Journal of eISSN: 2373-6437 JACCOA

Anesthesia & Critical Care: Open Access
Research Article
Volume 8 Issue 1 - 2017
Can Blood Groups, Neutrophil-Lymphocyte Ratio and Mean Platelet Volume Predict Mortality in Critically Ill Patients Developing Acute Kidney Injury?
Ebru Canakci1*, Ahmet Karatas2 and Yasemin Kaya3
1Ordu University, School of Medicine, Department of Anesthesia and Reanimation, Ordu, Turkey
2Ordu University, School of Medicine, Department of Internal Medicine, Nephrology Branch, Ordu, Turkey
3Ordu University, School of Medicine, Department of Internal Medicine, Ordu, Turkey
Received: May 08, 2017 | Published: May 17, 2017
*Corresponding author: Ebru Canakci, Ordu University School of Medicine Department of Anesthesia and Reanimation, Turkey, Email:
Citation: Canakci E, Karatas A, Kaya Y (2017) Can Blood Groups, Neutrophil-Lymphocyte Ratio and Mean Platelet Volume Predict Mortality in Critically Ill Patients Developing Acute Kidney Injury? J Anesth Crit Care Open Access 8(1): 00290. DOI: 10.15406/jaccoa.2017.08.00290

Abstract

Introduction and Aim: Acute kidney injury (AKI) in the recent years, is one of the main causes of morbidity and mortality in critically ill patients. Neutrophil lymphocyte ratio (NLR) is a novel and practical indicator of inflammation, and its effectiveness has been demonstrated in many diseases.

Material and Method: We retrospectively reviewed the medical records of totally 300 patients diagnosed with AKI, admitted to our intensive care unit between January 2010 and December 2017. As laboratory parameters, blood urea nitrogen (BUN) and creatinine levels, and glomerular filtration rate (GFR) as calculated according to MDRD formula were assessed both on the first day (BUN1, Cre1, GFR1) and last day (BUN2, Cre2, GFR2) of admission. C-reactive protein (CRP) level, white blood cell (WBC) count, neutrophil, lymphocyte and platelet values, mean platelet volume (MPV) and neutrophil lymphocyte ratio (NLR) were recorded.

Results: There was no association of blood groups with mortality or with other laboratory parameters (respectively p=0.986, p=0.456, p=0.872 all values not significance p>0,05). There was no statistically significant relationship of MPV value with mortality (p=0,314). Statistically, NLR showed very strong association with both mortality and AKI development (respectively p<0.0001, p<0.0001). There was also very strong association between mortality and other laboratory parameters (BUN1, BUN2, GFR1, GFR2, WBC, Platelet, NLR; all p<0.0001).

Conclusion: MPV and blood groups are not predictors of mortality in critically ill patients. The change in NLR can be an important follow-up parameter to predict survival of critically ill patients. As NLR increases, so does the rate of intensive care mortality and AKI risk.

Keywords: Acute kidney injury; Neutrophil-lymphocyte ratio; Mean platelet volume; Blood group; Mortality

Introduction and Aim

Acute renal failure (ARF) is described as deterioration of renal functions where elimination of nitrogen waste products (urea) is restrained and body's fluid-electrolyte balance is impaired as a result of sudden decrease in glomerular filtration rate within hours to days. Since there is no complete biochemical definition of ARF, more than 35 definitions have been proposed so far. ARF is a conventional term that is frequently used for patients admitted to intensive care unit due to acute dialysis requirement. However, evidence shows that even a minimal decline in renal function has profound effect on mortality and morbidity [1,2]. For this reason, the term ARF has been replaced by the term "acute kidney injury" (AKI) that was proposed by Acute Kidney Injury Network [3]. Despite all the advanced life-support systems and treatment options, AKI is still an important cause of mortality and morbidity for patients monitored in intensive care units (ICU). Epidemiological data regarding AKI varies greatly in the literature. While its prevalence varies between 1-31%, associated mortality rates are between 28-82% [4,5]. The reason for this wide range is the difference between the criteria used to diagnose AKI. The most frequent cause of AKI in patients admitted to ICU is sepsis and septic shock. AKI occurs in various degrees and is generally progressive, and it is often described as a syndrome due to these properties. Although it is potentially reversible, AKI is an important cause of chronic renal failure. AKI frequently accompanies other severe diseases, and causes significant increases in mortality and morbidity rates. The prevalence of AKI among patients monitored in ICU is 1-25%, and 5% of these patients require dialysis [6-8].

