Clinical impact of high platelet count and high hematocrit

Humans produce and remove 1011 platelets daily to maintain a steady-state platelet count. The production of platelets by bone marrow megakaryocytes and their removal from the blood circulation are tightly regulated mechanisms, and abnormalities in both processes can result in thrombocytopenia (low platelet count) or thrombocytosis (high platelet count), often associated with the risk of bleeding or overt thrombus formation, respectively. This review focuses on the role of glycans, also known as carbohydrates or oligosaccharides, including N- and O-glycans, proteoglycans, and glycosaminoglycans, in human and mouse platelet and megakaryocyte physiology. Based on recent clinical observations and mouse models, we focused on the pathological aspects of glycan biosynthesis and degradation and its effects on platelet numbers and megakaryocyte function.

Download Full-text

The Value of βTG/PF4 Ratio in Patients with High Platelet Count – Reply

Thrombosis and Haemostasis ◽

10.1055/s-0038-1661298 ◽

1985 ◽

Vol 53 (02) ◽

pp. 289-289 ◽

Cited By ~ 1

Author(s):

Piera Viero ◽

Sergio Cortelazzo ◽

Tiziano Barbui

Keyword(s):

Platelet Count ◽

High Platelet Count

Download Full-text

The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study

Clinical Chemistry and Laboratory Medicine (CCLM) ◽

10.1515/cclm-2020-0377 ◽

2020 ◽

Vol 58 (7) ◽

pp. 1106-1115 ◽

Cited By ~ 14

Author(s):

Yufen Zheng ◽

Ying Zhang ◽

Hongbo Chi ◽

Shiyong Chen ◽

Minfei Peng ◽

...

Keyword(s):

Risk Factors ◽

Platelet Count ◽

Disease Progression ◽

Neutrophil Count ◽

Calibration Curve ◽

Lymphocyte Count ◽

Severe Disease ◽

Clinical Impact ◽

Predictive Tool ◽

Potential Biomarker

AbstractObjectivesIn December 2019, there was an outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, and since then, the disease has been increasingly spread throughout the world. Unfortunately, the information about early prediction factors for disease progression is relatively limited. Therefore, there is an urgent need to investigate the risk factors of developing severe disease. The objective of the study was to reveal the risk factors of developing severe disease by comparing the differences in the hemocyte count and dynamic profiles in patients with severe and non-severe COVID-19.MethodsIn this retrospectively analyzed cohort, 141 confirmed COVID-19 patients were enrolled in Taizhou Public Health Medical Center, Taizhou Hospital, Zhejiang Province, China, from January 17, 2020 to February 26, 2020. Clinical characteristics and hemocyte counts of severe and non-severe COVID patients were collected. The differences in the hemocyte counts and dynamic profiles in patients with severe and non-severe COVID-19 were compared. Multivariate Cox regression analysis was performed to identify potential biomarkers for predicting disease progression. A concordance index (C-index), calibration curve, decision curve and the clinical impact curve were calculated to assess the predictive accuracy.ResultsThe data showed that the white blood cell count, neutrophil count and platelet count were normal on the day of hospital admission in most COVID-19 patients (87.9%, 85.1% and 88.7%, respectively). A total of 82.8% of severe patients had lymphopenia after the onset of symptoms, and as the disease progressed, there was marked lymphopenia. Multivariate Cox analysis showed that the neutrophil count (hazard ratio [HR] = 4.441, 95% CI = 1.954–10.090, p = 0.000), lymphocyte count (HR = 0.255, 95% CI = 0.097–0.669, p = 0.006) and platelet count (HR = 0.244, 95% CI = 0.111–0.537, p = 0.000) were independent risk factors for disease progression. The C-index (0.821 [95% CI, 0.746–0.896]), calibration curve, decision curve and the clinical impact curve showed that the nomogram can be used to predict the disease progression in COVID-19 patients accurately. In addition, the data involving the neutrophil count, lymphocyte count and platelet count (NLP score) have something to do with improving risk stratification and management of COVID-19 patients.ConclusionsWe designed a clinically predictive tool which is easy to use for assessing the progression risk of COVID-19, and the NLP score could be used to facilitate patient stratification management.

