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Supernormal Antithrombin Activity Is an Independent Predictor of In-Hospital Mortality in Patients With Sepsis: A Retrospective Observational Study.

ABSTRACT: Supernormal antithrombin (AT) activity is rare in patients with sepsis. This study compared mortality rate of patients with sepsis and supernormal AT activity with that of other patients. This retrospective study included patients with sepsis from 42 intensive care units (ICUs) in Japan. Patients were included if their AT activity was measured on ICU admission, and if they did not receive AT concentrate. They were categorized into low, normal, and supernormal with respective AT activity of ?70%, >70% to ?100%, and >100%. The primary outcome was hospital in-patient mortality. Nonlinear regression analysis showed that mortality risk gradually increased with AT activity in the supernormal range, but without statistical significance. Survival rate was significantly lower in low (67%) and supernormal (57%) AT groups than in the normal AT group (79%; P < .001 and P = .008, respectively). After adjusting for disease severity and AT activity on day 2, supernormal AT activity was the only independent predictor of mortality. Sepsis with supernormal AT activity associated with high mortality, independent of disease severity, might be a predictor of in-hospital mortality.

SUBMITTER: Azuhata T

PROVIDER: S-EPMC7288796 | biostudies-literature | 2020 Jan-Dec

REPOSITORIES: biostudies-literature

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Supernormal Antithrombin Activity Is an Independent Predictor of In-Hospital Mortality in Patients With Sepsis: A Retrospective Observational Study.

Azuhata Takeo T Hayakwa Mineji M Maekawa Kunihiko K Komatsu Tomohide T Kuwana Tsukasa T Kawano Daisuke D Nakamura Kazuhiro K Kinoshita Kosaku K Wada Takeshi T Tanjoh Katsuhisa K

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis 20200101

Supernormal antithrombin (AT) activity is rare in patients with sepsis. This study compared mortality rate of patients with sepsis and supernormal AT activity with that of other patients. This retrospective study included patients with sepsis from 42 intensive care units (ICUs) in Japan. Patients were included if their AT activity was measured on ICU admission, and if they did not receive AT concentrate. They were categorized into low, normal, and supernormal with respective AT activity of ≤70%, ...[more]

PMID: 32299224

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Project description:BackgroundOlder patients hospitalized with community-acquired pneumonia (CAP) are at high risk for short-term mortality. Activity of daily living (ADL) is associated with clinical outcomes in older patients. We aimed to investigate the prognostic value of ADL upon admission on the in-hospital mortality in older patients with CAP.MethodsWe conducted a retrospective cohort study involving patients aged ≥65 years admitted to Beijing Chao-Yang hospital due to CAP between June 2012 and June 2020. ADL evaluation upon admission was performed by Barthel Index (BI). Data from all patients were extracted from the electronic medical records.ResultsFour thousand eight hundred eighty patients were included, 131 patients (2.7%) died during their hospitalization. Median BI in the Deceased group was 45 (20-65), Deceased group had lower BI scores than Survivors group (p < 0.001). Low BI (< 60) was more frequent in patients who died in the hospital than in patients discharged alive (69.5% vs. 13%, p < 0.001). In-hospital mortality was higher among patients with worse ADL upon admission (BI< 60) compared to those BI≥60 (12.6% vs. 0.9%). The worse ADL upon admission (BI< 60) was associated with an increase in the risk of death during CAP hospitalization, worse ADL upon admission (BI< 60) showed an odds ratio (OR) for in-hospital mortality of 7.53 (95%CI: 2.77-20.48; P < 0.01). This association remained significant after adjustment for age, comorbid conditions, respiratory failure, pathogens and laboratory findings (OR, 3.74; 95%CI, 2.37-5.91; P < 0.01). Receiver operating characteristic (ROC) curve revealed that BI upon admission is a predictor related to in-hospital mortality in elderly patients, the area under the ROC curve of BI in predicting in-hospital mortality was 0.81 (with 95% confidence interval: 0.78-0.85). The predictive value of ADL upon admission was better than age in our study population.ConclusionActivity of daily living upon admission is an independent predictor of in-hospital mortality in older patients with community-acquired pneumonia.

Project description:BackgroundEarly and reliable identification of patients with sepsis who are at high risk of mortality is important to improve clinical outcomes. However, 3 major barriers to artificial intelligence (AI) models, including the lack of interpretability, the difficulty in generalizability, and the risk of automation bias, hinder the widespread adoption of AI models for use in clinical practice.ObjectiveThis study aimed to develop and validate (internally and externally) a conformal predictor of sepsis mortality risk in patients who are critically ill, leveraging AI-assisted prediction modeling. The proposed approach enables explaining the model output and assessing its confidence level.MethodsWe retrospectively extracted data on adult patients with sepsis from a database collected in a teaching hospital at Beth Israel Deaconess Medical Center for model training and internal validation. A large multicenter critical care database from the Philips eICU Research Institute was used for external validation. A total of 103 clinical features were extracted from the first day after admission. We developed an AI model using gradient-boosting machines to predict the mortality risk of sepsis and used Mondrian conformal prediction to estimate the prediction uncertainty. The Shapley additive explanation method was used to explain the model.ResultsA total of 16,746 (80%) patients from Beth Israel Deaconess Medical Center were used to train the model. When tested on the internal validation population of 4187 (20%) patients, the model achieved an area under the receiver operating characteristic curve of 0.858 (95% CI 0.845-0.871), which was reduced to 0.800 (95% CI 0.789-0.811) when externally validated on 10,362 patients from the Philips eICU database. At a specified confidence level of 90% for the internal validation cohort the percentage of error predictions (n=438) out of all predictions (n=4187) was 10.5%, with 1229 (29.4%) predictions requiring clinician review. In contrast, the AI model without conformal prediction made 1449 (34.6%) errors. When externally validated, more predictions (n=4004, 38.6%) were flagged for clinician review due to interdatabase heterogeneity. Nevertheless, the model still produced significantly lower error rates compared to the point predictions by AI (n=1221, 11.8% vs n=4540, 43.8%). The most important predictors identified in this predictive model were Acute Physiology Score III, age, urine output, vasopressors, and pulmonary infection. Clinically relevant risk factors contributing to a single patient were also examined to show how the risk arose.ConclusionsBy combining model explanation and conformal prediction, AI-based systems can be better translated into medical practice for clinical decision-making.

