Is mean platelet volume a better biomarker in pre-eclampsia?

Platelet count in preeclampsia: a systematic review and meta-analysis

OBJECTIVE

Many studies have reported the association between platelets and preeclampsia. However, sample sizes were small, and their findings were inconsistent. We conducted a systematic review and meta-analysis to evaluate the association in pooled samples and in detail.

DATA SOURCES

A systematic literature search was performed using Medline, Embase, ScienceDirect, Web of Science, Cochrane Library, NICHD-DASH, LILACS, and Scopus from inception to April 22, 2022.

STUDY ELIGIBILITY CRITERIA

Observational studies comparing platelet count between women with preeclampsia and normotensive pregnant women were included.

METHODS

The mean differences with 95% confidence interval in platelet count were calculated. Heterogeneity was assessed using I2 statistics. Sensitivity and subgroup analyses were conducted. Statistical analysis was performed using RevMan 5.3 and ProMeta 3 software.

RESULTS

A total of 56 studies comprising 4892 preeclamptic and 9947 normotensive pregnant women were included. Meta-analysis showed that platelet count was significantly lower in women with preeclampsia than in normotensive controls (overall: mean difference, -32.83; 95% confidence interval, -40.13 to -25.52; P<.00001; I2=92%; mild preeclampsia: mean difference, -18.65; 95% confidence interval, -27.17 to -10.14; P<.00001; I2=84%; severe preeclampsia: mean difference, -42.61; 95% confidence interval, -57.53 to -27.68; P<.00001; I2=94%). Significantly lower platelet count was also observed in the second trimester (mean difference, -28.84; 95% confidence interval, -44.59 to -13.08; P=.0003; I2=93%), third trimester (mean difference, -40.67; 95% confidence interval, -52.14 to -29.20; P<.00001; I2=92%), and before the diagnosis of preeclampsia (mean difference, -18.81; 95% confidence interval, -29.98 to -7.64; P=.009; I2=87%), but not in the first trimester (mean difference, -15.14; 95% confidence interval, -37.71 to 7.43; P=.19; I2=71%). Overall, the pooled sensitivity and specificity of platelet count were 0.71 and 0.77, respectively. The area under the curve was 0.80.

CONCLUSION

This meta-analysis confirmed that platelet count was significantly lower in preeclamptic women, irrespective of severity and presence or absence of associated complications, even before the onset of preeclampsia and in the second trimester of pregnancy. Our findings suggest that platelet count may be a potential marker to identify and predict preeclampsia.

Incremental predictive value of platelet parameters for preeclampsia: results from a large prospective cohort study

BACKGROUND

Platelet parameters during pregnancy were associated with the risk of preeclampsia (PE), but the predictive value of these parameters for PE remained unclear. Our aim was to clarify the individual and incremental predictive value of platelet parameters, including platelet count (PC), mean platelet volume (MPV), plateletcrit (PCT), and platelet distribution width (PDW) for PE.

METHODS

This study was based on the Born in Guangzhou Cohort Study in China. Data on platelet parameters were extracted from medical records of routine prenatal examinations. Receiver operating characteristic (ROC) curve was performed to analyze the predictive ability of platelet parameters for PE. Maternal characteristic factors proposed by NICE and ACOG were used to develop the base model. Detection rate (DR), integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI) were calculated compared with the base model to assess the incremental predictive value of platelet parameters.

RESULTS

A total of 30,401 pregnancies were included in this study, of which 376 (1.24%) were diagnosed with PE. Higher levels of PC and PCT were observed at 12-19 gestational weeks in women who developed PE later. However, no platelet parameters before 20 weeks of gestation reliably distinguished between PE complicated pregnancy and non-PE complicated pregnancy, with all values of the areas under the ROC curves (AUC) below 0.70. The addition of platelet parameters at 16-19 gestational weeks to the base model increased the DR for preterm PE from 22.9 to 31.4% at a fixed false positive rate of 5%, improved the AUC from 0.775 to 0.849 (p = 0.015), and yielded a NRI of 0.793 (p < 0.001), and an IDI of 0.0069 (p = 0.035). Less but significant improvement in prediction performance was also observed for term PE and total PE when all the four platelet parameters were added to the base model.

