What Is The Normal Range For Platelet Blood Count – Abstract Although changes in platelet count are thought to be harmful, their impact on patient survival has not been evaluated in large cohorts. The prevalence of thrombocytopenia and thrombocytosis was evaluated in a large international population of 36,262 patients aged ≥65 years. A significant association with shorter life expectancy was found for both thrombocytopenia (HR = 1.45; 95% CI: 1.36-1.56) and thrombocytosis (HR = 1.75; 95% CI: 1.56-1.97) when compared to the survival of patients with normal platelet count. to read. This continued to all nations. However, African-Americans (non-Hispanic Blacks) with thrombocytopenia or thrombocytosis had a significantly lower risk compared to non-Hispanic Caucasians (HR = 0.82; 95% CI: 0.69-0.96 and HR = 0.70; 95% CI: 0.53- 0.94, respectively) . Furthermore, Hispanics with thrombocytosis were found to have a lower mortality risk compared to non-Hispanic Caucasians with thrombocytosis (HR = 0.60; 95% CI: 0.44-0.81). A value of <125,000 platelets per microliter was a better predictor for non-Hispanic Blacks and these subjects with this platelet count had a similar survival to Caucasians with a value of <150,000 per microliter. In conclusion, thrombocytosis and thrombocytopenia are independently associated with a shorter life expectancy in elderly subjects and this is moderated by race. Using different thresholds to define the association of thrombocytopenia and thrombocytosis with the risk of all-cause mortality among non-Hispanic Blacks may, therefore, be appropriate. Introduction

Platelets play an important role in hemostasis and are also important in the development of health conditions including atherosclerosis and arterial thrombosis.21 Quantification of platelets in venous blood is a laboratory measurement, carried out by automated hematology analyzers that use a reference number of normal platelets. count between 150, 000 to 450, 000 platelets/μL of blood.3 Both low and rare (thrombocytopenia) and high (thrombocytosis) platelet count are common in many diseases including liver diseases, diseases, autoimmune diseases and diseases.4 Morbidity and death. related to abnormal platelet counts are often thought to be caused by such diseases. However, there are limited data on the prevalence of thrombocytopenia and thrombocytosis and the independent survival rate among older people.

What Is The Normal Range For Platelet Blood Count

What Is The Normal Range For Platelet Blood Count

The number of people aged ≥65 years in the United States is expected to reach 71 million by 2030.5. the number of asymptomatic adults who will be diagnosed with thrombocytopenia or thrombocytosis during routine complete blood count measurements. We, therefore, decided to study the frequency and independent effect on survival of abnormal platelet counts in a large inner-city, elderly outpatient population with different ethnicities and various comorbidities. Previous studies have reported differences in platelet counts between different races.76 The current study included a large minority group: this makes it more representative of population changes in the world and allows a better definition of races and ethnicities of abnormal platelet counts. on the survival of the elderly.

Solved Complete Blood Count Values Match The Complete Blood

The study group consisted of all patients ≥65 years of age who were seen at an outpatient clinic within the Montefiore medical system from January 1 1997 to May 1 2008 and had a complete blood count within 3 months from the date of the first visit. Critically ill patients were excluded by excluding from the analysis all individuals who had been recently discharged from one of our outpatient centers within 30 days prior to the index clinic visit. Approval for all study procedures was obtained from the Institutional Review Board of the Albert Einstein College of Medicine and Montefiore Medical Center.

