Introduction
Inflammatory bowel disease (IBD) is a complex disorder which instigated and amplified by the co-influence of genetic and environmental variables that perturb the immune micro-biome axis against luminal bacteria [1]. In developing country, parasites such as Blastocystis species and Giardia lamblia, are the leading causes for IBD [2]. It is mainly idiopathic disorder which can be caused by excessive and chronic inflammation of gastro-intestinal tract (GIT) that leading for rectal bleeding and weight loss [3]. Environmental and genetic factors such as altered luminal bacteria and increased intestinal permeability lead for a dysregulated immune system, resulting to gastrointestinal damage. It includes ulcerative colitis (UC) and Crohn’s disease (CD), but the chronic inflammation may not only be due to the immune system. The CD can affect all parts of alimentary canal and UC, primarily colon and the rectum. Appendical CD is rare and indistinguishable from acute appendicitis (AA) [4].
Severity of IBD depends on segment of the intestine involved. A complication or different disease presentations were intra and extra intestinal complications, such as bowel perforation, massive hemorrhage, abdominal abscess, fistula, malignancy, rectal bleeding, abdominal pain, constipation and hepatobiliary disease. Fistulas are typical complication of CD [5, 6]. Inflammatory bowel disease affects millions of individuals in the world. In approximation, about 25% of IBD patients are common before the age of 18 [7]. It is associated with comorbidity with novel virus, covid-19.
Indeed, gut-related micro vascular dysfunction in IBD leads to decreased vasodilation capacity and tissue hypo-perfusion as well as lower rate of mucosal healing and refractory inflammatory ulcerations related with Covid-19 infection [8]. Furthermore, chronic inflammation increases the risk of venous and arterial thrombosis in IBD patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [9]. It is now clear that comorbidities are associated with poorer clinical outcome in IBD patients with Covid-19 [10, 11]. Prevalence of comorbidities in this group of patients: about 60% have two or more comorbidities, which has an effect on treatment selection and disease outcomes [12].
Platelets contribute to the inflammatory process, microbial host defense; wound healing, angiogenesis and remodeling in addition to their essential role in hemostasis and thrombosis (7). Mean platelet volume (MPV),plateletcrit (PCT) and PDW are a set of platelet parameters collectively calculated by the automated complete blood count (CBC) profile [13, 14]. Platelets play a role in inflammation in a number of diseases, according to a wide body of evidence. In addition, recent research has found a correlation between platelet indices and inflammation. In IBD, there were several changes in platelet parameters, increased scale activity, density, platelet distribution width (PDW), PCT, and granulation augmentation. Moreover, the platelet releases a significant amount of pro-inflammatory substances when triggered at inflammatory sites [15–18]. Furthermore, most research showed thrombocytosis and lower MPV in CD patients (9.9fl) relative to healthy population (10.9fl) [19]. There is also evidence of reduced MPV in recurrence (7.8fl) and remission of CD (8.33fl) [20].
In current clinical practice, non–invasive biomarkers such as C-reactive protein (CRP) erythrocyte sedimentation rate (ESR) are commonly used as important for both early diagnosis and accurate monitoring of the disease activity in IBD patients [21–24]. As an acute phase protein, CRP is widely available and inexpensive diagnostic test; but, elevated serum CRP levels can also be affected by other extra intestinal inflammatory processes, and also there is genetic variability in the CRP production of individuals [25]. Moreover, because of the delayed reaction to disease conditions, ESR testing is less commonly used than CRP [21, 23]. Fecal calprotectin also has comparatively increased sensitivity and specificity and is the ideal clinical and biological marker for IBD evaluation [24, 26].
Tissue biopsy commonly used to confirm an IBD diagnosis for inflammation and changes in tissue architecture. However, CD is a transmural, a biopsy limited to the sub-mucosa that does not necessarily reflect disease activity in the deeper layers of the bowel wall. This type of test is invasive and it is less likely to be required if there is no inflammation [27]. It is fact that MPV has been used as a diagnostic marker in CRC [26, 28]. The diagnosis of an inflammatory disease is controversial and non-specific. In addition, there is wide disagreement over high costs, long-term requirements and low efficacy. In contradiction to this, the MPV test is low cost and more available in CBC.
It is fact that there is no gold standard diagnostic test to examine the severity and disease activities of IBD. In addition, there is wide disagreement over high costs, long-term requirements and low efficacy. However, MPV test is low cost and more available in CBC. Furthermore, there is no established guideline for considering MPV as diagnostic test in IBD. Therefore, cumulative evidence would be important to elucidate the diagnostic and prognostic values of MPV in IBD. In this regard, the main objectives this systematic review and meta-analysis were determining the pooled MPV and mean difference in IBD compared to health control to elucidate its potential diagnostic value. Hence, this systematic review and meta-analysis will provide sufficient evidence based information of MPV in IBD.
Methods
Design and protocol registration
This systematic review and meta-analysis was designed in accordance with Preferred Reporting Items for Systematic Review and meta-analysis Protocols (PRISMA-P) 2015 guide lines [29]. Pocket studies conducted on IBD were used to conduct this study to determine the pooled MPV and mean difference considering the CoCoPop (condition, context, population). The protocol was registered in the Prospero database under registration number CRD42021238610.
