|Year : 2015 | Volume
| Issue : 2 | Page : 24-33
Evaluation of red cell distribution width as a septic marker in comparison with clinical scores, C-reactive protein, and procalcitonin levels
Assem Abdel Razek1, Atef Abdel Aziz Mahrous2, Karim Mohammad Zakaria2
1 Department of Anaesthesia and Surgical Intensive Care, Alexandria University, Alexandria, Egypt
2 Department of Critical Care Medicine, Alexandria University, Alexandria, Egypt
|Date of Submission||15-Feb-2015|
|Date of Acceptance||15-Mar-2015|
|Date of Web Publication||30-Dec-2016|
Karim Mohammad Zakaria
Critical Care Medicine, Alexandria University, Alexandria
Source of Support: None, Conflict of Interest: None
Biomarkers, which were introduced in the diagnosis and risk assessment of sepsis, could contribute toward predicting outcome in those patients affected by sepsis, severe sepsis, and septic shock who could benefit from a quick and appropriate therapy. Among different molecules that have been suggested as sepsis biomarkers in the last few years is red cell distribution width, which appears quite promising because of its reported correlation with the septic process. The aim of this study was to compare between red cell distribution width, C-reactive protein (CRP), and procalcitonin as diagnostic and prognostic markers in sepsis.
Patients and methods
This study was carried out on 45 adult patients of both sexes who had sepsis, severe sepsis, and septic shock; all of them received the same treatment as recommended by the surviving sepsis campaign; 17 of these patients have survived and the other 28 did not survive (group I). There were 45 healthy adult volunteers (group II). The patients in the study group were those who were admitted to the units of the Critical Care Medicine Department in Alexandria Main University Hospital and who fulfilled the diagnostic criteria for severe sepsis or septic shock on arrival to ICU according to the SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Venous blood samples were obtained from group I on admission, day 5, and day 10 to determine red blood cell distribution width (RDW), CRP, and procalcitonin levels on admission, day 5, and day 10; the Sequential Organ Failure Assessment (SOFA) score was also measured on days 1, 5, and 10. The APACHE II score was measured only on admission. Patients were managed according to the surviving sepsis campaign guidelines.
On comparing the biomarkers studied in both groups, it was found that the values of RDW, CRP, and procalcitonin were significantly different between group I on admission and group II. CRP was less accurate than RDW and procalcitonin in assessing the severity of sepsis at admission. The best diagnostic cut-off for RDW on admission was 15.3%: at that level, sensitivity and specificity were 86.6 and 71.1%, respectively. The best diagnostic cut-off for CRP on admission was 39 mg/dl: at that level, sensitivity and specificity were 66.6 and 80%, respectively, and for procalcitonin, it was 1.4 ng/ml; at that level, sensitivity and specificity were 88.8 and 91.1%, respectively. Higher RDW values were found in patients with higher APACHE II and SOFA scores. RDW, the APACHE II score, and the SOFA score were significantly higher in nonsurvivors in comparison with survivors (P = 0.011, P < 0.001, and P < 0.001, respectively). On comparing the markers studied for their prognostic value, we found that RDW and procalcitonin were significantly higher in nonsurvivors than survivors (P = 0.11 and 0.002, respectively), and CRP concentrations were not statistically different between survivors and nonsurvivors at admission. The best prognostic cut-off for RDW on admission was 16.4%: at that level, sensitivity and specificity were 80 and 67.68%, respectively, and for procalcitonin, it was 5.1 ng/ml; at that level, sensitivity and specificity were 94.12 and 60.7%, respectively.
RDW is a new promising and readily available cheap biomarker that can aid the diagnosis of sepsis and also aid prediction of outcome comparable with more complex clinical scores (APACHE II and SOFA).
Keywords: CRP, procalcitonin, red blood cell distribution width, sepsis
|How to cite this article:|
Razek AA, Mahrous AA, Zakaria KM. Evaluation of red cell distribution width as a septic marker in comparison with clinical scores, C-reactive protein, and procalcitonin levels. Res Opin Anesth Intensive Care 2015;2:24-33
|How to cite this URL:|
Razek AA, Mahrous AA, Zakaria KM. Evaluation of red cell distribution width as a septic marker in comparison with clinical scores, C-reactive protein, and procalcitonin levels. Res Opin Anesth Intensive Care [serial online] 2015 [cited 2020 Jun 4];2:24-33. Available from: http://www.roaic.eg.net/text.asp?2015/2/2/24/161320
| Introduction|| |
Sepsis is a systemic, deleterious host response to infection leading to severe sepsis (acute organ dysfunction secondary to documented or suspected infection) and septic shock (severe sepsis plus hypotension not reversed with fluid resuscitation) ,,. Severe sepsis and septic shock are major healthcare problems, affecting millions of individuals around worldwide each year, killing one in four (and often more), and increasing in incidence ,.
