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ORIGINAL ARTICLE Table of Contents  
Ahead of print publication
Association of hematological parameters (mean platelet volume and red cell distribution width) with nonalcoholic fatty liver disease


1 Department of Medicine, SGT University, Gurugram, Haryana, India
2 Department of Medicine, VMMC and Safdarjung Hospital, New Delhi, India
3 Department of Medicine, Rama Medical College and Hospital, Hapur, Uttar Pradesh, India

Click here for correspondence address and email

Date of Submission11-Jan-2022
Date of Decision15-Mar-2022
Date of Acceptance30-Mar-2022
Date of Web Publication04-Aug-2022
 

  Abstract 


Objectives: We aimed to compare mean platelet volume (MPV) and red cell distribution width (RDW) values of the nonalcoholic fatty liver disease (NAFLD) patients with the normal population and also assess the correlation of MPV and RDW with grades of NAFLD. Methods: An observational case–control study was conducted over a period of 21 months (November 2018–July 2020). Sixty-five patients with NAFLD and 65 healthy controls were enrolled in this study. Demography, symptoms of the patients, and clinical investigations comprising hematological profile, liver enzyme tests, lipid profile, and viral markers were done. Ultrasound liver was done to assess the grading of NAFLD. The outcome measures were correlation between RDW, MPV, and NAFLD grade. Results: The median of RDW in cases was 14.5% which was significantly higher as compared to controls 12.4% (P < 0.05). The median MPV (μm3) in cases was significantly higher than controls (11.4 vs. 9, P < 0.05). The mean RDW (%) in Grade 3 was significantly higher as compared to Grade 2 and Grade 1 (17.04 vs. 14.63 vs. 12.95, P < 0.05). The mean MPV (μm3) in Grade 3 was significantly higher as compared to Grade 2 and Grade 1 (13.32 vs. 11.43 vs. 8.96, P < 0.05). A significant positive correlation was seen between grade of fatty liver with MPV (r = 0.908, P < 0.0001) and RDW (r = 0.892, P < 0.0001). Conclusion: Overall, our study results show increased MPV and RDW in cases as compared to controls with significant correlation with liver grade, suggesting that these markers can be used to assess the onset and severity of NAFLD.

Keywords: Mean platelet volume, nonalcoholic fatty liver disease, red cell distribution width


How to cite this URL:
Verma S, Verma M, Khari S. Association of hematological parameters (mean platelet volume and red cell distribution width) with nonalcoholic fatty liver disease. APIK J Int Med [Epub ahead of print] [cited 2022 Oct 6]. Available from: https://www.ajim.in/preprintarticle.asp?id=353256





  Introduction Top


Nonalcoholic fatty liver disease (NAFLD), which is defined as “the presence of hepatic fat accumulation after excluding other causes of hepatic steatosis such as liver disease and excessive alcohol consumption,”[1] encompasses a broad range of liver dysfunctions. This ranges from benign steatosis to nonalcoholic steatohepatitis (NASH).[2]

Worldwide, the prevalence rates of NAFLD are reported to be 25%.[3] In India, the prevalence rates of NAFLD vary from 9% to 32%.[4] Genetics and risk factors such as obesity, hypertension, and insulin resistance play an important pathological role.[5],[6]

The overall mortality per 1000 person-years was reported to be 15.44 for patients with NAFLD and 25.56 for patients with NASH. Researchers associated NASH (adjusted hazard ratio, 9.16), age (adjusted hazard ratio, 1.06), and the presence of type 2 diabetes mellitus (adjusted hazard ratio, 2.09) with increased all-cause and liver-related mortality after controlling for other variables.[7],[8]

The grave outcomes associated with NAFLD and increasing fibrosis have made NAFLD as one of the recognizable public health problems that are roughly affecting up to a quarter of the world's adult population.[9]

Presently various biomarkers are used to monitor the progression of NAFLD which are based on clinical spectrum of the patients. Several noninvasive scores such as aspartate-to-alanine aminotransferase ratio, aspartate transaminase/platelet ratio index, fibrosis index, and Fibrosis-4 (FIB-4) index for predicting liver fibrosis have already been described. Despite the suggestions that these scores correlate with degree of fibrosis, there is no sufficient data supporting the everyday use, yet.[10] In addition, medical search has put forth certain hematological parameters in determining the progression of NAFLD.