Project description:OBJECTIVES:To examine trends in asthma hospitalisation and mortality rates from 2000 to 2014 in Kuwait according to sex, age and nationality. METHODS:For this nationwide, retrospective observational study, data from hospital discharge records and death certificates listing asthma as the primary reason for hospitalisation or mortality were obtained from the National Center for Health Information database using International Classification of Diseases, Tenth Revision codes J45 and J46. Trends in sex-adjusted, age-adjusted and nationality-adjusted hospitalisation and mortality rates were examined. Poisson regression models were applied to test for linear trends overtime and estimate adjusted rate ratios and 95% CI. RESULTS:During the 15-year study period, a total of 43?652 hospitalisations and 484 deaths due to asthma exacerbations were identified. The average annual adjusted rates of asthma hospitalisation and mortality were estimated to be 134.9 (95% CI 131.8 to 138.1) and 2.1 (95% CI 1.8 to 2.4) per 100?000 population, respectively. Hospitalisation rates decreased by 49.5% in the total population (from 180.8 to 91.3 admissions per 100?000 population between 2000 and 2014, ptrend <0.001) and by 57.9% in the age group of 5-44?years (from 77.3 to 32.5 admissions per 100?000 population, ptrend <0.001). Mortality rates decreased from 4.1 to 0.9 deaths per 100?000 population between 2000 and 2014 in the total population (77.6% decrease, ptrend <0.001) and from 0.6 to 0.2 deaths per 100?000 population among those aged 5-44 years (61.9% reduction, ptrend=0.005). Kuwaiti compared with non-Kuwaiti subjects had higher risk of asthma hospitalisation and mortality. Among children aged ?19 years, the risk of hospitalisation was higher in boys compared with girls; however, among adults, women experienced more hospitalisations than men. CONCLUSIONS:Asthma hospitalisation and mortality rates have substantially decreased between 2000 and 2014 in Kuwait, with persisting differences between genders, age groups and citizens versus non-citizens. The observed decreasing trends in Kuwait are in agreement with global trends.

Project description:RationaleImmunosuppressive medical conditions are risk factors for mortality from severe infections. It is unknown whether hospital characteristics affect this risk.ObjectivesTo determine whether the odds of death for an immunosuppressed patient with sepsis relative to a nonimmunosuppressed patient with sepsis varies according to the hospital's yearly case volume of immunosuppressed patients with sepsis.MethodsPatients with sepsis at hospitals in the Vizient database were characterized as immunosuppressed or not immunosuppressed on the basis of diagnosis codes and medication use. Hospitals were grouped into quartiles based on their average volumes of immunosuppressed patients with sepsis per year. Multilevel logistic regression with clustering of patients by hospital was used to determine whether the odds of in-hospital death from sepsis owing to a suppressed immune state varied by hospital quartile.ResultsThere were 350,183 patients with sepsis at 60 hospitals in the Vizient database from 2010 to 2012. Immunosuppressed patients with sepsis at the 15 hospitals in the lowest quartile (64 to 224 immunosuppressed patients with sepsis per year) had an increased odds of in-hospital death relative to nonimmunosuppressed patients with sepsis at these hospitals (adjusted odds ratio, 1.38; 95% confidence interval, 1.27-1.50; P < 0.001). The odds of in-hospital death for immunosuppressed patients with sepsis relative to nonimmunosuppressed patients with sepsis was similar for patients at hospitals in the second, third, and fourth quartiles (225 to 1,056 immunosuppressed patients with sepsis per year). The adjusted odds of death from sepsis owing to a suppressed immune state of 1.21 (95% confidence interval, 1.18-1.25; P < 0.001) for patients at these 45 hospitals was significantly less than for patients at the 15 hospitals in the lowest quartile (P = 0.004 for difference).ConclusionsThe risk of death from sepsis owing to a suppressed immune state was greatest at hospitals with the lowest volume of immunosuppressed patients with sepsis. Further study is needed to determine whether this finding is related to differences in patient characteristics or in care delivery at hospitals with different amounts of exposure to immunosuppressed patients.

Dataset Information

Supernormal Antithrombin Activity Is an Independent Predictor of In-Hospital Mortality in Patients With Sepsis: A Retrospective Observational Study.

Publications

Supernormal Antithrombin Activity Is an Independent Predictor of In-Hospital Mortality in Patients With Sepsis: A Retrospective Observational Study.

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