Sepsis is defined as the presence (probable or documented) of infection together with systemic manifestations of infection. Severe sepsis is defined as sepsis plus sepsis-induced organ dysfunction or tissue hypoperfusion .
Diagnostic criteria for sepsis
Fever (>38.3°C), hypothermia (core temperature <36°C), heart rate more than 90/min or more than 2 SD above the normal value for age, tachypnea, altered mental status, significant edema or positive fluid balance (>20 ml/kg over 24 h), and hyperglycemia (plasma glucose > 140 mg/dl or 7.7 mmol/l) in the absence of diabetes are general variables .
Leukocytosis (WBC count > 12 000 μl/1), leukopenia (WBC count < 4000 μl/1),or normal WBC count with greater than 10% immature forms, plasma C-reactive protein more than two-folds above the normal value, plasma procalcitonin more than two-folds above the normal value are inflammatory variables .
Arterial hypotension, systolic blood pressure less than 90 mmHg, MAP more than 70 mmHg, or systolic blood pressure decrease more than 40 mmHg in adults or less than 2 SD below normal for age are hemodynamic variables .
Organ dysfunction variables
With progression of sepsis, the internal organs are affected, and the following manifestations may occur: arterial hypoxemia (PaO 2 /FiO 2 < 300), acute oliguria (urine output <0.5 ml/kg/h for ≥2 h despite adequate fluid resuscitation), creatinine increase of more than 0.5 mg/dl or 44.2 μmol/l, coagulation abnormalities (INR > 1.5 or aPTT > 60 s), ileus (absent bowel sounds), thrombocytopenia (platelet count <100 000 μl/1), hyperbilirubinemia (plasma total bilirubin >4 mg/dl or 70 μmol/l), tissue perfusion variables such as hyperlactatemia (>2 mmol/l), and decreased capillary refill or mottling .
Severe sepsis, sepsis-induced hypotension, and septic shock:
Severe sepsis is a sepsis associated with organ dysfunction, hypoperfusion, or hypotension (systolic blood pressure < 90 mmHg or a reduction >40 mmHg from baseline) and could be corrected by adequate fluid resuscitation; thus, sepsis can be considered as the cause of hypotension, and if not corrected by adequate fluid resuscitation, it is considered septic shock .
It is very important that clinicians have the tools to identify and diagnose sepsis promptly because early diagnosis and treatment may lead to improvement in both mortality and morbidity. Gold standards for the diagnosis of infection do not exist, but procalcitonin is known to be among the most promising sepsis markers in critically ill patients, can complement clinical signs and routine laboratory variables that are suggestive of sepsis ,,.
The use of procalcitonin in developing countries such as Egypt, however, remains very expensive and hardly accessible in all ICUs.
CRP can activate the complement system and can bind to phagocytic cells, suggesting that it can initiate the elimination of pathogens and targeted cells by interaction with both humoral and cellular effector systems of inflammation . The rapidity of the CRP response, in contrast to the slower adaptive immune response represented by antibody production, indicates that CRP is a component of the innate immune response .
Markedly increased levels of CRP are strongly associated with infections, mostly bacteria .
The red blood cell distribution width (RDW) represents an index of the heterogeneity of the erythrocytes (anisocytosis), which is calculated by dividing the standard deviation of erythrocyte volume by the mean corpuscular volume and multiplying by 100 to express the result as a percentage . RDW is widely available to clinicians because it is routinely reported as part of the complete blood count.
For several decades, RDW has typically been used in combination with the mean corpuscular volume to differentiate the cause of underlying anemia in clinical practice . Recently, highly significant associations have been described between RDW value and all-cause, noncardiac, and cardiac mortality in patients with coronary artery disease, acute and chronic heart failure, peripheral artery disease, stroke, pulmonary embolism, and pulmonary artery hypertension [16-21]. Moreover, several studies have reported that RDW shows the predictive value of all-cause mortality in critically ill or ICU patients ,,,.
Although it has been postulated that systemic inflammation, malnutrition, and impaired renal function play a significant role in the underlying pathological processes , the mechanism of the association between increased RDW and mortality remains unclear.