A laboratory marker which has gained attention in NAFLD is platelet count (PLT) count, its function, and size (mean platelet volume [MPV]).

MPV indicates the platelet size where higher values are related to platelet activation. It is also a biomarker of platelet function. The calculation of MPV is done by hematological analyzers based on the volume distribution while performing routine blood morphology test. The normal value of MPV is 7.5–12.0 fl, while the percentage of large platelets is accountable for 0.2% to 5% of the total platelet population. Several studies have addressed this laboratory marker, especially in alcoholic liver disease, liver cirrhosis, and prediction of fibrosis severity (grade) in NAFLD and NASH.[11]

Along with this, the variation in red cell distribution width (RDW) has also shown association with NAFLD.[12],[13],[14]

RDW measures the variability of size of erythrocyte in peripheral blood, that is, anisocytosis. RDW has recently received a lot of attention as a prognostic marker for a variety of medical illnesses, including heart failure, sepsis, autoimmune diseases, liver disorders, and various cancers.[15]

There is ongoing research on the use of combination of these laboratory markers that are noninvasive and simple methods for the early identification of high-risk NAFLD. Therefore, we aimed in this study to compare RDW and MPV values of the patients with NAFLD in comparison to the normal population and determine the correlation of the values of MPV and RDW with grade of liver disease.


  Methods Top


An observational case–control study was conducted in the Department of General Medicine, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, over a period of 21 months (November 2018–July 2020).

The study subjects included consecutive adult patients (>18 years) diagnosed with NAFLD based on abdominal ultrasonography examination. Age- and sex-matched patients who underwent ultrasound whole abdomen for any reason and were not found to have fatty liver or any other identified organic disease were taken as controls. The study excluded any patient with platelet disorders, anemia, hematological disorders, viral hepatitis, chronic liver disease (with unrelated liver pathology), and intake of hepatotoxic drugs like tamoxifen, glucocorticoids, isoniazid, amiodarone, methotrexate, highly active antiretroviral therapy, estrogen and sodium valproate.

The sample size was calculated as per the study by Aktas et al.[16] who observed that the mean value of RDW and MPV in the study group was 16.1 ± 0.6 and 9.8 ± 1.7, respectively, and in the control group was 15.8 ± 0.6 and 8.1 ± 0.8, respectively. Taking these values as reference, the minimum required sample size with 80% power of study and 5% level of significance was 63 patients in each study group. Hence, the total sample size taken was 130 (65 patients/group).

After the approval by the ethics committee, written informed consent was taken from respective patients or relatives of the diagnosed patients of NAFLD and controls. All investigations during the study were done from the side of the hospital and no additional cost was borne by the patients.

A total of 130 patients (65 cases and 65 controls) were subjected to detailed history and systemic examination including a detailed abdominal examination which was recorded in the study pro forma.

The diagnosis of NAFLD required evidence of fatty infiltration of the liver in the absence of excessive alcohol consumption and of other chronic liver diseases.[17] The patient underwent ultrasonography of the whole abdomen, where a positive case of NAFLD was diagnosed with diffuse increase in hepatic echogenicity “bright liver,” greater than the kidney cortex and spleen parenchyma due to intracellular accumulation of fat vacuoles along with hepatomegaly and vascular blurring of the portal vein or hepatic vein.

Based on the guidelines for the assessment and management of NAFLD in the Asia-Pacific region, fatty liver was diagnosed by the presence of at least two of the following three abnormal findings on abdominal ultrasonography:[18]

  1. Increased echogenicity of the liver near-field region with deep attenuation of ultrasound signal
  2. Hyperechogenicity of liver tissue (“bright liver”), as often compared to hyperechogenicity of the kidney cortex
  3. Vascular blurring.


