| Abstract|| |
Aims: This study aims to establish biological reference interval for novel platelet parameters. Settings and Design: A total of 945 healthy individuals, age ranges from 18 to 64 years (881 males and 64 females) coming for voluntary blood donation from June to August 2012 (3 months) were enrolled after exclusion of rejection criteria. Materials and Methods: The samples were assayed by running in complete blood count + reticulocyte mode on the Sysmex XE-2100 hematology analyzer and the reference interval for the population was calculated using Clinical and Laboratory Standards Institute guidelines. Statistical analysis used: Tests were performed using SPSS (Statistical Product and Service Solutions , developed by IBM corporation), version 13. Student t test and pearsons correlation analysis were also used. Results: The normal range for various parameters was platelet count: 150-520 × 10 3 /cu mm, immature platelet fraction (IPF): 0.3-8.7%, platelet distribution width (PDW): 8.3-25.0 fL, mean platelet volume (MPV): 8.6-15.5 fL, plateletcrit (PCT): 0.15-0.62%, high immature platelet fraction (H-IPF): 0.1-2.7%, platelet large cell ratio (P-LCR): 11.9-66.9% and platelet-X (PLT-X) (ch): 11.0-22.0. Negative correlation was observed between platelet count (r = −0.468 to r = −0.531; P < 0.001) and PCT (r = −0.080 to r = −0.235; P < 0.05 to P < 0.001) with IPF, PDW, MPV, H-IPF, P-LCR, and platelet-X. IPF/H-IPF showed a positive correlation among them and also with PDW, MPV, P-LCR, platelet-X (r = +0.662 to r = +0.925; P < 0.001). Conclusions: These novel platelet parameters offer newer avenues in research and clinical use. Establishing biological reference interval for different platelet parameters would help determine true high and low values and help guide treatment decisions.
Keywords: High immature platelet fraction, immature platelet fraction, platelet distribution width, platelet large cell ratio, reference interval
|How to cite this article:|
Sachdev R, Tiwari AK, Goel S, Raina V, Sethi M. Establishing biological reference intervals for novel platelet parameters (immature platelet fraction, high immature platelet fraction, platelet distribution width, platelet large cell ratio, platelet-X, plateletcrit, and platelet distribution width) and their correlations among each other. Indian J Pathol Microbiol 2014;57:231-5
|How to cite this URL:|
Sachdev R, Tiwari AK, Goel S, Raina V, Sethi M. Establishing biological reference intervals for novel platelet parameters (immature platelet fraction, high immature platelet fraction, platelet distribution width, platelet large cell ratio, platelet-X, plateletcrit, and platelet distribution width) and their correlations among each other. Indian J Pathol Microbiol [serial online] 2014 [cited 2019 Jul 19];57:231-5. Available from: http://www.ijpmonline.org/text.asp?2014/57/2/231/134676
| Introduction|| |
Our study focuses on evaluating reference interval for the novel platelet parameters such as platelet count (PLT), immature platelet fraction (IPF), platelet distribution width (PDW), mean platelet volume (MPV) plateletcrit (PCT), and platelet large cell ratio (P-LCR), high immature platelet fraction (H-IPF) and platelet-X (PLT-X) (ch). Using flow cytometry technology and specialized reagents for the reticulocyte mode, the Sysmex XE-2100 is able to quantify novel platelet parameters.
IPF plays a significant role in predicting peripheral platelet destruction in thrombocytopenia and assessing platelet recovery. This can avoid bone marrow procedures but more importantly avoid unnecessary platelet transfusions. Similarly, PDW, MPV, P-LCR, and PLT-X are markers of platelet activation. PDW is related with function and platelet activity. MPV increases as the platelet production increases and giant platelets enter the circulation. MPV has been reported to increase in myeloproliferative neoplasm, massive hemorrhage, leukemia, vasculitis and postsplenectomy.  Any differences in the above platelet parameters between the sexes were also analyzed.
| Materials and methods|| |
A total of 945 healthy individuals, age 18-64 years (881 males and 64 females) coming for voluntary blood donation from June to August 2012 (3 months) in the Departments of Pathology, Lab Medicine and Transfusion Medicine, were enrolled after exclusion of rejection criteria. The rejection criteria included subjects between 18 and 64 years, history of renal disorder, cardiac, chronic respiratory, liver diseases, malabsorption syndromes, malignancies, hypertension, diabetes mellitus, and hematological disorders which included anemia's, history of medication (analgesic, anticoagulant, iron supplements, oral contraceptives, antimetabolites, thyroxine, insulin alcohol, or tobacco). The institutional standard operating procedures were followed for the sample collection and for conducting the tests.
