Mean platelet volume is decreased in HIV-infected women




HIV infection is associated with higher than expected cardiovascular event rates and lowered platelet counts. These conditions are associated with an elevation of mean platelet volume (MPV). The present study compared MPV in HIV-infected and uninfected women and identified factors influencing MPV values in HIV-infected women.


A total of 234 HIV-infected and 134 HIV-uninfected participants from the Women's Interagency HIV Study (WIHS) had MPV values obtained. HIV-infected women were older, were more likely to have diabetes and had higher triglyceride levels than HIV-uninfected women.


The mean platelet count was lower in HIV-infected vs. uninfected women [249 cells/μL (95% confidence interval (CI) 238, 259 cells/μL) vs. 276 cells/μL (95% CI 265, 287 cells/μL), respectively; P < 0.01]. Adjusted mean MPV values were lower in the HIV-infected than in the uninfected group [8.66 fL (95% CI 8.52, 8.79 fL) vs. 9.05 fL (95% CI 8.87, 9.24 fL), respectively]. In multiple regression analysis, after adjusting for other covariates, MPV was positively associated with platelet count, and negatively with HIV infection (model R2 = 0.20; P < 0.01). In multiple regression analysis confined to HIV-infected women, a lower MPV was independently associated with a history of AIDS-defining illness (R2 = 0.28; P = 0.03), but not with nadir CD4 count or highly active antiretroviral therapy (HAART) use.


HIV-infected women had lower MPV values than uninfected women, suggesting impaired production rather than increased destruction. Higher than expected cardiovascular event rates cannot be attributed to greater platelet reactivity as measured by MPV.


Mean platelet volume (MPV) is a laboratory measure of platelet size that has long been routinely reported as part of complete blood counts [1-4]. Historically, this measure has been used to help differentiate the various causes of thrombocytopenia. As the size of immature platelets is larger than that of senescent platelets, decreased MPV generally indicates marrow underproduction, including aplastic anaemia, whereas higher MPV generally signifies high destruction in diseases such as immune thrombocytopenic purpura, pre-eclampsia and sepsis [1-4].

MPV has also been implicated as a marker of platelet reactivity, as larger platelet size has been correlated with greater activation, measured by a variety of techniques including those quantifying aggregation, thromboxane synthesis and beta-thromboglobulin release [5-8]. MPV is inversely correlated with platelet phospholipid (PL) omega-3 polyunsaturated fatty acid (PUFA) composition and glycoprotein IIb−IIIa receptor number [9, 10]. The role of platelet activation and aggregation contributing to thrombus formation after plaque rupture has led to multiple studies examining the prognostic value of MPV with regard to cardiovascular and cerebrovascular disease states [11-13]. MPV is increased in the presence of atherosclerosis and cardiovascular risk factors [14-16]. MPV is also increased in the presence of acute stroke, myocardial infarction and acute coronary syndromes [17-19]. Higher MPV is predictive of greater left ventricular dysfunction as well as secondary cardiovascular events and poorer outcomes following myocardial infarction [11-13, 20]. Accordingly, MPV has been implicated as a marker of cardiovascular risk.

Over the past decade, there has been growing concern over an increased risk of cardiovascular events in HIV-infected patients [21, 22]. HIV-infected persons have been observed to have higher than expected rates of myocardial infarction and stroke [21, 22]. While the use of highly active antiretroviral therapy (HAART) has resulted in improved survival, various diseases have been reported to worsen cardiovascular risk factors, including hypertension, diabetes, hyperlipidaemia and metabolic syndrome, and to contribute to higher cardiovascular risk. Also, platelet counts are lowered in the setting of HIV infection, even during treatment [23]. Despite both cardiovascular disease and thrombocytopenia being common in this patient population, there are few data pertaining to MPV in the setting of HIV infection. Accordingly, the objectives of the present study were to compare MPV in HIV-infected and uninfected women and to identify those factors associated with alterations in MPV in these patients.