CONCLUSIONS

Although no single platelet parameter at the early stage of pregnancy identified PE with high accuracy, the addition of platelet parameters to known independent risk factors could improve the prediction of PE.

Preeclampsia has an association with both platelet count and mean platelet volume: A systematic review and meta-analysis

Background

Preeclampsia (PE) is a pregnancy-specific disorder characterized by endothelial dysfunction, and activation of the coagulation system. Alteration of PLT parameters is the common hematological abnormality observed in women with PE. The main aim of this study was to systematically review previous studies from around the world to generate evidence about the relationship between platelet count (PC) and PE, as well as mean platelet volume (MPV) and PE, by calculating the pooled weighted mean difference (WMD) of PC and MPV between PE and normotensive (NT) groups.

Methods

Relevant articles which were published in the English language from January 10, 2011, to January 10, 2021, were systematically searched through PubMed, Web of Science, and African journals online. In addition, reference probing of published articles searching was employed through Google Scholar and Google for searching grey literature. The methodological qualities of articles were assessed using Joana Brigg’s institute critical appraisal checklist. A random-effects model was used to estimate pooled WMD of PLT parameters between the two groups with the respective 95% confidence intervals (CI) using Stata version 11.0. The I2 statistics and Egger’s regression test were used to assess heterogeneity and publication bias among included studies, respectively.

Results

A total of 25 articles were included in this systematic review and meta-analysis. Of which, 23 studies were used in each PC and MPV analysis. The overall pooled WMD of PC and MPV between PE and NT groups were -41.45 × 109/L [95% CI; -51.8, -31.0] and 0.98 fl [95% CI; 0.8, 1.1], respectively. The pooled WMD revealed that PC decreased significantly in the PE group compared to the NT group while MPV increased significantly in the PE group.

Conclusions

This systematic review and meta-analysis indicated that there is a significant decrease in PC and a significant increase in MPV during PE development among pregnant women. As a result, a change in these parameters among pregnant women may indicate the development of PE.

Improving preeclampsia risk prediction by modeling pregnancy trajectories from routinely collected electronic medical record data

Preeclampsia is a heterogeneous and complex disease associated with rising morbidity and mortality in pregnant women and newborns in the US. Early recognition of patients at risk is a pressing clinical need to reduce the risk of adverse outcomes. We assessed whether information routinely collected in electronic medical records (EMR) could enhance the prediction of preeclampsia risk beyond what is achieved in standard of care assessments. We developed a digital phenotyping algorithm to curate 108,557 pregnancies from EMRs across the Mount Sinai Health System, accurately reconstructing pregnancy journeys and normalizing these journeys across different hospital EMR systems. We then applied machine learning approaches to a training dataset (N = 60,879) to construct predictive models of preeclampsia across three major pregnancy time periods (ante-, intra-, and postpartum). The resulting models predicted preeclampsia with high accuracy across the different pregnancy periods, with areas under the receiver operating characteristic curves (AUC) of 0.92, 0.82, and 0.89 at 37 gestational weeks, intrapartum and postpartum, respectively. We observed comparable performance in two independent patient cohorts. While our machine learning approach identified known risk factors of preeclampsia (such as blood pressure, weight, and maternal age), it also identified other potential risk factors, such as complete blood count related characteristics for the antepartum period. Our model not only has utility for earlier identification of patients at risk for preeclampsia, but given the prediction accuracy exceeds what is currently achieved in clinical practice, our model provides a path for promoting personalized precision therapeutic strategies for patients at risk.

Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia

Aim

To establish a model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia in China.

Methods

We retrospectively collected the medical records of 896 pregnant women with preterm preeclampsia who were older than 35 years and delivered at the Affiliated Hospital of Qingdao University from June 2018 to December 2020. The pregnant women were divided into an adverse outcome group and a non-adverse outcome group according to the occurrence of adverse outcomes. The data were divided into a training set and a verification set at a ratio of 8:2. A nomogram model was developed according to a binary logistic regression model created to predict the adverse outcomes in advanced-age pregnant women with preterm preeclampsia. ROC curves and their AUCs were used to evaluate the predictive ability of the model. The model was internally verified by using 1000 bootstrap samples, and a calibration diagram was drawn.