Complete blood counts (CBCs) were performed from the venous blood samples in ethylenediaminetetraacetic acid tubes. The samples were run in CBC + reticulocyte mode on the Sysmex XE-2100 hematology analyzer within 2 h of collection. Values of Platelet count, PDW, MPV, PCT, IPF, H-IPF, P-LCR, and PLT-X (ch) were noted and the results were compiled and analyzed.
Three levels of internal quality controls provided by Sysmex, Japan were run daily as part of internal quality control. In addition, two normal samples were run 20 times to determine within run precision (reproducibility). Low platelet count samples (platelet counts of 50 × 10 3 /cu mm and between 10 and 50 10 3 /cu mm) were run 10 times to determine coefficient of variation (CV)% for IPF. The mean normal and reference interval for the population in the study were calculated using Clinical and Laboratory Standards Institute (CLSI) guidelines.
All tests were performed using SPSS(Statistical Product and Service Solutions , developed by IBM corporation), version 13. The parameters with normal distribution were expressed as mean, standard deviation, and standard error of the mean. Comparisons of mean between males and females were performed with Student's t-test. Inter-correlations between parameters were computed through the Pearson's correlation analysis. P < 0.05 was accepted as statistical significant Biological reference interval. The normal reference range was calculated using the CLSI guidelines. Normal upper and lower limits were defined using mean ± 1.96 standard error (SE) (95% confidence interval for mean) respectively.
| Results|| |
The analysis was carried out in 945 subjects comprising of 881 males (93.23%) and 64 females (6.77%). The mean ± SE age was 32.44 ± 9.03 (18-64) and 35.42 ± 9.17 (20-58) in males and females, respectively. The biological reference intervals analyzed for PLT, PDW, MPV, PCT, IPF, H-IPF, P-LCR, and PLT-X (ch) in both subjects have been depicted in [Table 1]. The mean ± standard deviation (normal range) in both subjects for various parameters were: PLT 251252.9 ± 57748.7 (150-520 × 10 3 /cu mm), IPF 2.199 ± 1.499 (0.3-8.7%), PDW 14.54 ± 3.10 (8.3-25.0 fL), MPV 11.70 ± 1.32 (8.6-15.5 fL), PCT 0.2883 ± 0.059 (0.15-0.62%), H-IPF 0.584 ± 0.46 (0.1-3.9%), P-LCR 38.5 ± 10.9 (11.9-66.9%) and PLT-X 15.5 ± 2.16 (11.0-22.0) [Table 1].
To determine the relation between (i) platelet count with IPF, PDW, MPV, H-IPF, P-LCR, and PLT-X; (ii) PCT with IPF, PDW, MPV, H-IPF, and PLT-X; (iii) IPF/H-IPF, within them and with platelet count, PDW, MPV, H-IPF, P-LCR, and PLT-X; (iv) PDW and IPF, MPV, H-IPF, P-LCR, PLT-X and (v) P-LCR and PLT-X, within them and PLT count, PCT, PDW, MPV, IPF, and H-IPF; Pearson's correlation analysis test was applied.
A negative correlation was observed between PLT (r = –0.468 to r = –0.531; P < 0.001) and PCT (r = –0.080 to r = –0.235; P < 0.05 to P < 0.001) with IPF [Figure 1]a and c], PDW, MPV, H-IPF, P-LCR, and PLT-X. IPF/H-IPF showed a positive correlation among them [Figure 2]a] and also with PDW [Figure 1]b], MPV [Figure 1]d], P-LCR [Figure 2]b], PLT-X [Figure 2]c] (r = +0.662 to r = +0.925; P < 0.001). Positive correlation was also observed between PDW and MPV, IPF, H-IPF, P-LCR, PLT-X (r = +0.707 to r = +0.969, P < 0.001) and between MPV with PDW, IPF, H-IPF, P-LCR, PLT-X (r = +0.686 to r = +0.969, P < 0.001) [Table 2]. P-LCR and PLT-X showed a negative correlation between platelet count and PCT (r = –0.080 to r = –0.509, P < 0.05 to P < 0.001) and positive correlation among them and with PDW, MPV, IPF, H-IPF, P-LCR, and PLT-X (r = +0.662 to r = +0.996; P < 0.001) [Table 2], no statistical significance was found between male and female subgroups.
|Figure 1: (a) Negative correlation between Platelet and immature platelet fraction (IPF); (b) positive correlation between platelet distribution width and IPF; (c) negative correlation between plateletcrit and IPF; (d) positive correlation between mean platelet volume and IPF;|
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|Figure 2: (a) Positive correlation between high immature platelet fraction (H-IPF) and IPF; (b) positive correlation etween platelet large cell ratio and IPF; (c) positive correlation between Platelet - X and IPF|
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The linear regression analysis of different study variables PLT, PDW, MPV, PCT, H-IPF, P-LCR and PLT-X with IPF has been depicted in [Table 3]. Higher the r2 × 100 values, greater are the chances of better correlations between the parameters. This also indicates the chances of change in the value of one in relation to the value of other. Change maximum with H-IPF and minimum with PCT. H-IPF, PLT-X, PDW, MPV, and P-LCR show more chances of change in relation to IPF and you can predict the change in their value in relation to IPF, e.g., 85.5% with H-IPF, 83.4% with PLT-X, PDW, etc. PCT have minimum relation though it is showing significance in the inter-correlation.
|Table 2: Inter-correlations between platelet paradigms in Indian subjects|
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Within run reproducibility of two normal samples showed a variation of 19 and 14%, respectively for IPF (target CV% <25%). In precision studies for low platelet counts of 50 × 10 3 /cu mm and IPF >3%, CV% of 14% was achieved (target <25%). In precision studies for low platelet counts of 10000-50000 cu mm and IPF >10%, CV% of 17.7% was achieved (target <25%) [Table 4].
|Table 3: Linear regression analysis of different study variables with IPF|
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|Table 4: Within run precision on two samples and allowable CV% for different parameters|
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| Discussion|| |
With the increasing use of these novel parameters, their role in various clinical conditions is being evaluated. IPF in particular has a role in determining marrow megakaryocytic response and peripheral platelet destruction. IPF is measured in reticulocyte mode using a fluorescent dye and a carefully designed gating system. Immature platelets are 1-2 days old, larger than mature platelets, and contain a lot of ribonucleic acid [Figure 3].  IPF is raised when there is peripheral platelet destruction causing thrombocytopenia (e.g., immune thrombocytopenia [ITP]). A decrease in IPF is noted when there is decreased production in the marrow. Low IPF suggests depressed bone marrow function or impending platelet recovery (hypoplasia/aplasia) and may precede recovery by several days. Low IPF is also a predictor of decreased megakaryopoiesis in sepsis.  Raised IPF predicts imminent platelet recovery following chemotherapy and may precede the platelet recovery by 24-48 h.  It is also raised in peripheral destruction in ITP and other disorders. IPF has an advantage, that it is not impacted by platelet transfusions, thus acting as a reliable marker.  Studies have also shown IPF to be an important prognostic marker in acute coronary syndromes.  Increase in IPF is also associated with hypo responsiveness of clopidogrel.  Cesari et al. observed mean IPF value as 2.9% which was similar to our value of 2.2%.  However, the range noted by Cesari et al. was 1.9-4.1%, which was more narrow than our range of 0.3-8.7%.
|Figure 3: Description of immature platelet fraction and reticulated platelets on a graph of Sysmex XE-2100|
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Other platelet parameters such as MPV, PDW, and PCT have an association with pulmonary tuberculosis (TB). High values correlate with acute phase reactants in TB. 
Platelet volume heterogeneity occurs during its production and its maturation occurs in the bone marrow. MPV depends on the degree of stimulation of megakaryocyte dependent on thrombopoietic stress and deoxyribonucleic acid content.  MPV is the median thrombocyte volume between upper and lower discriminator. It is a calculated parameter (PCT %/platelet count × 10 3 /μL). Our MPV range was 8.59-15.49 fL. Our value is slightly higher to that obtained by Demirin et al. and Aydogan et al. , Demirin et al. observed a range of 7.2-11.7 fL and noted that patients with higher values may have a higher incidence of arterial occlusive disease. Aydogan et al. observed a value of 7.7-12.1 fL. This is an important point which must be kept in mind for our Indian population as both males and females have shown higher range. Since the samples were analyzed strictly within 2 h, so increase in volume due to storage was excluded.
PDW or PDW is the distribution curve of platelets (fL) measured in 20% relative height with a total curve height of 100%. It is a measure of platelet anisocytosis. Our range is 8.29-25.00 fL. Aydogan et al. observed the reference value as 16.0-20.6 fL.  A high PDW is an indicator of coronary total occlusion (CTO). Vatankulu et al. observed that a PDW value of more than 15.7% demonstrated a sensitivity of 64% and specificity of 66% for CTO.  Positive significant correlation of PDW was observed with MPV, H-IPF, P-LCR, and PLT-X; IPF with PDW, MPV, H-IPF, P-LCR, and PLT-X in our Indian population. Increase of MPV and PDW comparatively suggests that young platelets are released into circulation. In the study by Aydogan et al., it was observed that the MPV and PDW values were higher in perforated appendicitis cases when compared to nonperforated cases.  They suggested that these parameters could take the physicians a step further in diagnosis of suspicious cases.
| Conclusion|| |
These novel platelet parameters offer newer avenues in research and clinical use. For IPF, the biological reference interval in our study is 0.3-8.7%, respectively. There was little or no change in other platelet parameters between them. Newer role of other parameters will be discovered in future studies. This study aims to define reference ranges in the Indian sub-continent along with giving a negative and positive correlation between the platelet parameters. Having a normal range would help determine true high and low values and thereby guide diagnosis and help plan treatment strategies.
| Acknowledgment|| |
The team members of blood bank and the hematology lab including Nixon Joseph, Divyajyoti Srivastava, Hemant Rawat, Silas Robinson.
Our chairman Dr. Vijay Kher and specialthanks to our mentor and inspiration, our CMD, Dr. Naresh Trehan.
| References|| |
|1.||Aydogan A, Akkucuk S, Arica S, Motor S, Karakus A, Ozkan OV, et al. The Analysis of Mean Platelet Volume and Platelet Distribution Width Levels in Appendicitis. Indian J Surg: 2 - 12. Available from Springerlink: http://link.springer.com/article/10.1007/s12262-013-0891-7. [Last accessed on 2013 Mar 7]. |
|2.||Cesari F, Marcucci R, Gori AM, Caporale R, Fanelli A, Casola G, et al. Reticulated platelets predict cardiovascular death in acute coronary syndrome patients. Insights from the AMI-Florence 2 Study. Thromb Haemost 2013;109:846-53. |
|3.||Cremer M, Weimann A, Szekessy D, Hammer H, Bührer C, Dame C. Low immature platelet fraction suggests decreased megakaryopoiesis in neonates with sepsis or necrotizing enterocolitis. J Perinatol 2013;33:622-6. |
|4.||Have LW, Hasle H, Vestergaard EM, Kjaersgaard M. Absolute immature platelet count may predict imminent platelet recovery in thrombocytopenic children following chemotherapy. Pediatr Blood Cancer 2013;60:1198-203. |
|5.||Bat T, Leitman SF, Calvo KR, Chauvet D, Dunbar CE. Measurement of the absolute immature platelet number reflects marrow production and is not impacted by platelet transfusion. Transfusion 2013;53:1201-4. |
|6.||Ibrahim H, Nadipalli S, DeLao T, Guthikonda S, Kleiman NS. Immature platelet fraction (IPF) determined with an automated method predicts clopidogrel hyporesponsiveness. Thromb Thrombolysis 2012;33:137-42. |
|7.||Sahin F, Yazar E, Yýldýz P. Prominent features of platelet count, plateletcrit, mean platelet volume and platelet distribution width in pulmonary tuberculosis. Multidiscip Respir Med 2012;7:38. |
|8.||Demirin H, Ozhan H, Ucgun T, Celer A, Bulur S, Cil H, et al. Normal range of mean platelet volume in healthy subjects: Insight from a large epidemiologic study. Thromb Res 2011;128:358-60. |
|9.||Vatankulu MA, Sonmez O, Ertas G, Bacaksiz A, Turfan M, Erdogan E, et al. A new parameter predicting chronic total occlusion of coronary arteries: Platelet distribution width. Angiology 2014;65:60-4. |
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Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4]