A Study on Correlation between Red Cell Distribution Width to Platelet Ratio (RPR) and Child Turcotte Pugh Score in Patients of Chronic Liver Disease at Tertiary Care Center of Jharkhand

Abstract

Background:

It was hypothesized that high red cell distribution width (RDW) due to anemia and the low platelet count due to cirrhosis studies impacts the RDW to platelet ratio (RPR), which can be used as a predictor of significant fibrosis and cirrhosis. For evaluation of the severity of liver disease Child–Turcotte–Pugh (CTP) score is universally used.

Aims:

To determine the correlation between RPR with CTP severity score in patients of chronic liver disease (CLD), and to evaluate the severity of CLD indirectly with RPR.

Methods:

This is a cross-sectional study of 100 patients diagnosed with CLD, conducted in RIMS Ranchi between February 2021 and July 2022. The categorical data were evaluated by the test of proportion, Chi-square, Fisher’s exact test as appropriate. The correlation between RPR and CTP total score and class was analyzed using Pearson correlation in SPSS version 22.

Results:

The mean RDW-coefficient of variation (measurement of red blood cell volume width deviation), referred to as volume curve width for the study population, was 17.1 ± 3.2, while the median and mode were 16.4. The range is between 12.4 and 30.7. The mean platelet value for the study population was 93,522/μl ± 38,756, while the median was 86,000. Univariate Regression Analysis: RPR with a P = 0.001, β = 7.869, t = 4.729, and r² = 0.186 depicts that the model explains 18.6% of the variance in the total CTP score.

Conclusion:

RPR holds the potential for evolving as a novel noninvasive marker for assessing the severity of CLD.

INTRODUCTION

Chronic liver disease (CLD) is a gradual decline in the function of the liver for more than 6 months. The important functions of the liver include the synthesis of proteins like albumin and clotting factors, detoxification of toxic by-products of metabolism, and excretion of bile.[1] Histological examination of liver tissue should be done after the liver biopsy to assess the extent of fibrosis, and accordingly, the choice to start and monitor treatment effects should be taken.[2] This histological examination of the liver tissue following liver biopsy is the reference standard test for estimating the histological stage of fibrosis. Following cirrhosis of the liver risk of hospitalization is from 1% to 5%, the risk of severe complications is 0.57% and mortality is from 0.009% to 0.12%.[3,4,5] Considering the high cost and the potentially serious problems associated with liver biopsy, it is difficult to go through this test procedure repeatedly for monitoring the process of liver cirrhosis.[6] Moreover, the sampling error and observer variability may be responsible for the altered diagnostic accuracy of liver biopsy.[7] Hence, different noninvasive tests like detecting liver stiffness with shear wave-based elastography methods, including transient elastography, point shear wave elastography, and two-dimensional shear wave elastography, have emerged as alternative noninvasive tests to detect liver cirrhosis.[8] That is why different noninvasive and cheaper laboratory tests were evolved to predict liver cirrhosis.[9,10,11] Red cell distribution width (RDW) is an automated measure of the heterogeneity of red blood cell (RBC) sizes (e.g. anisocytosis) and is routinely performed as part of a complete blood cell counts. Flawed iron mobilization, stress due to inflammation, and many other aspects cause an increase in RDW. Ferritin governs the pro-inflammatory cytokines in hepatic cirrhosis. An increase in RDW occurs after the escalation in the heterogeneity of RBC maturation and further damage mediated by the cytokine. RDW has recently become a point of attention as a marker to prognosticate several conditions such as heart failure, acute myocardial infarction, strokes, sepsis, renal failure, autoimmune diseases, liver diseases, and malignancies. The deviation of the RBC volume width (RDW-coefficient of variation [RDW-CV]) indicates the width of the volume curve. RDW-CV assessment is derived from one standard deviation of RBC volume divided by mean corpuscular volume (MCV) and multiplied by 100. Hence, it is affected by RBC size. RDW-standard deviation (RDW-SD) is the assessment of the width of the RBC size distribution represented in the form of histogram and measured in femtoliters (fL) at the 20% height level, so it is not changed by RBC size (reference range: RDW-SD: 39–46 FL; RDW-CV: 11.6%–14.6%). Platelet count is decreased in liver diseases mainly due to splenomegaly and sequestration of platelets. Deficient production of thrombopoietin in liver disease also contributes to low platelet count. Platelet count is a self-reliant prophesier of liver cirrhosis and thus, has been included in some nonalcoholic fatty liver disease. Further exploration about RPR in patients of liver disease, appropriateness, and precision of RPR for ascertaining stages of liver cirrhosis remains disputable. Meta-analysis was performed to analyze the evidence on the diagnosis of RPR for the prediction of staging liver cirrhosis.[12] The Child–Pugh scoring system (also known as the Child Turcotte Pugh score) was intended to anticipate mortality in cirrhosis patients.[13] It was formulated by Child and Turcotte in the year 1964; it was categorized into three groups: A – Good hepatic function, B – Moderately impaired hepatic function, C – Advanced hepatic dysfunction. Originally, it had five laboratory and clinical criteria including serum bilirubin, serum albumin, ascites, neurological disorder, and clinical nutritional status. It was again modified by Pugh in which prothrombin time was substituted for clinical nutrition status. Due to its simple, cost-effective, easy, and precise to prognosticate in cirrhosis, the association between RPR and the level of severity with respect to the Child Turcotte Pugh score in patients of CLD can be reliably determined. Hence, our present study is to determine the correlation between RDW to platelet ratio with Child–Turcotte–Pugh severity score in patients of CLD, and to evaluate the severity of CLD indirectly with RPR.