Results

Binary logistic regression analysis showed that platelet count (PLT), uric acid (UA), blood urea nitrogen (BUN), prothrombin time (PT), and lactate dehydrogenase (LDH) were the factors that independently influenced adverse outcomes (P < 0.05). The AUCs of the internal and external verification of the model were 0.788 (95% CI: 0.737 ~ 0.764) and 0.742 (95% CI: 0.565 ~ 0.847), respectively. The calibration curve was close to the diagonal.

Conclusions

The model we constructed can accurately predict the risk of adverse outcomes of pregnant women of advanced age with preterm preeclampsia, providing corresponding guidance and serving as a basis for preventing adverse outcomes and improving clinical treatment and maternal and infant prognosis.

Platelet Parameters and Risk of Hypertension disorders of Pregnancy: a Propensity Score Adjusted Analysis

While the role of platelets in cardiovascular diseases among the general population has been widely reported, evidence is inconsistent regarding the association between platelet indices with hypertension in pregnant women. In this study, we explored the associations between platelet parameters before 20 gestational weeks, an understudied period, with hypertensive disorders of pregnancy (HDP), including preeclampsia/eclampsia (PEEC) and gestational hypertension (GH). Based on the Born in Guangzhou Cohort Study, 12053 singleton pregnant women with platelet parameters, including platelet count (PC), mean platelet volume (MPV), plateletcrit (PCT), and platelet distribution width (PDW) measured at 14-19 gestational weeks were included. Conventional multivariable adjustment and propensity score analysis were used to control for confounders. The restricted cubic spline showed that the risk of PEEC increased linearly for PC, and non-linearly for PCT. For GH, the risk increased linearly for PC, MPV, and PCT, and non-linearly for PDW. When these indices were categorized into quintiles, women with higher PC and PCT were associated with increased risk of both PEEC and GH. Women with MPV exceeding the second quintile (≥ 8.8 fL) had a greater risk for GH, but not for PEEC. When HDP was classified into two groups (early- vs late-onset) based on the occurrence time, significant associations persisted for early-onset PEEC, early-onset GH, and late-onset GH. In conclusion, increased PC and PCT before 20 weeks of gestation were both associated with higher risk of PEEC and GH, while elevated MPV was only linked to GH.

Can complete blood count parameters that change according to trimester in pregnancy be used to predict severe preeclampsia?

We aimed to evaluate the effectiveness of changes over time in complete blood count (CBC) parameters to estimate the diagnosis of preeclampsia. Data on 161 severe preeclampsia patients and 161 healthy pregnant patients who met the study criteria of pregnant women whose CBC had been measured at 10-12, 22-24 and 28-30 weeks of pregnancy were compared. In the preeclampsia group, an increase in the mean platelet volume (MPV) value and a decrease in the number of platelets were statistically significant in the transition from the second to the third trimester. MPV and lymphocyte counts were more significant in the third trimester and neutrophil lymphocyte ratio (NLR) were more significant in the second trimester. We found that evaluation of the changes in lymphocyte, MPV and NLR values in three different trimesters of pregnancy rather than a single trimester was more meaningful to predict severe preeclampsia.Impact StatementWhat is already known on this subject? Studies have shown that MPV and NLR can predict preeclampsia. However, a clear cut off value could not be determined. The reasons for this may be that the gestational week during which the measurement is made is not standard and the patient groups are not homogeneous.What the results of this study add? In this study, CBC parameters at different stages of the preeclampsia process were compared in the severe preeclampsia group. According to our results, lymphocytes, NLR and MPV can be used to predict severe preeclampsia. In addition, NLR measurements in the second trimester and MPV and lymphocyte measurements in the third trimester were found to be more significant in predicting severe preeclampsia.What the implications are of these findings for clinical practice and/or further research? In order to predict severe preeclampsia, instead of a single measurement of CBC parameters, new calculations should be made that add change over time.