Systemic inflammatory response is associated with changes in white blood cell count in the peripheral blood, especially neutrophilia that is seen concurrent with relative lymphocytopenia [9]. Neutrophil lymphocyte ratio (NLR) is a practical, repeatable and inexpensive marker that can be used in assessment of systemic inflammation [10]. Mean platelet volume (MPV) is an indicator of platelet function and activation [11]. While children and young adults have higher MPV values, MPV does not vary between the sexes [12]. Increased MPV is an indicator of megakaryocytic enlargement occurring as a response to thrombopoietic stress. Large platelets can be defined as stress-platelets. MPV is increased when there is increased destruction of peripheral platelets, and is decreased when there is impairment of platelet production [13]. Since larger platelets are more reactive, MPV is regarded as an indicator of increased cardiovascular disease risk in the general population. Several studies have shown MPV as an indicator for atherosclerotic diseases [14]. In addition to atherosclerosis, platelet volume is also increased in the presence of atherosclerotic risk factors including hypertension, hyperlipidemia, diabetes mellitus, end-stage renal disease and obesity [14-16].

Blood groups were discovered in the 19th century, and they are kind of cellular identity that is determined by the antigenic structure present on the surface of red blood cells. The blood group system discovered by Landsteiner is the general blood group system that is known as the ABO blood groups. Another commonly used blood grouping system is known as the Rh system, and depends on the presence or absence of this antigenic structure. ABO and Rh blood group system is currently most commonly used grouping system used today. Nevertheless, many blood group systems have been developed in addition to the ABO and Rh system, and many studies have been conducted on this subject. Numerous studies from different fields have examined the importance of blood group systems in tissue and organ transplantations and the genetic basis of blood groups [17]. Regarding the diseases associated with mortality, early detection and diagnosis have utmost significance in terms of treatment success. Diseases that are considered as causes of mortality in especially the developed countries include cancers and cardiovascular diseases, which are thought to have a genetic background. The treatment of these diseases is quite cumbersome and expensive. Despite all the troubles and long treatment processes, it is not possible to completely cure these diseases. Nonetheless, as stated before, early diagnosis is very important regarding the course and treatment of these diseases. Considering all these reasons, it is important to investigate the relationship between some common diseases and the blood groups as they are very easily detectable genetical properties that are free from the influence of environmental factors [17,18].

In this retrospective study, we aimed to investigate the relationship between mortality and blood groups, neutrophil lymphocyte ratio (NLR) and mean platelet volume (MPV) in critically ill patients developed AKI, additionally to determine whether NLR and MPV have predictive value regarding AKI development.

Material and Methods

Following approval from Ordu University Clinical Studies Ethics Committee (Issue Nr:2016-14), medical records of 300 patients admitted to General Intensive Care Unit of Ordu University Training and Research Hospital and diagnosed with AKI were reviewed. Demographical properties (age, weight, height, sex) of all patients were recorded. Diagnosis at admission, accompanying comorbidities, whether mechanical ventilation was applied, whether the case was discharged or deceased, were noted for every case.As laboratory parameters, blood urea nitrogen (BUN) and creatinine levels, and glomerular filtration rate (GFR) as calculated according to MDRD formula were assessed both on the first day (BUN1, Cre1, GFR1) and last day (BUN2, Cre2, GFR2) of admission. C-Reactive Protein (CRP) level, white blood cell (WBC) count, neutrophil, lymphocyte and platelet values, mean platelet volume (MPV) and neutrophil lymphocyte ratio (NLR) were recorded. NLR values were categorized into three groups according to the percentage frequency among cases. Values between 0-40 were grouped as NLR 1, values between 41-60 were grouped as NLR 2, and values above 60 were grouped as NLR 3. Additionally blood groups (A, B, O, AB) and Rh factors (Rh⁺, Rh⁻) were noted for every case.