METHODS

Study design and setting

This was a cross-sectional analytical study approved by the Institutional Ethical Committee vide memo no: 390 dated November 17, 2021. Data were collected between February 2021 and July 2022 from patients with CLD (alcoholic liver disease, chronic hepatitis B, chronic hepatitis C, autoimmune hepatitis, Wilson’s disease, and cryptogenic cirrhosis) in the Department of Internal Medicine at Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.

Sample size

The global prevalence of cirrhosis from autopsy studies ranges from 4.5% to 9.5% of the general population.[14,15,16] The mid value of the range, that is, 7% was taken as the prevalence or P for the study. The sample size for infinite population n = z².p. (1 - p)/E², where n = Sample size for infinite population, z = Z score = 1.96, P = Population proportion = 0.07 (7%), E = Margin of error = 0.05 (5%), n = 101, was used for sample size determination and which was rounded off to 100 sample size.

Study population

Inclusion criteria

Patients gave written consent for the study. Age more than 18 years, a symptomatic liver disease for more than 6 months, radiologically confirmed CLD (alcoholic liver disease, chronic hepatitis B, chronic hepatitis C, autoimmune hepatitis, Wilson’s disease, cryptogenic cirrhosis) patients, and history of prior underlying insult resulting in chronicity.

Exclusion criteria

Participants who failed to give consent, children, and the adolescent age group (<18 years of age), pregnant females, malignancy, on any immunosuppressive agents, anemia due to nutritional deficiencies/hemolysis, cardiovascular disease, renal failure, stroke, and participants on medication that blunts red cell production or extermination.

Operational definitions

The diagnosis of CLD (alcoholic liver disease, chronic hepatitis B, chronic hepatitis C, autoimmune hepatitis, Wilson’s disease, cryptogenic cirrhosis) was made after thorough history taking, clinical examination, and biochemical and radiological evidence of CLD in ultrasonography or computed tomography scan of the whole abdomen with the presence of esophageal varices or portal hypertension gastritis in esophagogastroduodenoscopy.

The blood sample was drawn within 24 h of admission in the hospital and sent for a complete blood count, for which the sample was mixed thoroughly on a blood roller mixer and then analyzed via Sysmex XT 2000i, that uses fluorescence flow cytometry technology for hematological assessment of the blood sample. Prothrombin time/International normalized ratio (INR) was assessed by Hemostar XF 2.0-2 channel optomechanical measuring system. Liver function test (including serum albumin) and renal function test were measured by ARCHITECT i1000SR based on the chemiflex method.

Subsequently, their RDW and platelet count were noted and placed in the following formula to calculate RPR: RPR = RDW/PLT (10⁹/L) 10². RDW × 100/PLT (10⁹/L).

The Child–Pugh score for each of the patients was calculated after the arrival of their reports, considering the ascites and hepatic encephalopathy status on the day of admission before undertaking any interventions. Thus, the RPR and Child–Pugh score were noted for each patient and analyzed following the completion of the targeted sample size collection.

Analysis plan

All the findings were noted in a Microsoft Excel sheet, and statistical analysis was accomplished using the SPSS software 22.0 package (SPSS Inc., Chicago, USA). The categorical data were evaluated by the test of proportion, Chi-square, Fisher’s exact test as appropriate. The correlation between RPR and CTP total score and class was analyzed using Pearson correlation in SPSS. This was followed by univariate regression analysis of various independent factors in the study for the dependent factor of total CTP Score. The factor with a confidence interval of 95% and P < 0.05 was treated as statistically significant.

Human participant’s protection

This work was done following the ethical principles for medical research involving human subjects outlined in the Declaration of Helsinki.

RESULTS

A total of 120 patients diagnosed with CLD, who gave informed consent, were screened for the study, out of which 13 patients met the exclusion criteria, while 7 had incomplete data. Thus, finally, a total of 100 participants were included, out of which − 16 (16%) participants belonged to Child–Pugh class B while 84 (84%) belonged to class C. There were no patients in class A.