Studies by electronic microscopy have founded important alterations in RBC shape during the refractory phase of shock ,. They also showed morphologic and functional changes during sepsis in the RBC population. This led to the hypothesis that RBC alterations during shock and sepsis may contribute toward multiple organ dysfunction syndrome. It has been reported previously that the flexibility of RBC may be dysfunctional because of the endotoxins of bacteria in septic shock. The RBC exposed to endotoxin decreased their deformability and showed increased hidromiristic acid content, which is a component of bacterial endotoxina, suggesting a relationship ,,.
The initial results of clinical studies suggested that RDW may be a promising diagnostic and prognostic biomarker of systemic infections or sepsis.
| Aim of the work|| |
To evaluate the red cell distribution width as a diagnostic marker of sepsis and as a predictor of mortality compared with CRP, procalcitonin, and clinical scores [APAHE II and Sequential Organ Failure Assessment (SOFA)].
| Patients and methods|| |
All patients admitted to the critical care medicine department in Alexandria Main University Hospital who fulfilled the criteria of sepsis and severe sepsis according to International Sepsis Definitions Conference  during the period from November 2013 to April 2014 were included in the study, with a minimum of 30 patients. Approval of the medical ethics committee of Alexandria faculty of medicine and an informed consent from the patient's next of kin were obtained before carrying out the study.
Patients who fulfilled the criteria of sepsis and severe sepsis according to the International Sepsis Definitions Conference were included in this study .
- Patients younger than 18 years old.
- Patients with other causes associated with increased red cell distribution width.
- Patients with congestive heart failure, acute myocardial infarction, pulmonary embolism, and patients after cardiac arrest.
All patients included in the study were subjected to the following:
(1) Demographic data: age and sex.
(2) Complete assessment of medical history, including family history and drug history.
(3) Comprehensive physical examination.
(4) Vital signs.
(5) The following laboratory investigations and clinical scores were performed:
(a) On admission
- Blood culture: on admission and before administration of antibiotics.
- Culture from the suspected source of infection such as urine, sputum, and cerebrospinal fluid on admission.
- The Acute Physiology and Chronic Health Evaluation II (APACHE II) score.
- Complete blood count: microtubes containing the EDTA anticoagulant. The red cell distribution width was assessed using the auto hematology analyzer mindray BC-5500.
- Blood urea (mg/dl), serum creatinine (mg/dl), serum sodium (mg/dl), and serum potassium (mg/dl).
- Bilirubin, total and direct (mg/dl), alanine aminotransferase, and aspartate aminotransferase (μ/l).
- Arterial blood gases: when needed.
- The Glasgow Coma Scale.
- The SOFA score.
(c) On days 1, 5, and 10
- CRP level (mg/l): to determine the CRP level, blood samples were drawn into green-top vacutainer tubes containing lithium heparin as an anticoagulant.
- Procalcitonin level (ng/ml): procalcitonin (PCT) levels (normal range 0-0.5 ng/ml) were determined using a stat fax- 2100 ELISA (Awareness Technology, Inc. New York, USA) reader.
(d) Chest radiograph: when needed.
(6) All patients included in the study were subjected to the same protocol according to the surviving sepsis campaign 2012 .
Statistical analysis 
Data were fed to the computer and analyzed using the IBM SPSS software package version 20.0 (Belmont, CA) . Qualitative data were described as number and percent. Quantitative data were described as range (minimum and maximum), mean, SD, and median. Comparison between different groups in terms of categorical variables was performed using the χ2 -test. When more than 20% of the cells had an expected count less than 5, correction for χ2 was performed using Fisher's exact test or Monte Carlo correction. The distributions of quantitative variables were tested for normality using the Kolmogorov-Smirnov test, the Shapiro-Wilk test, and the D'Agstino test; also, a histogram and a QQ plot were used for vision test. If it showed normal data distribution, parametric tests were applied. If the data were abnormally distributed, nonparametric tests were used. For normally distributed data, comparisons between two independent populations were performed using an independent t-test. For abnormally distributed data, comparisons between two independent populations were performed using the Mann-Whitney U-test. To compare between the different periods, the Wilcoxon signed ranks test was applied. The agreement of RDW, CRP, and procalcitonin to differentiate between outcomes was used and was expressed as sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Receiver operating characteristic (ROC) curve was plotted to analyze a recommended cut-off; the area under the ROC curve indicates the diagnostic performance of the test. Area more than 50% yields acceptable performance and area of about 100% is the best performance for the test. Significance test results are quoted as two-tailed probabilities. The significance of the results obtained was assessed at the 5% level.
| Results|| |
There were no statistically significant differences between the subgroups of sepsis studied (sepsis, severe sepsis, and septic shock) in age or sex [Table 1].