Inclusion criteria and exclusion criteria
Inclusion criteria were.
1) observational community and institutional based studies conducted on CD, AA, UC, general IBD and protocolits and 2) studies that reported MPV with standard deviation (SD) or confidence interval (CI).
Exclusion criteria were.
1) case reports and abstract without full-length articles and 2) articles conducted on CRC, gangrenous appendicitis, drug efficacy, omitted generalizability.
Sources of data.
Relevant articles were found using major electronic databases (PubMed, MEDLINE, HINARI, Embase, Scopus, Cinahl, African online archives and other source like Google scholar. In addition to account for the studies omission during electronic database searches, a direct Google search was carried using listed reference in included articles.
Searching strategy.
We identified the entry terms by using MeSH (Medical subject heading) browser. Appropriate MeSH phrases and searching terms were merged using the Boolean operators "OR" and "AND" to fit the advanced searching. We used (“mean platelet volume” [Title/Abstract] OR “platelet, mean volume” [Title/Abstract]) OR “platelets, mean volume” [Title/Abstract] OR “volume, mean platelet” [Title/Abstract]) OR “volumes, mean platelet” [Title/Abstract] OR ‘‘MPV”[Title/Abstract] AND “platelet parameters” [Title/Abstract] AND “inflammatory marker” [Title/Abstract] AND “bowel disease” [Title/Abstract] AND “ulcerative colitis” [Title/Abstract] AND “Crohn’s disease” [Title/Abstract] AND “appendicitis” [Title/Abstract] for searching articles in PubMed. The above-mentioned entry terms were also extensively searched separately.
Outcome of interest.
Primary outcome of interest was the pooled SMD in MPV in IBD versus control. Second, we determined the pooled MPV in IBD and healthy controls.
Study selection.
Three independent authors (MM, ES and GM) identified the articles from reputable data bases and other sources. Searched articles were combined to Endnote X7 and duplicates were removed. Using inclusion criteria, two reviewers (GM and ES) evaluated the title, abstract and then full-text review for data abstraction. Any disagreements between two independent reviewers (GM and ES) were settled by (MM) in order to reach a consensus.
Quality assessment of the included studies.
Three independent reviewers (MM, ES and GM) investigated the quality of the articles. The full texts of the articles were used to evaluate whether the study met the selection criteria or the article’s eligibility was in doubt. Methodological validity was assessed for each study design using the quality evaluation tool of Joanna Brigg Institute (JBI) criteria [30]. The JBI check list of related items, sampling, eligibility protocols, description of study subject and setting, appropriate statistical analysis, case definition, confounder identification, valid and reliable result measurement, bias minimization, comparability in study participants and generalizability the of study were checked. The scoring system were 0 (not done), 1 (done), UC (unclear), NA (not applicable) and the judgments of score range for cross-sectional, 0 (lowest quality) to 8 (highest quality), for case-control, 0 (lowest quality) to 10 (highest quality) and for cohort 0 (lowest quality) to 11 (highest quality) [30]. Articles, scored average of ≥50% were included in this meta- analysis (S1 Table).
Data extraction.
After the assessment of the methodological and the allover characteristics of studies, data items were subjected to data extraction via data extraction Microsoft Excel sheet. For each articles, meeting the eligibility protocol, first author’s name, total sample size, publication year, population, study design, study area and results such as, average value of MPV and SD were extracted for each article.
Data synthesis
Random and fixed effect models were conducted using Stata version 11 to estimate the pooled MPV and mean difference in MPV in IBD patients and control. Due to substantial heterogeneity, random effect model was used. Standardized mean difference (SMD) as measurement scale was used to determine the difference in MPV at 95% CI. The degree of heterogeneity with in each study was tested by using Higgins’s I2 statistics showing the magnitude of heterogeneity [31]. Statistically significant heterogeneity was found to be I2 > 50%. Sensitivity analysis was conducted to identify disproportionately influencing the results. Subgroup analysis by population character was employed to resolve substantial heterogeneity. Publication bias and small study effects were estimated using funnel plot and Egger weighted test. A p-value < 0.05 was considered for evidence of significance in publication bias [32].
Results
The review process and description of included studies
Total of 51 studies, 5 abstracts and 46 full-text original articles were retrieved after searching the databases and other sources. After two duplicate studies removed [33, 34], 18 articles were discarded owing to irrelevant tittles. Eight articles were discarded after reading their abstracts. Twenty three articles were eligible for full-text review. Finally, 17 articles met the inclusion criteria (Fig 1). A total of 2,957 participants were involved from 17 included articles (1823 IBD patients and 1134 healthy controls). Six of them contained information on the; MPV for evaluation of disease activity in IBD, platelet indices in UC, coagulopathy in IBD, formation of platelet aggregation in IBD and neutrophil to lymphocyte ration in IBD (5 prospective cohort studies and 1comparative cross-sectional study) [35–40]. Five articles were, for the evaluation and investigation of platelet indices as a useful marker on CD (4 cohort and 1 retrospective cross-sectional) [36, 38, 39, 41, 42] (Table 1). Of those included articles, 2 were conducted for the investigation of MPV as useful biomarkers in general IBD (1 cross-sectional and 1 cohort) [35, 43] (Table 1).