Sociodemographic profile

The mean age of the study population was 44.92 ± 11.162 years. Out of the 100 patients, 14 were females and the rest 86 were males.

Cause of chronic liver disease in the study population

The distribution of CLD in this study is as follows: alcoholic liver disease – 73, chronic hepatitis B – 4, chronic hepatitis C – 3, autoimmune hepatitis – 3, Wilson’s disease – 1, cryptogenic cirrhosis – 16, total 100.

Red cell distribution width to platelet ratio (RPR)

The mean RDW-CV for the study population was 17.1 ± 3.2, while the median and mode were 16.4. The range is between 12.4 and 30.7. The mean platelet count value for the study population was 93,522/μl ± 38,756.5, while the median was 86,000. The range is between 27,000 and 292,000. The mean RPR of the study population was 0.21.

Correlation of RPR with individual parameters of Child–Turcotte–Pugh score

The correlation between RPR and total bilirubin was assessed by Pearson Correlation, which revealed a statistically insignificant positive correlation of r = 0.041, with a P = 0.687. The Pearson Correlation demonstrated a statistically negative correlation between RPR and serum albumin of r = 0.191, with a P = 0.05. The Pearson Correlation between RPR and INR revealed a statistically significant positive correlation of r = 0.312 with a P = 0.002 [Figure 1]. The Pearson Correlation shows a statistically significant positive correlation between RPR and ascites severity score of r = 0.217, with a P = 0.03 [Figure 2]. The Pearson Correlation revealed a statistically significant positive correlation between RPR and hepatic encephalopathy of r = 0.351, with a P = 0.001 [Figure 3]. The Pearson Correlation showed a statistically significant positive correlation between RPR and total CTP score of r = 0.431, with a P < 0.001 [Figure 4]. The Pearson Correlation analysis between RPR and CTP class revealed a statistically significant positive correlation of r = 0.323, with a P = 0.001 [Figure 5 and Table 1].

Figure 1.

Scatter plot showing the correlation between RPR and international normalized ratio. RPR = Red cell distribution width to platelet ratio, INR = International normalized ratio

Figure 2.

Scatter plot showing the correlation between RPR and ascites severity score. RPR = Red cell distribution width to platelet ratio

Figure 3.

Scatter plot showing the correlation between RPR and hepatic encephalopathy score. RPR = Red cell distribution width to platelet ratio

Figure 4.

Scatter plot showing the correlation between RPR and total CTP score. RPR = Red cell distribution width to platelet ratio, CTP = Child Pugh Turcotte score

Figure 5.

RPR = Red cell distribution width to platelet ratio, CTP = Child Pugh Turcotte score

Table 1.

Correlation of red cell distribution width to platelet ratio with individual parameters of Child-Turcotte-Pugh score

Parameter	Pearson correlation	Sig. (2 tailed)	n
RPR	1		100
Total bilirubin	0.041	0.687	100
Serum albumin	-0.191	0.057	100
INR	0.312**	0.002	100
ASCITIS score	0.217*	0.03	100
Hepatic encephalopathy	0.351**	0.000	100
Total CTP score	0.431**	0.000	100
CTP class	0.323**	0.001	100

RPR = Red cell distribution width to platelet ratio, INR = International Normalized Ratio, CTP Class = Child–Turcotte–Pugh Score, n = Number

Univariate regression analysis

Summary of univariate analysis of each of the independent factors

In this regression analysis with each of the factors, RPR and creatinine were found to have a statistically significant positive impact on the total CTP score. RPR with a P = 0.000, β = 7.869, t = 4.729, and r² = 0.186 depicts that the model explains 18.6% of the variance in the total CTP score. Creatinine with a P = 0.012, β =0.299, t = 2.566, and r² = 0.063 depicts that the model explains 6.3% of the variance in total CTP score [Table 2].

Table 2.

Univariate regression analysis

Independent factor	Standardized co-efficients		Standardized co-efficients	R 2	F	t	P
	B	Std. Error	Beta
AGE	-0.008	0.17	-0.049	0.002	0.233	-0.483	0.630
SEX	0.156	0.556	0.028	0.001	0.079	0.281	0.780
RPR	7.866	1.663	0.431	0.186	22.364	4.729	0.000
SGPT	0.003	0.05	0.056	0.003	0.306	0.553	0.581
Creatinine	0.299	0.117	0.251	0.063	6.584	2.566	0.012
Hemoglobin	-0.136	0.100	-0.136	0.019	1.847	-1.359	0.177
OBT	-0.019	0.400	-0.005	0.000	0.002	-0.048	0.961

RPR = Red cell distribution width to platelet ratio, SGPT = Serum glutamic pyruvic Transaminase, OBT = Occult blood test, R² = Coefficient of determination, F = Fischer’s test, t-test statistic, P = Probability

Bivariate analysis

This analysis was conducted involving those independent factors that have a statistically significant relationship with the total CTP score in their respective univariate analysis, that is, RPR and creatinine.

