Mean Platelet Volume-to-Platelet Count Ratio, Mean Platelet Volume-to-Lymphocyte Ratio, and Red Blood Cell Distribution Width-Platelet Count Ratio as Markers of Inflammation in Patients with Ascending Thoracic Aortic Aneurysm

Tekin, Yusuf Kenan; Tekin, Gülaçan

doi:10.21470/1678-9741-2019-0348

Cited by 12 publications

(6 citation statements)

References 23 publications

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“…Platelet function and activation is reflected by the MPV, and it could be used as a marker for inflammation [ 35 ]. The MPV is also a valuable marker in systemic inflammatory diseases and is thought to have a parallel correlation with CRP [ 36 ]. MPV levels have shown depressed levels during systemic inflammatory situations [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Which hematological markers have predictive value as early indicators of severe COVID-19 cases in the emergency department?

Şan¹,

Gemcioğlu²,

Davutoğlu³

et al. 2021

Turk J Med Sci

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IntroductionCoronavirus 2019 disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic infectious disease that causes morbidity and mortality. To date there are no proven diagnostic or prognostic parameters, but clinicians can use predictive parameters, such as the leukocyte and lymphocyte counts, C-reactive protein (CRP), D-dimer, and ferritin levels, and radiological imaging [1-3]. In the inflammation process of COVID-19, CRP, platelet, ferritin, and leukocyte values may increase, while albumin and lymphocyte values may decrease [4][5][6].White blood cells (WBCs), including neutrophils, lymphocytes, monocytes, have been used as inflammatory Background/aim: Coronavirus 2019 disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic infectious disease that causes morbidity and mortality. As a result of high mortality rate among the severe COVID-19 patients, the early detection of the disease stage and early effective interventions are very important in reducing mortality. Hence, it is important to differentiate severe and nonsevere cases from each other. To date, there are no proven diagnostic or prognostic parameters that can be used in this manner. Due to the expensive and not easily accessible tests that are performed for COVID-19, researchers are investigating some parameters that can be easily used. In some recent studies, hematological parameters have been evaluated to see if they can be used as predictive parameters. Materials and methods:In the current study, almost all hematological parameters were used, including the neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, monocyte/lymphocyte ratio, mean platelet volume to lymphocyte ratio, mean platelet volume to platelet ratio, plateletcrit, and D-dimer/fibrinogen ratio, neutrophil/lymphocyte/platelet scoring system, and systemic immune-inflammation index. A total of 750 patients, who were admitted to Ankara City Hospital due to COVID-19, were evaluated in this study. The patients were classified into 2 groups according to their diagnosis (confirmed or probable) and into 2 groups according to the stage of the disease (nonsevere or severe). Results:The values of the combinations of inflammatory markers and other hematological parameters in all of the patients with severe COVID-19 were calculated, and the predicted values of these parameters were compared. According to results of the study, nearly all of the hematological parameters could be used as potential diagnostic biomarkers for subsequent analysis, because the area under the curve (AUC) was higher than 0.50, especially for the DFR and NLR, which had the highest AUC among the parameters. Conclusion:Our findings indicate that, the parameters those enhanced from complete blood count, which is a simple laboratory test, can help to identify and classify COVID-19 patients into non-severe to severe groups.

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Section: Discussionmentioning

confidence: 99%

Which hematological markers have predictive value as early indicators of severe COVID-19 cases in the emergency department?

Şan¹,

Gemcioğlu²,

Davutoğlu³

et al. 2021

Turk J Med Sci

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“…During each patient's treat-ment, they were subjected to a complete medical his-tory, including medications, cerebrovascular accidents, or ischemic heart disease, an in-depth examination of the nervous system and general health, and an investigation of all recommended biochemical parameters. 11 Patients with evidence of acute ischemic stroke were considered for the study. The stroke was clinically identified (related to a sudden onset of neurological deficits lasting 24 hours or more) and confirmed via brain imaging (magnetic resonance imaging MRI and CT computed tomography).…”

Section: Methodsmentioning

confidence: 99%

Association of Mean Platelet Volume / Platelet Count Ratio with Clinical Severity and Infarct Volume in Patients with Acute Ischemic Stroke

Nayyar

Mahmood

Liaqat

et al. 2023

PAFMJ

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Objective: To examine the clinical severity and infarct volume of acute ischemic stroke (AIS) compared to control subjects by comparing the mean platelet volume/platelet count (MPV/PC) ratio. Study Design: Cross-sectional (validation) study. Place and Duration of Study: Acute Stroke Unit, Pak Emirates Military Hospital (PEMH), Rawalpindi, from Jul and Dec 2020. Methodology: This study included 50 consecutive AIS patients (Group-1) and 50 healthy subjects (Group-2). An automated haemanalyser determined MPV and MPV/PC ratios. In addition, a modified Rankin Scale for the severity of AIS and ABC/2 method for infarct volume was used. Results: This study comprised 69 males and 31 females. Statistical analysis showed that MPV and MPV/PC have significantly different mean values between Group-1 and Group-2 at a p-value of 0.001. In addition, according to the Rankin scale, a significant difference of means (p-value <0.001) of MPV and MPV/PC ratio was present between stroke patients with different infarct sizes. A higher CVA score per Rankin scale was associated with greater infarct size and higher MPV and MPV/PC values. Conclusion: Higher MPV and MPV/PC ratios are related to AIS compared to healthy individuals. Even greater MPV and MPV/PC ratio values are associated with increased infarct size. MPV and MPV/PC ratio measurements are simple, rapid, and highly cost-effective laboratory markers for risk stratification and early detection of cerebrovascular stroke.

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“…Mono-to-Eosin ratio Mono/Eosin 38 MGLR [23,62] Monocyte/granulocyte to lymphocyte ratio Mono× Lymph/Gran 39 MHR [63] Mono to HDLC ratio Mono/HDLC 40 MP [53] Mono × Plt 41 MPR [32]; MPV/PC [64]; MPV/ PLT ratio [65]; MPVPCR [66]; MPVPR [47] MPV-to-Plt ratio MPV/Plt PVR [67], Plt/MPV ratio [68]: PLT/MPV 42 MPctR MPV/Pct [69] MPV/PCT 43 MPVLR [37,47,66] MPV-to-Lymph ratio [47,66]; MPV/lymphocytes [36] MPV/Lymph 44 MWR [57] Monocyte-to-white blood cell ratio Mono/WBC 45 NAR [70] neutrophil/albumin Neu/Alb 46 NER [71] Neutrophil/erythrocyte ratio [71] Neu/RBC…”

Section: Mer [61]mentioning

confidence: 99%

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

Tan

Zhao

et al. 2023

BMC Cancer

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Background Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis. Methods Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set’s prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve. Results From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients. Conclusions This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

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Mean Platelet Volume-to-Platelet Count Ratio, Mean Platelet Volume-to-Lymphocyte Ratio, and Red Blood Cell Distribution Width-Platelet Count Ratio as Markers of Inflammation in Patients with Ascending Thoracic Aortic Aneurysm

Cited by 12 publications

References 23 publications

Which hematological markers have predictive value as early indicators of severe COVID-19 cases in the emergency department?

Which hematological markers have predictive value as early indicators of severe COVID-19 cases in the emergency department?

Association of Mean Platelet Volume / Platelet Count Ratio with Clinical Severity and Infarct Volume in Patients with Acute Ischemic Stroke

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

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