Diagnostic Performance of Mean Platelet Volume in the Diagnosis of Acute Myocardial Infarction A Meta-Analysis

Main Article Content

Kathrina Aseanne Acapulco
Shayne Julieane Morales
Tzar Francis Verame


Objective. The aim of this systematic review and meta-analysis is to determine summary estimates of the diagnostic accuracy of mean platelet volume for the diagnosis of myocardial infarction among adult patients with angina and/or its equivalents in terms of sensitivity, specificity, diagnostic odds ratio, and likelihood ratios.

Methodology. The primary search was done through search in electronic databases. Cross-sectional, cohort, and case-control articles studying the diagnostic performance of mean platelet volume in the diagnosis of acute myocardial infarction in adult patients were included in the study. Eligible studies were appraised using well-defined criteria.

Results. The overall mean MPV value of those with MI (9.702 fl; 95% CI 9.07 – 10.33) was higher than in those of the non-MI control group (8.85 fl; 95% CI 8.23 – 9.46). Interpretation of the calculated t-value of 2.0827 showed that there was a significant difference in the mean MPV values of those with MI and those of the non-MI controls. The summary sensitivity (Se) and specificity (Sp) for MPV were 0.66 (95% CI; 0.59 - 0.73) and 0.60 (95% CI; 0.43 – 0.75), respectively. The pooled diagnostic odds ratio (DOR) was 2.92 (95% CI; 1.90 – 4.50). The positive likelihood ratio of MPV in the diagnosis of myocardial infarction was 1.65 (95% CI; 1.20 – 22.27), and the negative likelihood ratio was 0.56 (95% CI; 0.50 – 0.64).

Conclusion. The intended role for MPV in the diagnostic pathway of myocardial infarction would perhaps be best as a triage tool. MPV values can discriminate between those who have MI and those without. For a patient with angina presenting with elevated MPV values, it is 1.65 times more likely that he has MI. It is implied that the decision to treat a patient with angina or its equivalents as a case of MI could be supported by an elevated MPV value.


Download data is not yet available.

Article Details

How to Cite
Acapulco, K. A., Morales, S. J., & Verame, T. F. (2020). Diagnostic Performance of Mean Platelet Volume in the Diagnosis of Acute Myocardial Infarction: A Meta-Analysis. Philippine Journal of Pathology, 5(2), 34-46. https://doi.org/10.21141/PJP.2020.11
Original Articles
Author Biographies

Kathrina Aseanne Acapulco, Perpetual Succour Hospital, Cebu City

Department of Pathology

Shayne Julieane Morales, Perpetual Succour Hospital, Cebu City

Department of Pathology

Tzar Francis Verame, Perpetual Succour Hospital, Cebu City

Department of Pathology


1. World Health Organization. Cardiovascular Diseases. Available from https://www.who.int/health-topics/cardiovascular-diseases/#tab=tab_1.

2. Amsterdam EA, Wenger NK, Brindis RG, et al. 2014 AHmetandoA/ACC guideline for the management of patients with non–ST-elevation acute coronary syndromes:executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;130(25):2354-94. https://www.ncbi.nlm.nih.gov/pubmed/25249586. https://doi.org/10.1161/CIR.0000000000000133.

3. Lippi G, Filippozzi L, Salvagno GL, et al. Increased mean platelet volume in patients with acute coronary syndromes. Arch Pathol Lab Med. 2009;133(9):1441-3. https://www.ncbi.nlm.nih.gov/pubmed/19722752. https://doi.org/10.1043/1543-2165-133.9.1441.

4. Mirzaie AZ, Abolhasani M, Ahmadinejad B, Panahi M. Platelet count and MPV, routinely measured but ignored parameters used in conjunction with the diagnosis of acute coronary syndrome: single study center in Iranian population, 2010. Med J Islam Repub Iran. 2012;26(1):17-21. https://www.ncbi.nlm.nih.gov/pubmed/23482685. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3587888.

5. Demirin H, Ozhan H, Ucgun T, et al. Normal range of mean platelet volume in healthy subjects: insight from a large epidemiologic study. Thromb Res. 2011;128(4):358-60. https://www.ncbi.nlm.nih.gov/pubmed/21620440. https://doi.org/10.1016/j.thromres.2011.05.007.

