Skip to main content
Download PDF
  • Systematic Review
  • Open access
  • Published:

Abnormal platelet parameters in inflammatory bowel disease: a systematic review and meta-analysis

BMC Gastroenterology volume 24, Article number: 214 (2024) Cite this article

Abstract

Background

Platelet dysfunction plays a critical role in the pathogenesis of inflammatory bowel disease (IBD). Despite clinical observations indicating abnormalities in platelet parameters among IBD patients, inconsistencies persist, and these parameters lack standardization for diagnosis or clinical assessment.

Methods

A comprehensive search was conducted in the PubMed, Embase, Web of Science, and Cochrane Library databases for relevant articles published up to December 16th, 2023. A random-effects model was employed to pool the weighted mean difference (WMD) and 95% confidence interval (95% CI) of platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) between IBD patients and healthy controls, and subgroup analyses were performed.

Results

The meta-analysis included 79 articles with 8,350 IBD patients and 13,181 healthy individuals. The results revealed significantly increased PLT and PCT levels (WMD: 69.910, 95% CI: 62.177, 77.643 109/L; WMD: 0.046%, 95% CI: 0.031%, 0.061%), and decreased MPV levels (WMD: -0.912, 95% CI: -1.086, -0.739 fL) in IBD patients compared to healthy individuals. No significant difference was found in PDW between the IBD and control groups (WMD: -0.207%, 95% CI: -0.655%, 0.241%). Subgroup analysis by disease type and disease activity showed no change in the differences for PLT, PCT, and MPV in the ulcerative colitis and Crohn’s disease groups, as well as the active and inactive groups. Notably, the active group exhibited significantly lower PDW levels than the control group (WMD: -1.138%, 95% CI: -1.535%, -0.741%).

Conclusions

Compared with healthy individuals, IBD patients display significantly higher PLT and PCT and significantly lower MPV. Monitoring the clinical manifestations of platelet abnormalities serves as a valuable means to obtain diagnostic and prognostic information. Conversely, proactive measures should be taken to prevent the consequences of platelet abnormalities in individuals with IBD.

Systematic review registration

PROSPERO CRD42023493848.

Key messages

• It is known that inflammatory bowel disease (IBD) is related to various alterations in platelets, but there are variations in reported results of platelet parameters in the IBD population in clinical studies.

• To elucidate the diagnostic and prognostic value of platelet parameters in IBD, we conducted a meta-analysis of 79 studies to provide more comprehensive conclusions on changes in platelet parameters in IBD.

• This meta-analysis reveals that individuals with IBD exhibit significantly elevated platelet count (PLT) and plateletcrit (PCT), alongside a significant decrease in mean platelet volume (MPV) compared to healthy individuals.

• The platelet parameters can offer reliable insights for assessing the severity of IBD and understanding potential pathophysiological mechanisms.

Peer Review reports

Introduction

Inflammatory bowel disease (IBD) is a chronic immune-mediated inflammation of the intestinal tract, characterized by recurring periods of relapse and remission [1]. It encompasses two primary disorders, ulcerative colitis (UC) and Crohn’s disease (CD), both of which have demonstrated a global increase in incidence over the past decade [2,3,4]. Although the etiology remains incompletely elucidated, Growing experimental and clinical evidence suggests that the initiation and progression of IBD involve an intricate interplay among immune, genetic, and environmental factors [5].

Platelets, as multifunctional cells, play a crucial role in regulating immunity and inflammation, in addition to their hemostatic function [6]. IBD is linked to various alterations in platelets, encompassing changes in number, shape, and function. These abnormalities are primarily attributed to the highly activated state of circulating platelets in IBD patients [7]. IBD patients have an imbalance between inflammation and coagulation function; inflammatory cytokines can induce abnormal coagulation processes, and the coagulation cascade promotes the progression of inflammation, initiating a vicious cycle where each process propagates and intensifies the other [8, 9]. The significance of activated platelets in the pathogenesis of IBD becomes more pronounced when considering that patients with IBD are prone to developing arterial thromboembolic events and venous thromboembolism [10, 11].

While platelet dysfunction is implicated in IBD pathogenesis, the existing evidence remains insufficient. Moreover, there are variations in reported results of platelet parameters in the IBD population in clinical studies, and platelet parameters have not yet been established as guidelines for the diagnosis or clinical evaluation of IBD. Therefore, accumulating evidence is crucial to elucidate the diagnostic and prognostic value of platelet parameters in IBD. To address this, we conducted a meta-analysis to provide more comprehensive conclusions on changes in platelet parameters in IBD, including platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT). As a cost-effective and straightforward laboratory indicator, examining the correlation between platelet parameters and IBD has the potential to contribute to more comprehensive clinical insights for the prevention, diagnosis, and treatment of IBD and related platelet disorders.

Methods

Search strategy and selection criteria

This systematic review and meta-analysis was conducted in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis (PRISMA) guideline and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline. (Table S1, S2) [12]. The protocol for this meta-analysis was registered with PROSPERO (CRD42023493848).

We performed a thorough search in the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant articles. Our search strategy encompassed MeSH (Medical Subject Headings) terms and entry terms without language restrictions. Furthermore, the reference lists of eligible articles were carefully screened to identify any additional relevant studies that were not initially retrieved during the literature search. The details of the search strategy are presented in Table S3.

The inclusion criteria were as follows: (1) Patients: adult IBD patients (the majority of participants > 18 years of age); (2) Control: adults in good health; (3) Outcomes: PLT, MPV, PDW, and PCT; (4) Study type: cross-sectional studies, case control studies, and cohort studies.

The exclusion criteria were as follows: (1) Animal experiments, reviews, conference abstracts, case reports and meta-analyses; (2) Research object limited to children or adolescents [3], Pregnant or lactating women, hematological diseases, malignant tumors, and any other diseases that could interfere with the platelet parameters; (3) Participants received anticoagulant medications, contraceptives, or heparin, and any other drugs unrelated to IBD treatment that may cause platelet abnormalities; (4) Study of drug efficacy (5) Full-text or sufficient data could not be extracted.

Data collection and extraction

EndNote 20 software was utilized to manage studies to remove duplicate articles obtained from the database. The screening of included articles, based on predefined inclusion and exclusion criteria, was performed independently by CX and ZS. Resolution of any discrepancies arising from this screening process involved discussion with another author (HS) until a consensus was reached. Extracted research information encompassed: (1) Background details including first author, publication year, country, study design, sample size, age, and sex; (2) Platelet parameters including PLT, MPV, PDW, and PCT, presented as mean ± standard deviation (SD). In instances where relevant data were missing, attempts were made to contact the corresponding author to obtain the required information. If multiple groups of data were presented within the same study, each group was treated as an independent entity for data extraction.

Quality assessment

The Newcastle-Ottawa Scale (NOS) was employed to assess the quality of cohort studies and case control studies [13], and the Agency for Healthcare Research and Quality (AHRQ) methodology checklist was used to evaluate cross-sectional studies [14]. The NOS evaluates research quality based on three aspects: selection of study groups, comparability of groups, and ascertainment of exposure or outcome of interest for case control or cohort studies, respectively (Methods 1, 2). Study quality was categorized as follows: low quality = 0–3 stars, moderate quality = 4–6 stars, and high quality = 7–9 stars [15]. On the other hand, the AHRQ methodology checklist comprises 11 items, including a definition of information source, inclusion and exclusion criteria, time period and continuity for identifying patients, personnel blinding, quality assurance assessments, confounding and missing data, and patient response rates and completeness (Methods 3). For each item, a score of “0” was assigned if the answer was “unclear” or “no”, and a score of “1” was given if the answer was “yes”. Study quality was categorized as follows: low quality = 0–3, moderate quality = 4–7, and high quality = 8–11 [16]. Two investigators (CX and SZ) independently assessed the quality of eligible articles, with any discrepancies resolved by a third investigator (HS).

Data synthesis and data analysis

The analysis encompassed the calculation and estimation of the Weighted Mean Difference (WMD) along with its 95% Confidence Interval (95% CI) for key platelet parameters (PLT, MPV, PDW, and PCT) in IBD patients compared to healthy controls across each study. For studies utilizing median, range, and/or interquartile range, we employed the methodologies proposed by Wan et al. [17] and Luo et al. [18] to estimate the sample mean and SD. A positive WMD indicated higher platelet parameter values in IBD patients. In cases where outcome changes were not explicitly reported, conversion formulas recommended in the Cochrane Handbook Version 6.4 were applied to calculate these changes [19].

