Dataset Information

Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients.

ABSTRACT:

Introduction

Recently, red cell distribution width (RDW), a measure of erythrocyte size variability, has been shown to be a prognostic marker in critical illness. The aim of this study was to investigate whether adding RDW has the potential to improve the prognostic performance of the simplified acute physiology score (SAPS) to predict short- and long-term mortality in an independent, large, and unselected population of intensive care unit (ICU) patients.

Methods

This observational cohort study includes 17,922 ICU patients with available RDW measurements from different types of ICUs. We modeled the association between RDW and mortality by using multivariable logistic regression, adjusting for demographic factors, comorbidities, hematocrit, and severity of illness by using the SAPS.

Results

ICU-, in-hospital-, and 1-year mortality rates in the 17,922 included patients were 7.6% (95% CI, 7.2 to 8.0), 11.2% (95% CI, 10.8 to 11.7), and 25.4% (95% CI, 24.8 to 26.1). RDW was significantly associated with in-hospital mortality (OR per 1% increase in RDW (95%CI)) (1.14 (1.08 to 1.19), P < 0.0001), ICU mortality (1.10 (1.06 to 1.15), P < 0.0001), and 1-year mortality (1.20 (95% CI, 1.14 to 1.26); P < 0.001). Adding RDW to SAPS significantly improved the AUC from 0.746 to 0.774 (P < 0.001) for in-hospital mortality and 0.793 to 0.805 (P < 0.001) for ICU mortality. Significant improvements in classification of SAPS were confirmed in reclassification analyses. Subgroups demonstrated robust results for gender, age categories, SAPS categories, anemia, hematocrit categories, and renal failure.

Conclusions

RDW is a promising independent short- and long-term prognostic marker in ICU patients and significantly improves risk stratification of SAPS. Further research is needed the better to understand the pathophysiology underlying these effects.

SUBMITTER: Hunziker S

PROVIDER: S-EPMC3580634 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients.

Hunziker Sabina S Celi Leo A LA Lee Joon J Howell Michael D MD

Critical care (London, England) 20120518 3

<h4>Introduction</h4>Recently, red cell distribution width (RDW), a measure of erythrocyte size variability, has been shown to be a prognostic marker in critical illness. The aim of this study was to investigate whether adding RDW has the potential to improve the prognostic performance of the simplified acute physiology score (SAPS) to predict short- and long-term mortality in an independent, large, and unselected population of intensive care unit (ICU) patients.<h4>Methods</h4>This observationa ...[more]

PMID: 22607685

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Project description:ObjectiveRed cell distribution width (RDW) is associated with mortality and bloodstream infection risk in the critically ill. In vascular surgery patients surviving critical care it is not known if RDW can predict subsequent risk of all-cause mortality following hospital discharge. We hypothesized that an increase in RDW at hospital discharge in vascular surgery patients who received critical care would be associated with increased mortality following hospital discharge.Design, setting, and participantsWe performed a two-center observational cohort study of critically ill non-cardiac vascular surgery patients surviving admission 18 years or older treated between November, 1997, and December 2012 in Boston, Massachusetts.ExposuresRDW measured within 24 hours of hospital discharge and categorized a priori as ?13.3%, 13.3-14.0%, 14.0-14.7%, 14.7-15.8%, >15.8%.Main outcomes and measuresThe primary outcome was all cause mortality in the 90 days following hospital discharge.ResultsThe cohort included 4,715 patients (male 58%; white 83%; mean age 62.9 years). 90 and 365-day post discharge mortality was 7.5% and 14.4% respectively. In the cohort, 47.3% were discharged to a care facility and 14.8% of patients were readmitted within 30 days. After adjustment for age, gender, race, Deyo-Charlson comorbidity Index, patient type, acute organ failures, prior vascular surgery and vascular surgery category, patients with a discharge RDW 14.7-15.8% or >15.8% have an adjusted OR of 90-day post discharge mortality of 2.52 (95%CI, 1.29-4.90; P = 0.007) or 5.13 (95%CI, 2.70-9.75; P <0.001) relative to patients with a discharge RDW ?13.3%. The adjusted odds of 30-day readmission in the RDW >15.8% group was 1.52 (95%CI, 1.12-2.07; P = 0.007) relative to patients with a discharge RDW ?13.3%. Similar adjusted discharge RDW-outcome associations are present at 365 days following hospital discharge and for discharge to a care facility.ConclusionsIn critically ill vascular surgery patients who survive hospitalization, an elevated RDW at hospital discharge is a strong predictor of subsequent mortality, hospital readmission and placement in a care facility. Patients with elevated RDW are at high risk for adverse out of hospital outcomes and may benefit from closer post discharge follow-up and higher intensity rehabilitation.

Project description:Acute kidney injury (AKI) is a serious complication in the intensive care unit (ICU), which may increase the mortality of critically ill patients. The red blood cell distribution width (RDW) has proved useful as a predictor of short-term prognosis in critically ill patients with AKI. However, it remains unknown whether RDW has a prognostic value of long-term all-cause mortality in these patients. The data of 18279 critically ill patients with AKI at first-time hospital admission were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The tertiles of the RDW values were used to divide subjects into three groups, namely RDW < 13.6% for the low RDW group, 13.6% ≤ RDW < 15.2% for the middle RDW group and RDW ≥ 15.2% for the high RDW group. Demographic data, mortality, 4-year survival time and severity scale scores were compared among groups. The Kaplan-Meier analysis and the Cox regression analysis were performed to assess the impact of RDW on all-cause mortality in AKI patients. The receiver operating characteristic (ROC) curve analysis was done to evaluate the prognostic value of RDW on the long-term outcome of critically ill patients with AKI. The median age of the enrolled subjects was 65.6 years. AKI patients with a higher RDW value had significantly shorter survival time and higher death rate. By the Kaplan-Meier analysis, patients in the higher RDW group presented significantly shorter survival time and higher death rate. The Cox regression model indicated RDW as an independent risk factor of all-cause mortality of AKI patients (HR 1.219, 95% CI, 1.211 to 1.228). By the ROC analysis, RDW appeared more efficient in predicting long-term prognosis as compared with conventional severity scales. The AUC of RDW (95% CI, 0.712 to 0.725) was significantly higher than other severity scale scores. In conclusion, RDW is positively correlated to survival time of 4-year follow-up in critically ill patients with AKI, and RDW is an independent prognostic factor of long-term outcomes of these patients.

Project description:BackgroundInflammation plays a key role in the pathophysiology and progression of acute kidney injury (AKI). Red cell distribution width (RDW) to platelet ratio (RPR) is a novel inflammatory index, and its prognostic effect on critically ill patients with AKI is rarely investigated. This work is aimed at investigating the association between RPR and in-hospital mortality in these patients.MethodsData were extracted from the Medical Information Mart for Intensive Care III database. All-cause death during hospitalization was selected as the primary outcome. Receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value, and the area under the curve (AUC) was applied to compare predictive ability among different indices. Cox proportional hazard models were utilized to assess the association between RPR and in-hospital mortality. Restricted cubic spline analysis for multivariate Cox model was performed to explore the shape of the relationship between RPR and mortality.ResultsA total of 24,166 critically ill patients with AKI were included. The relationship of RPR and in-hospital mortality was nonlinear with a trend to rise rapidly and then gradually. For mortality prediction, RPR had the optimal cut-off value of 0.093, of which the AUC was 0.791 (95% confidence interval (CI): 0.773-0.810), which was higher than those of RDW, platelet, sequential organ failure assessment score, simplified acute physiology score II, neutrophil to lymphocyte ratio, and platelet to lymphocytes ratio. After adjustments for various confounders, high RPR showed a significant association with increased mortality with hazard ratios of 1.46 (95% CI: 1.40-1.55) for categorical variable and 1.88 (95% CI: 1.80-1.97) for continuous variables in the fully adjusted model.ConclusionsElevated RPR on admission is substantially associated with high risk of in-hospital mortality in critically ill patients with AKI and thus may serve as a novel predictor of prognosis for these patients.

Project description:Background There is no evidence suggesting that red blood cell distribution width-to-albumin ratio (RA) predicts outcomes in severely ill older individuals with acute kidney injury (AKI). We hypothesized that RA is associated with all-cause mortality in critically ill older patients with AKI. Methods We recorded demographics, laboratory tests, comorbidities, vital signs, and other clinical information from the MIMIC-III V1.4 dataset. The primary endpoint was 90-day all-cause mortality, and the secondary endpoints were 30-day mortality, one-year mortality, renal replacement treatment (RRT), duration of stay in the intensive care unit (ICU), sepsis, and septic shock. We generated Cox proportional hazards and logistic regression models to determine RA's prognostic values and subgroup analyses to determine the subgroups' mortality. We conducted a Pearson correlation analysis on RA and C-reactive protein (CRP) in the cohort of patients from the Second Affiliated Hospital of Wenzhou Medical University. Results A total of 6,361 patients were extracted from MIMIC-III based on the inclusion and exclusion criteria. RA levels directly and linearly correlated with 90-day all-cause mortality. After controlling for ethnicity, gender, age, and other confounding variables in multivariate analysis, higher RA was significantly associated with an increased risk of 30-day, 90-day, and one-year all-cause mortality as opposed to the reduced levels of RA (tertile 3 vs. tertile 1: hazard ratios (HRs), 95% confidence intervals (CIs): 1.70, 1.43–2.01; 1.90, 1.64–2.19; and 1.95, 1.72–2.20, respectively). These results suggested that elevated levels of RA were linked to an elevated risk of 30-day, 90-day, and one-year all-cause death. There was a similar trend between RA and the use of RRT, length of stay in ICUs, sepsis, and septic shock. The subgroup analysis did not reveal any considerable interplay among strata. When areas under the curve were compared, RA was a weaker predictor than the SAPS II score but a stronger predictor than red blood cell distribution width (RDW) or albumin alone (P < 0.001); RA combined with SAPS II has better predictive power than SAPS II alone (P < 0.001). The Second Affiliated Hospital of Wenzhou Medical University cohort showed that CRP positively correlated with RA, with a coefficient of 0.2607 (P < 0.001). Conclusions RA was an independent prognostic predictor in critically ill older patients with AKI, and greater RA was linked to a higher probability of death. The risk of AKI is complicated when RRT occurs; sepsis and septic shock increase with RA levels.

Project description:IntroductionElevated red cell distribution width (RDW) has been associated with a range of health outcomes. This study aims to examine prognostic and etiological roles of RDW levels, both phenotypic and genetic predisposition, in predicting cardiovascular outcomes, diabetes, chronic kidney disease (CKD) and mortality.MethodsWe studied 27,141 middle-aged adults from the Malmö Diet and Cancer study (MDCS) with a mean follow up of 21 years. RDW was measured with a hematology analyzer on whole blood samples. Polygenic scores for RDW (PGS-RDW) were constructed for each participant using genetic data in MDCS and published summary statistics from genome-wide association study of RDW (n = 408,112). Cox proportional hazards regression was used to assess associations between RDW, PGS-RDW and cardiovascular outcomes, diabetes, CKD and mortality, respectively.ResultsPGS-RDW was significantly associated with RDW (Pearson's correlation coefficient = 0.133, p < 0.001). RDW was significantly associated with incidence of stroke (hazard ratio (HR) per 1 standard deviation = 1.06, 95% confidence interval (CI): 1.02-1.10, p = 0.003), atrial fibrillation (HR = 1.09, 95% CI: 1.06-1.12, p < 0.001), heart failure (HR = 1.13, 95% CI: 1.08-1.19, p < 0.001), venous thromboembolism (HR = 1.21, 95% CI: 1.15-1.28, p < 0.001), diabetes (HR = 0.87, 95% CI: 0.84-0.90, p < 0.001), CKD (HR = 1.08, 95% CI: 1.03-1.13, p = 0.004) and all-cause mortality (HR = 1.18, 95% CI: 1.16-1.20, p < 0.001). However, PGS-RDW was significantly associated with incidence of diabetes (HR = 0.96, 95% CI: 0.94-0.99, p = 0.01), but not with any other tested outcomes.DiscussionRDW is associated with mortality and incidence of cardiovascular diseases, but a significant association between genetically determined RDW and incident cardiovascular diseases were not observed. However, both RDW and PGS-RDW were inversely associated with incidence of diabetes, suggesting a putative causal relationship. The relationship with incidence of diabetes needs to be further studied.

Dataset Information

Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients.

Introduction

Methods

Results

Conclusions

Publications

Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients.

Similar Datasets

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