Materials and methods

Study population

The study was conducted in a sample of participants from the Women's Interagency HIV Study (WIHS), an ongoing multicentre observational cohort study of HIV disease in women. From the original cohort of HIV-infected and high-risk HIV-uninfected women recruited at six centres across the USA (Brooklyn, Bronx, Chicago, Los Angeles, San Francisco, and Washington, DC) between 1994 and 2011, 368 women from SUNY Downstate Medical Center in Brooklyn were included in this analysis. The study was approved by the Institutional Review Board. Women eligible for enrolment in the WIHS were 13 years of age or older, gave informed consent, completed an interviewer-assisted questionnaire in English or Spanish, had a physical and gynaecological examination, underwent blood collection and attended study visits every 6 months. The standardized interview-based questionnaire collected information regarding sociodemographics, access to care information, chronic illness, behaviours associated with HIV acquisition, medications, HIV treatment, and disease characteristics. Data were collected in a cross-sectional manner between WIHS visits 20 and 33 (April 2004 to March 2011). Since MPV values had not been routinely entered into the WIHS database, individual MPV values were retrieved from archived laboratory records available from this time period. Laboratory values were obtained on or as close as possible to the dates of patient's visit and a single laboratory value for each parameter was included in the statistical analysis for every patient.

Outcome classification

Laboratory tests conducted using standard WIHS protocols on blood collected at the study visit were used to generate values for HIV serostatus, fasting glucose, low-density lipoprotein cholesterol (LDL-C), and platelet and CD4 counts. HIV serostatus was determined using the Food and Drug Administration (FDA)-approved enzyme-linked immunosorbent assay testing and, if reactive, confirmed with the FDA-approved western blot HIV-1 confirmatory assay. Diabetes was defined as a fasting blood glucose value of > 126 mg/dL or a self-reported diagnosis of diabetes or treatment of diabetes with medications. LDL-C was estimated from the Friedewald equation [24].

Platelet measurements were performed using an automated laser-optical Siemens Advia 2120 (Siemens, Munich, Germany) counter that provided platelet count and MPV (in fL). The Siemens Advia 2120 counters perform a two-dimensional platelet analysis. The volume and refractive index of effectively sphered individual platelets are simultaneously determined on a cell-by-cell basis by measuring two angles of laser light scatter. These two scatter measurements are converted into volume (platelet size) using the Mie theory of light scattering for homogeneous spheres. EDTA was used as an anticoagulant and samples were tested within 4−30 h. An elevated mean platelet volume was defined as > 11.5 fL and a low value as < 7.5 fL, adjusting for the platelet count (Siemens Advia 2120). Day-to-day variability was previously assessed in 52 subjects who had platelet determinations on two consecutive days without a significant change in platelet count. The intraclass correlation coefficient was 0.94 [95% confidence interval (CI) 0.91, 0.96].

Risk factor classification

Data on body mass index (BMI) and blood pressure (BP) were obtained from clinical examinations. Anthropometric measurements of height and weight were performed according to the Third National Health and Examination Survey (NHANES III) procedures [25]. BMI was calculated based on measured weight and height and was classified as underweight (< 18.5 kg/m2), normal (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), and obese (≥ 30.0 kg/m2). Hypertension was defined as either measured systolic BP > 140 mm Hg or diastolic BP > 90 mm Hg or a self-reported diagnosis of hypertension with use of antihypertensive medications.

The WIHS semiannual visits include medical history and health behaviour questionnaires, assessments of medication use, standardized clinical and laboratory measurements, and phlebotomy. Race/ethnicity was self-reported at baseline. Information regarding cigarette smoking, the occurrence of an AIDS-defining illness (ADI), and highly active antiretroviral therapy (HAART) is collected routinely at each study visit via self-report. History of an ADI was defined as a prior report of conditions consistent with the 1993 Centers for Disease Control and Prevention surveillance definition. HIV status, RNA viral load and CD4 lymphocyte counts were determined at the time of the WIHS visit. HAART was defined as self-reported therapy being taken at the time of data collection.