[Figure omitted. See PDF.]
NB; UC: Ulcerative Colitis; CD: Crohn’s Disease; IBD: Inflammatory Bowel Disease; AA: Acute Appendicitis; CFPIAP: Child Food Protein Induced Allergic Proctocolitis.
[Figure omitted. See PDF.]
One was conducted to establish the relationship between neutrophil-to-lymphocyte ratio and MPV with the diagnosis and development of child food protein-induced allergic proctocolitis (FPIAP) tolerance in infants (retrospective cross-sectional) [44]. Three were conducted for new diagnostic marker parameters for MPV, PDW in appendicitis (2 case-controls and 1 cross-sectional) [45–47]. Of the research included, nine articles (52.9%) were published after 2010 [36, 41–47], whereas eight (47.06%) before 2010 [35, 37–40] (Table 1).
Publication bias
Potential publication bias was assessed by using funnel plot and egger’s statistics. The Egger’s test for publication bias was marginally insignificant (p = 0.59), suggesting that there was no indication of publication bias in included articles (Table 2). Furthermore, a funnel plot was used to demonstrate the existence or absence of publishing bias. Included studies seem symmetric and felled within the triangular region of funnel (Fig 2).
[Figure omitted. See PDF.]
Dot on the black line represents each individual article. Y-axis shows the standard error of mean difference (SEMD). The x-axis shows estimate mean difference (MD) of the included articles.
[Figure omitted. See PDF.]
Quality and heterogeneity test.
Regarding the quality, most of the studies scored high quality, greater than 75%. For individual studies, quality was assessed by using JBI critical appraising tool to minimize risk of bias. Each item was assessed for grading the articles as poor quality (<50%) good (50–75%) and high quality (>75%) (S1 Table). Included studies exhibited the substantial heterogeneity (I2, 93.1%; p < 0.001) in random model effect analysis of mean difference of MPV (Fig 5). To reduce the substantial heterogeneity, subgroup analysis, in difference in MPV based on population was done. The result showed no substantial heterogeneity in studies conducted on UC, general IBD, AA (I2; 33.7%, 33.9% and 37.9%; p = 0.18, 0.22 and 0.20) respectively, but still substantial heterogeneity was observed in studies conducted among CD (I2; 97.8%; p < 0.001) (Fig 6).
Sensitivity analysis.
Individual study had a negligible impact on the pooled estimate, indicating the robustness of the aggregated estimate. When examining the pooled MPV differences by ignoring one study at a time, the results were consistent and accurate (Table 3).
[Figure omitted. See PDF.]
Pooled estimated MPV and mean difference in MPV
The pooled estimated MPV in IBD and healthy control groups.
In this study, heterogeneity was checked and a random effect model was applied. Based on the random effect model analysis, the overall pooled MPV were 9.29fl; 95% CI: 9.01–9.57 and 9.50fl; 95% CI: 8.81–10.20; p < 0.001 in IBD patients and control groups, respectively (Figs 3 and 4).
[Figure omitted. See PDF.]
The size of the x-axis shows the estimate pooled MPV of the studies. In the pooled point calculation, the dotted line represents the MPV. The black dot in the middle of the gray box reflects the estimate pooled MPV of each studies point and the line shows the 95% CI of the estimates. The gray boxes represent each study weight that contributes to the estimation of the pooled MPV. I-squared illustrates the heterogeneity between the included studies.
[Figure omitted. See PDF.]
The size of the x-axis shows the estimate of pooled MPV of the studies. MPV is seen in the hard line (MPV = 0). In the pooled point calculation, the dotted line represents the MPV. The black dot in the middle of the gray box reflects the estimate pooled MPV of each studies point and the line shows the 95% CI of the estimates. The gray boxes represent each study weight that contributes to the estimation of the pooled MPV. I-squared illustrates the heterogeneity between the included studies.
The pooled estimated mean difference in MPV.
For each study, the mean difference in MPV between IBD and control was estimated. The pooled estimated SMD was -0.83fl; 95% CI: -1.15,-0.51; p < 0.001 (Fig 5). The finding was suggesting as the pooled average MPV in IBD patients was 0.83fl lower than the average pooled MPV of healthy controls. Since this pooling was extremely heterogeneous (I2 = 93.1%; p < 0.001) and so population based sub-group analysis was used to investigate potential sources of heterogeneity. The highest estimated mean difference in MPV and significant heterogeneity were observed among patients of CD; SMD = -2.30; 95% CI: -3.46, -1.14; I2 = 97.8%; p < 0.001 whereas the difference was lowest and insignificant heterogeneity in general IBD patients; SMD = -0.22; 95% CI: -0.61, -0.17; 33.9%; p = 0.98, UC; -0.63; 95% CI: -0.83, -0.42; I2 = 33.7%; p = 0.18, AA; -51; 95% CI: -0.66, -0.35; p = 0.20 (Fig 6).
[Figure omitted. See PDF.]