Download Full-text

Risk factors associated with progression of diabetic retinopathy in eyes treated with panretinal photocoagulation

Scientific Reports ◽

10.1038/s41598-021-93384-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sung Uk Baek ◽

Min Seon Park ◽

Bum-Joo Cho ◽

In Won Park ◽

Soonil Kwon

Keyword(s):

Risk Factors ◽

Visual Acuity ◽

Diabetic Retinopathy ◽

Platelet Count ◽

Multivariate Logistic Regression Analysis ◽

Panretinal Photocoagulation ◽

Lower Baseline ◽

Uncontrolled Diabetes ◽

High Platelet Count ◽

Baseline Visual Acuity

AbstractUncontrolled diabetes has been associated with progression of diabetic retinopathy (DR) in several studies. Therefore, we aimed to investigate systemic and ophthalmic factors related to worsening of DR even after completion of panretinal photocoagulation (PRP). We retrospectively reviewed DR patients who had completed PRP in at least one eye with a 3-year follow-up. A total of 243 eyes of 243 subjects (mean age 52.6 ± 11.6 years) were enrolled. Among them, 52 patients (21.4%) showed progression of DR after PRP (progression group), and the other 191 (78.6%) patients had stable DR (non-progression group). The progression group had higher proportion of proliferative DR (P = 0.019); lower baseline visual acuity (P < 0.001); and higher platelet count (P = 0.048), hemoglobin (P = 0.044), and hematocrit, (P = 0.042) than the non-progression group. In the multivariate logistic regression analysis for progression of DR, baseline visual acuity (HR: 0.053, P < 0.001) and platelet count (HR: 1.215, P = 0.031) were identified as risk factors for progression. Consequently, we propose that patients with low visual acuity or high platelet count are more likely to have progressive DR despite PRP and require careful observation. Also, the evaluation of hemorheological factors including platelet counts before PRP can be considered useful in predicting the prognosis of DR.

Download Full-text

Immobilization and high platelet count are associated with thromboembolic complications in heparin-induced thrombocytopenia

Pharmacoepidemiology and Drug Safety ◽

10.1002/pds.4235 ◽

2017 ◽

Vol 26 (10) ◽

pp. 1149-1155 ◽

Cited By ~ 3

Author(s):

Juliane Bolbrinker ◽

Edeltraut Garbe ◽

Antonios Douros ◽

Matthias Huber ◽

Elisabeth Bronder ◽

...

Keyword(s):

Platelet Count ◽

Thromboembolic Complications ◽

Heparin Induced Thrombocytopenia ◽

High Platelet Count

Download Full-text

Pretreatment platelet count predicts survival outcome of patients with de novo non-M3 acute myeloid leukemia

PeerJ ◽

10.7717/peerj.4139 ◽

2017 ◽

Vol 5 ◽

pp. e4139 ◽

Cited By ~ 6

Author(s):

Qianying Zhang ◽

Kanchun Dai ◽

Laixi Bi ◽

Songfu Jiang ◽

Yixiang Han ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Platelet Count ◽

Predictive Value ◽

Myeloid Leukemia ◽

De Novo ◽

Univariate Analysis ◽

Survival Outcome ◽

Cox Regression Analysis ◽

High Platelet Count ◽

Acute Myeloid

Background Pretreatment platelet count has been reported as a potential tool to predict survival outcome in several solid tumors. However, the predictive value of pretreatment platelet count remains obscure in de novo acute myeloid leukemia (AML) excluding acute promyelocytic leukemia (M3). Methods We conducted a retrospective review of 209 patients with de novo non-M3 AML in our institute over a period of 8 years (2007–2015). Receiver operating characteristic (ROC) curve analysis was used to determine the optimal platelet (PLT) cutoff in patients. We analyzed the overall survival (OS) and disease free survival (DFS) using the log-rank test and Cox regression analysis. Results By defining the platelet count 50 × 109/L and 120 × 109/L as two cut-off points, we categorized the patients into three groups: low (<50 × 109/L), medium (50–120 × 109/L) and high (>120 × 109/L). On univariate analysis, patients with medium platelet count had longer OS and DFS than those with low or high platelet count. However, the multivariate analysis showed that only longer DFS was observed in patients with medium platelet count than those with low or high platelet count. Conclusion Our findings indicate that pretreatment platelet count has a predictive value for the prognosis of patients with non-M3 AML.

Download Full-text