All clinical data, including complete blood count and comorbidities were retrieved using the Clinical Looking Glass (CLG), a quality improvement health monitoring software (Emerging Health Information Technology, Yonkers, NY, USA). CLG is an integrated clinical information system developed at Montefiore Medical Center that integrates demographic, clinical, and administrative datasets and allows them to be reproduced in a structured format for statistical access. Demographic data (age, gender and ethnicity) was determined by CLG based on registration information. Ethnicity was classified as “non-Hispanic White” (non-Hispanic Caucasian), “non-Hispanic Black” (African-American), “Hispanic” or “other”. The Charlson comorbidity index (CCI), a standardized risk adjustment tool used in research that can measure the effect of multiple diseases on mortality using ICD-9 diagnostic codes, 98 was calculated using information from the CLG. The CCI includes many comorbid conditions including myocardial infarct, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatologic diseases, peptic ulcer disease, liver disease, diabetes with or without complications, hemiplegia/paraplegia, kidney disease , malignant tumors, metastatic diseases and AIDS. As previously described by Charlson et al., 8 age-adjusted CCI scores can be calculated, by measuring and scoring each comorbid condition and then assigning 1 point for every 10 increments of age over 40 years. The validity of the CCI age-adjusted assessment of quality of life quality has been studied more than other similar criteria and this index has been shown to perform well in primary care in outpatient and community settings.10 Mortality data were compared to CLG based on the patient’s name, medical record and social security numbers. The social security death registry was used by CLG to obtain the date of death. Because anemia and neutropenia can independently affect survival, these covariates were included in our analysis. Anemia was defined according to the World Health Organization (WHO) criteria of hemoglobin <13 g/dL in men and 10 g/dL, and severe anemia if the hemoglobin level was ≤10 g/dL. Neutropenia was defined as an absolute neutrophil count <1500/μL of blood. Neutropenia was classified as "mild" if the absolute neutrophil count was between 1000 to 1499/μL, "moderate" if it was between 500 to 999/μL and "severe" if the absolute neutrophil count was <500/μL of venous blood. Thrombocytopenia and thrombocytosis were defined as a platelet count of 450,000/μL, respectively.

The Kolmogorov-Smirnov test was used for analysis of variance for all continuous variables. The selection of statistical comparisons of continuous variables between groups was based on whether the data allowed parametric or non-parametric analysis. Categorical variables were compared using the Pearson χ test. Multivariate analysis was performed with binary logistic regression tests to evaluate the influence of patients’ demographic characteristics and comorbidities on platelet count. Because the log-minus-log survival curves did not show a violation of the proportional-hazards assumption, a Cox proportional hazards model was developed to examine the independent association of abnormal platelet count with subsequent mortality after controlling for comorbidities and demographic variables. The age-adjusted CCI was treated as a continuous variable in the regression model and used as a covariate for risk-adjustment. Other potential confounders such as race, gender, anemia and neutropenia were treated as categorical covariates. To examine whether there was heterogeneity in the association between abnormal platelet counts and risk of death in different ethnicities, an additional Cox proportional hazards model was created to test the interaction of ethnic terms with platelet count status. Odds ratios (OR) and hazard ratios (HR) were derived from logistic and Cox regression analyzes respectively and are presented with the corresponding 95% confidence interval (95% CI). There was no significance of the variables analyzed. To explain the negative effect of platelet count on survival, LOESS regression was used to estimate the relative risks for each race against platelet count after adjusting for potential confounders (gender, anemia, neutropenia and age-adjusted CCI score). A P value of <0.05 was considered statistically significant. P values ​​for post hoc paired comparisons were adjusted by the Bonferroni method.

A total of 36,262 individuals (14,038 men and 22,224 women) met our inclusion criteria. Demographics and baseline characteristics, age-adjusted CCI scores, anemia and neutropenia levels of our study population are shown in Table 1. Males had higher-adjusted CCI scores compared to females (mean position 18, 610.8 versus 17, 828.8) respectively; P<0.001). Non-Hispanic Blacks had higher age-adjusted CCI scores compared to all other races (P value < 0.01). More than half of our study population was minority with 53.3% of men and 64% of women being non-Hispanic Blacks or Hispanics. The prevalence of abnormal platelet counts by gender and ethnicity is shown in Table 2. Non-Hispanic whites had lower mean platelet counts (230,000/μL) compared to non-Hispanic Blacks (238,000/μL; P < 0.001), Hispanics (242,000/μL) , P<0.001) or all other species (237, 000/μL; P<0.001). Hispanics had higher mean platelet counts (P < 0.01 for all comparisons). In addition, non-Hispanic Whites had significantly higher thrombocytopenia rates (9.2%) compared to non-Hispanic Blacks (6.9%; P<0.01), Hispanics (6.5%; P<0.01) and other races (6.4%; P<0.01). Thrombocytosis rates did not the biggest difference is among non-Hispanic Whites (2%), non-Hispanic Blacks (2.3%) and Hispanics (1.8%). However, "other" races had significantly lower thrombocytosis rates (1.3%) compared to non-Hispanic Whites and non-Hispanic Blacks (P < 0.01). Women had a higher platelet count than men and this was consistent across ethnic groups

Understanding Mean Platelet Volume (mpv) Blood Test: High Mpv, Low Mpv Meaning

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