Statistical methods

Continuous variables are reported as mean ± standard deviation (SD). Student's t-tests were used to determine the significance of differences in means. Pearson's χ2 test statistic was used to assess differences in proportions for dichotomous and categorical variables; if the expected frequencies within a cell were small (i.e. n < 5) then Fisher's exact test was used. Spearman's correlation coefficient was used to assess univariate relationships between scored variables. Simple and multiple linear regression models were used to predict MPV from clinical risk factors, HIV status, race, BMI category, smoking, hypertension, diabetes, platelet count and low-density lipoprotein cholesterol levels. In HIV-infected women, further linear regression models were used to predict MPV from HIV-specific variables, nadir CD4 count, history of an ADI (defined as a prior report of conditions consistent with the 1993 Centers for Disease Control and Prevention surveillance definition) and current use of HAART, in addition to clinical risk factors, race, BMI category, smoking, hypertension, diabetes, platelet count and low-density lipoprotein cholesterol levels. MPV values were square-root-transformed to correct mild skew of distribution. Loess plots were used to examine the univariate relationships of the continuous predictors platelet count, low-density lipoprotein cholesterol, viral load and CD4 count nadir with the transformed dependent variable. Viral load was positively skewed and was log10- transformed. Both platelet and nadir CD4 counts as predictors of MPV appeared to exhibit a change of slope near counts of 350 cells/μL, so piecewise linear response surfaces for platelet and nadir CD4 counts were constructed, to allow slopes to change at 350 cells/μL. Inspection of model residuals was conducted to detect skew and outliers. A P-value < 0.05 was used to guide interpretation. All analyses were performed using spss version 20 (IBM, Armonk, NY).


A total of 368 women with records of MPV values were enrolled in the study, of whom 234 were HIV-infected and 134 were uninfected. No patient was known to have idiopathic or thrombotic thrombocytopenic purpura. HIV-infected women were older, were more likely to have diabetes, and had higher triglyceride levels than HIV-uninfected women (Table 1). The mean platelet count was lower in HIV-infected than uninfected women [249 cells/μL (95% CI 238, 259 cells/μL) vs. 276 cells/μL (95% CI 265, 287 cells/μL), respectively; P < 0.01]. The bivariate relationship between platelet count and MPV is shown in Figure 1. In multiple regression analysis, in addition to lower platelet counts (β = −0.54 for < 350 cells/μL; P < 0.01), adjusted mean MPV was lower in the HIV-infected than in the uninfected group [adjusted means 8.66 fL (95% CI 8.52, 8.79 fL) vs. 9.05 fL (95% CI 8.87, 9.24 fL), respectively; β = −0.17; P < 0.01; R2 = 0.20; P < 0.01 for model]. An association between being underweight and having higher MPV did not reach statistical significance (P = 0.07). The same multivariate analysis was repeated after exclusion of subjects with thrombocytopenia (< 150 cells/mL) and the results remained unchanged.

Figure 1.

The relationship between mean platelet volume and platelet count in the Women's Interagency HIV Study (WIHS).

Table 1. Characteristics of HIV-infected and -uninfected participants in the Women's Interagency HIV Study (WIHS)
CharacteristicHIV-infected women (n = 234)HIV-uninfected women (n = 134)P-valuea
  1. BP, blood pressure; CI, confidence interval; HAART, highly active antiretroviral therapy; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SD, standard deviation.
  2. aP-values for differences in means were calculated using t-test statistics. P-values for differences in proportions were calculated using Pearson's χ2 test statistic unless the cells had n < 5; then Fisher's exact test was used.
  3. bFor body mass index (BMI), underweight is < 18.5 kg/m2, normal is 18.5–24.9 kg/m2, overweight is 25.0–29.9 kg/m2, and obese is ≥ 30.0 kg/m2.
  4. cAn AIDS-defining illness (ADI) is a prior report of conditions consistent with the 1993 Centers for Disease Control and Prevention surveillance definition.
  5. dExpressed as an adjusted mean value.
Age (years) (mean ± SD)41.0 ± 8.636.1 ± 10.6< 0.01
Race/ethnicity [n (%)]  0.18
African American175 (74.8)108 (80.6) 
Hispanic36 (15.4)20 (14.9) 
White/other23 (9.8)6 (4.5) 
BMI [n (%)]b  0.20
Underweight8 (3.4)3 (2.2) 
Normal BMI84 (35.9)36 (26.9) 
Overweight68 (29.1)40 (29.9) 
Obese74 (31.6)55 (41) 
Current smoker [n (%)]108 (46.2)52 (38.8)0.17
Systolic BP (mm Hg) (mean ± SD)119 ± 17118 ± 170.68
Hypertension [n (%)]57 (24.4)31 (23.1)0.79
Diabetes [n (%)]33 (14.1)30 (22.4)0.04
Total cholesterol (mg/dL) (mean ± SD)174 ± 38176 ± 400.65
HDL cholesterol (mg/dL) (mean ± SD)50 ± 6284 ± 410.46
Triglycerides (mg/dL) (mean ± SD)127 ± 7184 ± 41< 0.01
LDL cholesterol (mg/dL) (mean ± SD)103 ± 35105 ± 340.56
CD4 count [n (%)]   
≥ 500 cells/μL109 (46.6) 
200–499 cells/μL84 (35.9) 
< 200 cells/μL41 (17.5) 
History of an ADI [n (%)]c128 (54.7) 
Current HAART [n (%)]197 (84.2) 
Platelet count (cells/μL) (mean ± SD)249 ± 80276 ± 66< 0.01
Platelet volume (fL) [mean (95% CI)]d8.66 (8.52, 8.79)9.05 (8.87, 9.24)< 0.01