The size of the x-axis shows the SMD estimate of the studies. Hard line indicates no difference (SMD = 0). In the pooled point calculation, the dotted line represents the mean difference. The black dot in the middle of the gray box reflects the SMD estimate of each sample’s point and the line shows the 95% CI of the estimates. The gray boxes represent each study weight that contributes to the estimation of the pooled mean difference. I-squared illustrates the heterogeneity between the included studies.
[Figure omitted. See PDF.]
The x-axis scale displays the estimation of the SMD in MPV. The hard line shows no difference. The dotted line represents the mean difference in the pooled point estimate of each study. In the center of the gray box, the black dot reflects the SMD estimate of each article’s point estimate and the line shows the 95% CI of the estimates. I-squared indicates the heterogeneity across the included studies, p indicating for statistical significance of heterogeneity.
Discussion
Platelet activation plays a critical role in thrombosis and inflammation in physiopathology. The RDW and MPV have been shown in several studies to be useful in the diagnosis of IBD. Both RDW and MPV are clinically significant hematologic markers that are routinely used in CBC. However, the efficacy of laboratory tests for IBD diagnosis has been poorly understudied. Meanwhile, MPV has long been used to measure platelet development in the bone marrow and has clinical relevance in some cases; MPV levels may be altered in hypertension, diabetes and IBD [13, 48–52]. But there is no well-established diagnostic value for MPV in IBD. Furthermore, it is very scant evidence of MPV in IBD in clinical practice. Therefore, this review would highlight accurate aggregated evidence of MPV in IBD.
In this study, 17 original articles conducted on different types of IBD namely active and inactive UC, general IBD, AA and CD were included. The pooled SMD in MPV = -0.83fl (95% CI: -1.15, -0.5; p-value < 0.001. It is fact that the pathophysiology IBD and MPV are biologically plausible. According to the finding, IBD patients had 0.83fl lower MPV as compared to healthy controls. It could be due to consumption or sequestration of platelets in the vascular segments associated with high grade of inflammation of the disease [53].
The finding was consistent with systematic review and meta-analysis conducted among patients of AA (weighted mean difference, -0.64; 95% CI, -0.74 to -0.54; P = 0.034 [54]. Furthermore, the pooled estimates of MPV in this study was in line with study in China, (MPV = 9.55 ± 0.17 in IBD and 11.1 ± 0.16 in healthy controls) [41]. The possible explanation would be similarity in intensity of systemic inflammatory response, consumption and sequestration of platelet during activation of the coagulation system [55]. On the other hand, the finding was in contradiction with a systematic review and meta-analysis conducted on coronary artery disease patients in Thailand [56] and neonatal sepsis; pooled mean difference in MPV were 0.84fl, 1.49fl, respectively [57]. The possible explanation might be disparity in disease pattern (low grade inflammatory response), population characteristic and micro-thrombi formation of platelet in the microvasculature related to bacteremia, cardiovascular risk factors and the other genetic factors, which result in increased MPV [58].
There was substantial heterogeneity in pooling SMD (I2 = 93.1%; p <0.001). Usually based on random effect model in population based subgroup analysis of mean difference in MPV, significant heterogeneity was observed in studies conducted among CD patients, (I2; 97.8%; p < 0.001). The possible explanation would be difference in study design, population, statistical methods, reference range, standard operating procedures and electronic cell counters. However, there was no substantial heterogeneity in studies conducted on general IBD, UC and AA. The reason may be due to similarity in cutoff value, study methodology, sample size, population characteristic and standard operating procedure.
Implication in current clinical practice and future perspectives of MPV in IBD
While the pathogenesis of IBD still being understood, it has been proved that the release of inflammatory mediators via the activation of immune and coagulation pathways contributes to endothelial dysfunction, which is responsible for the disease’s clinical phenotype. Platelets were frequently consumed during thromboembolic events in association of the pathogenesis of IBD [19, 59]. The MPV correlated with function of platelet and is sensitive, specific and surrogate biomarker of many inflammatory disorders [60].
Platelets have both anti-inflammatory and anti-thrombotic properties. Systemic thromboembolism is more common in patients with IBD and multifocal micro vascular infarction has been suggested as a pathogenesis cause in CD. Meanwhile, increased platelet activation and aggregation are common features of IBD, which may lead to the risk of systemic thromboembolism and the pathogenesis of mucosal inflammation [19]. In active IBD, MPV is significantly decreased and it is negatively correlated with recognized IBD activity markers and platelet activation products [38].
The MPV and endoscopic activity index of IBD had a negative relationship (r: -0.358 p: 0.005) [39]. In contrary, it is inversely related with disease pattern and significantly correlated with endoscopic severity and histological activities of IBD [19]. Furthermore, thrombocyte count and MPV are considered as useful markers of IBD [20]. Several studies have indicated that platelets can play a role in CD pathogenesis and the MPV has been linked to CD and has been used as a possible inflammatory marker [61, 62]. In addition, it is fact that patients with CD had significant decreased MPV [40]. Furthermore, MPV is, non-invasive and available in CBC and used to discriminate cause of thrombocytopenia [63]. And also MPV was 76.6% reliable inflammatory marker in differentiating CD under Receiver operating characteristic (ROC) curve with a sensitivity and a specificity of 78.7% and 74.0%, respectively [42]. In addition, the overall accuracy of MPV in determining active UC was 71% with 67% sensitivity and 73% specificity [39].