Grades of fatty liver are described as:

  1. Grade I: Increased hepatic echogenicity with visible periportal and diaphragmatic echogenicity
  2. Grade II: Increased hepatic echogenicity with imperceptible periportal echogenicity, without obscuration of diaphragm
  3. Grade III: Increased hepatic echogenicity with imperceptible periportal echogenicity and obscuration of diaphragm.[19]


Information on age, gender, alcohol consumption, cigarette smoking, and medical history was obtained and recorded in the study pro forma. Standing height and body weight were measured without shoes or thick clothing, and body mass index (BMI) was calculated as body weight (in kg)/height (m).

Excessive alcohol was defined according to the “US National Institute on Alcohol Abuse and Alcoholism.” The “heavy drinking” was defined as “consuming >4 drinks a day or 14 drinks a week for males and consuming >3 drinks a day or 7 drinks a week for females.”[20]

A patient was considered to be hypertensive if (1) blood pressure reading was >140/90 mmHg on two consecutive occasions with sphygmomanometer (as per JNC 8 guidelines, 2015)[21] or (2) the patient was taking antihypertensive medication and had controlled blood pressure.

Diabetes was defined as on the bases of subject's patient's history or usage of hypoglycemic medications or fasting plasma glucose value ≥126 mg/dl, postprandial plasma glucose value ≥200 mg/dl, and HbA1C ≥6.5 g% (as per the American Diabetic Association guidelines, 2015).[22]

Blood sample was collected in four vials for all the patients. Two blood samples of 5 ml each were collected from each study subject in ethylenediaminetetraacetic acid (EDTA) vial and plain red-topped vial. EDTA vial was run in fully automated hematology analyzer Beckman Coulter and plain vial was centrifuged at 1500 rpm for 10 min to derive serum sample which was run in the fully automated biochemistry analyzer Beckman Coulter for other biochemical tests.

One sample of 2 ml was collected in sodium fluoride gray vial for serum glucose estimation. One sample of 2 ml was collected in the purple-capped coagulation tube for coagulation assays.

Biochemical, radiological, and hematological analysis

The various biochemical and hematological investigations that were performed on the participants in the study were as follows:

  1. Complete blood count
  2. ]

    • Hemoglobin level
    • Erythrocyte sedimentation rate
    • Mean corpuscular volume
    • RDW
    • PLT and MPV
    • White blood cell count.


  3. Liver function test


    • Serum bilirubin
    • Aspartate transaminase (AST)
    • Alanine transaminase (ALT)
    • Alkaline phosphatase (ALP).


  4. Blood glucose– fasting and postprandial.
  5. Total serum proteins/albumin
  6. HIV, HBsAg, and anti-HCV
  7. Coagulation profile (prothrombin time [PT], activated partial thromboplastin time (APTT), and international normalized ratio [INR])
  8. Antinuclear antibodies
  9. Ultrasound abdomen (done by the same senior radiologist to remove interobserver bias).


The outcome measures were correlation between RDW, MPV with clinical variables, grading, and laboratory parameters.

Statistical analysis

Categorical variables were presented in number and percentage (%) and continuous variables were presented as mean ± standard deviation and median. Normality of data was tested by Kolmogorov–Smirnov test. If the normality was rejected, then nonparametric test was used.

Quantitative variables were compared using Mann–Whitney test (as the data sets were not normally distributed) between the two groups, and analysis of variance/Kruskal–Wallis test was used for comparison between more than two groups. Qualitative variables were compared using Chi-square test.

Spearman rank correlation coefficient was used to assess the correlation of grade of fatty liver with complete blood count and correlation of RDW and MPV with various parameters. P < 0.05 was considered statistically significant.

The data were entered in MS Excel spreadsheet, and analysis was done using the Statistical Package for the Social Sciences (SPSS), IBM Manufacturer, Chicago, USA, version 21.0.


