Neurological function at 90 days was correlated with the rCAST (r = 0.63, p < 0.001). CONCLUSIONS: rCAST showed high predictive accuracy for the neurological prognosis of OHCA patients managed by TTM, comparable to that of the oCAST score. The scores on the rCAST were strongly correlated with the neurological functions at 90 days, implying that the rCAST is a useful scale for assessing the severity of brain injury after cardiac arrest.