Many literatures suggest that, MPV may provide valuable information on the course and prognosis in many pathological conditions, such as cardiovascular diseases, respiratory diseases, CD, rheumatoid arthritis, juvenile systemic lupus erythematous, diabetes mellitus, extreme infection, injuries, serious illness, trauma, systemic inflammatory response syndrome, thrombotic infections and the majority of neoplastic disease. The MPV levels were found to be lower in UC and increase in adult’s systemic lupus erythematous and a variety of neoplastic illnesses [60, 64–68]. Mean platelet volume is a routinely measured platelet size marker with established predictive value for a variety of cardiovascular disorders [56].
The longitudinal study estimated the promising efficacy of this marker as measured in the 24th-28th gestational weekly interval suggested that the combined assessment of MPV in the first trimester was able to identify preeclampsia and intrauterine growth restriction with a sensitivity and specificity of 75% and 85.3%, respectively [69]. Furthermore, in this study MPV was significantly decreased in IBD.
Strength and limitation of the study.
Articles were searched strategically and extensively through different searching engines. Moreover, the study was conducted in accordance to PRISMA guideline and protocols. However, there are potential limitations of the study. First, the articles used were published only in English and most of them were in Turkey, may cause geographical bias. The other limitation was platelet parameters underwent a number of changes in inflammatory disease. So, determining all platelet parameters would provide important diagnostic and prognostic information. However, included studies only reported MPV and other platelet parameters were not investigated in the study.
Conclusion and recommendation.
The current meta-analysis demonstrated that MPV has decreased significantly in IBD with prominent mean difference, suggesting that MPV would represent the promising test in diagnosis and monitoring IBD. Therefore, MPV would be diagnostic and prognostic marker in clinical practice of IBD. Platelet indices would provide reliable information for assessing the severity of the disease and insight the possible pathophysiology of IBD. Therefore, before using single MPV as inflammatory marker, further cumulative evidence of all platelet indices are warranted. In addition, adequate clinical trials should be designed to establish the diagnostic and prognostic value of MPV as inflammatory marker in IBD.
Supporting information
S1 Table. The methodological quality of the included studies using JBI critical appraising tool.
https://doi.org/10.1371/journal.pone.0273417.s001
(DOCX)
S1 Checklist. The PRISMA (Preferred reporting items for systematic and meta-analysis) checklists.
https://doi.org/10.1371/journal.pone.0273417.s002
(DOCX)
S1 Data.
https://doi.org/10.1371/journal.pone.0273417.s003
(XLSX)
Citation: Bambo GM, Shiferaw E, Melku M (2022) A mean platelet volume in inflammatory bowel disease: A systematic review and meta-analysis. PLoS ONE 17(8): e0273417. https://doi.org/10.1371/journal.pone.0273417
About the Authors:
Getachew Mesfin Bambo
E-mail: [email protected]
Affiliations Department of Medical Laboratory Science, College of Health Sciences, Mizan Tepi University, Mizan, Ethiopia, Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, University of Gondar, Gondar, Ethiopia
https://orcid.org/0000-0003-0427-2831
Elias Shiferaw
Contributed equally to this work with: Elias Shiferaw, Mulugeta Melku
Affiliation: Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, University of Gondar, Gondar, Ethiopia
Mulugeta Melku
Contributed equally to this work with: Elias Shiferaw, Mulugeta Melku
Current address: College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
Affiliation: Department of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, University of Gondar, Gondar, Ethiopia
https://orcid.org/0000-0002-3383-9377
1. Graham DB, Xavier RJ. Pathway paradigms revealed from the genetics of inflammatory bowel disease. Nature. 2020; 578(7796):527–39. pmid:32103191
2. Grothe B, Park TJ. Structure and function of the bat superior olivary complex. Microsc Res Tech. 2000;51(4):382–402. pmid:11071721
3. Bernstein CN, Fried M, Krabshuis J, Cohen H, Eliakim R. Inflammatory bowel disease: a global perspective. Global guidelines Milwaukee: World Gatroenterology Organization. 2009.
4. Han Hulin K H, Rehman Abdul, Jang Se Min, and Paik Seung Sam. Appendiceal Crohn’s disease clinically presenting as acute appendicitis. World J Clin Cases. 2014;2(16):888–92. pmid:25516865
5. Strong S, Steele SR, Boutrous M, Bordineau L, Chun J, Stewart DB, et al. Clinical practice guideline for the surgical management of Crohn’s disease. Diseases of the Colon & Rectum. 2015 Nov 1;58(11):1021–36. pmid:26445174
6. Zhuang H, Zhao JY, Wang YF. Gastrocolic fistula in Crohn’s disease detected by oral agent contrast-enhanced ultrasound: A case report of a novel ultrasound modality. World Journal of Gastroenterology. 2020;26(17):2119. pmid:32536779
7. Corica D, Romano C. Biological therapy in pediatric inflammatory bowel disease. Journal of clinical gastroenterology. 2017;51(2):100–10.