Bivariate regression analysis

Thus, the RPR and Cr value have a statistically significant impact on the CTP total score [Table 3].

Table 3.

Bivariate regression analysis

Parameter	Unstandardized co-efficients		Standardized co-efficients	t	Sig.
Creatinine	0.256	0.107	0.214	2.4	0.018
RPR	7.52	1.631	0.412	4.612	0.000

t-test statistic, sig = Significance

DISCUSSION

This study aimed to identify an easy, noninvasive, accurate, affordable, and convenient method to evaluate the severity of CLD. The Child–Turcotte–Pugh score is a widely used tool to assess the severity of CLD. Thus, in this study, an attempt was made to establish the correlation between red cell Distribution Width to platelet ratio (RPR) and Child–Turcotte–Pugh severity score in participants of CLD.

Out of 100 patients included in this study, 84 patients belonged to Child–Pugh Class C, 16 patients belonged to Class B, and there were no patients in Class A [Figure 1]. Similar studies were done in the past on CLD patients, revealed a better proportion of patients in Class A with a predominance of Class C. In the study by Baker et al. (2022), 64% of patients belonged to Class C, 28% to Class B, and 8% to Class A.[17]

In our study, the mean RDW-CV for the study population was 17.1 ± 3.2, while the median and mode were 16.4. Ranged between 12.4 and 30.7. Chen et al. (2018) conducted the study with a mean RDW-CV of 14.22 ± 2.83 in the estimation group and 13.77 ± 1.74 in the validation group.[18] Cengiz and Ozenirler (2015) had a mean RDW-CV of 13.84 ± 0.16.[19]

The mean platelet count in our study was 93,522/μl ± 38,756.530 while the median was 86,000. The range is between 27,000 and 292,000. Chen et al. (2013) had a mean platelet count of 150,370/μl ± 51,960 in the estimation group and 157,090/μl ± 55,780 in the validation group.[18] Cengiz et al. (2015) had a mean platelet count of 230,007/μl ± 76,840.[19] Thus, the mean platelet count was significantly higher in their study population as compared to our study population, thereby this would affect the RPR values.

The RPR values were further correlated with the total score of the Child–Turcotte–Pugh classification. In the study, the score ranged from 7 to 15, with most of the population occupying a score of 10 (22%), followed by 12 (19%). No previous studies have been conducted in the literature to compare the relation between these two parameters, that is, RPR and Child–Pugh Class and score.

In this study, not only did we correlate RPR value with Child–Pugh score, but we also attempted to find if RPR is correlated with any of the individual parameters of the score, that is, total bilirubin, inr value, serum albumin, ascites severity, and hepatic encephalopathy score.

The correlation between RPR and INR value revealed a statistically significant positive correlation of 0.312 with a P = 0.002. Also, there was a positive correlation of RPR with ascites severity score and hepatic encephalopathy score of 0.217 with a P = 0.030 and 0.351 with a P = 0.001, respectively. However, the study failed to show any statistically significant correlation of RPR with total bilirubin and serum albumin scores.

Finally, RPR was correlated with the total Child–Pugh Score and class with Pearson correlation. The results showed a statistically significant positive correlation of RPR with Child–Pugh Total score and Class of 0.431 with a P = 0.001 and 0.323 with a P = 0.001, respectively. Further, we performed a univariate regression analysis using total CTP score as the dependent factor and various parameters recorded in the study as independent factors, that is, age, sex, RPR, SGPT, creatinine, hemoglobin, and occult blood test, for evaluating their effect on the total CTP score. The independent factor was considered to have a statistically significant positive or negative impact on the total score if the P value came below 0.05. In this regression analysis with each of the factors, RPR and creatinine were found to have a statistically significant positive impact on the Total CTP score.

This was followed by a bivariate regression analysis utilizing the two statistically significant parameters, that is, RPR and creatinine. They both stood out as independent factors in the analysis that had a positive impact on the Total CTP score with β =7.52 and t = 4.612 with a P = 0.001 for RPR; and β = 0.256, t = 2.4 with a P = 0.018 for creatinine.

The following limitations were present in the study: The study only comprised decompensated patients, and there was not even a single patient belonging to Child–Pugh A, which is contrary to the real scenario. The presence of a control group would have helped in comparing and thus strengthening the observation and results. This correlation will have limited use in patients having raised serum creatinine levels, as serum creatinine is also correlated with the total CTP score.

CONCLUSION

It can be concluded that RPR values should be evaluated for each patient, as it can be easily done with a CBC report. In a resource or time-limited setting where all the parameters of the CTP score are not available, RPR can act as a guide for further steps. The above observations and results of this study will require further evaluation in a larger population and comparison with a control group for better validation.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.