The I² statistic quantitatively assessed the heterogeneity of studies, categorized as low (0–25%), moderate (25–75%), and high (> 75%) heterogeneity. A random-effects model was applied due to high heterogeneity. Meta-regression analyses were conducted to identify potential sources of heterogeneity, considering factors such as disease type, disease activity, region, study year, study type, and quality assessment. Subgroup analyses were performed based on disease type (UC, CD, and Unclassified), disease activity (active, inactive, and Unclassified), region (Asia, Europe, North America, Africa, and Oceania), study year (Before 2000 and Since 2000) study type (Case control study, Cohort study, and Cross-sectional study), and quality assesment (High quality and Moderate quality). Through this comprehensive exploration, we aim to clarify whether variations in disease characteristics, geographic location, temporal trends, study design, and study quality contribute to the heterogeneity among studies.

Moreover, sensitivity analysis was conducted, systematically removing one study at a time to assess the robustness of the results. Funnel plots and Egger’s test were employed to scrutinize publication bias. In instances of detected publication bias, the trim and fill method was applied to rectify funnel plot asymmetry.

All statistical analyses were conducted using Stata Version 12.0, and significance was defined as a 2-tailed P value < 0.05.

Results

Search and selection result

In our initial search, a total of 4,106 publications were identified, from which 1,150 duplicate records were eliminated. Following the screening of the remaining 2,956 records, we excluded studies involving animal experiments, reviews, meeting abstracts, case reports, or meta-analyses, resulting in a total exclusion of 1,479 publications. Additionally, 1,219 articles were deemed irrelevant based on title and abstract assessment. Subsequently, 258 publications remained for a thorough evaluation of the full text. Of those 258 studies, 151 were excluded because of inadequate data or no full text, 8 articles were found to be unsuitable populations, 18 articles were removed because of their unsuitable control group, and 3 articles were disregarded due to their focus on drug efficacy. Finally, 79 eligible articles have been retained for inclusion in this systematic review and meta-analysis [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98]. The specific screening process is shown in Fig. 1.

Fig. 1
figure 1

Flow diagram of study selection

Full size image

Studies characteristics and quality assessment

The characteristics of 79 studies included in this systematic review and meta-analysis are illustrated in Table S4. These studies, spanning the period from 1975 to 2023, were conducted globally. One study adopted a gender-stratified approach [45], while the remaining studies encompassed both genders. Among the 79 studies, there were 20 case control studies, 8 cohort studies, and 51 cross-sectional studies. Based on the NOS and AHRQ methodology checklist, 70 articles were categorized as high quality, with the remaining 9 articles considered of moderate quality. Detailed assessment scores are shown in Table S4.

Meta-analyses

77 articles (161 available data) [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45, 47–55, 57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98] reported the difference in PLT between the IBD group and the control group. The results indicated a significant increase in PLT values in IBD patients compared to healthy individuals (WMD: 69.910, 95% CI: 62.177, 77.643 109/L, P < 0.001, Fig. 2). For MPV, the synthesis of data from 25 articles (with 55 available data) [23, 26, 31, 34, 36, 41, 45, 46, 49, 50, 52, 55, 56, 59, 60, 62, 68, 70, 77, 78, 84,85,86, 91, 92] revealed a significant decrease in MPV values in IBD patients when compared with healthy people (WMD: -0.912, 95% CI: -1.086, -0.739 fL, P < 0.001, Fig. 3). In the analysis of PDW, encompassing 8 articles (with 22 available data) [45, 60, 62, 63, 68, 85, 86, 97], no significant difference was observed between the IBD group and the control group (WMD: -0.207%, 95% CI: -0.655%, 0.241%, P = 0.260, Fig. 4). Turning to PCT, the inclusion of 9 articles (with 19 available data) [23, 34, 60, 62, 63, 68, 85, 86, 94] revealed a significant increase in PCT values among IBD patients compared to healthy people (WMD: 0.046%, 95% CI, 0.031%, 0.061%, P < 0.001, Fig. 5).

Fig. 2
figure 2

Weighted Mean Difference in PLT between the IBD Group and the Control Group. PLT measurements are reported in 109/L. Abbreviations: IBD: inflammatory bowel disease; UC: ulcerative colitis; CD: Crohn’s disease; PLT: platelet count; WMD: weighted mean difference; 95% CI: 95% confidence interval

Full size image
Fig. 3
figure 3

Weighted Mean Difference in MPV between the IBD Group and the Control Group. MPV measurements are reported in femtoliters (fL). Abbreviations: IBD: inflammatory bowel disease; UC: ulcerative colitis; CD: Crohn’s disease; MPV: mean platelet volume; WMD: weighted mean difference; 95% CI: 95% confidence interval

Full size image
Fig. 4
figure 4

Weighted Mean Difference in PDW between the IBD Group and the Control Group. PDW measurements are reported in percentage (%). Abbreviations: IBD: inflammatory bowel disease; UC: ulcerative colitis; CD: Crohn’s disease; PDW: platelet distribution width; WMD: weighted mean difference; 95% CI: 95% confidence interval

Full size image
Fig. 5
figure 5

Weighted Mean Difference in PCT between the IBD Group and the Control Group. PCT measurements are reported in percentage (%). Abbreviations: IBD: inflammatory bowel disease; UC: ulcerative colitis; CD: Crohn’s disease; PCT: plateletcrit; WMD: weighted mean difference; 95% CI: 95% confidence interval

Full size image

Meta-regression analyses and planned subgroup analyses

The evidence demonstrated a high between-study heterogeneity (Figure S1-S4). Meta-regression analyses were performed based on covariates including disease type, disease activity, region, study year, study type, and quality assessment. The meta-regression results suggested that disease activity might serve as the primary source of heterogeneity among studies investigating abnormal platelet parameters in IBD (Table S5). Furthermore, study year potentially contributes to heterogeneity in PLT studies, while study type may be a source of heterogeneity in PDW studies. The remaining covariates did not exhibit significant heterogeneity in the studies of platelet parameters in IBD.

Furthermore, we conducted subgroup analyses based on disease type, disease activity, region, study year, study type, and quality assessment. As depicted in Fig. 2, both the UC group (WMD: 60.494, 95% CI: 45.298, 75.690 109/L) and CD group (WMD: 82.952, 95% CI: 70.532, 95.372 109/L) exhibited significantly higher PLT levels than healthy individuals. Regarding disease activity, PLT levels were significantly higher in both the active group (WMD: 95.451, 95% CI: 81.460, 109.442 109/L) and inactive group (WMD: 21.866, 95% CI: 14.043, 29.688 109/L) compared to the control group. In terms of different regions, PLT levels in the Asia group (WMD: 73.579, 95% CI: 59.348, 87.810 109/L), Europe group (WMD: 68.076, 95% CI: 50.952, 85.200 109/L), North America group (WMD: 93.697, 95% CI: 55.906, 131.487 109/L), Africa group (WMD: 39.764, 95% CI: 6.294, 73.235 109/L), and Oceania group (WMD: 25.752, 95% CI: 5.809, 45.696 109/L) were all significantly higher than those in the control group. Among the subgroups in the study year, PLT levels were significantly higher in both the before 2000 group (WMD: 101.660, 95% CI: 66.770,136.550 109/L) and the since 2000 group than in the control group (WMD: 66.611, 95% CI: 58.557, 77.466 109/L). Concerning different study types, the cross-sectional study group (WMD: 70.932, 95% CI: 56.853, 85.011 109/L), case control study group (WMD: 67.685, 95% CI: 55.484, 79.887 109/L), and cohort study group (WMD: 68.116, 95% CI: 50.848, 85.384 109/L) all had significantly higher PLT than healthy control. For studies of different quality scores, both the high quality group (WMD: 70.758, 95% CI: 62.545, 78.970 109/L) and moderate quality group (WMD: 63.189, 95% CI: 37.400, 88.979 109/L) demonstrated significantly higher PLT levels than healthy individuals.