CRP levels on admission differed significantly between patients with sepsis and patients without sepsis (P < 0.001). Procalcitonin levels on admission differed significantly between patients with sepsis and patients without sepsis (P < 0.001).
|Table 1 Comparison between the three subgroups of septic patients according to demographic data|
Click here to view
RDW on admission showed a statistically significant difference between patients with sepsis and the control group (P < 0.001) [Table 2].
|Table 2 Comparison between levels of the studied group on admission and the control group|
Click here to view
The ROC curves of the biomarkers studied were designed and are presented in [Figure 1]; the results were significant for all biomarkers. The areas under the curve (AUCs) calculated from the ROC curves were 0.857 (P < 0.001) for CRP, 0.95 (P < 0.001) for PCT, and 0.80 (P < 0.001) for RDW, respectively [Figure 1].
|Figure 1: Receiver operating characteristic curve for CRP, procalcitonin, and RDW on admission for the diagnosis of sepsis. AUC, area under the curve; CI, confidence interval; RDW, red blood cell distribution width.|
Click here to view
Cut-off point, sensitivity, specificity, positive predictive value, and negative predictive value for the different biomarkers studied
The best diagnostic cut-off for CRP was 39 mg/dl: at that level, sensitivity and specificity were 66.6 and 80%, respectively.
The best diagnostic cut-off for PCT was 1.4 ng/ml; at that level, sensitivity and specificity were 88.8 and 91.1%, respectively.
The best diagnostic cut-off value for RDW was 15.3 mg/dl: at that level, sensitivity and specificity were 86.6 and 71.1% respectively [Table 3].
|Table 3 Agreement (sensitivity, specificity, and accuracy) for CRP, procalcitonin, and RDW on admission with sepsis|
Click here to view
There was no statistically significant difference between sepsis and severe sepsis or septic shock according to the levels of CRP on admission. There was a statistically significant difference between subgroups (sepsis, severe sepsis, and septic shock) according to procalcitonin level on admission (P1 < 0.001, P2 < 0.001*, P3 = 0.005*) [Table 4]. There was a statistically significant difference between sepsis and septic shock (P2 = 0.001) and between severe sepsis and septic shock (P3 = 0.003) according to RDW on admission, whereas there was no statistically significant difference between sepsis and severe sepsis according to RDW on admission.
|Table 4 Levels of the markers studied in the three subgroups of sepsis studied|
Click here to view
CRP level on admission in patients who survived ranged from 28 to 274 mg/dl, with a mean CRP level of 89.86 ± 77.44 mg/dl and a median level of 46 mg/dl. In nonsurviving patients, the CRP level on admission ranged from 30 to 303 mg/dl, with a mean CRP level of 132.2 ± 73.1 mg/dl and a median level of 132 mg/dl. There was no statistically significant difference in the CRP levels between survivors and nonsurvivors on day 1, whereas there were a statistically significant difference on days 5 and 10 [Table 5].
Procalcitonin level on admission in surviving patients ranged from 0.9 to 18.7 ng/ml, with a mean procalcitonin level of 6.05 ± 4.98 ng/ml and a median level of 3.80 ng/ml; in nonsurviving patients, it ranged from 5.10 to 19.30 ng/ml, with a mean level of 10.20 ± 4.83 ng/ml and a median level of 8.50 ng/ml. There were statistically significant differences between survivors and nonsurvivors according to procalcitonin levels on day 1, day 5, and day 10 (P = 0.002, P < 0.001, and 0.001), respectively [Table 5].
RDW in surviving patients ranged from 14.10 to 18.60% on admission, with a mean RDW of 16.14 ± 1.17% and a median level of 15.98%; in nonsurviving patients, it ranged from 14.30 to 22.20%, with a mean RDW of 17.91 ± 2.57% and a median RDW of 17.10%.
On the day of admission and on day 5 (P = 0.009*), there were statistically significant differences between survivors and nonsurvivors according to RDW levels (P = 0.011), whereas there were no statistically significant differences between survivors and nonsurvivors on day 10 (P = 0.338) [Table 5].
There was a strong positive correlation found between RDW and the SOFA score on admission (r = 0.528, P < 0.001) and on day 5 (r = 0.559, P < 0.001), but a weak positive correlation was found on day 10 (r = 0.015, P = 0.947).
A strong positive correlation was found between RDW and the APACHE II score on admission (r = 0.539, P < 0.001) [Table 6].
