Machine learning algorithms for predicting days of high incidence for out-of-hospital cardiac arrest.

Predicting out-of-hospital cardiac arrest (OHCA) events might improve outcomes of OHCA patients. We hypothesized that machine learning algorithms using meteorological information would predict OHCA incidences. We used the Japanese population-based repository database of OHCA and weather information. The Tokyo data (2005-2012) was used as the training cohort and datasets of the top six populated prefectures (2013-2015) as the test. Eight various algorithms were evaluated to predict the high-incidence OHCA days, defined as the daily events exceeding 75% tile of our dataset, using meteorological and chronological values: temperature, humidity, air pressure, months, days, national holidays, the day before the holidays, the day after the holidays, and New Year's holidays. Additionally, we evaluated the contribution of each feature by Shapley Additive exPlanations (SHAP) values. The training cohort included 96,597 OHCA patients. The eXtreme Gradient Boosting (XGBoost) had the highest area under the receiver operating curve (AUROC) of 0.906 (95% confidence interval; 0.868-0.944). In the test cohorts, the XGBoost algorithms also had high AUROC (0.862-0.923). The SHAP values indicated that the "mean temperature on the previous day" impacted the most on the model. Algorithms using machine learning with meteorological and chronological information could predict OHCA events accurately.

Enterococcus spp. have higher fitness for survival, in a pH-dependent manner, in pancreatic juice among duodenal bacterial flora.

BACKGROUND AND AIM: Bacterial infection is involved in the progression of many gastrointestinal diseases, including those of pancreas; however, how and which bacteria colonize in pancreatic juice and tissue have yet to be elucidated. Recently, we reported that Enterococcus faecalis exists in the pancreatic juice and tissues of patients with chronic pancreatic disease. Here, we investigated the survival of E. faecalis in duodenal juice with different pH conditions. METHODS: Pancreatic juice samples from 62 patients with cancers of the duodeno-pancreato-biliary region were evaluated for the presence of E. faecalis. 16S ribosomal RNA polymerase chain reaction and 16S-based metagenome analyses were performed to determine the bacterial composition. The survival of E. faecalis in various pancreatic juice conditions was evaluated. RESULTS: Of 62 samples, 27% (17/62) were positive for Enterococcus spp., among which 71% (12/17) contained E. faecalis. Enterococcus spp. showed the highest fitness for survival in alkaline pancreatic juice among various bacterial species. The microbiome of pancreatic juice from patients with pancreatic and bile duct cancer showed diversity, but Enterococcus spp. were enriched among duodenal tumors and intraductal papillary mucinous neoplasms. CONCLUSIONS: Alkalinity is one of the important factors for the selective survival of E. faecalis among microbiota. E. faecalis can colonize the pancreatic duct when the pancreatic juice condition is altered.

Serum levels of tau protein increase according to the severity of the injury in DAI rat model.

Traumatic brain injury (TBI) in the form of diffuse axonal injury (DAI) is difficult to diagnose in the early phase of the injury. Early diagnosis of DAI may provide opportunity for developing treatment and management strategies. Tau protein has been demonstrated to increase in the early phase of TBI with high diagnostic accuracy in patients with DAI. We tested the biological plausibility of tau protein using a rat DAI model by evaluating the association between serum tau levels and the severity of brain injury. DAI was induced in animals using the Marmarou model. After a survival of 60 minutes, rats were anesthetized and sacrificed after obtaining blood samples (5ml) from the heart. Eighteen rats were employed in the present study and were randomly subjected to sham-operated control (n=4), mild DAI (n=7), and severe DAI (n=7). Of seven severe DAI rats, two rats that had focal injury caused by skull fracture were excluded in the measurement of tau protein level. The serum levels of tau protein in the rat DAI model were found to increase significantly and consistently according to the severity of the injury. Rats with DAI showed significantly higher serum levels of tau protein compared to sham rats; the severe DAI rats had higher levels of tau than moderate DAI and sham rats (sham vs. mild,  P=0.02; mild vs. severe,  P=0.02). In conclusion, serum tau protein levels may be useful as a biomarker for diagnosing and estimating the severity of DAI in the early phase.

Impact of increased calls to rapid response systems on unplanned ICU admission.

BACKGROUND: Whether hospital bed number and rapid response system (RRS) call rate is associated with the clinical outcomes of patients who have RRS activations is unknown. We test a hypothesis that hospital volume and RRS call rates are associated with the clinical outcomes of patients with RRSs. METHODS: This is a retrospective chart analysis of an existing dataset associated with In-Hospital Emergency Registry in Japan. In the present study, 4818 patients in 24 hospitals from April 2014 to March 2018 were analyzed. Primary outcome variable was an unplanned intensive care unit (ICU) admission after RRS activation. RESULTS: In the primary analysis of the study using a multivariate analysis adjusting potential confounding factors, higher RRS call rate was significantly associated with decreased unplanned ICU admissions (P < 0.0001, Odds ratio [OR] 0.95, 95% confidence interval [CI] 0.92-0.98), but there was no significant association of hospital volume with unplanned ICU admissions (P = 0.44). In the secondary analysis of the study, there was a non-significant trend of increased cardiac arrest on arrival at the location of the RRS provider at large-volume hospitals (P = 0.084, OR 1.16, 95% CI 0.98-1.38). Large-volume hospitals had a significantly higher 1-month mortality rate (P = 0.0040, OR 1.10, 95% CI 1.03-1.18). CONCLUSION: Hospitals with increased RRS call rates had significantly decreased unplanned ICU admission in patients who had RRS activations. Patients who had RRS activations at large-volume hospitals had an increased 1-month mortality rate.

Tau protein as a diagnostic marker for diffuse axonal injury.