Statistical analysis

Normality assessment was made with Kolmogorov-Smirnov test, and homogeneity check of group variances was made with Levene test. Means of two independent groups were compared with t-test, whereas comparison of the means of three or more groups were made with one-way analysis of variance. Identification of the different groups was made with Tukey multiple comparison test with 5% significance level. Results of Tukey test were expressed in letters along with the descriptive statistics results. Calculations and interpretations were made at 5% significance level. All calculations were performed using SPSS v24 (IBM Inc., Chicago, IL, USA) statistics package software.

Results

Frequency distribution of patients according to examined parameters are presented in Table 1. One-way analysis of variance was performed in order to determine whether the studied parameters showed any difference according to blood groups. The results are presented in Table 2. As it is shown in Table 2, variance analysis for BUN 1 indicates there is no statistically significant difference between the blood groups (p>0.05). Similarly, there is no significant difference between the blood groups regarding other variables (p>0.05). Therefore, studied parameters did not show any difference according to the blood groups. It is concluded that blood groups are not predictors for AKI development. Studies with larger sample size are required to determine the effect of blood groups on AKI development. Student t-test was performed in order to determine whether the studied parameters showed any change according to sex, and the results are presented in Table 3.

Variables

Frequency

%

ABO Groups

0

56

18.4

A

187

61.5

B

36

11.8

AB

21

6.9

RH

Negative

89

29.3

Positive

211

69.4

Sex

Male

144

48

Female

156

52

Renal failure

AKI

135

44.4

Non-AKI

165

54.3

Mechanical ventilation

MV applied

142

47.3

MV not applied

158

52.7

Discharge state

Exitus

146

48.7

Discharged

154

51.3

Diagnosis

CVA

42

13.8

Pneumonia

36

11.8

Intoxication

26

8.6

CHF

36

11.8

Trauma

11

3.6

COPD

29

9.5

DM

30

9.9

Malignancy

33

10.9

Pulmonary edema

17

5.6

GIS hemorrhage

14

4.6

CAD

26

8.6

Age

Mean±Std.Dev.: 67.727±15.954

Table 1: Frequency table based on patients' demographic variables and examined parameters.

CVA: Cerebrovascular Accident; DM: Diabetes Mellitus; CAD: Coroner Artery Disease; CHF: Congestive Heart Failure; COPD: Chronic Obstructive Pulmonary Disease

Variables

0 (n=56)

A (n=187)

B (n=36)

AB (n=21)

P-Value

Mean

SD

Mean

SD

Mean

SD

Mean

SD

BUN1

42,786

23,593

43,255

25,753

44,000

28,354

45,095

29,665

0,986 NS

BUN 2

35,460

16,559

32,683

16,536

36,611

16,517

35,343

17,371

0,456 NS

Cre1

1,970

1,482

4,681

35,507

1,804

1,672

5,971

15,043

0,872 NS

Cre2

1,743

1,450

2,232

6,349

1,647

1,206

2,091

1,548

0,882 NS

GFR1

56,804

43,414

56,182

41,350

62,767

46,365

56,000

49,159

0,866 NS

GFR2

52,321

39,154

58,286

39,289

59,972

39,874

46,238

39,374

0,437 NS

CRP

7,518

5,916

7,397

5,990

8,161

6,437

7,760

6,715

0,917 NS

WBC

13,597

13,059

15,294

14,072

11,418

7,600

13,051

9,316

0,361 NS

Neutrofil

30,199

31,079

32,891

32,065

31,542

31,700

37,919

35,507

0,815 NS

Lymphosit

6,048

7,058

8,672

29,429

7,894

9,088

5,269

5,929

0,851 NS

Platelet

2,69,923

1,38,961

2,90,344

1,45,426

2,69,469

1,45,743

2,73,048

1,34,710

0,712 NS

MPV

8,131

1,924

12,197

49,404

8,252

2,813

9,034

2,723

0,875 NS

NLR

28,916

30,184

30,966

59,948

25,609

29,886

29,443

34,622

0,949 NS

Table 2: Descriptive statistics and ANOVA results for the variables according to ABO groups.