The ROC curve for mortality showed that the AUC was 0.728, 0.741, and 0.733 for RDW, the SOFA score, and the APACHE II score, respectively. The addition of RDW to the SOFA score increased the AUC from 0.741 to 0.765 and the addition of RDW to the APACHE II score increased the AUC from 0.733 to 0.752 [Figure 2].
|Figure 2: Receiver operating characteristic curve for RDW, SOFA, and APACHE II on admission for the diagnosis of mortality. APACHE II, Acute Physiology and Chronic Health Evaluation II; RDW, red blood cell distribution width; SOFA, Sequential Organ Failure Assessment.|
Click here to view
| Discussion|| |
In the present study, the age of the patients in group I ranged from 48 to 81 years, with a mean age of 63.89 ± 8.91 years; 18 patients (40%) in group I were women, whereas 27 patients were men (60%).
In agreement with the present study, the mean age of patients with severe sepsis in most epidemiological studies ranged between 55 and 64 years ,,,,,. Angus et al.  found that there is a direct relationship between advanced age and the incidence of severe sepsis and septic shock, with a marked increase in incidence in elderly individuals . Karlsson et al.  carried out a prospective observational study to investigate the predictive value of a decrease in PCT in patients with severe sepsis; they found that the mean age of patients with severe sepsis was 59.8 years. Moreover, and similar to the present study, they found a significant difference between men, who accounted for 168 patients (68%) in their study population, and women, who accounted for 74 patients (32%) in their study population (P < 0.001).
In this study, the median level of procalcitonin concentrations in plasma on admission was 6.1 mg/dl in the septic group and 0.80 mg/dl in the control group. Procalcitonin levels on admission differ significantly between patients with sepsis and the control group (P = <0.001).
In agreement with our study, Luzzani et al.  found in their study that the median plasma PCT concentrations in nonseptic (systemic inflammatory response syndrome) and septic (sepsis, severe sepsis, or septic shock) patients were 0.4 and 3.65 ng/ml (P < 0.0001), respectively.
The higher levels of PCT in our study compared with the study carried out by Luzzani et al.  could be because of the fact that most of the cases studied were admitted by severe sepsis and septic shock, and the control group included healthy volunteers.
Luzzani et al.  found in their study that the median plasma CRP concentrations in nonseptic (systemic inflammatory response syndrome) and septic (sepsis, severe sepsis, or septic shock) patients were 79.9 and 115.6 mg/l (P < 0.0001), respectively.
In our study, the CRP level on admission ranged from 5 to 45 mg/dl in the control group and from 28 to 303 mg/dl in the septic group (sepsis, severe sepsis, or septic shock). The mean levels of CRP concentrations in plasma on admission were 113.29 ± 83.48 mg/dl in the septic group of patients and 25.67 ± 13.33 mg/dl in the control group. The median levels of CRP concentrations in plasma on admission were 96 mg/dl in the septic group and 18 mg/dl in the control group. CRP levels on admission differed significantly between patients with sepsis and the control group (P < 0.001).
In the present study, the area under the ROC curve was 0.95 for PCT [95% confidence interval (CI), 0.92-0.93] compared with 0.85 for CRP (95% CI, 0.78-0.93) (P < 0.001).
Luzzani et al.  found that the area under the ROC curve was 0.925 for PCT (95% CI, 0.899-0.952) compared with 0.677 for CRP (95% CI, 0.622-0.733) (P < 0.0001). The linear correlation between PCT plasma concentrations and the four categories (SIRS, sepsis, severe sepsis, and septic shock) was much stronger than in the case of CRP (Spearman's ρ, 0.73 vs. 0.41; P < 0.05), which was similar to that found in our study.
In the present study, it was found that the CRP level at day 1 was not accurate in predicting mortality, whereas its level differed significantly between survivors and nonsurvivors on day 5 and day 10.
In this study, it was found that procalcitonin level was a good predictor of mortality; there were statistically significant differences between survivors and nonsurvivors according to procalcitonin levels on day 1, day 5, and day 10 (P = 0.002, P < 0.001, P < 0.001), respectively.
Jain et al.  found that among the biomarkers, the levels of serum procalcitonin on admission were significantly higher among nonsurvivors compared with that of survivors (P < 0.01), whereas hsCRP levels did not show any significant difference between both groups (P = 0.74), which was similar to the results found in our study, in which there was no statistically significant difference in the CRP levels between survivors and nonsurvivors on day 1 [Table 5].
Jain et al.  found in their study that the level of procalcitonin decreased significantly among survivors over the course of 28 days. This result was similar to that observed in our study [Table 5], where the mean procalcitonin level on admission in surviving cases was 6.05 ± 4.98 ng/l; the mean level was 2.09 ± 3.03 ng/ml on day 5 and on 0.57 ± 0.30 ng/l on day 10.
Jain et al.  also found that the level of hsCRP decreased over the course of in-hospital stay among survivors, which might be because of the fact that CRP is an acute inflammatory reactant and its levels improve with time. These observations were similar to those found in our study, where the mean CRP levels of the survivors were 89.86 ± 77.44, 70.96 ± 55.87, and 37.43 ± 24.90 mg/dl at days 1, 5, and 10 ,respectively.
In agreement with the present study, Devran et al.  found that the initial CRP was not a good predictor of mortality, but control CRP was found to be as significant as the SOFA score for predicting response to sepsis treatment and prognosis. In the study carried out by Devran et al. , after the third-fifth day of treatment, the median CRP values were higher among nonsurvivors than survivors (105 vs. 44 mg/l, respectively). In our study, CRP levels on day 5 and day 10 were a predictor of mortality whereas this was not so at admission.
The RDW value in our study showed statistically significant differences between survivors and nonsurvivors on the day of admission and on day 5, on day 1 (P = 0.011) and on day 5 (P = 0.009), whereas there was no statistically significant difference between survivors and nonsurvivors on day 10 (P = 0.338).
In agreement with our study, Lorente et al.  found higher RDW in nonsurviving (n = 104) than in surviving (n = 193) septic patients on day 1 (P = 0.001), day 4 (P = 0.001), and day 8 (P = 0.002) of ICU admission. Cox regression analyses showed that RDW on days 1 (P < 0.001), 4 (P = 0.005), and 8 (P = 0.03) were associated with 30-day mortality. ROC curves showed that RDW on days 1 (P < 0.001), 4 (P < 0.001), and 8 (P < 0.001) could be used to predict 30-day mortality. RDW showed a positive correlation with the SOFA score on days 1, 4, and 8.
Raϊl Carrillo Esper et al.  found in their study, carried out to compare the sepsis group with a control group for RDW, that the mean RBC-DW was 18.23 ± 2.01 in the sepsis group and 12 ± 0.27 in the control group (P < 0.05; t = 3.580, 95% CI). Also, they found that RDW was also statistically higher in patients with the highest SOFA values, which was similar to the present study, but not APACHE II, in contrast to the present study. This may be attributed to the exclusion criteria of the septic group in their study; more complex exclusion criteria were used for patients admitted to ICU including the presense of hepatic cirrhosis and use of drugs that may induce changes in the morphology and rheology of RBCs, in addition to the control group included in their study, which included healthy adult blood donors and patients admitted to the MS-ICU with diagnoses other than sepsis, severe sepsis, and septic shock, without exclusion criteria.
The present study showed that the mean levels of RDW on admission were 16.81 ± 2.0% in the septic group of patients and 15.14 ± 0.86% in the control group, with a statistically significant difference between patients with sepsis and the control group (P < 0.001). We also found a positive correlation between RDW and each of APACHE II score at day 1 and SOFA score on days 1, 5, and 10 although the correlation was weak on day 10. This could be because of the fact that most of the survivors with relatively lower RDW values were discharged before day 10, with the remaining patients with higher RDW values discharged after day 10. The smaller sample size in the study on sepsis, severe sepsis, and septic shock patients and the limited exclusion criteria in the present study in comparison with the study carried out by Lorente et al.  may have also led to the differences.
Sadaka et al. , in their study, which was carried out on 279 patients with septic shock estimating the ROC area under the curve (AUC), showed that RDW has very good discriminative power for hospital mortality (AUC = 0.74). The AUC was 0.69 for APACHE II and 0.69 for SOFA. On adding RDW to APACHE II, the AUC increased from 0.69 to 0.77. In this study, we found that the ROC curve for mortality showed that the AUC was 0.728, 0.741, and 0.733 for RDW, the SOFA score, and the APACHE II score, respectively. The addition of RDW to the SOFA score increased the AUC from 0.741 to 0.765 and the addition of RDW to the APACHE II score increased the AUC from 0.733 to 0.752. The smaller sample size and the fact that our study was carried out on sepsis, severe sepsis, and septic shock patients may have led to the different results obtained.
| Conclusion|| |
RDW is a new promising cheap and readily available biomarker that can aid the diagnosis of patients with sepsis with high specificity and sensitivity, which is similar to classically used biomarkers (CRP and procalcitonin). Also, RDW is a good predictor of mortality, with a strong positive correlation with SOFA and APACHE II scores. The addition of RDW to the APACHE II score or the SOFA score led to an increase in the AUC for each score.
| Acknowledgements|| |
Conflicts of interest
| References|| |
Bernard GR, Wheeler AP, Russell JA, Schein R, Summer WR, Steinberg KP, et al
. The effects of ibuprofen on the physiology and survival of patients with sepsis. The Ibuprofen in Sepsis Study Group. N Engl J Med 1997; 336:912-918.
McCloskey RV, Straube RC, Sanders C, Smith SM, Smith CR. Treatment of septic shock with human monoclonal antibody HA-1A. A randomized, double-blind, placebo-controlled trial. CHESS Trial Study Group. Ann Intern Med 1994; 121:1-5.
Zeni F, Freeman B, Natanson C. Anti-inflammatory therapies to treat sepsis and septic shock: a reassessment. Crit Care Med 1997; 25: 1095-1100.
Sasse KC, Nauenberg E, Long A, Anton B, Tucker HJ, Hu TW. Long-term survival after intensive care unit admission with sepsis. Crit Care Med 1995; 23:1040-1047.
Annane D, Bellissant E, Cavaillon JM. Septic shock. Lancet 2005; 365: 63-78.
Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, et al
. SCCM/ESICM/ACCP/ATS/SIS. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med 2003; 31:1250-1256.
Rey C, Los Arcos M, Concha A, Medina A, Prieto S, Martinez P, Prieto B Procalcitonin and C-reactive protein as markers of systemic inflammatory response syndrome severity in critically ill children. Intensive Care Med 2007; 33:477-84.
Uzzan B, Cohen R, Nicolas P, Cucherat M, Perret GY. Procalcitonin as a diagnostic test for sepsis in critically ill adults and after surgery or trauma: a systematic review and meta-analysis. Crit Care Med 2006; 34:1996-2003.
Tang BM, Eslick GD, Craig JC. Accuracy of procalcitonin for sepsis diagnosis in critically ill patients: systematic review and metaanalysis. Lancet Infect Dis 2007; 7:210-217.
Marnell L, Mold C, Du Clos TW. C-reactive protein: ligands, receptors and role in inflammation. Clin Immunol 2005; 117:104-111.
Janeway CA Jr, Medzhitov R. Innate immune recognition. Annu Rev Immunol 2002; 20:197-216.
Vanderschueren S, Deeren D, Knockaert DC, Bobbaers H, Bossuyt X, Peetermans W. Extremely elevated C-reactive protein. Eur J Intern Med 2006; 17:430-433.
Bazick HS, Chang D, Mahadevappa K, Gibbons FK, Christopher KB. Red cell distribution width and all-cause mortality in critically ill patients. Crit Care Med 2011; 39:1913-1921.
Morris M, Davey FR, Henry JB. Basic examination of blood. In diagnosis and management by laboratory methods
. 20th ed. Philadelphia: WB Saunders Company; 2001.
Demir A, Yarali N, Fisgin T, Duru F, Kara A. Most reliable indices in differentiation between thalassemia trait and iron deficiency anemia. Pediatr Int 2002; 44:612-616.
Felker GM, Allen LA, Pocock SJ, Shaw LK, McMurray JJ, Pfeffer MA, et al.
Red cell distribution width as a novel prognostic marker in heart failure: data from the CHARM Program and the Duke Databank. J Am Coll Cardiol 2007; 50:40-47.
Ani C, Ovbiagele B. Elevated red blood cell distribution width predicts mortality in persons with known stroke. J Neurol Sci 2009; 277:103-108.
Hampole CV, Mehrotra AK, Thenappan T, Gomberg-Maitland M, Shah SJ. Usefulness of red cell distribution width as a prognostic marker in pulmonary hypertension. Am J Cardiol 2009; 104:868-872.
Pascual-Figal DA, Bonaque JC, Redondo B, Caro C, Manzano-Fernandez S, Sánchez-Mas J, et al
. Red blood cell distribution width predicts long-term outcome regardless of anaemia status in acute heart failure patients. Eur J Heart Fail 2009; 11:840-6.
Sangoi MB, Da Silva SH, da Silva JE, Moresco RN. Relation between red blood cell distribution width and mortality after acute myocardial infarction. Int J Cardiol 2011; 146:278-280.
Ye Z, Smith C, Kullo IJ. Usefulness of red cell distribution width to predict mortality in patients with peripheral artery disease. Am J Cardiol 2011; 107:1241-1245.
Wang F, Pan W, Pan S, Ge J, Wang S, Chen M. Red cell distribution width as a novel predictor of mortality in ICU patients. Ann Med 2011; 43:40-46.