Can Platelet Count and Mean Platelet Volume be Used as Markers of Postdural Puncture Headache in Obstetric Patients?

Objective

In this study, considering the importance of platelet function in inflammatory processes, we explored whether there are relationships of platelet indices with postdural puncture headache (PDPH) and pain developing after use of spinal needles and whether patient characteristics contribute to the development of PDPH.

Methods

This prospective, observational study included 76 patients (Group 1) with PDPH and 93 patients (Group 2) without PDPH. The postoperative hemoglobin, hematocrit, platelet count (PC), and mean platelet volume (MPV) values were recorded, along with age, blood type, Rh factor, gravida, parity, and gestational age. In addition, the time of the onset of pain was recorded in patients who complained of a postspinal headache.

Results

Hemoglobin and hematocrit values in Group 1 were significantly lower than in Group 2 (both, p=0.024). The PC of Group 1 was significantly higher than that of Group 2 (p < 0.001), whereas the MPV was significantly lower (p < 0.001). The area under the curve (AUC) values were significant for hemoglobin, hematocrit, PC, and MPV (p=0.022, p=0.024, p < 0.001, and p < 0.001, resp.). For MPV, the AUC value was 0.293, sensitivity was 1%, and specificity was 99%. The highest likelihood ratio (LR+) value was 1.22 at a cut-off value of 13.3 fL. For the PC, the AUC value was 0.666, the sensitivity was 9%, and the specificity was 99%, while the highest LR + value was 8.56 at a cut-off value of 352 × 10⁹/L. There was no significant relationship between the parameters examined and the onset of pain.

Conclusion

In this study, the PC was higher and MPV was lower in obstetric patients with PDPH compared with the control group. However, we also found that these two values cannot be used as markers of PDPH.

Systemic inflammatory response markers in preeclampsia

PURPOSE

Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), platelet distribution width (PDW), red cell distribution width (RDW), mean platelet volume (MPV), and plateletcrit (PCT) are known as systemic inflammatory response markers. In this study, we aimed to evaluate changes in NLR, PLR, PDW, RDW, MPV, and PCT in preeclampsia (PE) and their use in predicting its severity.

MATERIALS AND METHODS

This is a retrospective case-control study. The study comprised 64 control group (healthy pregnant females), 51 females with mild PE, and 13 with severe PE. These three groups were compared with demographic data and inflammation markers.

RESULTS

There were no statistically significant differences between healthy pregnant females and preeclaptic females in terms of median age, hemoglobin, lymphocyte, neutrophil, platelet, NLR, PLR, PDV, RDW, MPV, PCT (P > 0.05). The control group has a higher number of gravity and parity than the PE group (P < 0.001). MPV value is a lower PE group than the control group (P < 0.001). Both gravity and parity were significantly higher in the patients with mild PE than in the control group (P < 0.001). MPV value was statistically higher in the control group compared both mild and severe PE (P < 0.001), however, no statistical difference between mild and severe PE (P = 0.305).

CONCLUSIONS

MPV may be clinically useful markers in the prediction of PE. Further, prospective multicenter studies are needed to reveal the association between these markers and PE.

Changes of platelet count throughout pregnancy in women with antiphospholipid syndrome

OBJECTIVE

Antiphospholipid antibodies (aPL) activate several cell types, such as endothelial cells, monocytes, neutrophils, fibroblasts, trophoblasts and platelets, thus leading to thrombosis and obstetric complications in patients with antiphospholipid syndrome (APS). The aim of the present study was the longitudinal investigation of platelet count in women with APS. Additionally, platelet count in women with APS who developed preeclampsia during pregnancy were compared to women with APS and uncomplicated pregnancy for potential early detection of preeclampsia.

MATERIAL AND METHODS

This longitudinal study included 65 women with APS, 38 women with preeclampsia and 84 women with normal pregnancies, where platelet count was determined every four weeks, starting in early pregnancy.