SD: Standard deviation; NS: Statistically not significant (p>0,05).

As it is shown in Table 3, mean BUN 1 level was slightly higher in females than in males; however, the difference was not statistically significant according to t-test (p>0.05). Mean BUN 2 level was significantly higher in females compared to males (p<0.05). Similarly, NLR was significantly higher in females compared to males (p<0.05). Similarly, other variables did not show significant difference between the blood groups (p>0.05). Therefore, blood group is not important factor for the variables examined in this study. Mean GFR 2 level was statistically higher in males compared to females (p<0.01). Other variables did not show statistically significant difference between the sexes (p>0.05). This can be explained by the relationship of creatinine level with the muscle mass in the body, and additionally because there was not so much difference between the initial and last creatinine measurement values as it is present in BUN level. In addition, although the GFR shows greater change during the initial stages of the renal function loss, the expected change in creatinine levels is smaller.

Variables

Male (n=144)

Female (n=156)

 

t-Value

P-Value

Mean

SD

Mean

SD

BUN 1

41,063

25,221

45,530

26,318

-1,499

0,135 NS

BUN 2

31,752

15,887

35,805

17,025

-2,127

0,034*

Cre 1

2,227

5,926

5,483

38,854

-0,995

0,321 NS

Cre 2

2,107

6,851

2,018

2,561

0,153

0,879 NS

GFR 1

62,097

42,498

52,440

42,606

1,964

0,051 NS

GFR 2

64,050

41,178

49,591

36,295

3,232

0,001**

CRP

7,086

6,211

7,953

5,900

-1,239

0,216 NS

WBC

12,949

12,966

15,653

12,932

-1,807

0,072 NS

Neutrofil

30,700

31,495

34,313

32,419

-0,978

0,329 NS

Lymphosit

8,989

22,213

6,801

25,010

0,799

0,425 NS

Platelet

2,78,489

1,39,449

2,86,811

1,46,891

-0,502

0,616 NS

MPV

13,154

56,217

8,518

3,702

1,028

0,305 NS

NLR

23,110

28,944

36,040

64,378

-2,212

0,028*

Table 3: Descriptive statistics and Student’s t-test results for the variables according to Sex.

SD: Standard deviation; NS: Statistically not significant (p>0,05); *: Statistically significant (p<0,05); **: Statistically significant (p<0,01).

In order to determine whether other parameters showed any change according to presence of AKI, Student t-test was applied, and the results are presented in Table 4. As shown in Table 4, mean levels of Cre1, Cre2, lymphocyte and MPV did not change depending on the presence of AKI (p>0.05). Student t-test results showed that mean levels of BUN1, BUN2, CRP, WBC, Neutrophil and NLR were significantly higher among patients with AKI, compared to the non-AKI group (p<0.001/p<0.05). In contrast, mean levels of GFR1, GFR2 and platelet were significantly higher in the non-AKI group compared to the AKI group (p<0.001). These statistical results are in perfect agreement with our clinical observations. We observed increased mortality risk in patiens with AKI. This can be explained by the relationship between creatinine level and body muscle mass, and because there was not so much difference between initial and last creatinine measurement values as compared to BUN levels. In addition, although the GFR shows greater change during the initial stages of the renal function loss, the expected change in creatinine levels is smaller. Furthermore, creatinine levels may be misleading in patients with sepsis. In order to determine whether the studied parameters showed any change according to discharge situation, Student t-test was applied, and the results are presented in Table 5. As shown in Table 5, mean levels of Cre1, Cre2, CRP, neutrophil, lymphocyte and MPV did not show change depending on the discharge states of patients (p>0.05). Student t-test results indicate that mean levels of BUN 1, BUN2, WBC and NLR were significantly higher among the deceased patients compared to the discharged patients (p<0.001/p<0.01). This statistical result is in perfect agreement with our clinical observations. Indeed, elevated levels of BUN 1, BUN 2, WBC and NLR values are commonly observed in patients who end up with mortality. Because, bacteremia can develop in many critically ill patients; and renal perfusion can deteriorate due to hypotension, BUN levels can increase. Furthermore, bacteremia causes neutrophilia and increased white blood cell count. This supports our hypothesis which states that increased NLR can predict mortality. By contrast, mean levels of GFR1, GFR2 and platelet were significantly higher in discharged patients compared to the deceased patients (p<0.001). Higher mean levels of GFR 1 and GFR 2 in discharged patients, and the statistically significant difference also supports our hypothesis that states NLR is a predictor of AKI. Platelet counts were higher in discharged patients, and lower in deceased patients, and the difference was statistically significant. This may be because thrombocytopenia is more frequent in critically ill patients, and especially in mortal cases. Thrombocytopenia with accompanying sepsis and thrombocytopenia due to polypharmacy, or thrombocytopenia due to heparin is frequently encountered in critically ill patients. This may be the reason why mean platelet count was significantly lower in deceased patients, and why mean platelet count was higher among discharged patients since the aforementioned clinical situations are rare in discharged patients.

