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External validation of bloodstream infection mortality risk score in a population-based cohort.

ABSTRACT: A risk score was recently derived to predict mortality in adult patients with Gram-negative bloodstream infection (BSI). The aim of this study was to provide external validation of the BSI mortality risk score (BSIMRS) in a population-based cohort. All residents of Olmsted County, Minnesota, with Escherichia coli and Pseudomonas aeruginosa BSI from 1 January 1998 to 31 December 2007 were identified. Logistic regression was used to examine the association between BSIMRS and mortality. Area under receiver operating characteristic curve (AUC) was calculated to quantify the discriminative ability of the BSIMRS to predict a variety of short-term and long-term outcomes. Overall, 424 unique Olmsted County residents with first episodes of E. coli and P. aeruginosa BSI were included in the study. Median age was 68 (range 0-99) years, 280 (66%) were women, 61 (14%) had cancer and 9 (2%) had liver cirrhosis. The BSIMRS was associated with 28-day mortality (p <0.001) with an AUC of 0.86. There was an almost 56% increase in 28-day mortality for each point increase in BSIMRS (OR 1.56, 95% CI 1.40-1.78). A BSIMRS ? 5 had a sensitivity of 74% and a specificity of 87% to predict 28-day mortality with a negative predictive value of 97%. The BSIMRS had AUC of 0.85, 0.85 and 0.81 for 7-, 14- and 365-day mortality, respectively. BSIMRS stratified mortality with high discrimination in a population-based cohort that included patients of all age groups who had a relatively low prevalence of cancer and liver cirrhosis.

SUBMITTER: Al-Hasan MN

PROVIDER: S-EPMC4254722 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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External validation of bloodstream infection mortality risk score in a population-based cohort.

Al-Hasan M N MN Juhn Y J YJ Bang D W DW Yang H-J HJ Baddour L M LM

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases 20140326 9

A risk score was recently derived to predict mortality in adult patients with Gram-negative bloodstream infection (BSI). The aim of this study was to provide external validation of the BSI mortality risk score (BSIMRS) in a population-based cohort. All residents of Olmsted County, Minnesota, with Escherichia coli and Pseudomonas aeruginosa BSI from 1 January 1998 to 31 December 2007 were identified. Logistic regression was used to examine the association between BSIMRS and mortality. Area under ...[more]

PMID: 25455590

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Project description:BackgroundEscherichia coli is the most common cause of bloodstream infections (BSIs) and mortality is an important aspect of burden of disease. Using a multinational population-based cohort of E. coli BSIs, our objectives were to evaluate 30-day case fatality risk and mortality rate, and determine factors associated with each.MethodsDuring 2014-2018, we identified 30-day deaths from all incident E. coli BSIs from surveillance nationally in Finland, and regionally in Sweden (Skaraborg) and Canada (Calgary, Sherbrooke, western interior). We used a multivariable logistic regression model to estimate factors associated with 30-day case fatality risk. The explanatory variables considered for inclusion were year (2014-2018), region (five areas), age (< 70-years-old, ≥70-years-old), sex (female, male), third-generation cephalosporin (3GC) resistance (susceptible, resistant), and location of onset (community-onset, hospital-onset). The European Union 28-country 2018 population was used to directly age and sex standardize mortality rates. We used a multivariable Poisson model to estimate factors associated with mortality rate, and year, region, age and sex were considered for inclusion.ResultsFrom 38.7 million person-years of surveillance, we identified 2961 30-day deaths in 30,923 incident E. coli BSIs. The overall 30-day case fatality risk was 9.6% (2961/30923). Calgary, Skaraborg, and western interior had significantly increased odds of 30-day mortality compared to Finland. Hospital-onset and 3GC-resistant E. coli BSIs had significantly increased odds of mortality compared to community-onset and 3GC-susceptible. The significant association between age and odds of mortality varied with sex, and contrasts were used to interpret this interaction relationship. The overall standardized 30-day mortality rate was 8.5 deaths/100,000 person-years. Sherbrooke had a significantly lower 30-day mortality rate compared to Finland. Patients that were either ≥70-years-old or male both experienced significantly higher mortality rates than those < 70-years-old or female.ConclusionsIn our study populations, region, age, and sex were significantly associated with both 30-day case fatality risk and mortality rate. Additionally, 3GC resistance and location of onset were significantly associated with 30-day case fatality risk. Escherichia coli BSIs caused a considerable burden of disease from 30-day mortality. When analyzing population-based mortality data, it is important to explore mortality through two lenses, mortality rate and case fatality risk.

