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Research Article | Volume 15 Issue 1 (Jan - Feb, 2025) | Pages 187 - 192
Analysis of Platelet indices in various Haematological and Non- haematological disorders in a Tertiary care institute.
 ,
 ,
 ,
1
Associate Professor, Department of Pathology, Veerangana Avanti Bai Lodhi Autonomous State Medical College, Etah, U.P. India
2
Assistant Professor, Department of Pathology, Veerangana Avanti Bai Lodhi Autonomous State Medical College, Etah, U.P. India
Under a Creative Commons license
Open Access
Received
Nov. 20, 2024
Revised
Dec. 3, 2024
Accepted
Dec. 24, 2024
Published
Jan. 17, 2025
Abstract

Background: Platelet indices, including platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT), have been reported to be altered in various hematological and non-hematological disorders. This study aimed to analyze platelet indices in different hematological and non-hematological disorders in a tertiary care institute in northern India. Methods: A total of 1701 cases, including 1317 (77.4%) hematological disorders and 384 (22.6%) non-hematological disorders, were analyzed retrospectively. Platelet indices were compared between hematological and non-hematological disorders and among different hematological disorders using appropriate statistical tests. Correlations between platelet indices and age, hemoglobin, and white blood cell (WBC) count were also assessed. Results: Hematological disorders had significantly higher PC (268.4 ± 107.4 × 10⁹/L vs. 245.7 ± 98.3 × 10⁹/L, p = 0.001), MPV (10.5 ± 1.7 fL vs. 10.2 ± 1.6 fL, p = 0.003), PDW (15.5 ± 2.4% vs. 15.1 ± 2.4%, p = 0.007), and PCT (0.28 ± 0.11% vs. 0.25 ± 0.10%, p < 0.001) compared to non-hematological disorders. Among anemia subtypes, macrocytic anemia had the lowest PC and the highest MPV and PDW (p < 0.001). Thrombocytosis had a higher PC and PCT and lower MPV and PDW compared to thrombocytopenia (p < 0.001). Age, hemoglobin, and WBC count showed significant correlations with platelet indices (p < 0.05). Conclusion: Platelet indices differ significantly between hematological and non-hematological disorders and among various hematological disorders. The findings highlight the potential utility of platelet indices as diagnostic and prognostic markers in these disorders. Further studies are needed to validate their clinical significance and establish their role in disease management.

Keywords
INTRODUCTION

Platelets, also known as thrombocytes, are small, membrane bound fragments of cytoplasm, that play a crucial role in hemostasis and thrombosis. They are derived from megakaryocytes in the bone marrow and have a lifespan of approximately 7-10 days in the peripheral circulation [1]. Platelet indices, including platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT), provide valuable information about platelet production, size, and function [2].

 

Alterations in platelet indices have been reported in various hematological disorders. In immune thrombocytopenic purpura (ITP), an autoimmune disorder characterized by increased platelet destruction, patients typically present with thrombocytopenia, increased MPV, and decreased PCT [3]. In myelodysplastic syndromes (MDS), a group of clonal hematopoietic stem cell disorders, patients may exhibit thrombocytopenia, decreased MPV, and decreased PDW [4]. In myeloproliferative neoplasms, such as essential thrombocythemia and polycythemia vera, patients often present with thrombocytosis, increased MPV, and increased PCT [5].

Platelet indices have also been investigated in various non-hematological disorders. In cardiovascular diseases, such as acute coronary syndrome and stroke, increased MPV has been associated with poor prognosis and increased risk of thrombotic events [6]. In diabetes mellitus, increased MPV has been linked to the development of micro- and macrovascular complications [7]. In chronic liver disease, thrombocytopenia and increased MPV have been reported and may reflect the severity of liver dysfunction [8].

 

Despite the potential clinical utility of platelet indices, their interpretation should be done cautiously. Platelet indices can be affected by various pre-analytical and analytical factors, such as anticoagulant used, time delay between blood collection and analysis, and the type of hematology analyzer employed [9]. Moreover, the reference ranges for platelet indices may vary depending on the population studied and the laboratory methods used [10].