Variables

AKI (n=142)

Non AKI (n=158)

t-Value

P-Value

Mean

SD

Mean

SD

BUN 1

59,901

26,899

28,542

12,426

13,175

0,000***

BUN 2

40,878

18,250

27,551

11,838

7,576

0,000***

Cre1

6,520

40,655

1,583

5,612

1,511

0,132 NS

Cre2

2,331

1,759

1,817

6,806

0,874

0,383 NS

GFR 1

30,645

29,579

80,829

38,681

-12,516

0,000***

GFR 2

35,720

28,385

75,236

38,434

-10,036

0,000***

CRP

8,303

5,462

6,848

6,485

2,090

0,038*

WBC

17,234

14,640

11,768

10,724

3,713

0,000***

Neutrophil

36,565

33,702

28,996

29,999

2,058

0,040*

Lymphosit

5,399

21,558

10,055

25,329

-1,705

0,089

Platelet

2,42,249

1,26,987

3,19,276

1,47,441

-4,822

0,000***

MPV

8,344

2,418

12,899

53,733

-1,009

0,314 NS

NLR

43,366

45,632

17,672

52,439

4,504

0,000***

Table 4: Descriptive statistics and Student’s t-test results for the variables according to AKI Groups.

SD: Standard deviation; NS: Statistically not significant (p>0,05); *: Statistically significant (p<0,05); ***: Statistically significant (p<0,001).

Variables

Ex (n=146)

Discharge (n=154)

t-Value

P-Value

Mean

SD

Mean

SD

BUN 1

58,932

27,227

28,647

12,417

12,501

0,000***

BUN 2

40,909

18,130

27,176

11,561

7,864

0,000***

Cre1

6,381

40,098

1,587

5,685

1,468

0,143 NS

Cre2

2,346

1,759

1,791

6,887

0,945

0,345 NS

GFR1

31,641

30,498

81,188

38,583

-12,296

0,000***

GFR2

35,460

28,701

76,508

37,624

-10,583

0,000***

CRP

8,065

5,499

7,036

6,520

1,474

0,142 NS

WBC

16,995

14,510

11,852

10,847

3,489

0,001**

Neutrofil

36,261

33,723

29,088

29,921

1,951

0,052 NS

Lenfosit

5,446

21,286

10,131

25,633

-1,717

0,087 NS

Platelet

2,42,269

1,26,500

3,21,258

1,47,806

-4,961

0,000***

MPV

8,357

2,391

13,005

54,426

-1,031

0,303 NS

NLR

42,926

45,428

17,422

52,811

4,473

0,000***

Table 5: Descriptive statistics and Student’s t-test results for variables according to Discharge situation.

SD: Standard deviation; NS: Statistically not significant (p>0,05); *: Statistically significant (p<0,05); ***: Statistically significant (p<0,001).