6. Latger-Cannard V, Hoarau M, Salignac S, Baumgart D, Nurdem P, Lecompte T. Mean platelet volume: comparison of three analysers towards standardization of platelet morphological phenotype. Int J Lab Hematol.2012;34(3):300-10. https://www.ncbi.nlm.nih.gov/pubmed/22225539. https://doi.org/10.1111/j.1751-553X.2011.01396.x.

7. Chu H, Chen WL, Huang CC, et al. Diagnostic performance of mean platelet volume for patients with acute coronary syndrome visiting an emergency department with acute chest pain: the Chinese scenario. Emerg Med J. 2011;28)7):569-74. https://www.ncbi.nlm.nih.gov/pubmed/20650916. https://doi.org/10.1136/emj.2010.093096.

8. Harbord RM, Whiting P. Metandi: meta-analysis of diagnostic accuracy using hierarchical logistic regression. The Stata Journal. 2009;9:211-29. https://journals.sagepub.com/doi/pdf/10.1177/1536867X0900900203.

9. Wang J, Leeflang M. Recommended software/packages for meta-analysis of diagnostic accuracy. J Lab Precis Med. 2019;4:22.

10. Campbell JM, Klugar M, Ding S, et al. Chapter 9: Diagnostic test accuracy systematic reviews. In: Aromataris E, Munn Z, eds. JBA Manual for evidence synthesis. JBI; 2020. Available from https://synthesismanual.jbi.global. https://doi.org/10.46658/JBIMES-20-10.

11. Macaskill P, Gatsonis C, Deeks J, Harbord R, Takwoingi Y. Chapter 10: Analysing and presenting results. In: Deeks JJ, Bossuyt PM, Gatsonis C, eds. Version 1.0. Cochrane handbook for systematic reviews of diagnostic test accuracy. London: The Cochrane Collaboration; 2010. Available from http://srdta.cochrane.org/.

12. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis: statistical meta-analysis
with applications. UK: John Wiley and Sons Ltd.;2009.

13. Bossuyt PM, Davenport C, Deeks J, Hyde C, Leeflang M, Scholten R. Chapter 11: Interpreting results and drawing conclusions. In: Deeks JJ, Bossuyt PM, Gatsonis C, eds, Cochrane handbook for systematic reviews of diagnostic test accuracy version 0.9. The Cochrane Collaboration; 2013. Available from: http://srdta.cochrane.org/.

14. Assiri, Abdullah S., et al. Diagnostic importance of platelet parameters in patients with acute coronary syndrome admitted to a tertiary care hospital in southwest region. Saudi Arabia. J Saudi Heart Assoc. 2012; 24(1): 17-21. https://www.ncbi.nlm.nih.gov/pubmed/23960663. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3727553. https://doi.org/10.1016/j.jsha.2011.08.004.

15. Cemin R, Donazzan L, Lippi G, Clari F, Daves M. Blood cells characteristics as determinants of acute myocardial infarction. Clin Chem Lab Med. 2011;49(7):1231-6. https://www.ncbi.nlm.nih.gov/pubmed/21534844. https://doi.org/10.1515/CCLM.2011.183.

16. Dehghani M R, Taghipour-Sani L, Rezaei Y, Rostami R. Diagnostic importance of admission platelet volume
indices in patients with acute chest pain suggesting acute coronary syndrome. Indian Heart J. 2014;66(6):622-
8. https://www.ncbi.nlm.nih.gov/pubmed/25634396. https://www.ncbi.nlm.nih.gov/mc/articles/PMC4310955. https://doi.org/10.1016/j.ihj.2014.10.415.

17. Huang HL, Chen CH, Kung CT, et al. Clinical utility of mean platelet volume and immature platelet fraction in acute coronary syndrome. Biomed J. 2019;42(2):107-15. https://www.ncbi.nlm.nih.gov/pubmed/31130246. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541877. https://doi.org/10.1016/j.bj.2018.12.005.

18. Kamińska J, Koper OM, Siedlecka-Czykier E, Matowicka-Karna J, Bychowski J, Kemona H. The utility of inflammation and platelet biomarkers in patients with acute coronary syndromes. Saudi J Biol Sci. 2018;25(7):1263-71. https://www.ncbi.nlm.nih.gov/pubmed/30505168. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252018. https://doi.org/10.1016/j.sjbs.2016.10.015.