For MPV, as illustrated in Fig. 3, MPV levels in both the UC group (WMD: -0.918, 95% CI: -1.218, -0.617 fL) and CD group (WMD: -1.026, 95% CI: -1.285, -0.767 fL) were significantly lower than healthy individuals, while the difference in the unclassified group was not statistically significant (WMD: -0.489, 95% CI: -0.980, 0.003 fL). Regarding disease activity, MPV levels were significantly lower in both the active group (WMD: -1.308, 95% CI: -1.640, -0.976 fL) and inactive group (WMD: -0.527, 95% CI: -0.958, -0.095) compared to the control group. Considering different regions, MPV levels in the Asia group (WMD: -1.103, 95% CI: -1.261, -0.787 fL), Europe group (WMD: -0.684, 95% CI: -0.882, -0.487 fL), and Africa group (WMD: -1.610, 95% CI: -1.990, -1.230 fL) were all significantly lower than those in the control group. In the study year subgroups, MPV levels were significantly lower in the since 2000 group than in the control group (WMD: -0.922, 95% CI: -1.092, -0.752 fL), while the difference was not statistically significant in the before 2000 group (WMD: -0.668, 95% CI: -1.393, 0.056 fL). Turning to different study types, the cross-sectional study group (WMD: -0.786, 95% CI: -1.034, -0.538 fL), case control study group (WMD: -1.090, 95% CI: -1.484, -0.695 fL), and cohort study group (WMD: -1.120, 95% CI: -1.394, -0.845 fL) all had significantly lower MPV than healthy control. In studies of different quality scores, both the high quality group (WMD: -0.966, 95% CI: -1.180, -0.752 fL) and moderate quality group (WMD: -0.678, 95% CI: -0.916, -0.440 fL) exhibited significantly lower MPV levels than healthy individuals.

As shown in Fig. 4, the difference in PDW between both the UC group (WMD: 0.444%, 95% CI: -0.284%, 1.173%) and CD group (WMD: -0.540%, 95% CI: -1.118%, 0.038%) was not statistically significant when compared with the control group. Regarding disease activity, PDW levels were significantly lower in the active group (WMD: -1.138%, 95% CI: -1.535%, -0.741%) than in the control group, while PDW levels were significantly higher in the unclassified group (WMD: 1.261%, 95% CI: 0.735%, 1.787%). There was no significant difference between inactive group (WMD: -0.161%, 95% CI: -0.640%, 0.317%) and the control group. Concerning different study types, the cross-sectional study group (WMD: -0.764%, 95% CI: -1.226%, -0.302%) and case control study group (WMD: -0.668%, 95% CI: -1.672%, -0.335%) had significantly lower PDW than healthy control, while the cohort study group had significantly higher PDW (WMD: 1.261%, 95% CI: 0.735%, 1.787%). For studies of different regions and quality scores, the difference in the Asia group (WMD: -0.076%, 95% CI: -0.707%, 0.555%) and Europe group (WMD: -0.283%, 95% CI: -0.798%, 0.231%), as well as the high quality group (WMD: -0.252%, 95% CI: -0.788%, 0.283%) and moderate quality group (WMD: -0.002%, 95% CI: -0.525%, 0.520%) was not significant compared with the healthy control.

As demonstrated in Fig. 5, both the UC group (WMD: 0.038%, 95% CI: 0.026%, 0.051%) and CD group (WMD: 0.056%, 95% CI: 0.038%, 0.073%) exhibited significantly higher PCT levels than healthy individuals, while the difference in the unclassified group was not statistically significant (WMD: 0.000%, 95% CI: -0.005%, 0.005%). Regarding disease activity, PCT levels were significantly higher in both the active group (WMD: 0.068%, 95% CI: 0.046%, 0.090%) and inactive group (WMD: 0.029%, 95% CI: 0.013%, 0.044%) compared to the control group. For studies of different regions, the PCT levels in the Aisa group (WMD: 0.058%, 95% CI: 0.041%, 0.074%) and Europe group (WMD: 0.032%, 95% CI: 0.012%, 0.052%) were significantly higher than those in the control group. Additionally, PCT levels were significantly higher in the before 2000 group (WMD: 0.040%, 95% CI: 0.018%, 0.062%) and since 2000 group (WMD: 0.046%, 95% CI: 0.030%, 0.062%), as well as the cross-sectional study group (WMD: 0.041%, 95% CI: 0.018%, 0.065%), case control study group (WMD: 0.055%, 95% CI: 0.033%, 0.077%), and cohort study group (WMD: 0.038%, 95% CI: 0.022%, 0.053%) when compared with the control group. In terms of study quality, both the high quality group (WMD: 0.046%, 95% CI: 0.032%, 0.060%) and moderate quality group (WMD: 0.045%, 95% CI: 0.010%, 0.080%) exhibited significantly higher PCT levels than those in the control group.

Sensitivity analysis and publication bias

The sensitivity analysis revealed that individual studies did not exert a significant influence on the difference in PLT, MPV, PDW, and PCT between IBD patients and healthy people (Table S6). The funnel plots a general symmetry (Figure S2), and Egger’s test further indicated the absence of publication bias within the encompassed studies for PLT and PDW (Table S7, Figure S3). Nevertheless, publication bias was identified in studies in MPV and PCT (Table S7, Figure S3). Following the inclusion of an additional 13 and 10 studies, respectively, no substantial alterations were observed in the pooled effect values and 95% confidence intervals, signifying the stability of the results (Table S8, Figure S4).

Discussion

This systematic review and meta-analysis reveals that PLT and PCT are significantly higher, while MPV is significantly lower in the IBD population compared with healthy people. However, no significant difference was observed in PDW between the two groups.

The initial evidence of a platelet abnormality in IBD was reported in 1968 when an increased PLT was observed in a case series of IBD patients having an exacerbation of clinical activity [99]. Regarding changes in PLT in IBD in this meta-analysis, PLT was significantly increased in both the UC and CD groups. The mechanisms underlying the abnormal increase in PLT in IBD patients remain elusive. Platelet production is mainly regulated by plasma thrombopoietin [100]. Under normal circumstances, platelet production is controlled by a negative feedback mechanism based on PLT in the blood, with platelet production being inversely correlated with thrombopoietin levels [101]. However, it is worth noting that the levels of thrombopoietin were significantly higher in patients with IBD than in the general population [102]. In addition, available data present ambiguity as other investigations have demonstrated a lack of correlation between PLT and thrombopoietin concentration [29], suggesting the existence of additional regulatory factors contributing to increased PLT in IBD [103]. Several studies have elucidated the pivotal role of platelet in connecting inflammation and coagulation in both UC and CD, establishing a detrimental cycle in which contributing parameters mutually propagate and intensify [8, 104]. There is compelling evidence supporting the notion that platelets function as potent proinflammatory cells, in addition to their role in hemostasis [105]. In IBD, platelet circulate in a highly activated state, as evidenced by an elevated concentration of circulating platelet activation markers in the systemic circulation of patients [106]. Specific platelet granular products, including P-selectin, GP IIb/IIIa, CD40L, and GP53, are assimilated into the cytoplasmic membrane, imparting them with a more adhesive and interactive phenotype [107]. Furthermore, during activation, platelets develop receptors for chemokines, cytokines, and complement components, enabling their participation in various inflammatory cascades in IBD [7]. In this meta-analysis, PLT levels were higher in both the active and inactive groups than in the control group, indicating a persistent state of activation in platelet and coagulation systems in IBD. It was demonstrated that, even without any stimulation, platelets from IBD patients displayed spontaneous aggregation and hypersensitivity [108]. This observation could potentially explain why one-third of thrombotic events occurred during clinical remission [109, 110]. PLT can serve as a simple marker for distinguishing between the active and inactive phases of IBD. The sensitivity and specificity of PLT in detecting active CD were reported at 80.0% and 86.7%, respectively, with an impressive identification accuracy reflected by an area under the receiver operating characteristic curve (AUROC) of 0.909 [85]. While elevated PLT is associated with IBD disease activity, it is not an independent predictor of thrombotic events in patients with IBD, as many other diseases, such as malignancies, can also lead to increased PLT [111].

For MPV, our meta-analysis found that the changes in MPV among IBD patients were significantly lower compared to those in the control group, irrespective of whether they belonged to the UC or CD groups or the active and inactive groups. A previous meta-analysis has reported a decrease in MPV in IBD patients [112], which was consistent with our findings. The reduced MPV levels were frequently reported and exhibited a correlation with endoscopic findings and disease activity indexes, such as C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) [68, 84]. Platelet volume decreases in the presence of an inflammatory process, primarily due to abnormalities in thrombopoiesis and increased platelet consumption. Inflammatory mediators stimulate bone marrow precursors to enhance platelet generation at the cost of maturation time, delivering smaller platelet in circulation, while at the same time larger and more active platelet are consumed at inflammatory sites [113, 114] Several studies have indicated that MPV could serve as a potential inflammatory marker for IBD. In a diagnostic study, MPV demonstrated a sensitivity of 60.0% and specificity of 77.5% for detecting active CD, while for active UC, the sensitivity and specificity were 56.3% and 77.5%, respectively. The AUROC was 0.718 for CD and 0.691 for UC [60]. However, Saler T. et al.’s studies contradicted these findings, suggesting that MPV lacked differential value in distinguishing between active and inactive IBD [115]. Further research is needed to determine whether MPV can reliably differentiate IBD activity.

