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Simple Prognostic Markers to Predict Mortality in Intensive Care Unit: Red Cell Distribution Width

Background: We tried to examine association between the prognostic intensive care unit (ICU) scores and red cell distribution width (RDW) for prediction of mortality in a cohort of ICU patients at a single centre in Turkey. Methods: This is a retrospective cohort study conducted in a 9-bed mixed ICU of a tertiary hospital from January to December 2013. One hundred and nine ICU patients requiring intensive care following an elective or emergent surgical procedure, trauma or medical severe disease were enrolled in the study. Demographic data, admission clinical parameters and Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA), Simplified Acute Physiology Score (SAPS) II scores were collected. The primary outcome was ICU mortality which is defined as death before hospital discharge for any reason. Receivers operating characteristic (ROC) curves were used to examine the performance of variables in predicting ICU mortality. Results: There were significant positive correlations between RDW and APACHE II, SOFA and SAPS II scores. RDW levels were significantly higher in non-survivors (16.94±3.05 versus 15.62±2.82, p<0.001). The optimal cutoff value of RDW for prediction of mortality according to ROC analyses was 14.5. ICU mortality rate was 18.9% if RDW level was less than 14.5%; and 81.1 % if RDW level was greater than14.5%. Conclusions: We found that ICU mortality was higher RDW was greater than 14.5%. We also found positive correlation between RDW and ICU mortality scores.


Introduction
Red cell distribution width (RDW) level is a hemogram test parameter that reflects the measurement of red cell dimensions. RDW generally increases in cases of ineffective erythropoiesis or increased red cell destruction. Studies conducted in recent years have revealed the usefulness of RDW as a new prognostic marker in varied conditions, including cardiovascular, thromboembolic and neurological diseases; sepsis, trauma; and acute and chronic inflammatory disorders (1)(2)(3)(4)(5)(6)(7)(8)(9)(10). Furthermore, studies have shown the relationship between high RDW levels and high mortality rates at the time of admission to the intensive care unit (11)(12)(13)(14). Clinicians need models to estimate the mortality of patients in the intensive care unit (ICU). ICU scoring systems use a large number of variables that are often observed only among critically ill patients (e.g., arterial blood gas measurements).
It is not known which of these scores provide the best performance for patients in the ICU. The Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, and Sequential Organ Failure Assessment (SOFA) scores are the most commonly used scoring systems for ICU patients (15)(16)(17).
In this study, we examined a cohort of ICU patients to determine association between the prognostic scores and RDW for prediction of mortality at a single centre in Turkey.

Methods
This retrospective cohort study was conducted in a 9-bed mixed ICU of a tertiary hospital from January to December 2013. Patients with hematologic disorders, severe anemia, inflammatory disease, iron supplementation therapy, venous thrombosis, red blood cell transfusion, hepatitis B or C, untreated thyroid disease, and severe liver and/or renal insufficiency and trauma patients with excessive blood loss, were excluded from the study.
109 ICU patients were enrolled into the study requiring ICU admission following an elective or emergent surgical procedure, trauma and severe medical disease. Patient demographic data, etiology of ICU admission, length of ICU stay (LOS), mechanical ventilation (MV) support, continuous inotropic support, physiologic parameters including fever, heart rate, mean arterial pressure (MAP), daily urine output, presence of sepsis were abstracted from each patient record.
Laboratory data including hemoglobin, RDW, mean corpuscular volume (MCV), hematocrit level (Htc), white blood cell count (WBC), neutrophil ratio (Neu), platelet count (PLT), blood glucose, blood urea nitrogen (BUN), creatinine, calcium level, hepatic and cholestasis enzymes, lactate dehydrogenase (LDH) levels, arterial and venous blood gas analyses (partial pressure oxygen, pH, bicarbonate and base excess) were also collected on patient admission. The reference range for RDW in our laboratory is 11.5-14.5%. APACHE II, SOFA Score and SAPS II Score were calculated on admission.
The primary outcome measure was determined as ICU mortality, defined as death before ICU discharge for any reason.

Statistical Analyses
Skewness and Kurtosis test were used to assess normality. The normally distributed data was presented as mean ± SD (standard deviation) and non-normally distributed data was presented as median value (interquartile range). The Spearman's rank correlation was used to define a correlation between scoring systems, and RDW. Baseline characteristics between survivors and non-survivors were compared with an unpaired Student's t-test or the Mann-Whitney U test for continuous variables and a χ2 test or Fisher's exact test for categorical variables. Cox regression analyses was conducted to identify the independent risk factors associated with ICU mortality, including all variables with a p value <0.10 in the univariate analysis (using a stepwise forward regression model). Receivers operating characteristic (ROC) curves were used to examine the performance of variables in predicting ICU mortality. The area under the curve (AUC, also known as C-index) was calculated from the ROC curve. Hosmer-Lemeshow method was used to test the goodness-of-fit of the regression model. All statistical procedures were performed with SPSS 15.0 (SPSS Inc, Chicago, Illinois). The p-value for statistical significance was p<0.05.

Results
Median age of the patients was 72 years     (Figure 1).

Discussion
There are studies showing that initial high RDW values are associated with mortality in intensive care patients (14,18). Our results are consistent with previous studies showing that ICU mortality was higher when increased RDW was present. Our results are in compliance with previous studies showing that ICU mortality was higher when increased RDW was present.
Scoring systems have been developed to measure the severity of the disease and the prognosis of patients in the ICU. These measurements are beneficial in making clinical decisions, standardizing studies, and comparing the quality of patient care in different ICUs (16).
APACHE II (15), SAPS II (16), and SOFA (17) are widely accepted and used scoring systems. We have found a positive correlation between RDW levels and ICU mortality scores. The latest updates of these scores have acceptable discrimination and calibration. However, estimated scoring systems have important limitations in terms of data collection, mortality calculation, effectiveness and cost. RDW is a quantitative measure of anisocytosis and is calculated by dividing the standard deviation of the erythrocyte volume by MCV. It increases in various conditions. The relation between RDW and mortality is not known completely. Several hypotheses for this relation have been proposed and the most popular ones include inflammatory response and oxidative stress. In animal models, RDW is associated with the presence of certain oxidative stress-related molecules, such as reactive oxygen species (ROS), superoxide dismutase (SOD), and glutathione peroxidase (19).
Previously, Zhang et al. found that high RDW was associated with increased hospital mortality and a longer stay in the ICU. However, the ability of RDW to distinguish patients with a better survival prognosis is suboptimal and repeated RDW measurements did not offer additional clinical value in predicting results (13 (12) and supports the conclusion that RDW does not stem from inflammation (23).
RDW is a part of routine complete blood count analysis and does not generate any additional costs. This feature of RDW makes it an easily accessible variable. If other studies can support our findings, RDW could become a part of more commonly used and more advanced disease severity scoring tests (e.g., APACHE IV, SAPS III), thus increasing their accuracy.
Our study has certain limitations. First, we did not examine the causes of high RDW, such as iron or vitamin B12 deficiency, which can disrupt the relationship between RDW and negative outcomes. Second, this is a single-center study. A study with multiple centers would reduce the concerns about the case mixture and benefit from a larger sample size.

Conclusion
We found that ICU mortality was higher when RDW was greater than 14.5%. We also found a positive correlation between RDW and commonly used ICU mortality scores. This might suggest that instead of using scoring systems which require computation of multiple variables we could utilize a single easily accessible laboratory value (ie RDW) to predict mortality in ICU patients.