8. AnChiu C, Xian W, Moss CF. Flying in silence: Echolocating bats cease vocalizing to avoid sonar jamming. Proc Natl Acad Sci U S A. 2008;105(35):13116–21. pmid:18725624
9. Garg M, Royce SG, Tikellis C, Shallue C, Batu D, Velkoska E, et al. Imbalance of the renin–angiotensin system may contribute to inflammation and fibrosis in IBD: a novel therapeutic target?. Gut. 2020;69(5):841–51. pmid:31409604
10. Zhu N, Zhang D, Wang W. China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727–33. pmid:31978945
11. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. Jama. 2020;323(20):2052–9. pmid:32320003
12. Teeling EC, Springer MS, Madsen O, Bates P, O’Brien SJ, Murphy WJ. A molecular phylogeny for bats illuminates biogeography and the fossil record. Science. 2005;307(5709):580–4. pmid:15681385
13. Lippi G, Pavesi F, Pipitone S. Evaluation of mean platelet volume with four haematological analyzers: harmonization is still an unresolved issue. Blood Coagul Fibrinolysis. 2015;26:235–7.
14. Colkesen Y, Muderrisoglu H. The role of mean platelet volume in predicting thrombotic events. Clinical Chemistry and Laboratory Medicine (CCLM). 2012;50(4):631–4. pmid:22112054
15. Huang HS, Chang HH. Platelets in inflammation and immune modulations: functions beyond hemostasis. Arch Immunol Ther Exp. 2012;60(6):443–51. pmid:22940877
16. Cognasse F, Lafarge S, Chavarin P, Acquart S, Garraud O. Lipopolysaccharide induces sCD40L release through human platelets TLR4, but not TLR2 and TLR9. Intensive Care Med. 2007;33(2):382–4. pmid:17180393
17. Smyth SS, McEver RP, Weyrich AS, Morrell CN, Hoffman MR, Arepally GM, et al. Platelet functions beyond 1hemostasis. J Thromb Haemost. 2009;7(11):1759–66.
18. Banchereau J, Steinman RM. Dendritic cells and the control of immunity. Nature. 1998;392(6673):245–52. pmid:9521319
19. Herman R, Sładek M, Pieczarkowski S, Dumnicka P, Fyderek K. Is mean platelet volume a good predictor of sustained response to one year infliximab therapy in pediatric patients with Crohn’s disease? Folia Medica Cracoviensia. 2017;2:63–71. pmid:29121038
20. Douda T, Bures J, Rejchrt S, Kopácová M, Pecka M, Malý J. Mean platelet volume (MPV) in Crohn’s disease patients. Casopis lekaru ceskych. 2006;145(11):870–3.
21. Lewis JD. The utility of biomarkers in the diagnosis and therapy of inflammatory bowel disease. Gastroenterology. 2011 May 1;140(6):1817–26. pmid:21530748
22. Henderson P., Kennedy N.A., Van Limbergen J.E., Cameron F.L., Satsangi J., Russell R.K. et al. 2015. Serum C-reactive protein and CRP genotype in pediatric inflammatory bowel disease: influence on phenotype, natural history, and response to therapy. Inflammatory bowel diseases, 21(3):596–605. pmid:25636121
23. Mosli M.H., Zou G, Garg S.K., et al. C-reactive protein, fecal calprotectin, and stool lactoferrin for detection of endoscopic activity in symptomatic inflammatory bowel disease patients: a systematic review and meta-analysis. American Journal of Gastroenterology.2015;110(6):802–819. pmid:25964225
24. Cherfane CE, Gessel L, Cirillo D, Zimmerman MB, Polyak S. Monocytosis and a low lymphocyte to monocyte ratio are effective biomarkers of ulcerative colitis disease activity. Inflammatory bowel diseases. 2015;21(8):1769–75 pmid:25993688
25. Li J-Y, Li Y, Jiang Z, Wang R-T, Wang X-S. Elevated mean platelet volume is associated with presence of colon cancer. Asian Pacific Journal of Cancer Prevention. 2015;15(23):10501–4.
26. Hamada E, Taniguchi T, Baba S, Maekawa M. Investigation of unexpected serum CA19-9 elevation in Lewis-negative cancer patients. Annals of clinical biochemistry. 2012;49(3):266–72. pmid:22492877
27. De Voogd FA, Mookhoek A, Gecse KB, De Hertogh G, Bemelman WA, Buskens CJ, et al. Systematic review: histological scoring of strictures in Crohn’s disease. Journal of Crohn’s and Colitis. 2020;14(6):734–42. pmid:32645156
28. Stojkovic Lalosevic M, Pavlovic Markovic A, Stankovic S, Stojkovic M, Dimitrijevic I, Radoman Vujacic I, et al. Combined diagnostic efficacy of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV) as biomarkers of systemic inflammation in the diagnosis of colorectal cancer. Disease markers. 2019;2019:1–8. pmid:30800188
29. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic reviews. 2015;4(1):1–9. pmid:25554246
30. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, et al. Chapter 7: Systematic reviews of etiology and risk. Joanna Briggs Institute Reviewer’s Manual. The Joanna Briggs Institute. 2017 [cited 2020]. https://reviewersmanual.joannabriggs.org/display/MANUAL.