PDW directly measures variability in platelet size, varies with platelet activity, and mirrors the heterogeneity in platelet morphology [116, 117]. Under physiological conditions, a direct correlation exists between MPV and PDW, with both typically changing in the same direction [117]. In our study, we found no statistical difference between the PDW levels in IBD patients and healthy people, but PDW levels in the active group were significantly lower than those in the normal control. Similar to our findings, previous studies have also found that patients with active IBD have significantly lower PDW levels than healthy controls [60, 68]. Moreover, patients with active IBD were found to have significantly lower PDW levels than those in remission [85]. PCT is a measurement method derived from PLT and MPV, and is numerically equal to the product of the two indicators. In the present study, PCT levels were significantly higher in the IBD population than in the healthy control group. Several other studies have also shown that PCT is significantly higher in IBD populations [60, 62, 63], with PCT demonstrating a significant association with ESR and white blood cell count [60]. It was also revealed that PDW was positively and PCT was negatively correlated with disease activity in UC [60]. In a diagnostic study by Galijašević M. et al. [85], the AUROC for the differentiation of UC and CD activity by PDW was 0.722 and 0.798, respectively, indicating fair diagnostic accuracy. However, this accuracy was surpassed by PCT, whose AUROC for the differentiation of UC and CD activity was 0.731 and 0.891, respectively. Tang J. et al.’s study demonstrated that PCT emerged as the most effective index for monitoring disease activity in CD patients with high-sensitivity CRP levels lower than 10.0 mg/L (sensitivity 71%, specificity 85%, AUROC 0.77) [68]. Nevertheless, it is noteworthy that PDW and PCT were often underestimated, and the number of studies conducted on these platelet parameters was far less than those on PLT and MPV.

The multifaceted nature of platelets positions them prominently in human health and various diseases, extending beyond IBD [118]. This meta-analysis represents a pioneering effort to systematically evaluate differences in all major platelet parameters between IBD patients and healthy individuals. We implemented a robust search strategy to identify relevant studies and examined differences in all significant platelet parameters between IBD patients and healthy individuals. Despite the novelty of our work, certain limitations should be noted. For instance, there was considerable heterogeneity in partial summary results. While subgroup analysis elucidated some sources of heterogeneity, others remained unexplained. In some studies, details regarding disease type and activity were lacking, and insufficient data extraction for additional confounders (e.g., sex, age, IBD medication) hindered further analysis. Furthermore, variations in the criteria for diagnosing and clinically evaluating IBD, coupled with differences in the platelet analyzers utilized, might introduce potential biases and challenge the generalizability of these findings to a broader context.

Conclusion

In conclusion, this meta-analysis reveals that individuals with IBD exhibit significantly elevated PLT and PCT, alongside a significant decrease in MPV compared to healthy individuals. Moreover, PDW demonstrates a significant reduction only in patients with active IBD compared to those in a healthy state. The platelet parameters can offer reliable insights for assessing the severity of IBD and understanding potential pathophysiological mechanisms. Monitoring the clinical manifestations of platelet abnormalities serves as a valuable means to obtain diagnostic and prognostic information. Conversely, proactive measures should be taken to prevent the consequences of platelet abnormalities in individuals with IBD. Furthermore, there is a pressing requirement for more rigorous clinical trials to establish diagnostic criteria and advance the clinical evaluation of IBD at the platelet parameters level.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Baumgart DC, Carding SR. Inflammatory bowel disease: cause and immunobiology. Lancet. 2007;369(9573):1627–40. https://doi.org/10.1016/s0140-6736(07)60750-8

    Article  CAS  PubMed  Google Scholar 

  2. Ungaro R, Mehandru S, Allen PB, Peyrin-Biroulet L, Colombel JF. Ulcerative colitis. Lancet. 2017;389(10080):1756–70. https://doi.org/10.1016/s0140-6736(16)32126-2

    Article  PubMed  Google Scholar 

  3. Gros B, Kaplan GG. Ulcerative colitis in adults: a review. JAMA. 2023;330(10):951– 65. https://doi.org/10.1001/jama.2023.15389

    Article  CAS  PubMed  Google Scholar 

  4. The global. Regional, and national burden of inflammatory bowel disease in 195 countries and territories, 1990–2017: a systematic analysis for the global burden of Disease Study 2017. Lancet Gastroenterol Hepatol. 2020;5(1):17–30. https://doi.org/10.1016/s2468-1253(19)30333-4

    Article  Google Scholar 

  5. Senchenkova E, Seifert H, Granger DN. Hypercoagulability and platelet abnormalities in inflammatory bowel disease. Semin Thromb Hemost. 2015;41(6):582–9. https://doi.org/10.1055/s-0035-1556590

    Article  CAS  PubMed  Google Scholar 

  6. Dib PRB, Quirino-Teixeira AC, Merij LB, Pinheiro MBM, Rozini SV, Andrade FB, et al. Innate immune receptors in platelets and platelet-leukocyte interactions. J Leukoc Biol. 2020;108(4):1157–82. https://doi.org/10.1002/jlb.4mr0620-701r

    Article  CAS  PubMed  Google Scholar 

  7. Voudoukis E, Karmiris K, Koutroubakis IE. Multipotent role of platelets in inflammatory bowel diseases: a clinical approach. World J Gastroenterol. 2014;20(12):3180–90. https://doi.org/10.3748/wjg.v20.i12.3180

    Article  PubMed  PubMed Central  Google Scholar 

  8. Yoshida H, Granger DN. Inflammatory bowel disease: a paradigm for the link between coagulation and inflammation. Inflamm Bowel Dis. 2009;15(8):1245–55. https://doi.org/10.1002/ibd.20896

    Article  PubMed  Google Scholar 

  9. Petrey AC, de la Motte CA. Hyaluronan in inflammatory bowel disease: cross-linking inflammation and coagulation. Matrix Biol. 2019;78–9. https://doi.org/10.1016/j.matbio.2018.03.011

  10. Cheng K, Faye AS. Venous thromboembolism in inflammatory bowel disease. World J Gastroenterol. 2020;26(12):1231–41. https://doi.org/10.3748/wjg.v26.i12.1231

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Stadnicki A, Stadnicka I. Venous and arterial thromboembolism in patients with inflammatory bowel diseases. World J Gastroenterol. 2021;27(40):6757–74. https://doi.org/10.3748/wjg.v27.i40.6757

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ. 2021;372:n160. https://doi.org/10.1136/bmj.n160

    Article  PubMed  PubMed Central  Google Scholar 

  13. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25(9):603–5. https://doi.org/10.1007/s10654-010-9491-z

    Article  PubMed  Google Scholar 

  14. Rostom ADC, Cranney A, Saloojee N, Sy R, Garritty C et al. Celiac Disease. Rockville (MD): Agency for Healthcare Research and Quality (US); 2004 Sep. (Evidence Reports/Technology Assessments, No. 104.) Appendix D. Quality Assessment Forms. http://www.ncbi.nlm.nih.gov/books/NBK35156

  15. Wells GA SB, Connell D, Peterson J, Welch V, Losos M et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.htm

  16. Hu J, Dong Y, Chen X, Liu Y, Ma D, Liu X, et al. Prevalence of suicide attempts among Chinese adolescents: a meta-analysis of cross-sectional studies. Compr Psychiatry. 2015;61:78–89. https://doi.org/10.1016/j.comppsych.2015.05.001

    Article  PubMed  Google Scholar 

  17. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135. https://doi.org/10.1186/1471-2288-14-135

    Article  PubMed  PubMed Central  Google Scholar 

  18. Luo D, Wan X, Liu J, Tong T. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res. 2018;27(6):1785–805. https://doi.org/10.1177/0962280216669183

    Article  PubMed  Google Scholar 

  19. Higgins JPTTJ, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane, 2023. www.training.cochrane.org/handbook

  20. Lam A, Borda IT, Inwood MJ, Thomson S. Coagulation studies in ulcerative colitis and Crohn’s disease. Gastroenterology. 1975;68(2):245–51.