In order to determine whether the studied parameters showed change according to NLR groups, one-way analysis of variance was applied, and results are presented in Table 6. NLR values were categorized. Values between 0-40 were grouped as NLR1, values between 41-60 were grouped as NLR2, and values above 60 were grouped as NLR3. As it is seen from Table 6, results of variance analysis indicate that the difference between NLR groups were statistically significant for lymphocyte and MPV variables (p>0.05). Other variables did not show significant difference between the NLR groups (p<0.01/p<0.001). In order to determine the different groups, Tukey test was applied, and the results are expressed with letters along with the means. The fact that the studied parameters showed statistically significant difference between the NLR groups proves that NLR is a predictor of AKI and mortality in critically ill patients. The fact that GFR, BUN and Cre results became significant as NLR increased emphasizes the predictive strength of NLR in AKI patients. Mortality rate is increased as the NLR is increased. Our results prove that MPV is not a predictor of mortality in critically ill patients.

Variables

NLR 1 (n=223)

NLR 2 (n=33)

NLR 3 (n=44)

P-Value

Low (0-40)

Moderate (41-60)

High (61 above)

Mean

SD

Mean

SD

Mean

SD

BUN 1

38,106B

23,957

59,909A

19,338

57,750A

28,988

0,000***

BUN 2

31,388B

15,389

32,955B

16,294

47,064A

16,786

0,000***

Cre1

1,987B

4,875

18,897 A

84,046

2,484B

1,980

0,000***

Cre2

1,538B

2,148

2,641AB

2,433

4,275A

12,033

0,000***

GFR1

67,422A

43,596

16,685B

12,292

34,932B

21,869

0,005**

GFR2

64,665A

41,094

41,642B

22,852

26,477B

14,373

0,004**

CRP

7,081B

6,241

12,242A

4,747

6,318B

4,197

0,000***

WBC

11,359C

8,008

27,575A

14,234

19,624B

21,995

0,000***

Neutrofil

24,939B

26,770

54,773A

35,353

54,653A

36,067

0,000***

Lymphocyt

7,956

21,680

10,552

43,852

5,293

5,816

0,625 NS

Platelet

301,747A

1,39,976

242,201AB

1,04,820

217,336B

1,60,387

0,000***

MPV

11,641A

45,193

8,54B5

2,686

7,840B

5,536

0,793 NS

NLR

10,247C

10,243

58,825B

6,811

107,362A

93,033

0,000***

Table 6: Descriptive statistics and ANOVA results for the variables according to NLR groups.

SD: Standard deviation; NS: Statistically not significant (p>0,05); *: Statistically significant (p<0,05); ***: Statistically significant (p<0,001).
Means that do not share a letter are significantly different (P<0,05)

Discussion

Acute kidney injury (AKI) is a clinical syndrome in which there is often reversible reduction of GFR accompanied by accumulation of nitrogen metabolites such as urea and creatinine, fluid and electrolyte imbalances, and disorders of acid base metabolism. It is gaining increasing importance due to the high prevalence in critically ill patients and its close association with mortality [19]. Many different factors may play role in the etiology of AKI. One of the leading cause of AKI observed in critically ill patients is sepsis. In one study by Palmar et al. [20], the prevalence of AKI was reported as 19% in sepsis, 23% in severe sepsis, and 51% in septic shock [20]. In another epidemiological study involving patients diagnosed with AKI, Wang et al. found that more than 50% of the patients had accompanying sepsis or septic shock. In our study, 60% of the patients with AKI had septic shock [21]. High NLR, CRP and WBC levels in our cases suggest presence of bacteremia and sepsis in majority of our cases. According to our clinical observations, most of the cases diagnosed with AKI have accompanying bacteremia or sepsis. Our results are in agreement with the literature data. Presence of AKI significantly increases the risk of mortality in intensive care, and mortality rate is increased up to 90% in case renal replacement therapy is required [22]. In one study including 211 patients with sepsis, Peng et al. found significantly increased 28-day mortality rate in the AKI group [23]. In the present study, the comparison of patients with and without AKI showed higher mortality rate in patients with AKI. This result is consistent with the literature data. Studies that examined AKI development during ICU stay have found that RIFLE and AKIN had significant effects on in-hospital survival; and no difference was found between the two classifications with regard to their ability to predict survival [24], Park et al. [25] evaluated AKI development in ICU patients based on RIFLE classification alone, and they found significant effect of RIFLE on hospital survival [25]. In the present study, we also used RIFLE classification for diagnosing AKI.