  Results Top


There were 16 females and 49 males in the cases, while 23 women and 42 men in control subjects. The mean ages of the case and control groups were 43.97 ± and 40.11 ± years, respectively (P = 0.386). No significant difference was seen in the age in years between cases and controls (P > 0.05). There was no difference in the distribution of gender between cases and controls (P > 0.05) [Table 1].
Table 1: Comparison of demographic characteristics between cases and controls

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In our study on 65 NAFLD patients, stage of NAFLD was Grade 1 in 27 (41.54%), Grade 2 in 17 (26.16%), and Grade 3 in 21 (32.3%) patients [Figure 1].
Figure 1: Distribution of grade of nonalcoholic fatty liver disease

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Among Grade 1 patients (n = 27), 20 were asymptomatic while 7 had fatigue; among Grade 2 patients (n = 17), 3 were asymptomatic while 14 had abdominal pain; and among Grade 3 patients (n = 21), 3 had fatigue and 18 had abdominal pain.

The mean of fasting blood sugar (FBS), postprandial blood sugar (PPBS), and hemoglobin A1C (HbA1C) of cases was 115.52 mg/dL, 156.09 mg/dL, and 6.31%, respectively. The mean of PT, APTT, and INR of cases was 13.05 s, 30.24 s, and 1.49. Liver profile showed that the mean value of AST, ALT, and ALP of cases was 40.43 U/L, 39.62 U/L, and 117.2 U/L, respectively. Among the viral markers, HIV, HBsAg, and anti-HBC were negative in all cases.

Compared to controls, cases had significantly higher glycemic parameters including FBS (115.52 ± 16.63 vs. 97 ± 7, P < 0.0001), PPBS (156.09 ± 22.07 vs. 123.3 ± 12.71, P < 0.0001), and HbA1C (%) (6.31 ± 1 vs. 5.5 ± 0.8, P < 0.0001); direct bilirubin (mg/dL) (0.66 ± 0.36 vs. 0.2 ± 0.16, P < 0.0001); low-density lipoprotein (LDL) (89.82 ± 15.67 vs. 56 ± 17.76, P < 0.0001); and INR (1.49 ± 0.33 vs. 1.2 ± 0.31, P < 0.0001) [Table 2].
Table 2: Comparison of parameters between cases and controls

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The median of RDW in cases was 14.5% which was significantly higher as compared to controls 12.4% (P < 0.05) [Figure 2]. The median MPV (μm≥) in cases was also significantly higher than controls (11.4 vs. 9, P < 0.05) [Figure 3].
Figure 2: Comparison of red cell distribution width between cases and controls (nonparametric variables)

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Figure 3: Comparison of mean platelet volume between cases and controls (nonparametric variables)

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There was a significant association of the presence of symptoms with grading of NAFLD as fatigue and abdominal pain were present in higher proportion of patients with Grade 3 while Grade 1 patients were more asymptomatic (P < 0.0001). The mean RDW (%) in Grade 3 was significantly higher as compared to Grade 2 and Grade 1 (17.04 vs. 14.63 vs. 12.95, P < 0.05). The mean MPV (μm3) in Grade 3 was significantly higher as compared to Grade 2 and Grade 1 (13.32 vs. 11.43 vs. 8.96, P < 0.05) [Table 3].
Table 3: Association of symptoms, red cell distribution width, and mean platelet volume with grade of nonalcoholic fatty liver disease

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A significant positive correlation was seen between grade of fatty liver with MPV (r = 0.908, P < 0.0001) and RDW (%) (r = 0.892, P < 0.0001) [Figure 4] and [Figure 5].
Figure 4: Correlation of grade of fatty liver with mean platelet volume (μm3)

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Figure 5: Correlation of grade of fatty liver with red cell distribution width (%)

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A significant positive correlation was seen between MPV and systolic blood pressure (SBP) (r = 0.432, P = 0.0004), diastolic blood pressure (DBP) (r = 0.491, P < 0.0001), FBS (r = 0.318, P = 0.010), PPBS (r = 0.298, P = 0.016), HbA1C (r = 0.366, P = 0.003), BMI (r = 0.504, P < 0.0001), AST (r = 0.434, P = 0.0003), ALP (r = 0.405, P = 0.001), total cholesterol (r = 0.613, P < 0.0001), triglycerides (r = 0.627, P < 0.0001), LDL-cholesterol (LDL-C) (r = 0.486, P = 0.0001), very-low-density lipoprotein-cholesterol (VLDL-C) (r = 0.468, P = 0.0001), total serum protein (r = 0.671, P < 0.0001), globulin (r = 0.259, P = 0.038), albumin (r = 0.667, P < 0.0001), PT (r = 0.488, P < 0.0001), APTT (r = 0.376, P = 0.002), and INR (r = 0.325, P = 0.009) [Table 4].
Table 4: Correlation of red cell distribution width and mean platelet volume with various parameters