31. Higgins JP TS. Quantifying heterogeneity in a meta‐analysis. Statistics in medicine. 2002;21(11):1539–58. pmid:12111919
32. Sterne JA, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. Journal of clinical epidemiology. 2001;54(10):1046–55. pmid:11576817
33. Albayrak Y, Albayrak A, Albayrak F, Yildirim R, Aylu B, Uyanik A, et al. Mean platelet volume: a new predictor in confirming acute appendicitis diagnosis. Clinical and Applied Thrombosis/Hemostasis. 2011;17(4):362–6. pmid:20460349
34. Bilici S, Sekmenli T, Göksu M, Melek M, Avci V. Mean platelet volume in diagnosis of acute appendicitis in children. African health sciences. 2011;11(3). pmid:22275934
35. Irving PM, Macey MG, Shah U, Webb L, Langmead L, Rampton DS. Formation of platelet-leukocyte aggregates in inflammatory bowel disease. Inflammatory bowel diseases. 2004;10(4):361–72. pmid:15475744
36. Öztürk ZA, Yesil Y, et al. Inverse relationship between neutrophil lymphocyte ratio (NLR) and bone mineral density (BMD) in elderly people. Archives of gerontology and geriatrics. 2013;57(1):81–5. pmid:23490023
37. Kayahan H, Akarsu M, Ozcan MA, Demir S, Ates H, Unsal B, et al. Reticulated platelet levels in patients with ulcerative colitis. International journal of colorectal disease. 2007;22(12):1429–35. pmid:17549498
38. 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. The American journal of gastroenterology. 2001;96(3):776–81. pmid:11280550
39. Yüksel O, Helvacı K, et al. An overlooked indicator of disease activity in ulcerative colitis: mean platelet volume. Platelets. 2009;20(4):277–81. pmid:19459134
40. Shen J, Zhang Y, et al. Biomarkers of altered coagulation and fibrinolysis as measures of disease activity in active inflammatory bowel disease: a gender-stratified, cohort analysis. Thrombosis research. 2009;123(4):604–11. pmid:18499234
41. Liu S, Ren J, Han G, et al. Mean platelet volume: a controversial marker of disease activity in Crohn’s disease. European Journal of Medical Research. 2012;17(1):1–7. pmid:23058104
42. Tang J, Gao X, et al. Plateletcrit: A sensitive biomarker for evaluating disease activity in C rohn’s disease with low hs‐CRP. Journal of digestive diseases. 2015;16(3):118–24. pmid:25565427
43. 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. International Journal of Medical Sciences. 2011;8(7):540. pmid:21960745
44. Nacaroğlu H, Karaman S, et al. Markers of inflammation and tolerance development in allergic proctocolitis. Archivos Argentinos de Pediatria. 2018;116(1).e1–e7.
45. Tanrikulu C, Akkapulu N, Coskun F, et al. Mean platelet volume and red cell distribution width as a diagnostic marker in acute appendicitis. Iranian Red Crescent Medical Journal. 2014;16(5):e10211. pmid:25031841
46. Ceylan B, Aslan T, Çınar A, Akkoyunlu Y, et al. Can platelet indices be used as predictors of complication in subjects with appendicitis?. Wiener klinische Wochenschrift. 2016;128(8):620–5. pmid:25869761
47. Dinc B, Oskay A, Dinc S, Bas B, Tekin S. New parameter in diagnosis of acute appendicitis: platelet distribution width. World Journal of Gastroenterology: WJG. 2015;21(6):1821. pmid:25684947
48. Aktas G, Alcelik A, Tekelioglu V, et al. Red cell distribution width and mean platelet volume in patients with irritable bowel syndrome. Prz Gastroenterol. 2014;9(3):160–163. pmid:25097713
49. Coskun A, Yavasoglu I, Sargin G. The role of mean platelet volume in patients with non-specific abdominal pain in an emergency department. Prz Gastroenterol. 2015;10(3):156–159. pmid:26516381
50. Arhan M, Önal İK, Taş A, et al. The role of red cell distribution width as a marker in inflammatory bowel disease. Turk J Med Sci. 2011;41(2):227–234.