Project description:Background: Klebsiella pneumoniae bloodstream infection (Kp-BSI) is a serious threat to pediatric patients. The objective of this study was to explore the risk factors, validate the prediction efficiency of pediatric Sequential Organ Failure Assessment (SOFA) and establish better early predictors of mortality in pediatric patients with Kp-BSI.Methods: All children diagnosed with Kp-BSI were included in this retrospective cohort study from January 2009 to June 2019. Basic characteristics, symptoms and physical examinations, treatments, laboratory statistics, and SOFA at the onset of Kp-BSI were recorded. The Cox proportional hazard model and receiver operating characteristic curves were used to assess the association between the variables and the 90-day mortality and their predictive value. DeLong's test of receiver operating characteristic curves and integrated discrimination improvement index were used to determine the improvement in predictive capacity of the modified SOFA models. A predictive score was developed using multivariate logistic regression.Results: Of the 146 children enrolled, 33 (22.6%) patients died within 90?days. Hospitalization in the last 6 months, intra-abdominal source of infection, presence of organ failure, and altered levels of blood biomarkers, including C-reactive protein, albumin, and lactate were significant risk factors for 90-day mortality. The area under the curve (AUC) of SOFA for predicting 90-day mortality was 0.80 (95% CI 0.71-0.89). Moreover, we found that a prediction model combining SOFA with two other parameters, namely hospitalization in the last 6 months and intra-abdominal source of infection, was better at predicting mortality (AUC?=?0.89, 95% CI 0.82-0.96; sensitivity?=?0.86; specificity?=?0.84). According to this novel risk model, we defined three statistically different groups: low-risk, medium-risk and high-risk groups, with an observed 90-day mortality of 5.4, 35.7, and 72.0%, respectively. With reference to the low-risk patients, the medium-risk and high-risk groups had a higher mortality, with hazard ratios of 8.36 (95% CI 3.60-27.83) and 20.27 (95% CI 7.47-54.95), respectively.Conclusions: The modified SOFA may be better than the original score to predict 90-day mortality in pediatric patients with Kp-BSI. Future prospective studies are required to validate this novel scoring system in external cohorts.

Project description:BackgroundIn increasingly ageing populations, there is an emergent need to develop a robust prediction model for estimating an individual absolute risk for all-cause mortality, so that relevant assessments and interventions can be targeted appropriately. The objective of the study was to derive, evaluate and validate (internally and externally) a risk prediction model allowing rapid estimations of an absolute risk of all-cause mortality in the following 10?years.MethodsFor the model development, data came from English Longitudinal Study of Ageing study, which comprised 9154 population-representative individuals aged 50-75?years, 1240 (13.5%) of whom died during the 10-year follow-up. Internal validation was carried out using Harrell's optimism-correction procedure; external validation was carried out using Health and Retirement Study (HRS), which is a nationally representative longitudinal survey of adults aged ?50?years residing in the United States. Cox proportional hazards model with regularisation by the least absolute shrinkage and selection operator, where optimisation parameters were chosen based on repeated cross-validation, was employed for variable selection and model fitting. Measures of calibration, discrimination, sensitivity and specificity were determined in the development and validation cohorts.ResultsThe model selected 13 prognostic factors of all-cause mortality encompassing information on demographic characteristics, health comorbidity, lifestyle and cognitive functioning. The internally validated model had good discriminatory ability (c-index=0.74), specificity (72.5%) and sensitivity (73.0%). Following external validation, the model's prediction accuracy remained within a clinically acceptable range (c-index=0.69, calibration slope ?=0.80, specificity=71.5% and sensitivity=70.6%). The main limitation of our model is twofold: 1) it may not be applicable to nursing home and other institutional populations, and 2) it was developed and validated in the cohorts with predominately white ethnicity.ConclusionsA new prediction model that quantifies absolute risk of all-cause mortality in the following 10-years in the general population has been developed and externally validated. It has good prediction accuracy and is based on variables that are available in a variety of care and research settings. This model can facilitate identification of high risk for all-cause mortality older adults for further assessment or interventions.

Dataset Information

External validation of bloodstream infection mortality risk score in a population-based cohort.

Publications

External validation of bloodstream infection mortality risk score in a population-based cohort.

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