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A significant positive correlation was seen between RDW (%) and SBP (r = 0.417, P = 0.001), DBP (r = 0.488, P < 0.0001), FBS (r = 0.362, P = 0.003), PPBS (r = 0.327, P = 0.008), HbA1C (r = 0.410, P = 0.001), BMI (r = 0.414, P = 0.001), AST (r = 0.396, P = 0.001), ALP (r = 0.316, P = 0.011), total cholesterol (r = 0.610, P < 0.0001), triglycerides (r = 0.575, P < 0.0001), LDL-C (r = 0.494, P < 0.0001), VLDL-C (r = 0.360, P = 0.003), total serum protein (r = 0.664, P < 0.0001), globulin (r = 0.431, P = 0.0004), albumin (r = 0.615, P < 0.0001), PT (r = 0.410, P = 0.001), APTT (r = 0.395, P = 0.001), and INR (r = 0.289, P = 0.020) [Table 4].


  Discussion Top


The present study was able to uphold the notion of using RDW and MPV as markers of severity of NAFLD. This is important as they are noninvasive marker and can be routinely monitored.

Both the markers were significantly higher as compared to controls, signifying the importance of their early derangements in NAFLD.

Our findings were corroborated by various other studies. In a similar study as ours, Celikbilek M et al.[23] also reported that the mean MPV was significantly higher in those with NAFLD as compared to the control group (9.70 ± 1.13 vs. 9.10 ± 0.82, P = 0.003). Even Madan SA et al.[24] found that MPV was significantly higher in patients with NAFLD than those without. In another study, Nallathambi N et al.[25] noted that MPV was significantly higher in NAFLD than nonfatty liver disease group (P = 0.01). Yang et al.[26] found that RDW was significantly higher in patients with NAFLD as compared to healthy controls (13.23 vs. 12.96, P = 0.000).

In contrast to our study, Kilciler et al.[27] found that there were no differences between patients with NAFLD and controls according to MPV levels. This was mainly attributed to the absence of other metabolic risk factors in their study, a case where MPV might not be involved in the mechanism of NAFLD.

In addition to finding higher values of MPV and RDW in cases, we also found that they showed an increasing trend with the increasing grading of NAFLD. Grading of NAFLD denotes that there is increasing fibrosis in the liver which demarcates a higher mortality and severity of the disease. Moreover, the symptoms also increase with the increasing fibrosis.[27],[28],[29],[30]

This association of MPV and RDW with grading of NAFLD was also seen in the studies of Cengiz et al.,[28] who found that as compared to the mild fibrosis patients, those with advanced fibrosis had greater RDW values (15.86% vs. 13.63%, P < 0.01). There was a correlation between RDW and fibrotic scores (r = 0.579, P < 0.01). Similarly, Kim et al.[29] found a graded association between high RDW and advanced liver fibrosis among NAFLD patients. There was a significant correlation of RDW with BARD and FIB-4 scores, which was used to measure NAFLD severity.

Saremi et al.[30] reported a positive association of NAFLD with higher MPV (odds ratio: 1.9; 95% confidence interval: 1.20–3.02). There was a significant difference in MPV in NAFLD Grades 1–3 (P < 0.05).

Besides the association of MPV and RDW with NAFLD and grades of NAFLD, these parameters also showed association with certain biochemical parameters.

For MPV association with biochemical parameters, our findings were in line with Ozhan et al.,[31] who reported that MPV was positively correlated with AST (r: 0.186, P < 0.042), ALT level (r: 0.279; P: 0.002), and presence of NAFLD (0.492; P < 0.001) and negatively correlated with platelet number (r: −0.26; P: 0.004) and creatinine (r: −0.255; P: 0.005). Close relationship between ALT levels and MPV value could further enhance the prognostic value of MPV in NAFLD patients and MPV could serve as a surrogate marker of Liver failure risk in a clinical setting.

The reasoning behind such correlations remains complex. As platelet functions are influenced by platelet size, density, age, and previous hemostatic interactions, any disease-causing reactive platelet production and alteration in the platelet sizes and volume such as hemolysis, liver disease, and cardiac disease may result in decreased bleeding time and increased platelet activation. Furthermore, an increase in MPV may result from the use of small platelets during acute ischemia.

Similarly, RDW also showed a significant correlation with biochemical parameters. The relationship between RDW and inflammation in hepatic diseases has been extensively studied in several studies. In the study of Milic et al.,[32] 241 patients with alcoholic and nonalcoholic hepatic cirrhosis and anemia (hemoglobin <13 g/dL in males and hemoglobin <12 g/dL in females) were retrospectively analyzed. The mean RDW was found to be higher in both patient groups, although it did not reach statistical significance (P > 0.05). Hu et al.[33] reported that there was a positive correlation between the severity of Child–Pugh score and RDW in patients with cirrhosis. Chen et al.[34] found that hemoglobin, RDW, and platelets were independent predictors of the liver fibrosis stage in patients with chronic hepatic B. Another study by Lou et al.[35] found that higher RDW values were associated with disease severity in patients with hepatitis B.

Dogan et al.[36] reported that there was a relationship between RDW and grade of steatosis (P = 0.704, r = 0.035), between RDW and AST (P = 0.856, r = −0.017), between RDW and ALT (P = 0.223, r = −0.112), between RDW and ALP (P = 0.318, r = 0.092), between RDW and gamma-glutamyl transferase (GGT) (P = 0.597, r = 0.049), and between RDW and lactate dehydrogenase (P = 0.195, r = 0.119). However, there was no statistically significant relationship between RDW and grade of hepatic steatosis and liver enzymes.

The mechanism underlying the association between the RDW and the progression of fibrosis is also not well understood. Lippi et al.[37] speculated that the association between RDW and inflammatory states was simply an epiphenomenon of underlying abnormal iron metabolism and/or anemia. Lan et al.[38] found that RDW values were increased and were related to various biomarkers and MELD grades in liver disease, and RDW could be used as an inflammatory marker for predicting chronic hepatitis B, liver cirrhosis, and hepatocellular carcinoma when combined with hemoglobin (Hgb), AST, GGT, ALP, and globulin.

Limitations of the study

  1. The study cohort is relatively small and NAFLD diagnosis was not confirmed by liver biopsy, which is the best diagnostic tool for confirming NAFLD. The diagnosis of NAFLD was based on ultrasonography examination. Ultrasonography is not sensitive enough to detect mild steatosis
  2. Although MRI has a higher sensitivity in detecting fatty liver, it is not used routinely due to cost and availability. Analyses were based on a simple baseline determination that may not reflect patients' status over long period
  3. The present analysis is limited in its ability to establish causal or temporal relationships between MPV and RDW and NAFLD. Due to the lack of data, the possible causes that may affect RDW values, such as iron, Vitamin B12 deficiency, and folic acid, were not investigated
  4. This study involved a single center and has posed a selection bias. Therefore, the performance of the MPV and RDW should be further confirmed in multicenter designed studies.



  Conclusion Top


Overall, our study results show increased MPV and RDW in the cases as compared to controls with significant correlation with grading of NAFLD. This suggests that MPV and RDW can be used as a novel noninvasive marker to assess the onset and severity of NAFLD. However, future studies are recommended to discover the detailed mechanism of RDW association in liver diseases. Our findings have important public health and clinical implications. These indices can be applied to rural populations as well where public resources are limited. As the prevalence of NAFLD is on the rise, our study might be helpful to develop a single, simple, and cost-effective index to identify high-risk population group.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Correspondence Address:
Sonika Verma,
Kh-361/1, Sultanpur, M.G Road, New Delhi - 110 030
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ajim.ajim_11_22



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