51. Yeşil A, Senateş E, Bayoğlu I, et al. Red cell distribution width: A novel marker of activity in inflammatory bowel disease. Gut Liver. 2011;5(4):460–467. pmid:22195244
52. Moein S, Qujeq D, Majidinia M, Yousefi B, et al. MiRNAs and inflammatory bowel disease: An interesting new story. J Cell Physiol. 2019;234(4):3277–3293. pmid:30417350
53. Margetic S. Inflammation and haemostasis. Biochem Med (Zagreb). 2012;22:49–62. pmid:22384519
54. Fan Z, Zhang Y, Pan J, Wang S. Acute appendicitis and mean platelet volume: A systemic review and meta-analysis. Annals of Clinical & Laboratory Science. 2017;47(6):768–72. pmid:29263055
55. Budak Y, Polat M, Huysal K. The use of platelet indices, plateletcrit, mean platelet volume and platelet distribution width in emergency non-traumatic abdominal surgery: a systematic review. Biochemia medica. 2016;26(2):178–93. pmid:27346963
56. Sansanayudh N, Anothaisintawee T, Muntham D, McEvoy M, Attia J. Mean platelet volume and coronary artery disease: a systematic review and meta-analysis. International journal of cardiology. 2014;175(3):433–40. pmid:25017904
57. Wang J, Wang Z, Zhang M, Lou Z, Deng J, Li Q. Diagnostic value of mean platelet volume for neonatal sepsis: A systematic review and meta-analysis. Medicine. 2020;99(32):e21649. pmid:32769935
58. Larsen SB, Grove EL, Hvas AM, Kristensen SD. Platelet turnover in stable coronary artery disease-influence of thrombopoietin and low-grade inflammation. PLoS One. 2014;9:e85566. pmid:24465602
59. Järemo P, Sandberg-Gertzen H. Platelet density and size in inflammatory bowel disease. Thrombosis and haemostasis. 1996;75(04):560–1. pmid:8743178
60. Schmoeller D, Picarelli MM, Paz Munhoz T, Poli de Figueiredo CE, Staub HL. Mean platelet volume and immature platelet fraction in autoimmune disorders. Frontiers in medicine. 2017;4:146. pmid:28932736
61. Ripoche J: Blood platelets and inflammation: their relationship with liver and digestive diseases. Clin Res Hepatol Gastroenterol 2011, 35: 353–357. pmid:21482218
62. Yovel Y, Franz MO, Stilz P, Schnitzler HU. Plant classification from bat-like echolocation signals. PLoS Comput Biol. 2008;4(3):e1000032. pmid:18369425
63. Wiegrebe L. An autocorrelation model of bat sonar. Biol Cybern. 2008;98(6):587–95. pmid:18491168
64. Greenhall AM. House bat management. Jamestown, ND: Northern Prairie Wildlife Research Center Online; 1982.
65. Leaf-nosed bat. Encyclopædia Britannica: Encyclopædia Britannica Online; 2009.
66. Jen PHS, Wu CH. Echo duration selectivity of the bat varies with pulse-echo amplitude difference. Neuroreport. 2008;19(3):373–7. pmid:18303584
67. Holland RA, Kirschvink JL, Doak TG, Wikelski M. Bats use magnetite to detect the earth’s magnetic field. PLoS One. 2008;3(2):e1676, 1–6. pmid:18301753
68. Brinklov S, Kalko EKV, Surlykke A. Intense echolocation calls from two ’whispering’ bats, Artibeus jamaicensis and Macrophyllum macrophyllum (Phyllostomidae). J Exp Biol. 2009;212(1):11–20.
69. Missfelder-Lobos T E, Lees C., Albaiges G., Nicolaides K.H. Platelet changes and subsequent development of pre-eclampsia and fetal growth restriction in women with abnormal uterine artery Doppler screening. Ultrasound Obstet Gynecol. 2002;19(5):443–8. pmid:11982975
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Abstract
Background
Inflammatory bowel disease (IBD) is a chronic gastrointestinal tract inflammatory state, which is affecting millions of individuals in the world. It can affect alimentary canals such as colon, rectum, ileum and other parts. In IBD, platelet parameters underwent several changes. Therefore, the aim of this review was determining the estimated pooled mean platelet volume and mean difference in inflammatory bowel disease to elucidate its potential diagnostic value.
Methods
Articles were extensively searched in bibliographic databases using Medical Subject Heading and entry phrases or terms. In addition, articles were directly searched in Google Scholar to account for the studies omission in searching bibliographic databases. Observational (cohort, cross-sectional and case-control) studies, published in English language and conducted on IBD were included. For studies meeting the eligibility criteria, the first author’s name, publication year, population, study design, study area, sample size, mean platelet volume and standard deviation were extracted and entered in to Microsoft-excel. The analysis was done by Stata version 11. In order to estimate the pooled mean platelet volume and mean difference, random effect model was done. The heterogeneity was quantified using Higgin’s I2 statistics. Publication bias was determined using Egger’s test statistics and funnel plot. Sub-group analysis based on population carried to reduce heterogeneity.
Results
A total of 17 relevant articles with 2957 participants (1823 IBD cases and 1134 healthy controls) were included to this study. The pooled estimated MPV was 9.29fl; 95% CI: 9.01–9.57 and 9.50fl; 95% CI: 8.81–10.20 in IBD and control groups, respectively. The standardized pooled estimate of mean difference in mean platelet volume was -0.83fl; 95% CI: -1.15, -0.51; I2: 93.1%; P-value < 0.001. In subgroup analysis based on population, the highest estimated mean difference in MPV was observed among patients of CD; -2.30; 95% CI: -3.46, -1.14; I2: 97.8%; P-value < 0.001.
Conclusion
According to the current systematic review and meta-analysis, mean platelet volume was lower in IBD compared to control. The decreased mean platelet volume could be attributed to platelet consumption or sequestration associated with the progression of IBD. As a result, in IBD, mean platelet volume can provide diagnostic and prognostic information.
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Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer