Dataset Information

The predisposition, infection, response and organ failure (Piro) sepsis classification system: results of hospital mortality using a novel concept and methodological approach.

ABSTRACT:

Introduction

PIRO is a conceptual classification system in which a number of demographic, clinical, biological and laboratory variables are used to stratify patients with sepsis in categories with different outcomes, including mortality rates.

Objectives

To identify variables to be included in each component of PIRO aiming to improve the hospital mortality prediction.

Methods

Patients were selected from the Portuguese ICU-admitted community-acquired sepsis study (SACiUCI). Variables concerning the R and O component included repeated measurements along the first five days in ICU stay. The trends of these variables were summarized as the initial value at day 1 (D1) and the slope of the tendency during the five days, using a linear mixed model. Logistic regression models were built to assess the best set of covariates that predicted hospital mortality.

Results

A total of 891 patients (age 60±17 years, 64% men, 38% hospital mortality) were studied. Factors significantly associated with mortality for P component were gender, age, chronic liver failure, chronic renal failure and metastatic cancer; for I component were positive blood cultures, guideline concordant antibiotic therapy and health-care associated sepsis; for R component were C-reactive protein slope, D1 heart rate, heart rate slope, D1 neutrophils and neutrophils slope; for O component were D1 serum lactate, serum lactate slope, D1 SOFA and SOFA slope. The relative weight of each component of PIRO was calculated. The combination of these four results into a single-value predictor of hospital mortality presented an AUC-ROC 0.84 (IC(95%):0.81-0.87) and a test of goodness-of-fit (Hosmer and Lemeshow) of p?=?0.368.

Conclusions

We identified specific variables associated with each of the four components of PIRO, including biomarkers and a dynamic view of the patient daily clinical course. This novel approach to PIRO concept and overall score can be a better predictor of mortality for patients with community-acquired sepsis admitted to ICUs.

SUBMITTER: Granja C

PROVIDER: S-EPMC3548822 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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The predisposition, infection, response and organ failure (Piro) sepsis classification system: results of hospital mortality using a novel concept and methodological approach.

Granja Cristina C Póvoa Pedro P Lobo Cristina C Teixeira-Pinto Armando A Carneiro António A Costa-Pereira Altamiro A

PloS one 20130118 1

<h4>Introduction</h4>PIRO is a conceptual classification system in which a number of demographic, clinical, biological and laboratory variables are used to stratify patients with sepsis in categories with different outcomes, including mortality rates.<h4>Objectives</h4>To identify variables to be included in each component of PIRO aiming to improve the hospital mortality prediction.<h4>Methods</h4>Patients were selected from the Portuguese ICU-admitted community-acquired sepsis study (SACiUCI). ...[more]

PMID: 23349756

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Project description:PURPOSE: To develop a clinical staging system based on the PIRO concept (Predisposition, Infection, RESPONSE and Organ dysfunction) for hospitalized patients with infection. METHODS: One year prospective cohort study of all hospitalized patients with infection (n?=?1035), admitted into a large tertiary care, university hospital. Variables associated with hospital mortality were selected using logistic regressions. Based on the regression coefficients, a score for each PIRO component was developed and a classification tree was used to stratify patients into four stages of increased risk of hospital mortality. The final clinical staging system was then validated using an independent cohort (n?=?186). RESULTS: Factors significantly associated with hospital mortality were • for Predisposition: age, sex, previous antibiotic therapy, chronic hepatic disease, chronic hematologic disease, cancer, atherosclerosis and a Karnofsky index<70; • for Insult/Infection: type of infection • for RESPONSE: abnormal temperature, tachypnea, hyperglycemia and severity of infection and • for Organ dysfunction: hypotension and SOFA score?1. The area under the ROC curve (CI95%) for the combined PIRO model as a predictor for mortality was 0.85 (0.82-0.88). Based on the scores for each of the PIRO components and on the cut-offs estimated from the classification tree, patients were stratified into four stages of increased mortality rates: stage I: ?5%, stage II: 6-20%, stage III: 21-50% and stage IV: >50%. Finally, this new clinical staging system was studied in a validation cohort, which provided similar results (0%, 9%, 31% and 67%, in each stage, respectively). CONCLUSIONS: Based on the PIRO concept, a new clinical staging system was developed for hospitalized patients with infection, allowing stratification into four stages of increased mortality, using the different scores obtained in Predisposition, RESPONSE, Infection and Organ dysfunction. The proposed system will likely help to define inclusion criteria in clinical trials as well as tailoring individual management plans for patients with infection.

Project description:This study aimed to assess the value of quick sequential organ failure assessment (qSOFA) combined with other risk factors in predicting in-hospital mortality in patients presenting to the emergency department with suspected infection. This post-hoc analysis of a prospective multicenter study dataset included 34 emergency departments across Japan (December 2017 to February 2018). We included adult patients (age ≥16 years) who presented to the emergency department with suspected infection. qSOFA was calculated and recorded by senior emergency physicians when they suspected an infection. Different types of sepsis-related risk factors (demographic, functional, and laboratory values) were chosen from prior studies. A logistic regression model was used to assess the predictive value of qSOFA for in-hospital mortality in models based on the following combination of predictors: 1) qSOFA-Only; 2) qSOFA+Age; 3) qSOFA+Clinical Frailty Scale (CFS); 4) qSOFA+Charlson Comorbidity Index (CCI); 5) qSOFA+lactate levels; 6) qSOFA+Age+CCI+CFS+lactate levels. We calculated the area under the receiver operating characteristic curve (AUC) and other key clinical statistics at Youden's index, where the sum of sensitivity and specificity is maximized. Following prior literature, an AUC >0.9 was deemed to indicate high accuracy; 0.7-0.9, moderate accuracy; 0.5-0.7, low accuracy; and 0.5, a chance result. Of the 951 patients included in the analysis, 151 (15.9%) died during hospitalization. The AUC for predicting in-hospital mortality was 0.627 (95% confidence interval [CI]: 0.580-0.673) for the qSOFA-Only model. Addition of other variables only marginally improved the model's AUC; the model that included all potentially relevant variables yielded an AUC of only 0.730 (95% CI: 0.687-0.774). Other key statistic values were similar among all models, with sensitivity and specificity of 0.55-0.65 and 0.60-0.75, respectively. In this post-hoc data analysis from a prospective multicenter study based in Japan, combining qSOFA with other sepsis-related risk factors only marginally improved the model's predictive value.

Project description:Importance:The quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) score has not been well-evaluated in low- and middle-income countries (LMICs). Objective:To assess the association of qSOFA with excess hospital death among patients with suspected infection in LMICs and to compare qSOFA with the systemic inflammatory response syndrome (SIRS) criteria. Design, Settings, and Participants:Retrospective secondary analysis of 8 cohort studies and 1 randomized clinical trial from 2003 to 2017. This study included 6569 hospitalized adults with suspected infection in emergency departments, inpatient wards, and intensive care units of 17 hospitals in 10 LMICs across sub-Saharan Africa, Asia, and the Americas. Exposures:Low (0), moderate (1), or high (≥2) qSOFA score (range, 0 [best] to 3 [worst]) or SIRS criteria (range, 0 [best] to 4 [worst]) within 24 hours of presentation to study hospital. Main Outcomes and Measures:Predictive validity (measured as incremental hospital mortality beyond that predicted by baseline risk factors, as a marker of sepsis or analogous severe infectious course) of the qSOFA score (primary) and SIRS criteria (secondary). Results:The cohorts were diverse in enrollment criteria, demographics (median ages, 29-54 years; males range, 36%-76%), HIV prevalence (range, 2%-43%), cause of infection, and hospital mortality (range, 1%-39%). Among 6218 patients with nonmissing outcome status in the combined cohort, 643 (10%) died. Compared with a low or moderate score, a high qSOFA score was associated with increased risk of death overall (19% vs 6%; difference, 13% [95% CI, 11%-14%]; odds ratio, 3.6 [95% CI, 3.0-4.2]) and across cohorts (P < .05 for 8 of 9 cohorts). Compared with a low qSOFA score, a moderate qSOFA score was also associated with increased risk of death overall (8% vs 3%; difference, 5% [95% CI, 4%-6%]; odds ratio, 2.8 [95% CI, 2.0-3.9]), but not in every cohort (P < .05 in 2 of 7 cohorts). High, vs low or moderate, SIRS criteria were associated with a smaller increase in risk of death overall (13% vs 8%; difference, 5% [95% CI, 3%-6%]; odds ratio, 1.7 [95% CI, 1.4-2.0]) and across cohorts (P < .05 for 4 of 9 cohorts). qSOFA discrimination (area under the receiver operating characteristic curve [AUROC], 0.70 [95% CI, 0.68-0.72]) was superior to that of both the baseline model (AUROC, 0.56 [95% CI, 0.53-0.58; P < .001) and SIRS (AUROC, 0.59 [95% CI, 0.57-0.62]; P < .001). Conclusions and Relevance:When assessed among hospitalized adults with suspected infection in 9 LMIC cohorts, the qSOFA score identified infected patients at risk of death beyond that explained by baseline factors. However, the predictive validity varied among cohorts and settings, and further research is needed to better understand potential generalizability.

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

The predisposition, infection, response and organ failure (Piro) sepsis classification system: results of hospital mortality using a novel concept and methodological approach.

Introduction

Objectives

Methods

Results

Conclusions

Publications

The predisposition, infection, response and organ failure (Piro) sepsis classification system: results of hospital mortality using a novel concept and methodological approach.

Similar Datasets

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