    Article  CAS  PubMed  Google Scholar 

  21. Bygdeman S, Tomenius J, Thunell S, PLATELET-FUNCTION IN, CROHNS-DISEASE. Thromb Res. 1977;11(2):263–5. https://doi.org/10.1016/0049-3848(77)90044-5

    Article  CAS  PubMed  Google Scholar 

  22. Fukushima K, Yagita A, Orima I, Tatekawa I, Kumakawa T, Mori M. SIGNIFICANCE OF THROMBOCYTOSIS IN INFLAMMATORY BOWEL DISEASES. J Jpn Soc Coloproctol. 1990;43(7):1343–51.

    Article  Google Scholar 

  23. Zhao L, THROMBOCYTIC NUMBER VOLUME AND THE FUNCTION OF ADHESION RATE AND MAXIMUM AGGREGATION RATE IN PATIENTS WITH ULCERATIVE COLITIS, et al. J China Med Univ. 1990;19(SUPPL):53–6.

    Google Scholar 

  24. Wiedermann CJ, Sacerdote P, Propst A, Propst T, Judmaier G, Kathrein H, et al. Decreased β-endorphin content in peripheral blood mononuclear leukocytes from patients with Crohn’s disease. Brain Behav Immun. 1994;8(3):261–9. https://doi.org/10.1006/brbi.1994.1024

    Article  CAS  PubMed  Google Scholar 

  25. Chiarantini E, Valanzano R, Liotta AA, Cellai AP, Fedi S, Ilari I, et al. Hemostatic abnormalities in inflammatory bowel disease. Thromb Res. 1996;82(2):137–46. https://doi.org/10.1016/0049-3848(96)00060-6

    Article  CAS  PubMed  Google Scholar 

  26. Järemo P, Sandberg-Gertzen H. Platelet density and size in inflammatory bowel disease. Thromb Haemost. 1996;75(4):560–1.

    Article  PubMed  Google Scholar 

  27. Chiarantini E, Valanzano R, Liotta AA, Cellai AP, Ilari I, Prisco D, et al. Persistence of hemostatic alterations in patients affected by Crohn’s disease after bowel surgery. Thromb Res. 1997;87(6):539–46. https://doi.org/10.1016/s0049-3848(97)00183-7

    Article  CAS  PubMed  Google Scholar 

  28. Heits F, Stahl M, Ludwig D, Stange EF, Jelkmann W. Elevated serum thrombopoietin and interleukin-6 concentrations in thrombocytosis associated with inflammatory bowel disease. J Interf Cytok Res. 1999;19(7):757–60. https://doi.org/10.1089/107999099313604

    Article  CAS  Google Scholar 

  29. Kapsoritakis AN, Potamianos SP, Sfiridaki AI, Koukourakis MI, Koutroubakis IE, Roussomoustakaki MI, et al. Elevated thrombopoietin serum levels in patients with inflammatory bowel disease. Am J Gastroenterol. 2000;95(12):3478–81. https://doi.org/10.1111/j.1572-0241.2000.03364.x

    Article  CAS  PubMed  Google Scholar 

  30. Sturm A, Schulte C, Schatton R, Becker A, Cario E, Goebell H, et al. Transforming growth factor-beta and hepatocyte growth factor plasma levels in patients with inflammatory bowel disease. Eur J Gastroenterol Hepatol. 2000;12(4):445–50. https://doi.org/10.1097/00042737-200012040-00013

    Article  CAS  PubMed  Google Scholar 

  31. Kapsoritakis AN, Koukourakis MI, Sfiridaki A, Potamianos SP, Kosmadaki MG, Koutroubakis IE, et al. Mean platelet volume: a useful marker of inflammatory bowel disease activity. Am J Gastroenterol. 2001;96(3):776–81. https://doi.org/10.1111/j.1572-0241.2001.03621.x

    Article  CAS  PubMed  Google Scholar 

  32. van Bodegraven AA, Schoorl M, Baak JP, Linskens RK, Bartels PC, Tuynman HA. Hemostatic imbalance in active and quiescent ulcerative colitis. Am J Gastroenterol. 2001;96(2):487–93. https://doi.org/10.1111/j.1572-0241.2001.03532.x

    Article  PubMed  Google Scholar 

  33. Dai X, Niu F, Zheng P. Proinflammatory cytokines: tumor necrosis factor-α and interleukin-6 in patients with Crohn’s disease. Chin J Gastroenterol. 2003;8(1):33–4.

    Google Scholar 

  34. Kapsoritakis A, Sfiridaki A, Maltezos E, Simopoulos K, Giatromanolaki A, Sivridis E, et al. Vascular endothelial growth factor in inflammatory bowel disease. Int J Colorectal Dis. 2003;18(5):418–22. https://doi.org/10.1007/s00384-003-0495-y

    Article  PubMed  Google Scholar 

  35. Dong WG, Liu SP, Zhu HH, Luo HS, Yu JP. Abnormal function of platelets and role of angelica Sinensis in patients with ulcerative colitis. World J Gastroenterol. 2004;10(4):606–9. https://doi.org/10.3748/wjg.v10.i4.606

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Irving PM, Macey MG, Shah U, Webb L, Langmead L, Rampton DS. Formation of platelet-leukocyte aggregates in inflammatory bowel disease. Inflamm Bowel Dis. 2004;10(4):361–72. https://doi.org/10.1097/00054725-200407000-00007

    Article  PubMed  Google Scholar 

  37. Andoh A, Yoshida T, Yagi Y, Bamba S, Hata K, Tsujikawa T, et al. Increased aggregation response of platelets in patients with inflammatory bowel disease. J Gastroenterol. 2006;41(1):47–54. https://doi.org/10.1007/s00535-005-1721-x

    Article  CAS  PubMed  Google Scholar 

  38. Drzewoski J, Gasiorowska A, Małecka-Panas E, Bald E, Czupryniak L. Plasma total homocysteine in the active stage of ulcerative colitis. J Gastroenterol Hepatol. 2006;21(4):739–43. https://doi.org/10.1111/j.1440-1746.2006.04255.x

    Article  CAS  PubMed  Google Scholar 

  39. Efrat B, Iris G, Wang H, Eitan S, Yona K. A subgroup of first-degree relatives of Crohn’s disease patients shows a profile of inflammatory markers in the blood which is more typical of Crohn’s disease patients than of normal individuals. Mediators Inflamm. 2006;2006(2):74785. https://doi.org/10.1155/mi/2006/74785

    Article  PubMed  PubMed Central  Google Scholar 

  40. Payzin B, Adakan FY, Yalçin HC, Çetinkaya GS, Berkmen S, Eraslan S, et al. Natural coagulation inhibitory proteins and activated protein C resistance in Turkish patients with inflammatory bowel disease. Turk J Gastroenterol. 2006;17(3):183–90.

    PubMed  Google Scholar 

  41. Kayahan H, Akarsu M, Ozcan MA, Demir S, Ates H, Unsal B, et al. Reticulated platelet levels in patients with ulcerative colitis. Int J Colorectal Dis. 2007;22(12):1429–35. https://doi.org/10.1007/s00384-007-0330-y

    Article  PubMed  Google Scholar 

  42. Maher MM, Soloma SH. Assessment of thrombophilic abnormalities during the active state of inflammatory bowel disease. Saudi J Gastroenterol. 2008;14(4):192–7. https://doi.org/10.4103/1319-3767.41743

    Article  PubMed  PubMed Central  Google Scholar 

  43. Cakal B, Akoz AG, Ustundag Y, Yalinkilic M, Ulker A, Ankarali H. Red cell distribution width for assessment of activity of inflammatory bowel disease. Dig Dis Sci. 2009;54(4):842–7. https://doi.org/10.1007/s10620-008-0436-2

    Article  PubMed  Google Scholar 

  44. Krzystek-Korpacka M, Neubauer K, Matusiewicz M. Platelet-derived growth factor-BB reflects clinical, inflammatory and angiogenic disease activity and oxidative stress in inflammatory bowel disease. Clin Biochem. 2009;42(16–17):1602–9. https://doi.org/10.1016/j.clinbiochem.2009.08.002

    Article  CAS  PubMed  Google Scholar 

  45. Shen J, Ran ZH, Zhang Y, Cai Q, Yin HM, Zhou XT, et al. Biomarkers of altered coagulation and fibrinolysis as measures of disease activity in active inflammatory bowel disease: a gender-stratified, cohort analysis. Thromb Res. 2009;123(4):604–11. https://doi.org/10.1016/j.thromres.2008.04.004