In multiple regression analysis confined to HIV-infected women, a history of an ADI [adjusted mean 8.59 fL (95% CI 8.39, 8.78 fL) vs. 8.93 fL (95% CI 8.71, 9.15 fL) for no history of ADI; P = 0.03] was associated with significantly lower MPV, whereas smoking (P = 0.01) and being underweight (P = 0.03) were associated with higher MPV values (R2 = 0.28; P < 0.01 for model). There were no significant relationships between MPV and HAART use, nadir CD4 count or viral load (Table 2). As an association has, controversially, been reported to exist between abacavir and platelet function, the potential relationship between abacavir use and MPV was further assessed. Among HIV-infected subjects, 45 were taking abacavir and 189 were not. Square-root transformed values of MPV were similar between the two groups [mean 2.96 (SD 0.20) vs. 2.94 (SD 0.17), respectively; P = 0.53]. Inclusion of abacavir (β = −0.014; P = 0.64) in the multivariate model did not significantly change the model.

Table 2. Results of multiple linear regression with mean platelet volume as the dependent variable
 βP-valueβ (HIV-infected)P-value (HIV-infected)
  1. HAART, highly active antiretroviral therapy; LDL, low-density lipoprotein.
  2. aFor body mass index (BMI), underweight is < 18.5 kg/m2, normal is 18.5–24.9 kg/m2, overweight is 25.0–29.9 kg/m2, and obese is ≥ 30.0 kg/m2.
  3. bAn AIDS-defining illness (ADI) is a prior report of conditions consistent with the 1993 Centers for Disease Control and Prevention surveillance definition.
  4. cViral load entered after log10 transformation to correct for skewed distribution.
Platelet count−0.54< 0.01−0.54< 0.01
HIV−0.17< 0.01
Current smoker0.
LDL cholesterol0.010.940.030.59
Viral loadc0.060.48
CD4 count−0.100.73


Concern regarding cardiovascular disease in HIV-infected individuals has led to multiple studies examining the associations of HIV infection with atherosclerosis [21]. Recently, the measurement of MPV, which is routinely included in a complete blood count report and is used clinically to aid in the evaluation of thrombocytopenia, has been shown to provide prognostic information in patients with acute and chronic coronary artery disease syndromes [26]. As HIV-infected patients have been reported to have lower platelet counts and higher cardiovascular event rates, we sought to determine the relationship between MPV and HIV infection.

Few prior studies have assessed MPV values in HIV-infected populations [26-28]. The present study findings are consistent with those of Koenig et al., who studied 34 HIV-infected subjects and found two-thirds of them to have thrombocytopenia, of whom 92% had inappropriately low platelet volume [26]. However, this study was limited in terms of the number of subjects, in contrast to our cohort study which has a larger sample size and is more focused on women. Koenig et al. observed that the platelet number−volume relationship was similar to that seen in myelosuppressive bone marrow disorders and confirmed 90% of thrombocytopenic patients to have normal or decreased magakaryocytes on bone marrow examination. Cole et al. studied six HIV-infected patients and observed similar MPV values (10.5 vs. 9.5 fL) compared with uninfected patients despite markedly reduced numbers of platelets [27]. In contrast, larger not smaller MPV was recently reported among HIV-infected treatment-naïve patients by Mena et al., who also noted MPV to increase significantly during the untreated course of asymptomatic HIV infection in 103 subjects (83% male) [28]. Although a precise explanation for the latter study findings is lacking, HIV-related thrombocytopenia is probably multifactorial, with direct invasion of megakaryocytes by HIV causing apoptosis, dysmegakaryopoiesis, either abnormal or dysfunctional production of megakaryocytes and immune-related peripheral platelet destruction proposed as mechanisms for lowered platelet counts [29]. Therefore, different mechanisms of thrombocytopenia are likely to account for the disparate findings between previous studies and the present study. In our cohort of HIV-infected women, higher MPV values were significantly associated with underweight status. This finding is a new one, as prior studies have shown higher MPV values associated with obesity in the general population [30]. Of note, MPV was unrelated to use of HAART or viral load.