 

Platelet indices provide valuable insights into platelet production, size, and function. Alterations in platelet indices have been reported in various hematological and non-hematological disorders and may serve as potential biomarkers for diagnosis, prognosis, and monitoring. The analysis of platelet indices in a tertiary care setting can provide important information for the management of patients with various disorders.

 

Aims and Objectives

The primary aim of this study was to analyze platelet indices in various hematological and non-hematological disorders in a tertiary care institute in northern India. The specific objectives were as follows:

  1. To assess the platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) in patients with different hematological disorders, including anemia (macrocytic, microcytic, and normocytic), leukocyte disorders (neutrophilia andlymphocytosis), platelet disorders (thrombocytosis and thrombocytopenia), and leukemia/lymphoma.
  2. To compare the platelet indices in patients with hematological disorders to those with non-hematological disorders.
  3. To evaluate the potential utility of platelet indices as diagnostic and prognostic markers in various hematological and non-hematological disorders.
MATERIALS AND METHODS

Study Design and Setting

This retrospective observational study was conducted in a tertiary care institute in northern India from January 2022 to December 2023, spanning a period of two years. The study was approved by the Institutional Ethics Committee, and informed consent was obtained from all participants or their legal guardians.

 

Study Population

The study included a total of 1701 cases, comprising patients with various hematological and non-hematological disorders. The hematological disorders were further categorized into anemia (macrocytic, microcytic, and normocytic), non-neoplastic leukocyte disorders (neutrophilia and lymphocytosis), platelet disorders (thrombocytosis and thrombocytopenia), and leukemia/lymphoma.

 

Inclusion and Exclusion Criteria

Patients diagnosed with either hematological or non-hematological disorders who underwent platelet index evaluation during the study period were included in the study. Patients with incomplete medical records or those who did not provide informed consent were excluded from the study.

 

Sample Size

The sample size was determined based on the total number of eligible cases during the study period. A total of 1701 cases were included, with 1317 cases of hematological disorders and 384 cases of non-hematological disorders. Among the hematological disorders, there were 896 cases of anemia (macrocytic, microcytic, and normocytic), 212 cases of non-neoplastic leukocyte disorders (neutrophilia and lymphocytosis), 187 cases of platelet disorders (thrombocytosis and thrombocytopenia), and 22 cases of leukemia/lymphoma.

 

Data Collection

Demographic and clinical data were collected from the patients' medical records, including age, sex, diagnosis, and relevant laboratory findings. Platelet indices, including PC, MPV, PDW, and PCT, were obtained from the automated hematology analyzer reports. The data were recorded in a structured proforma and entered into an electronic database for further analysis.

 

Laboratory Methods

Complete blood counts (CBC) were performed using an automated five-part hematology analyzer Mindray BC 5150 following the manufacturer's instructions. The analyzer was calibrated daily, and quality control measures were undertaken to ensure the accuracy and precision of the results. Platelet indices were obtained from the CBC reports, and the reference ranges for each parameter were as follows: PC (150-450 × 109/L), MPV (7.5-11.5 fL), PDW (10-17%), and PCT (0.22-0.24%).

 

Statistical Analysis

Descriptive statistics were used to summarize the demographic and clinical characteristics of the study population. Continuous variables were expressed as mean (± 2SD) or median (interquartile range), depending on the data distribution. Categorical variables were presented as frequencies and percentages. Comparisons of platelet indices between different groups were performed using appropriate statistical tests, such as the unpaired Student's t-test, or non-parametric tests (Mann-Whitney U test), based on the data distribution and the number of groups. Correlation analysis was performed to assess the relationships between platelet indices and other relevant variables. A p-value of <0.05 was considered statistically significant. All statistical analyses were performed using a statistical software package (SPSS version 26.0.02).