Whether there is an association between blood groups and various diseases, or in other words, whether some blood groups are associated with higher risk for some diseases has been investigated by many researchers [26,27]. In literature, its associations with some infectious diseases, some cancer types and especially cardiovascular diseases have been investigated. Kaya et al. found lower risk of coronary artery disease in individuals with blood group O, whereas this risk was found to be higher with A, B and AB blood groups [27]. In the present study, we did not find association of blood groups with mortality or AKI. Additionally, the present study is to first study to examine the relationship of blood groups with mortality and AKI. Considering that the present study included a sample size of 300 patients and data collected over 7 years, it is obvious that studies with even larger sample size, and longer study period are needed to demonstrate any possible association with blood groups.

In our review of literature, we encountered many studies examining whether NLR is a predictor of various diseases. A great number of these studies are related with the association with coronary artery disease. One study from Michigan University, USA, evaluated NLR values measured at the time of admission and all-cause mortality at 6th month in 2833 patients diagnosed with acute coronary syndrome (ACS) (564 ACS with ST-segment elevation, 2269 ACS with unstable angina pectoris/ non-ST-segment elevation); and similar to our results, NLR was found as an effective predictor of mortality. That study had the largest sample size in related literature [28]. One study that evaluated NLR values measured at the time of presentation and in-hospital and all-cause 30th day mortality found that NLR was an effective parameter in only Type 2 diabetes [29]. Studies investigating the association with mortality evaluated in-hospital, post-discharge, 30th day and 6th month mortality rates [28,29]. The study by Azab et al. from Staten University (Staten Island, New York, USA) had the longest follow-up period [30]. This study evaluated NLR values at presentation and mean NLR values (average NLR value calculated from 3 different differential white blood cell count on different days) in 619 ACS patients with unstable angina pectoris/ non-ST segment elevation, and 4th year mortality rates from USA Social Security Mortality Index records [28,29]. Our study had a retrospective design, and a comparison regarding follow-up time cannot be made. However, our results in terms of the association between NLR and mortality are in agreement with the literature data.

There are few studies that examined the relationship between AKI and NLR. Considering this fact, our study is among the first few studies related with AKI and NLR. Besides this good situation, but unfortunately there are some limitations of our study. It is primarily a retrospective file review, so we can not predict the degree of correlation with clinical outcomes. We could grade kidney injury according to the RIFLE or KDIGO guide. We still believe that the results are in accordance with the literature. In one study involving patients diagnosed with AKI and severe sepsis, Yılmaz et al. [31] reported that NLR is a predictor with higher sensitivity and specificity compared to CRP or WBC [31]. Their study was a 3-year retrospective study including 118 critically ill patients, whereas our study is 7-year retrospective study including 300 patients. In comparison to the study by Yılmaz et al., larger sample size and longer study period bestow more strength to the present study. Analyzed laboratory parameters, demographic variables and accompanying comorbidities show great similarity between the studies. On the other hand, one superior side of the study by Yılmaz et al. is that they included APACHE II and SOFA scores of the patients in the analysis. Since the ICU in our hospital is categorized as grade II ICU, we could not obtain APACHE II and SOFA scores of all our patients, therefore these scores were not included in analysis. Because Yılmaz et al. used these intensive care scoring systems, their study is superior in this regard [31]. In one study involving hemodialysis patients, Neuen et al. [31] stated that NLR was a simple and inexpensive predictor of mortality. They followed up 170 hemodialysis patients for 3 weeks, and they found NLR could predict all-cause mortality, and particularly mortality due to cardiovascular reasons. Additionally, they found positive correlation between increased CRP and increased NLR levels [32]. The study results of Neuen et al. [32] are in complete agreement with our results. In our study, we also found significant results for CRP, platelet, WBC and neutrophil values in addition to NLR when cases with AKI were compared to the non-AKI group [32]. In their letter to editor, Balta et al. criticized some aspects of the study by Yılmaz et al. Balta et al. stated that NLR could not be a predictor in cases with AKI, because NLR can be affected by many factors including the methods used for phlebotomy, and NLR could be lower in patients receiving statin treatment and antihypertensive treatment (valsartan, nebivolol, amlodipin), and they stated that the results reported by Yılmaz et al. [31] were not reliable, and that these results should be supported with other serum inflammation markers [33]. In our opinion, the critical reviews put forward by Balta et al. are not justifiable. Yılmaz et al. could achieve a homogenous sample, and included critically ill patients with concurrent severe sepsis and AKI. These cases with severe sepsis do not receive antihypertensive medications, instead, they are hypotensive patients that require positive inotropic support. Moreover, the authors even detected the origin of infection in cases diagnosed with severe sepsis. Additionally, Yılmaz et al. [31] categorized NLR values, and NLR values were found in a close range. For this reason, we think the criticisms by Balta et al. have no ground. Our study is the third study to evaluate the association between NLR and AKI, coming after the studies by Yılmaz et al. [31] and Neuen et al. [32], and our results are in complete agreement with their results.