The major finding in our study is that HIV infection was associated with lower MPV among women. Of note, gender was not found to influence MPV in uninfected patients. Importantly, the significant relationship between HIV status and MPV persisted after adjusting for platelet count, which was also lower in the infected group. More advanced HIV disease, as defined by a history of an ADI, was associated with further lowering of MPV.

Although, to our knowledge, this is the largest evaluation of MPV in HIV-infected individuals published to date, it is subject to the limitations of a cross-sectional design, including difficulty in attributing causality between the investigated factors and MPV. Only 16% of HIV-infected subjects were untreated, which limits the assessment of the effect of antiretroviral therapy on MPV. Only 17% of all subjects had thrombocytopenia (< 150 cells/mL). We evaluated single values and so did not assess temporal changes in MPV in this initial study. Left ventricular function and atherosclerosis are known to be associated with MPV values; although they were not investigated in this study, the cohort has undergone sophisticated assessments of cardiac and vascular disease. In addition, given the age of the cohort, attempting to link MPV to cardiovascular clinical events at this juncture could be premature. Although the women in the WIHS reflect the demographics of the HIV epidemic among women in the USA, it may not be appropriate to generalize the results to HIV-infected men. Moreover, women in this study had relatively well-controlled HIV infection, and had been enrolled in a prospective study for many years at the time of MPV assessment. All subjects (infected and uninfected) had MPV measured using the Siemens Advia counter, which has been shown to yield lower MPV values than other devices [31]. Although antiplatelet medications were not considered, aspirin has been shown to alter platelet size [32]. Although EDTA was used as an anticoagulant, the samples were tested within 4−30 h, making it unlikely that this affected MPV measurement. Despite these limitations, we conclude that MPV, which has been proposed as a risk marker for cardiovascular events, is lower and not higher in the setting of HIV infection in women. This suggests impaired platelet production rather than increased peripheral destruction. Therefore, higher than expected cardiovascular event rates probably should not be attributed to greater platelet reactivity as measured by MPV. Given that thrombocytopenia has been found to be associated with increased morbidity and mortality, low CD4 counts and a rapid progression to full-blown AIDS, the prognostic value of MPV determination in the setting of HIV infection has not been established [29]. Therefore, the broader significance of this simple and inexpensive laboratory aid in the setting of HIV infection merits further study.


Data in this article were collected by the Women's Interagency HIV Study (WIHS) Collaborative Study Group with centres (Principal Investigators) at New York City/Bronx Consortium (Kathryn Anastos); Brooklyn, NY (Howard Minkoff); Washington DC Metropolitan Consortium (Mary Young); The Connie Wofsy Study Consortium Of Northern California (Ruth Greenblatt); Los Angeles County/Southern California Consortium (Alexandra Levine); Chicago Consortium (Mardge Cohen); Data Coordinating Center (Stephen Gange). The WIHS is funded by the National Institute of Allergy and Infectious Diseases (UO1-AI-35004, UO1-AI-31834, UO1-AI-34994, UO1-AI-34989, UO1-AI-34993 and UO1-AI-42590) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (UO1-HD-32632). The study is co-funded by the National Cancer Institute, the National Institute on Drug Abuse, and the National Institute on Deafness and Other Communication Disorders. Funding is also provided by the National Center for Research Resources (UCSF-CTSI Grant Number UL1 RR024131). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. We acknowledge Jeremy Weedon, PhD, MA, BS, Department of Epidemiology and Biostatistics, State University of New York Downstate Medical Center, Brooklyn, New York, for his contribution as the statistical advisor to this project.