19. Khode V, Sindhur J, Kanbur D, Ruikar K, Nallulwar S. Mean platelet volume and other platelet volume indices in patients with stable coronary artery disease and acute myocardial infarction: a case control study. J Cardiovasc Dis Res. 2012;3(4):272-5. https://www.ncbi.nlm.nih.gov/pubmed/23233769. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3516005. https://doi.org/10.4103/0975-3583.102694.

20. Kiliçli-Çamur N, Demirtunc C, Konuralp C, Eskiser A, Basaran Y. Could mean platelet volume be a predictive marker for acute myocardial infarction? Medical Science Monitor. 2005;11(8):CR387-92.

21. Özlü MF, Öztürk S, Ayhan SS, et al. Predictive value of mean platelet volume in young patients with non- ST-segment elevation acute coronary syndromes: a retrospective observational study. Anadolu Kardiyol Derg. 2013;13(1):57-61. https://www.ncbi.nlm.nih.gov/pubmed/23086804. https://doi.org/10.5152/akd.2013.007.

22. Şenaran H, Ileri M, Altinbas A. et al. Thrombopoietin and mean platelet volume in coronary artery disease. Clin Cardiol. 2001;24(5):405-8. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6655056/pdf/CLC-24-405.pdf.

23. Wang X, Xu XL, Li XM, Zhao R, Yang X, Cong HL. Diagnostic value of mean platelet volume combined with troponin I for acute coronary syndrome. Am J Med Sci. 2016;352(2):159-65. https://www.ncbi.nlm.nih.gov/pubmed/27524214. https://doi.org/10.1016/j.amjms.2016.04.014.

24. Yaghoubi A, Golmohamadi Z, Alizadehasi A, Azarfarin R. Role of platelet parameters and haematological indices in myocardial infarction and unstable angina. J Pak Med Assoc. 2013;63(9):1133-7. https://www.ncbi.nlm.nih.gov/pubmed/24601192.

25. Yilmaz MB, Gokhan C, Guray Y, et al. Role of mean platelet volume in triagging acute coronary syndromes. J Thromb Thrombolysis. 2008;26(1):49-54. https://www.ncbi.nlm.nih.gov/pubmed/17705053. https://doi.org/10.1007/s11239-007-0078-9.

26. Buoro S, Seghezzi M, Manenti B, et al. Biological variation of platelet parameters determined by the Sysmex XN hematology analyzer. Clin Chim Acta. 2017;470:125–32. https://www.ncbi.nlm.nih.gov/pubmed/28479317. https://doi.org/10.1016/j.cca.2017.05.004.

27. Akobeng AK. Understanding diagnostic tests 2: likelihood ratios, pre-and post-test probabilities and their use in clinical practice. Acta Paediatr. 2007;96(4):487-91. https://www.ncbi.nlm.nih.gov/pubmed/17306009. https://doi.org/10.1111/j.1651-2227.2006.00179.x.

28. Cho SY, Lee HJ, Lee W-I, Park TS. Mean platelet volume according to the ethnic difference. Int J Lab Hematol. 2014;36(5);587-8. https://www.ncbi.nlm.nih.gov/pubmed/24206452. https://doi.org/10.1111/ijlh.12162.

29. Korniluk A, Koper-Lenkiewicz OM, Kamińska J, Kemona H, Dymicka-Piekarska V. Mean platelet volume (MPV): new perspectives for an old marker in the course and prognosis of inflammatory conditions. Mediators Inflamm. 2019: 9213074. https://www.ncbi.nlm.nih.gov/pubmed/31148950. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6501263. https://doi.org/10.1155/2019/9213074.

30. Noris P, Melazzini F, Balduini CL. New roles for mean platelet volume measurement in the clinical practice? Platelets. 2016;27(7):607-12. https://ncbi.nlm.nih.gov/pubmed/27686008. https://doi.org/10.1080/09537104.2016.1224828.

31. Schünemann H, Brożek J, Guyatt G, Oxman A. GRADE handbook for grading quality of evidence and strength of recommendations. Updated October 2013. The GRADE Working Group; 2013. Available from https://gdt.gradepro.org/app/handbook/handbook.html.

32. Bradburn MJ, Deeks JJ, Altman DG. Metan-an alternative meta-analysis command. Stata Technical Bulletin. 1999;8(44). https://econpapers.repec.org/article/tsjstbull/y_3a1999_3av_3a8_3ai_3a44_3asge24.htm.