Hunziker S, Celi LA, Lee J, Howell MD. Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients. Crit Care 2012; 16:R89.
Oh HJ, Park JT, Kim JK, Yoo DE, Kim SJ, Han SH, et al.
Red blood cell distribution width is an independent predictor of mortality in acute kidney injury patients treated with continuous renal replacement therapy. Nephrol Dial Transplant 2012; 27:589-594.
Förhécz Z, Gombos T, Borgulya G, Pozsonyi Z, Prohászka Z, Jánoskuti L. Red cell distribution width in heart failure: prediction of clinical events and relationship with markers of ineffective erythropoiesis, inflammation, renal function, and nutritional state. Am Heart J 2009; 158:659-666.
Poraicu D, Sandor S, Menessy Y. Decrease of red blood cell filterability seen in intensive care. Red blood cell cremation «in vivo» as morphological evidence of increased red blood viscosity in low flow states. Resuscitation 1983; 10:305-316.
Aliberti G, Proietta M, Pulignano I, Di Giovanni C, Tritapepe L, Vercillo G. Respiratory changes in human red cells. Clin Lab Haematol 2001; 23:361-363.
Betticher DC, Keller H, Maly FE, Reinhart WH. The effect of endotoxin and tumour necrosis factor on erythrocyte and leucocyte deformability in vitro. Br J Haematol 1993; 83:130-137.
Pösch JMB, Ruef P, Schnauffer M. The effect of different Escherichia coli endotoxins on red blood deformability. Clin Hemorheol 1995; 15:749-753.
Pöschl JM, Leray C, Ruef P, Cazenave JP, Linderkamp O. Endotoxin binding to erythrocyte membrane and erythrocyte deformability in human sepsis and in vitro. Crit Care Med 2003; 31:924-928.
Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, et al.
Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock, 2012. Intensive Care Med 2013; 39:165-228.
Daly LE, Bourke GJ, Bourke GJ. Interpretation and uses of medical statistics
. 5th ed. Oxford; Malden, MA: Blackwell Science; 2000. xiii, 568
Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med 2003; 348: 1546-1554.
Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 2001; 29:1303-1310.
Flaatten H. Epidemiology of sepsis in Norway in 1999. Crit Care 2004; 8:R180-R184.
Van Gestel A, Bakker J, Veraart CP, van Hout BA. Prevalence and incidence of severe sepsis in Dutch intensive care units. Crit Care 2004; 8:R153-R162.
Brun-Buisson C, Doyon F, Carlet J, Dellamonica P, Gouin F, Lepoutre A, et al.
Incidence, risk factors, and outcome of severe sepsis and septic shock in adults. A multicenter prospective study in intensive care units. French ICU Group for Severe Sepsis. JAMA 1995; 274:968-974.
Finfer S, Bellomo R, Lipman J, French C, Dobb G, Myburgh J. Adult-population incidence of severe sepsis in Australian and New Zealand intensive care units. Intensive Care Med 2004; 30:589-596.
Karlsson S, Heikkinen M, Pettilä V, Alila S, Väisänen S, Pulkki K, et al.
Predictive value of procalcitonin decrease in patients with severe sepsis: a prospective observational study. Crit Care 2010; 14:R205.
Luzzani A, Polati E, Dorizzi R, Rungatscher A, Pavan R, Merlini A. Comparison of procalcitonin and C-reactive protein as markers of sepsis. Crit Care Med 2003; 31:1737-1741.
Jain S, Sinha S, Sharma SK, Samantaray JC, Aggrawal P, Vikram NK, et al.
Procalcitonin as a prognostic marker for sepsis: a prospective observational study. BMC Res Notes 2014; 7:458.
Devran O, Karakurt Z, Adýgüzel N, Güngör G, Moçin OY, Balcý MK, et al.
C-reactive protein as a predictor of mortality in patients affected with severe sepsis in intensive care unit. Multidiscip Respir Med 2012; 7:47.
Lorente L, Martín MM, Abreu-González P, Solé-Violán J, Ferreres J, Labarta L, et al.
Red blood cell distribution width during the first week is associated with severity and mortality in septic patients. PLoS One 2014; 9:e105436.
Esper RC, Domingues VC, Cordova LD, et al
. Red C ell Distribution Width Changes in septic patients Rev Asoc Mex Med Crit Y Ter Int 2008; 22:20-25.
Sadaka F, O′Brien J, Prakash S. Red cell distribution width and outcome in patients with septic shock. J Intensive Care Med 2013; 28:307-313.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]