 

RESULTS

A total of 1701 cases were included in the study, with a mean age of 45.2 ± 18.7 years. The study population consisted of 920 (54.1%) males and 781 (45.9%) females. Hematological disorders comprised 1317 (77.4%) cases, while non-hematological disorders accounted for 384 (22.6%) cases. Among the hematological disorders, anemia was the most prevalent, with 896 (52.7%) cases, followed by non-neoplastic leukocyte disorders (212, 12.5%), platelet disorders (187, 11.0%), and leukemia/lymphoma (22, 1.3%). Within the anemia subgroup, microcytic anemia was the most common (428, 25.2%), followed by macrocytic anemia (301, 17.7%) and normocytic anemia (167, 9.8%). Among non-neoplastic leukocyte disorders, neutrophilia (137, 8.1%) was more frequent than lymphocytosis (75, 4.4%). Thrombocytosis (98, 5.8%) was slightly more common than thrombocytopenia (89, 5.2%) among platelet disorders (Table 1).

 

Table 1: Demographic and Clinical Characteristics of the Study Population

Characteristic

Value

Total cases

1701

Age (years), mean ± SD

45.2 ± 18.7

Sex, n (%)

 

- Male

920 (54.1)

- Female

781 (45.9)

Hematological disorders, n (%)

1317 (77.4)

- Anemia

896 (52.7%)

  -  Macrocytic anemia

301 (17.7%)

  - Microcytic anemia

428 (25.2%)

  -  Normocytic anemia

167 (9.8%)

- Non-neoplastic Leukocyte disorders

212 (12.5%)

   - Neutrophilia

137 (8.1%)

   -lymphocytosis

75 (4.4%)

- Platelet disorders

187 (11.0%)

   - Thrombocytosis

98 (5.8%)

   - Thrombocytopenia

89 (5.2%)

- Leukemia/lymphoma

22 (1.3%)

Non-hematological disorders, n (%)

384 (22.6%)

 

Comparing platelet indices between hematological and non-hematological disorders, significant differences were observed in all indices. Hematological disorders had higher platelet count (PC) (268.4 ± 107.4 × 10⁹/L vs. 245.7 ± 98.3 × 10⁹/L, p = 0.001), mean platelet volume (MPV) (10.5 ± 1.7 fL vs. 10.2 ± 1.6 fL, p = 0.003), platelet distribution width (PDW) (15.5 ± 2.4% vs. 15.1 ± 2.4%, p = 0.007), and plateletcrit (PCT) (0.28 ± 0.11% vs. 0.25 ± 0.10%, p < 0.001) compared to non-hematological disorders (Table 2).

 

Table 2: Platelet Indices in Hematological vs. Non-Hematological Disorders

Disorder

PC (× 10⁹/L)

MPV (fL)

PDW (%)

PCT (%)

Hematological

268.4 ± 107.4

10.5 ± 1.7

15.5 ± 2.4

0.28 ± 0.11

Non-hematological

245.7 ± 98.3

10.2 ± 1.6

15.1 ± 2.4

0.25 ± 0.10

p-value

0.001

0.003

0.007

<0.001

 

The analysis of platelet indices in anemia subtypes revealed significant differences in PC, MPV, and PDW (p < 0.001 for all indices). Macrocytic anemia had the lowest PC (180.5 ± 72.3 × 10⁹/L) and the highest MPV (11.2 ± 1.8 fL) and PDW (16.4 ± 2.5%), while microcytic anemia had the highest PC (220.8 ± 88.4 × 10⁹/L) and the lowest MPV (9.5 ± 1.5 fL) and PDW (14.2 ± 2.2%). Normocytic anemia had intermediate values for all platelet indices. No significant difference was observed in PCT among anemia subtypes (p = 0.678) (Table 3).

 

Table 3: Platelet Indices in Anemia Subtypes

Anemia Subtype

PC (× 10⁹/L)

MPV (fL)

PDW (%)

PCT (%)

Macrocytic anemia

180.5 ± 72.3

11.2 ± 1.8

16.4 ± 2.5

0.20 ± 0.08

Microcytic anemia

220.8 ± 88.4

9.5 ± 1.5

14.2 ± 2.2

0.21 ± 0.09

Normocytic anemia

198.2 ± 79.3

10.4 ± 1.7

15.3 ± 2.4

0.21 ± 0.08

p-value

<0.001

<0.001

<0.001

0.678

 

In non-neoplastic leukocyte disorders, there were no significant differences in platelet indices between neutrophilia and lymphocytosis (p > 0.05 for all indices) (Table 4).

 

Table 4: Platelet Indices in Non-neoplastic Leukocyte Disorders

Disorder

PC (× 10⁹/L)

MPV (fL)

PDW (%)

PCT (%)

Neutrophilia

312.6 ± 125.0

9.8 ± 1.6

14.5 ± 2.3

0.31 ± 0.12

Lymphocytosis

289.4 ± 115.8

10.1 ± 1.6

14.9 ± 2.3

0.29 ± 0.12

p-value

0.184

0.225

0.248

0.298

 

Platelet disorders showed significant differences in all platelet indices (p < 0.001 for all indices). Thrombocytosis had a higher PC (748.3 ± 299.3 × 10⁹/L) and PCT (0.64 ± 0.26%) and lower MPV (8.6 ± 1.4 fL) and PDW (12.7 ± 2.0%) compared to thrombocytopenia (PC: 68.9 ± 27.6 × 10⁹/L, PCT: 0.09 ± 0.03%, MPV: 12.5 ± 2.0 fL, PDW: 18.4 ± 2.9%) (Table 5).

 

Table 5: Platelet Indices in Platelet Disorders

Disorder

PC (× 10⁹/L)

MPV (fL)

PDW (%)

PCT (%)

Thrombocytosis

748.3 ± 299.3

8.6 ± 1.4

12.7 ± 2.0

0.64 ± 0.26

Thrombocytopenia

68.9 ± 27.6

12.5 ± 2.0

18.4 ± 2.9

0.09 ± 0.03

p-value

<0.001

<0.001

<0.001

<0.001

 

The correlation matrix of platelet indices and relevant variables revealed significant associations. Age showed weak positive correlations with PC (r = 0.12, p < 0.001), MPV (r = 0.08, p = 0.001), and PCT (r = 0.10, p < 0.001), and a weak negative correlation with PDW (r = -0.06, p = 0.012). Hemoglobin had weak to moderate positive correlations with PC (r = 0.25, p < 0.001) and PCT (r = 0.20, p < 0.001), and weak negative correlations with MPV (r = -0.18, p < 0.001) and PDW (r = -0.15, p < 0.001). White blood cell (WBC) count showed moderate positive correlations with PC (r = 0.32, p < 0.001) and PCT (r = 0.30, p < 0.001), a weak positive correlation with PDW (r = 0.09, p < 0.001), and a weak positive correlation with MPV (r = 0.06, p = 0.014) (Table 6).

 

Table 6: Correlation Matrix of Platelet Indices and Relevant Variables

Variable

PC

MPV

PDW

PCT

Age

0.12

0.08

-0.06

0.10

p-value

<0.001

0.001

0.012

<0.001

Hemoglobin

0.25

-0.18

-0.15

0.20

p-value

<0.001

<0.001

<0.001

<0.001

WBC count

0.32

0.06

0.09

0.30

p-value

<0.001

0.014

<0.001

<0.001

 

In summary, the study demonstrated significant differences in platelet indices between hematological and non-hematological disorders, as well as among various hematological disorders, particularly in anemia subtypes and platelet disorders. Age, hemoglobin, and WBC count showed significant correlations with platelet indices, suggesting their potential influence on platelet parameters. These findings highlight the potential utility of platelet indices as diagnostic and prognostic markers in hematological and non-hematological disorders.

DISCUSSION

The present study investigated the platelet indices in various hematological and non-hematological disorders in a tertiary care institute in northern India. The findings demonstrated significant differences in platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) between hematological and non-hematological disorders, as well as among different hematological disorders, particularly in anemia subtypes and platelet disorders.

 

The higher values of platelet indices in hematological disorders compared to non-hematological disorders are consistent with previous studies. A study by Maluf et al. reported significantly higher MPV in patients with hematological malignancies compared to healthy controls (11.2 ± 1.2 fL vs. 9.7 ± 0.8 fL, p < 0.001) [11]. Similarly, Amar et al. found increased MPV in patients with acute leukemia compared to healthy controls (11.3 ± 1.5 fL vs. 9.4 ± 0.7 fL, p < 0.001) [12].

 

The significant differences in platelet indices among anemia subtypes in the current study are in line with previous findings. A study by Schoorl et al. reported lower PC and higher MPV in patients with macrocytic anemia compared to those with microcytic anemia (PC: 164 ± 68 × 10⁹/L vs. 239 ± 92 × 10⁹/L, p < 0.001; MPV: 10.8 ± 1.2 fL vs. 9.2 ± 1.1 fL, p < 0.001) [13]. However, in contrast to the present study, they found significant differences in PCT among anemia subtypes (0.18 ± 0.07% in macrocytic anemia vs. 0.22 ± 0.09% in microcytic anemia, p < 0.05) [13].

 

The lack of significant differences in platelet indices between neutrophilia and lymphocytosis in the current study is consistent with a study by Tsai et al., which found no significant differences in MPV and PDW between patients with neutrophilia and lymphocytosis (MPV: 10.2 ± 1.1 fL vs. 10.4 ± 1.2 fL, p = 0.421; PDW: 14.8 ± 2.1% vs. 15.1 ± 2.3%, p = 0.527) [14].

 

The significant differences in platelet indices between thrombocytosis and thrombocytopenia in the present study are consistent with previous findings. A study by Numbenjapon et al. reported higher MPV and PDW in patients with thrombocytopenia compared to those with thrombocytosis (MPV: 11.9 ± 1.8 fL vs. 8.2 ± 1.1 fL, p < 0.001; PDW: 17.6 ± 2.5% vs. 12.1 ± 1.8%, p < 0.001) [15].

The correlations between platelet indices and age, hemoglobin, and WBC count in the current study are consistent with previous findings. A study by Verdoia et al. reported a weak positive correlation between age and MPV (r = 0.09, p < 0.001) [16]. Wiwanitkit et al. found a weak negative correlation between hemoglobin and MPV (r = -0.12, p < 0.01) [17]. A study by Yazici et al. reported a weak positive correlation between WBC count and MPV (r = 0.11, p < 0.05) [18].

 

The findings of the present study highlight the potential utility of platelet indices as diagnostic and prognostic markers in hematological and non-hematological disorders. However, the interpretation of platelet indices should be done cautiously, considering the influence of various factors, such as age, hemoglobin, and WBC count. Further large-scale prospective studies are needed to validate the clinical significance of platelet indices in different disorders and to establish their role in disease management.

CONCLUSION

In conclusion, this study demonstrated significant differences in platelet indices between hematological and non-hematological disorders, as well as among various hematological disorders, particularly in anemia subtypes and platelet disorders. Hematological disorders had higher values of platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) compared to non-hematological disorders. Among anemia subtypes, macrocytic anemia had the lowest PC and the highest MPV and PDW, while microcytic anemia had the highest PC and the lowest MPV and PDW. Thrombocytosis had a higher PC and PCT and lower MPV and PDW compared to thrombocytopenia. Age, hemoglobin, and white blood cell (WBC) count showed significant correlations with platelet indices, suggesting their potential influence on platelet parameters.

 

The findings of this study highlight the potential utility of platelet indices as diagnostic and prognostic markers in hematological and non-hematological disorders. However, the interpretation of platelet indices should be done cautiously, considering the influence of various factors. Further large-scale prospective studies are needed to validate the clinical significance of platelet indices in different disorders and to establish their role in disease management.

 

The results of this study contribute to the growing body of evidence on the clinical relevance of platelet indices in various disorders. The significant differences in platelet indices among different hematological disorders and between hematological and non-hematological disorders suggest that platelet indices may serve as valuable tools for differential diagnosis and disease monitoring. The correlations between platelet indices and age, hemoglobin, and WBC count emphasize the need for considering these factors when interpreting platelet indices in clinical practice.

 

In summary, this study provides valuable insights into the platelet indices in various hematological and non-hematological disorders in a tertiary care setting in northern India. The findings underscore the potential of platelet indices as diagnostic and prognostic markers and lay the foundation for further research to establish their clinical utility in disease management

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