    Article  CAS  PubMed  Google Scholar 

  46. Yüksel O, Helvaci K, Başar O, Köklü S, Caner S, Helvaci N, et al. An overlooked indicator of disease activity in ulcerative colitis: mean platelet volume. Platelets. 2009;20(4):277–81. https://doi.org/10.1080/09537100902856781

    Article  CAS  PubMed  Google Scholar 

  47. Krzystek-Korpacka M, Neubauer K, Berdowska I, Zielinski B, Paradowski L, Gamian A. Impaired erythrocyte antioxidant defense in active inflammatory bowel disease: impact of anemia and treatment. Inflamm Bowel Dis. 2010;16(9):1467–75. https://doi.org/10.1002/ibd.21234

    Article  PubMed  Google Scholar 

  48. Krzystek-Korpacka M, Neubauer K, Matusiewicz M. Circulating midkine in Crohn’s disease: clinical implications. Inflamm Bowel Dis. 2010;16(2):208–15. https://doi.org/10.1002/ibd.21011

    Article  PubMed  Google Scholar 

  49. Arhan M, Onal IK, Tas A, Kurt M, Kalkan IH, Ozin Y, et al. The role of red cell distribution width as a marker in inflammatory bowel disease. Turk J Med Sci. 2011;41(2):227–34. https://doi.org/10.3906/sag-0912-418

    Article  Google Scholar 

  50. Dogan Y, Soylu A, Eren GA, Poturoglu S, Dolapcioglu C, Sonmez K, et al. Evaluation of QT and P wave dispersion and mean platelet volume among inflammatory bowel disease patients. Int J Med Sci. 2011;8(7):540–6. https://doi.org/10.7150/ijms.8.540

    Article  PubMed  PubMed Central  Google Scholar 

  51. Mohammadi M, Hayatbakhsh MM, Zahedi MJ, Jalalpour MR, Pakgohar A. Serum interleukin-23 levels in patients with ulcerative colitis. Iran J Immunol. 2011;8(3):183–8.

    CAS  PubMed  Google Scholar 

  52. Polińska B, Matowicka-Karna J, Kemona H. Assessment of the influence of the inflammatory process on the activation of blood platelets and morphological parameters in patients with ulcerative colitis (colitis ulcerosa). Folia Histochem Cytobiol. 2011;49(1):119–24. https://doi.org/10.5603/fhc.2011.0017

    Article  PubMed  Google Scholar 

  53. Yarur AJ, Deshpande AR, Pechman DM, Tamariz L, Abreu MT, Sussman DA. Inflammatory bowel disease is associated with an increased incidence of cardiovascular events. Am J Gastroenterol. 2011;106(4):741–7. https://doi.org/10.1038/ajg.2011.63

    Article  PubMed  Google Scholar 

  54. Yeşil A, Senateş E, Bayoğlu IV, Erdem ED, Demirtunç R, Kurdaş Övünç AO. Red cell distribution width: a novel marker of activity in inflammatory bowel disease. Gut Liver. 2011;5(4):460–7. https://doi.org/10.5009/gnl.2011.5.4.460

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Huang Q, Wang E, Lin M, Yan X, Zhang Y. Analysis of P-selectin and platelet parameters in patients with ulcerative colitis. Chin J Gastroenterol. 2012;17(7):430–2. https://doi.org/10.3969/j.issn.1008-7125.2012.07.011

    Article  Google Scholar 

  56. Liu S, Ren J, Han G, Wang G, Gu G, Xia Q, et al. Mean platelet volume: a controversial marker of disease activity in Crohn’s disease. Eur J Med Res. 2012;17(1):27. https://doi.org/10.1186/2047-783x-17-27

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Akdoǧan RA, Durakoǧlugil ME, Kocaman SA, Çiçek Y, Durakoǧlugil T, Ergül E, et al. Increased pulse wave velocity and carotid intima-media thickness in patients with ulcerative colitis. Dig Dis Sci. 2013;58(8):2293–300. https://doi.org/10.1007/s10620-013-2634-9

    Article  PubMed  Google Scholar 

  58. Garg M, Rosella O, Lubel JS, Gibson PR. Association of circulating vitamin D concentrations with intestinal but not systemic inflammation in inflammatory bowel disease. Inflamm Bowel Dis. 2013;19(12):2634–43. https://doi.org/10.1097/01.MIB.0000436957.77533.b2

    Article  PubMed  Google Scholar 

  59. Liu WX, Zhang S, Dai C, Ren Y. Correlation between routine blood indexes and disease activity in patients with inflammatory bowel disease. World Chin J Digestol. 2013;21(33):3654–60. https://doi.org/10.11569/wcjd.v21.i33.3654

    Article  CAS  Google Scholar 

  60. Öztürk ZA, Dag MS, Kuyumcu ME, Cam H, Yesil Y, Yilmaz N, et al. Could platelet indices be new biomarkers for inflammatory bowel diseases? Eur Rev Med Pharmacol Sci. 2013;17(3):334–41.

    PubMed  Google Scholar 

  61. Schoepfer AM, Beglinger C, Straumann A, Safroneeva E, Romero Y, Armstrong D, et al. Fecal calprotectin more accurately reflects endoscopic activity of ulcerative colitis than the Lichtiger Index, C-reactive protein, platelets, hemoglobin, and blood leukocytes. Inflamm Bowel Dis. 2013;19(2):332–41. https://doi.org/10.1097/MIB.0b013e3182810066

    Article  PubMed  Google Scholar 

  62. Voudoukis E, Karmiris K, Oustamanolakis P, Theodoropoulou A, Sfiridaki A, Paspatis GA, et al. Association between thrombocytosis and iron deficiency anemia in inflammatory bowel disease. Eur J Gastroenterol Hepatol. 2013;25(10):1212–6. https://doi.org/10.1097/MEG.0b013e328363e354

    Article  CAS  PubMed  Google Scholar 

  63. Avdagić N, Babić N, Začiragić A, Hadžović-Džuvo A, Lepara O, Nakaš-Ićindić E. Could mean platelet volume serve as a marker of disease activity in Crohn’s disease? Folia Medica -. Facultatis Medicinae Universitatis Saraeviensis. 2014;49(1):23–31.

    Google Scholar 

  64. Ciećko-Michalska I, Wierzbicka-Tutka I, Szczepanek M, Fedak D, Jabłoński K, Cibor D, et al. TGF-β1 and granulocyte elastase in the evaluation of activity of inflammatory bowel disease. A pilot study. Postepy Hig Med Dosw (Online). 2014;68:66–72. https://doi.org/10.5604/17322693.1086361

    Article  PubMed  Google Scholar 

  65. Dolapcioglu C, Soylu A, Kendir T, Ince AT, Dolapcioglu H, Purisa S, et al. Coagulation parameters in inflammatory bowel disease. Int J Clin Exp Med. 2014;7(5):1442–8.

    PubMed  PubMed Central  Google Scholar 

  66. Huo H, Li YM. Clinical relevance of platelets and D -dimer in patients with ulcerative colitis. World Chin J Digestol. 2014;22(28):4360–3. https://doi.org/10.11569/wcjd.v22.i28.4360

    Article  CAS  Google Scholar 

  67. Garg M, Burrell LM, Velkoska E, Griggs K, Angus PW, Gibson PR, et al. Upregulation of circulating components of the alternative renin-angiotensin system in inflammatory bowel disease: a pilot study. J Renin Angiotensin Aldosterone Syst. 2015;16(3):559–69. https://doi.org/10.1177/1470320314521086

    Article  CAS  PubMed  Google Scholar 

  68. Tang J, Gao X, Zhi M, Zhou HM, Zhang M, Chen HW, et al. Plateletcrit: a sensitive biomarker for evaluating disease activity in Crohn’s disease with low hs-CRP. J Dig Dis. 2015;16(3):118–24. https://doi.org/10.1111/1751-2980.12225

    Article  CAS  PubMed  Google Scholar 

  69. Cibor D, Owczarek D, Butenas S, Salapa K, Mach T, Undas A. Levels and activities of Von Willebrand factor and metalloproteinase with thrombospondin type-1 motif, number 13 in inflammatory bowel diseases. World J Gastroenterol. 2017;23(26):4796–805. https://doi.org/10.3748/wjg.v23.i26.4796

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Gawronska B, Matowicka-Karna J, Kralisz M, Kemona H. Markers of inflammation and influence of nitric oxide on platelet activation in the course of ulcerative colitis. Oncotarget. 2017;8(40):68108–14. https://doi.org/10.18632/oncotarget.19202

    Article  PubMed  PubMed Central  Google Scholar 

  71. Szczeklik K, Pytko-Polończyk J, Cibor D, Owczarek D, Mach T. Oral mucosa lesions in patients with active Crohn’s disease - a prospective study. Przegl Lek. 2017;74(2):57–61.

    PubMed  Google Scholar 

  72. Ye L, Zhang YP, Yu N, Jia YX, Wan SJ, Wang FY. Serum platelet factor 4 is a reliable activity parameter in adult patients with inflammatory bowel disease: a pilot study. Med (Baltim). 2017;96(11):e6323. https://doi.org/10.1097/md.0000000000006323

    Article  CAS  Google Scholar 

  73. Chen GL, Xiong DQ, Jiang ZY, Zhang CM, Hu QY. Diagnostic value of platelet-tolymphocyte ratio and neutrophilto-lymphocyte ratio in Crohn’s disease. World Chin J Digestol. 2018;26(2):93–8. https://doi.org/10.11569/wcjd.v26.i2.93

    Article  Google Scholar 

  74. Szczeklik K, Krzyściak W, Cibor D, Domagała-Rodacka R, Pytko-Polończyk J, Mach T, et al. Markers of lipid peroxidation and antioxidant status in the serum and saliva of patients with active Crohn disease. Pol Arch Intern Med. 2018;128(6):362–70. https://doi.org/10.20452/pamw.4273

    Article  PubMed  Google Scholar 

  75. Szczeklik K, Mach T, Cibor D, Owczarek D, Sapa J, Papież M, et al. Correlation of Paraoxonase-1 with the severity of Crohn’s Disease. Molecules. 2018;23(10). https://doi.org/10.3390/molecules23102603

  76. Wang D, Han J. Study on correlation between platelet, fibrinogen, D-Dimer and Ulcerative Colitis. Chin J Gastroenterol. 2018;23(8):486–8. https://doi.org/10.3969/j.issn.1008-7125.2018.08.008

    Article  Google Scholar 

  77. Coskun Y, ROLE OF MEAN PLATELET VOLUME AS A MARKER OF DISEASE, ACTIVITY IN PATIENTS WITH ULCERATIVE COLITIS. Acta Med Mediterranea. 2019;35(6):3355–60. https://doi.org/10.19193/0393-6384_2019_6_528

    Article  Google Scholar 

  78. Erecan E, Yorulmaz E, Ozdemir B, Yorulmaz H, Davutoglu C, SERUM FETUIN-A LEVELS, IN PATIENTS WITH ULCERATIVE COLITIS. Acta Med Mediterranea. 2019;35(6):2927–31. https://doi.org/10.19193/0393-6384_2019_6_457

    Article  Google Scholar 

  79. Jiang Q, Wu Q, Li H, Lü C. Correlation of Coagulation disorders with Disease activity in patients with Crohn’s Disease. Chin J Gastroenterol. 2019;24(4):224–9. https://doi.org/10.3969/j.issn.1008-7125.2019.04.008

    Article  Google Scholar 

  80. Kothari HG, Gupta SJ, Gaikwad NR. Utility of carotid intima-media thickness as an auxiliary vascular parameter of structural alteration in ulcerative colitis. Inflamm Intest Dis. 2019;4(1):27–34. https://doi.org/10.1159/000499199

    Article  PubMed  PubMed Central  Google Scholar 

  81. Bai X, Bai G, Tang L, Liu L, Li Y, Jiang W. Changes in MMP-2, MMP-9, inflammation, blood coagulation and intestinal mucosal permeability in patients with active ulcerative colitis. Exp Ther Med. 2020;20(1):269–74. https://doi.org/10.3892/etm.2020.8710

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Li L, Xu P, Zhang Z, Zhou X, Chen C, Lu C. Platelets can reflect the severity of Crohn’s disease without the effect of anemia. Clin (Sao Paulo). 2020;75:e1596. https://doi.org/10.6061/clinics/2020/e1596

    Article  Google Scholar 

  83. Sari C, Özer Sarı S, Duran Karaduman B, Koseoglu H, Şimşek E. Assessment of left ventricular contractile functions in inflammatory bowel disease according to disease activity. J Dig Dis. 2020;21(11):629–38. https://doi.org/10.1111/1751-2980.12943

    Article  CAS  PubMed  Google Scholar 

  84. Chen Z, Lu Y, Wu J, Zhang H. Clinical significance of blood platelets and mean platelet volume in patients with ulcerative colitis. J Int Med Res. 2021;49(4):3000605211009715. https://doi.org/10.1177/03000605211009715

    Article  CAS  PubMed  Google Scholar 

  85. Galijašević M, Dervišević A, Fajkić A, Avdagić N, Suljević D. Platelet Mass Index and other platelet parameters in the Assessment of Inflammatory Bowel diseases activity. Curr Health Sci J. 2021;47(4):566–74. https://doi.org/10.12865/chsj.47.04.13

    Article  PubMed  PubMed Central  Google Scholar 

  86. Zhang G, Chen H, Guo Y, Zhang W, Jiang Q, Zhang S, et al. Activation of platelet NLRP3 inflammasome in Crohn’s Disease. Front Pharmacol. 2021. https://doi.org/10.3389/fphar.2021.705325

    Article  PubMed  PubMed Central  Google Scholar 

  87. Zhang MH, Wang H, Wang HG, Wen X, Yang XZ. Effective immune-inflammation index for ulcerative colitis and activity assessments. World J Clin Cases. 2021;9(2):334–43. https://doi.org/10.12998/wjcc.v9.i2.334

    Article  PubMed  PubMed Central  Google Scholar 

  88. Ammar SR, Ghazy MA, Mabrouk MM, Gawaly AM. Role of serum hepcidin and reticulocyte hemoglobin concentration in evaluation of anemia in ulcerative colitis patients. J Appl Hematol. 2022;13(1):28–34. https://doi.org/10.4103/joah.joah_127_21

    Article  Google Scholar 

  89. Lu J, Yu F, Huang J, Yu H, Li F, Le Z, et al. Hypocholesterolemia and inflammatory biomarkers act as predictors of severe vitamin D Deficiency in patients with Crohn’s Disease: a clinical analysis of 862 patients in China. Front Nutr. 2022;9:806887. https://doi.org/10.3389/fnut.2022.806887

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Abdel Hameed NA, Shaker OG, Hasona NA. LINC00641/miR-378a and their cross-talk with TNF-a/IFN-g as potential biomarkers in Ulcerative Colitis and Crohn’s diseases. J Interf Cytok Res. 2023;43(11):531–7. https://doi.org/10.1089/jir.2023.0097

    Article  CAS  Google Scholar 

  91. Basha OM, Hafez RA, Salem SM, Anis RH, Hanafy AS. Impact of gut microbiome alteration in Ulcerative Colitis patients on disease severity and outcome. Clin Exp Med. 2023;23(5):1763–72. https://doi.org/10.1007/s10238-022-00917-x

    Article  CAS  PubMed  Google Scholar 

  92. Feng R, Tian Z, Mao R, Ma R, Luo W, Zhao M, et al. Gut microbiome-generated phenylacetylglutamine from Dietary protein is Associated with Crohn’s Disease and exacerbates colitis in mouse model possibly via platelet activation. J Crohns Colitis. 2023;17(11):1833–46. https://doi.org/10.1093/ecco-jcc/jjad098

    Article  PubMed  Google Scholar 

  93. Geng B, Ding X, Li X, Liu H, Zhao W, Gong H, et al. Peripheral blood T-lymphocyte subsets are potential biomarkers of disease severity and clinical outcomes in patients with ulcerative colitis: a retrospective study. BMC Gastroenterol. 2023;23(1). https://doi.org/10.1186/s12876-023-02769-5

  94. Huang J, Lu J, Jiang F, Song T. Platelet/Albumin ratio and plateletcrit levels are potential new biomarkers for assessing endoscopic inflammatory bowel disease severity. BMC Gastroenterol. 2023;23(1):393. https://doi.org/10.1186/s12876-023-03043-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Liu Q, Wang D, Yang X, Ma F, Han W, Hu J, et al. The Mechanosensitive Ion Channel PIEZO1 in intestinal epithelial cells mediates inflammation through the NOD-Like receptor 3 pathway in Crohn’s Disease. Inflamm Bowel Dis. 2023;29(1):103–15. https://doi.org/10.1093/ibd/izac152