RESULTS

Platelet count was significantly lower in women with APS compared to women who developed preeclampsia and normal pregnancies starting at 12 weeks of gestation. The areas under the curve (AUC) for platelet count were 0.765 at 12 weeks of gestation (95% of CI of 0.634-0.896), 0.747 at 20 weeks (95% of CI of 0.600-0.894), 0.719 at 24 weeks (95% of CI of 0.555-0.882), respectively. The cut off points for platelets were 216 at 12-14 weeks of gestation, 226.5 at 20 weeks of gestation, and 163.5 at 24 weeks of gestation, respectively.

DISCUSSION

We demonstrated a significant lower platelet count in women with APS throughout gestation. Additionally, platelet count is significantly decreased in women with APS who developed preeclampsia. According to our results, platelet count seems to have a predictive value for the development of preeclampsia in these women.

Comparison of mean platelet volume (MPV) and sFlt-1/PlGF ratio as predictive markers for preeclampsia

INTRODUCTION

Preeclampsia is characterised by an increased platelet consumption with consecutive reduction of overall platelet count and a consecutive rise in mean platelet volume (MPV). MPV has therefore been suggested as a predictive marker for preeclampsia. We aimed to investigate MPV longitudinally in women with preeclampsia compared to healthy controls during pregnancy for potential early detection of preeclampsia and to compare potential MPV changes against the sFlt-1/PlGF ratio.

STUDY DESIGN

This longitudinal study included 38 women with preeclampsia and 84 women with normal pregnancies, where MPV and sFlt-1 and PLGF levels were determined every 4 weeks, starting in early pregnancy.

RESULTS

MPV was significantly higher in women who developed preeclampsia compared to women with normal pregnancies at 12, (p = .029), 24 (p = .011), 28 (p = .037), 32 (p = .002), and 36 weeks of gestation, respectively (p = .015). Further analysis revealed a cut-off point of 10.85 fl (sensitivity 65.6%, specificity 26.2%) for the prediction of preeclampsia. The sFlt-1/PlGF ratio was significantly higher in women who developed preeclampsia compared to women with normal pregnancies at the same time points (p = .001). The cut-off point for predicting preeclampsia was 10.3 (sensitivity 87.5%, specificity 11.9%). ROC curve analysis showed that MPV has a high predictive value for early-onset preeclampsia (p < .05) but not for late-onset preeclampsia.

CONCLUSION

MPV is significantly elevated even in early pregnancy in women who develop preeclampsia and seems, therefore, a valuable predictor for preeclampsia even at early gestation. However, according to our results, MPV seems reliable in predicting early onset preeclampsia.

Neutrophil-to-lymphocyte ratio and platelet indices in pre-eclampsia

OBJECTIVE

To compare the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and platelet indices between women with pre-eclampsia and normotensive pregnant women.

METHODS

A cross-sectional study conducted from January to July 2017 at a tertiary care hospital in Delhi, India. The study compared pregnant women aged 18-40 years with pre-eclampsia diagnosed at term with healthy pregnant women matched for gestational age. Venous blood samples were drawn and complete blood count was analyzed. The parameters recorded were hemoglobin, red cell distribution width (RDW), platelet count, mean platelet volume (MPV), plateletcrit, and platelet distribution width.

RESULTS

There were 67 women included in each group. NLR was higher in women with pre-eclampsia compared with the control group (6.8 ± 7.6 vs 3.0 ± 0.98; P=0.001). Both PLR (14.18 ± 14.4 vs 9.54 ± 3.6; P=0.012) and MPV (9.45 ± 1.19 vs 9.02 ± 1.1; P=0.029) were higher in the study group compared with the control group. Platelet count was lower in pre-eclamptic women compared with the control group (188 ± 89.7 vs 200.1 ± 62.36; P=0.014). RDW was also higher in the study group (P=0.025).

CONCLUSIONS

The present study found that the inflammatory markers NLR, PLR, RDW, and MPV were higher in women with pre-eclampsia. Measuring NLR and PLR may be useful in predicting pre-eclampsia among women at high risk during prenatal follow-up.