BACKGROUND: Diffuse axonal injury (DAI) is difficult to identify in the early phase of traumatic brain injury (TBI) using common diagnostic methods. Tau protein is localized specifically in nerve axons. We hypothesized that serum level of tau can be a useful biomarker to diagnose DAI in the early phase of TBI. METHODS & RESULTS: We measured serum tau levels in 40 TBI patients who were suspected of DAI within 6 hours after TBI to evaluate the accuracy of the tau level as a diagnostic marker for DAI. Diagnosis of DAI was confirmed according to magnetic resonance imaging (MRI) findings. The serum tau level in the DAI group (n = 13) was significantly higher than that in the non-DAI group (n = 27) (DAI vs. non-DAI, 25.3 [0 to 99.1] pg/mL vs. 0 [0 to 44.4] pg/mL, P = 0.03)). A receiver-operating characteristic curve to evaluate the diagnostic ability of serum tau level within 6 hours for DAI showed an area under the curve of 0.690 with 74.1% for sensitivity and 69.2% for specificity. Serum tau level was not significantly higher in unfavorable outcome group (Glasgow Outcome scale [GOS] score = 1-3 at hospital discharge) compared with favorable outcome group (GOS score = 4-5) (P = 0.19). CONCLUSIONS: Tau protein may be a useful biomarker for diagnosis of DAI in the early phase of TBI.

Proteome analysis of hemofilter adsorbates to identify novel substances of sepsis: a pilot study.

Blood purification therapy using hemofilters with high adsorbing capabilities has been reported to remove excessive humoral mediators from the blood of patients with sepsis. However, there are insufficient studies of the adsorbates bound to hemofilter membranes. We hypothesized that these adsorbates in acute kidney injury (AKI) patients with sepsis were different from those in patients without sepsis and that proteome analysis of the adsorbates would identify novel substances of sepsis. This study included 20 patients who had AKI upon admission to intensive care units (ICUs) and who received continuous renal replacement therapy using polymethyl methacrylate hemofilters. We isolated adsorbates from the hemofilters after use and performed comprehensive proteome analysis. A total of 429 proteins were identified in these adsorbates. Adsorbates from the hemofilters of patients with sepsis had significantly increased frequency of proteins associated with "immune system process" and "biological adhesion" functions compared to those of non-sepsis patients (P < 0.05). Of 429 proteins, 197 were identified only in sepsis adsorbates. Of these, 3 proteins including carbonic anhydrase 1 (CA1) and leucine-rich alpha-2-glycoprotein (LRG1) were identified in all samples from sepsis patients and have not been previously reported in sepsis patients. Validation analysis of patient serum revealed that patients with sepsis had increased serum levels of CA1 and LRG1 compared to patients without sepsis (P < 0.05). To conclude, there were significant differences in the characteristics of the adsorbates from sepsis and non-sepsis patients. CA1 and LRG1 appear to be novel substances associated with sepsis.

Timing and Location of Medical Emergency Team Activation Is Associated with Seriousness of Outcome: An Observational Study in a Tertiary Care Hospital.

PURPOSE: The medical emergency team (MET) can be activated anytime and anywhere in a hospital. We hypothesized the timing and location of MET activation are associated with seriousness of outcome. MATERIALS AND METHODS: We tested for an association of clinical outcomes with timing and location using a university hospital cohort in Japan (n = 328). The primary outcome was short-term serious outcome (unplanned ICU admission after MET activation or death at scene). RESULTS: Patients for whom the MET was activated in the evening or night-time had significantly higher rates of short-term serious outcome than those for whom it was activated during the daytime (vs. evening: adjusted OR = 2. 53, 95% CI = 1.24-5.13, P = 0.010; night-time: adjusted OR = 2.45, 95% CI = 1.09-5.50, P = 0.030). Patients for whom the MET was activated in public space had decreased short-term serious outcome compared to medical spaces (public space: adjusted OR = 0.19, 95% CI = 0.07-0.54, P = 0.0017). Night-time (vs. daytime) and medical space (vs. public space) were significantly associated with higher risks of unexpected cardiac arrest and 28-day mortality. CONCLUSIONS: Patients for whom the MET was activated in the evening/night-time, or in medical space, had a higher rate of short-term serious outcomes. Taking measures against these risk factors may improve MET performance.

Reduction of unexpected serious adverse events after introducing medical emergency team.

Aim: To assess the clinical benefits of introducing a medical emergency team system for early medical intervention in hospital care. Methods: This prospective analysis included all cases of medical emergency team activation during the first year after the introduction of the medical emergency team system at Chiba University Hospital (Chiba, Japan) in February 2011. The rates of in-hospital mortality and unexpected events before and after introduction of the medical emergency team system were compared. Results: The total number of medical emergency team activation calls was 83 (4.9 per 1,000 admissions). The activation of the medical emergency team system was requested most frequently from the general ward (56.6%) and by a physician (57.8%), with the most important reasons for activation being cardiac arrest (37.3%), breathing abnormality (33.7%), and impaired consciousness (32.5%). The most frequent medical interventions by the medical emergency team were intubation (43.3%) and oxygen inhalation (41.0%). Approximately one-half of the patients requiring activation of the medical emergency team system were critically ill and needed subsequent intensive care unit admission. Although no significant difference was observed between the pre- and post- medical emergency team in-hospital mortalities (2.1% versus 2.0%, respectively), the incidence rate of serious events significantly decreased (12.4% versus 6.8%, respectively; P = 0.015). Conclusion: Most patients requiring activation of the medical emergency team system were critically ill and needed emergency treatment at the location of the medical emergency team activation, with subsequent critical care. Although the introduction of the medical emergency team system did not affect the in-hospital mortality rate, it reduced the incidence of unexpected serious adverse events, suggesting that it may be clinically useful.