    Article  CAS  PubMed  Google Scholar 

  96. Sleutjes JAM, Van Der Woude CJ, Verploegh PJP, Aribas E, Kavousi M, Van Roeters JE, et al. Cardiovascular risk profiles in patients with inflammatory bowel disease differ from matched controls from the general population. Eur J Prev Cardiol. 2023;30(15):1615–22. https://doi.org/10.1093/eurjpc/zwad124

    Article  PubMed  Google Scholar 

  97. Xue J, Zhang M, Zhang Y, Ouyang M, Chen Z, Cheng S, et al. Diagnostic value of red blood cell distribution width for the activity of Crohn′s disease. Chin J Inflamm Bowel Dis. 2023;7(4):324–30. https://doi.org/10.3760/cma.j.cn101480-20230607-00091

    Article  Google Scholar 

  98. Ye Y, Gu D, Wei W, Miao J. Correlation Analysis of TAM Subfamily of Receptor Tyrosine Kinases in Ulcerative Colitis. Chin J Gastroenterol. 2023;27(5):257–62. https://doi.org/10.3969/j.issn.1008-7125.2022.05.001

    Article  Google Scholar 

  99. Morowitz DA, Allen LW, Kirsner JB. Thrombocytosis in chronic inflammatory bowel disease. Ann Intern Med. 1968;68(5):1013–21. https://doi.org/10.7326/0003-4819-68-5-1013

    Article  CAS  PubMed  Google Scholar 

  100. Wang JC, Hashmi G. Elevated thrombopoietin levels in patients with myelofibrosis may not be due to enhanced production of thrombopoietin by bone marrow. Leuk Res. 2003;27(1):13–7. https://doi.org/10.1016/s0145-2126(02)00069-3

    Article  PubMed  Google Scholar 

  101. Schafer AI, Thrombocytosis. N Engl J Med. 2004;350(12):1211. https://doi.org/10.1056/NEJMra035363

    Article  CAS  PubMed  Google Scholar 

  102. Heits F, Stahl M, Ludwig D, Stange EF, Jelkmann W. Elevated serum thrombopoietin and interleukin-6 concentrations in thrombocytosis associated with inflammatory bowel disease. J Interferon Cytokine Res. 1999;19(7):757–60. https://doi.org/10.1089/107999099313604

    Article  CAS  PubMed  Google Scholar 

  103. Papa A, Danese S, Piccirillo N, Toriani-Terenzi C, Bartolozzi F, Piscaglia AC, et al. Thrombopoietin serum levels in patients with inflammatory bowel disease with and without previous thromboembolic events. Hepatogastroenterology. 2003;50(49):132–5.

    PubMed  Google Scholar 

  104. Boccatonda A, Balletta M, Vicari S, Hoxha A, Simioni P, Campello E. The Journey through the Pathogenesis and treatment of venous thromboembolism in Inflammatory Bowel diseases: a narrative review. Semin Thromb Hemost. 2023;49(7):744–55. https://doi.org/10.1055/s-0042-1758869

    Article  CAS  PubMed  Google Scholar 

  105. Danese S, Motte Cd Cde L, Fiocchi C. Platelets in inflammatory bowel disease: clinical, pathogenic, and therapeutic implications. Am J Gastroenterol. 2004;99(5):938–45. https://doi.org/10.1111/j.1572-0241.2004.04129.x

    Article  PubMed  Google Scholar 

  106. Collins CE, Cahill MR, Newland AC, Rampton DS. Platelets circulate in an activated state in inflammatory bowel disease. Gastroenterology. 1994;106(4):840–5. https://doi.org/10.1016/0016-5085(94)90741-2

    Article  CAS  PubMed  Google Scholar 

  107. Matowicka-Karna J. Markers of inflammation, activation of blood platelets and coagulation disorders in inflammatory bowel diseases. Postepy Hig Med Dosw (Online). 2016;70:305–12. https://doi.org/10.5604/17322693.1199305

    Article  PubMed  Google Scholar 

  108. Webberley MJ, Hart MT, Melikian V. Thromboembolism in inflammatory bowel disease: role of platelets. Gut. 1993;34(2):247– 51. https://doi.org/10.1136/gut.34.2.247

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Jackson LM, O’Gorman PJ, O’Connell J, Cronin CC, Cotter KP, Shanahan F. Thrombosis in inflammatory bowel disease: clinical setting, procoagulant profile and factor V Leiden. QJM. 1997;90(3):183–8. https://doi.org/10.1093/qjmed/90.3.183

    Article  CAS  PubMed  Google Scholar 

  110. Talbot RW, Heppell J, Dozois RR, Beart RW Jr. Vascular complications of inflammatory bowel disease. Mayo Clin Proc. 1986;61(2):140-5.https://doi.org/10.1016/s0025-6196(12)65200-8

  111. Simanek R, Vormittag R, Ay C, Alguel G, Dunkler D, Schwarzinger I, et al. High platelet count associated with venous thromboembolism in cancer patients: results from the Vienna Cancer and thrombosis study (CATS). J Thromb Haemost. 2010;8(1):114–20. https://doi.org/10.1111/j.1538-7836.2009.03680.x

    Article  CAS  PubMed  Google Scholar 

  112. Bambo GM, Shiferaw E, Melku M. A mean platelet volume in inflammatory bowel disease: a systematic review and meta-analysis. PLoS ONE. 2022;17(8):e0273417. https://doi.org/10.1371/journal.pone.0273417

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Collins CE, Rampton DS. Platelet dysfunction: a new dimension in inflammatory bowel disease. Gut. 1995;36(1):5–8. https://doi.org/10.1136/gut.36.1.5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Giannotta M, Tapete G, Emmi G, Silvestri E, Milla M. Thrombosis in inflammatory bowel diseases: what’s the link? Thromb J. 2015;13:14. https://doi.org/10.1186/s12959-015-0044-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Saler T, Özgür Keşkek Ş, Ergin C, Ahbab S, Sağlam Z. Mean platelet volume in patients with inflammatory bowel disease. Gen Intern Med Clini Innov. 2016;1(3):40–3. https://doi.org/10.15761/gimci.1000112

    Article  Google Scholar 

  116. Wiwanitkit V. Plateletcrit, mean platelet volume, platelet distribution width: its expected values and correlation with parallel red blood cell parameters. Clin Appl Thromb Hemost. 2004;10(2):175–8. https://doi.org/10.1177/107602960401000208

    Article  PubMed  Google Scholar 

  117. Vagdatli E, Gounari E, Lazaridou E, Katsibourlia E, Tsikopoulou F, Labrianou I. Platelet distribution width: a simple, practical and specific marker of activation of coagulation. Hippokratia. 2010;14(1):28–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  118. Franco AT, Corken A, Ware J. Platelets at the interface of thrombosis, inflammation, and cancer. Blood. 2015;126(5):582–8. https://doi.org/10.1182/blood-2014-08-531582

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Youdao Translation (https://fanyi.youdao.com/#/) for providing translation assistance in the process of literature screening and data synthesis.

Funding

The study was supported by the project of Jiangsu Province Traditional Chinese medicine digestive disease medical innovation center [grant number CXZX202208].

Author information

Authors and Affiliations

  1. Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China

    Cheng Xu, Li-ting Hu, Yi-heng Tong, Jing-yi Hu & Hong Shen

  2. Nanjing University of Chinese Medicine, Nanjing, China

    Cheng Xu, Zhen Song, Li-ting Hu & Yi-heng Tong

  3. Yancheng Binhai Hospital of Traditional Chinese Medicine, Yancheng, China

    Zhen Song

Authors
  1. Cheng Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhen Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li-ting Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yi-heng Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jing-yi Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hong Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Cheng Xu and Hong Shen conceived and designed the study. Cheng Xu and Zhen Song contributed to data collection. Cheng Xu, Zhen Song, Li-ting Hu, and Yi-heng Tong conducted the data analysis and interpretation. Cheng Xu drafted the initial manuscript. Jing-yi Hu and Hong Shen revised the manuscript. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Hong Shen.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, C., Song, Z., Hu, Lt. et al. Abnormal platelet parameters in inflammatory bowel disease: a systematic review and meta-analysis. BMC Gastroenterol 24, 214 (2024). https://doi.org/10.1186/s12876-024-03305-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12876-024-03305-9

Keywords

BMC Gastroenterology

ISSN: 1471-230X

Contact us