Güldiken et al. [34] compared MPV values and other peripheral blood cell counts in cases with acute ischemic stroke, and they reported that although MPV did not show significant change in acute ischemic stroke, increased leukocyte and neutrophil counts were good indicators of major vessel disease subtype and stroke severity. In our study, we did not find association between MPV values and AKI or mortality [34]. In one study, Karagöz et al. [35] categorized critically ill patients in two groups as deceased and discharged patients, and they examined the associations of hemogram parameters and especially MPV with mortality. They found strong association between increased MPV values and mortality [35]. Their results are not in agreement with our results. In our study, when we compared discharged and deceased cases, we found statistically significant results for platelet, NLR, GFR and BUN levels, whereas we did not find significant association between MPV and mortality. The study by Karagöz et al. [34] is a retrospective study including critically ill patients, and they did not conduct their study on a specific disease group. The reason why we had different results may be related to the fact that we included cases with a specific disease. In one study, Farah and Samra [36] compared NLR and MPV values between cases diagnosed with ischemic stroke and 30 healthy volunteers, and they found higher NLR values in cases with ischemic stroke compared to healthy volunteers, whereas they did not find difference in MPV values. Farah and Samra [36] proposed that NLR was a good predictor for stroke and prognosis of stroke, while MPV was not [36]. Their results are in complete agreement with our results. We also found that while NLR was a good predictor for mortality, MPV did not have a predicting value. In their study, Liu et al. investigated the association between MPV and mortality in cases with acute myocardial infarction. In that retrospective study including 567 cases, they concluded that MPV was a predictor for mortality. Their results are in contrast with our results. This may be because they had a larger sample size and included a different patient group [37]. In another study, Yilmaz G et al. [38] compared NLR and MPV values and their relationship with proteinuria level between cases with chronic renal failure (CRF) and healthy volunteers. While there was statistically strong correlation between NLR level and proteinuria level in cases with CRF, there was no correlation between MPV and proteinuria levels [38]. These results are in agreement with our results. Our results are consistent with literature data. There are few studies examining the association between MPV and intensive care mortality, therefore our study is among the first studies on this subject.

Conclusion

In conclusion, considering the literature knowledge and our study results, it can be stated that MPV and blood groups are not predictors for AKI or mortality in critically ill patients, whereas NLR appears to be a strong predictor of AKI and mortality in critically ill patients. It should be emphasized that the NLR ratio should be calculated for each hospitalized ICU patient and if the ratio is high, it is likely that kidney injury may develop and measures should be taken accordingly. We believe that NLR ratio should be included in follow-up and treatment of intensive care patients.

Acknowledgement

We wish to thank Assist. Prof. Dr. YelizKasko Arıcı (Ph.D) for helping us with the statistical analyses of the present study.

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