volume (p = 0.017), significantly increased and the levels of mean corpuscular volume (MCV; p = 0.023), RBC distribution width-coefficient of variation (p = 0.005), platelet distribution width (p = 0.015), and ferritin (p = 0.002) significantly decreased compared to the baseline in group receiving quercetin. Between group analysis revealed that RBC significantly increased (p = 0.025) but, mean corpuscular volume (p = 0.004), mean corpuscular hemoglobin (MCH; p = 0.002), and ferritin (p = 0.013) significantly decreased compared to placebo group. In this work quercetin showed significant effect on RBC, ferritin, MCV, and MCH in intervention group.TRIAL REGISTRATION: Iranian Center for Clinical Trials Identifier: IRCT2016060628299N1]]>
Anemia ; Blood Platelets ; Erythrocyte Indices ; Erythrocytes ; Ferritins ; Hematology ; Humans ; Inflammation ; Liver Diseases ; Mean Platelet Volume ; Non-alcoholic Fatty Liver Disease ; Oxidative Stress ; Pilot Projects ; Public Health ; Quercetin

OBJECTIVE: To establish a model for predicting the short-term prognosis of patients with HBV-related acute-onchronic liver failure (HBV-ACLF) based on red blood cell distribution width (RDW) and the model for end-stage liver disease (MELD) scores. METHODS: A total of 245 patients with HBV-ACLF were retrospectively analyzed for their clinical data and results of routine hematological tests, liver function, renal function, coagulation test, HBV-DNA, and other indicators at admission. Univariate analysis and binary logistic regression analysis were used to test the short-term risk factors for death of the patients, and the MELD-RDW model was established. The accuracy of each index and the established model was verified using the ROC curve. RESULTS: The surviving patients with HBV-ACLF had significantly decreased RDW (14.97 ± 1.38) and MELD score (23.54±4.35) compared with those in the patients dead within 90 days (17.05±2.92 and 28.95±5.99, respectively). Multivariate analysis indicated that RDW was a significant independent prognostic factor for mortality in patients with HBVACLF (OR=1.840, 95%CI: 1.47902.289, < 0.005). The risk assessment model was [logisticMELD-RDW]=-9.375+0.582×RDW- 0.091×ALB-0.05×PTA+0.186×MELD. The area under the ROC curve of MELD score combined with RDW was 0.878, which was higher than RDW (0.724) and MELD score (0.780) alone. CONCLUSIONS RDW is an independent prognostic indicator for mortality in patients with HBV-ACLF. Compared with MELD score, the risk assessment model based on MELD and RDW has a greater value in predicting the short-term prognosis of patients with HBV-ACLF.
Acute-On-Chronic Liver Failure ; blood ; mortality ; Cell Size ; End Stage Liver Disease ; blood ; mortality ; Erythrocyte Volume ; Erythrocytes ; cytology ; Hepatitis B ; blood ; complications ; mortality ; Humans ; Prognosis ; ROC Curve ; Retrospective Studies

To investigate the association between red blood cell volume distribution width (RDW) and osteophytes.
 Methods: This cross-sectional study was conducted in the Department of Health Examination Center of Xiangya Hospital, Central South University in Changsha, Hunan Province, China. A total of 8 334 subjects were included in this study. The severity of osteophytes was graded using the criteria of the Osteoarthritis Research Society International (OARSI). Osteophytes incident was defined as at least one side of the knee had a osteophytes grade ≥1. According to the quartiles of the RDW level, the subjects were divided into 4 groups. Multivariate logistic regression analysis was used to calculate the odds ratio (OR) and the 95% confidence interval (CI) of the knee osteophytes incidence between each RDW group and the lowest level group. Tests for linear trends were conducted based on logistic regression using a median variable of RDW level in each category.
 Results: Quartile 1 (Q1), RDW≤9.78; Q2, 9.7813.10. The multivariable adjusted ORs (95%CI) of the prevalence of osteophytes were 1.38 (1.06 to 1.79) in the second percentile interval, and 1.27 (0.97 to 1.66) and 1.50 (1.15 to 1.94) in the third and fourth percentile interval, respectively. Test for linear trends suggested that there was a positive association between the RDW level and the risk of knee osteophytes incidence (P=0.019).
 Conclusion: The risk of osteophytes incidence increases with the increasing RDW levels.
China ; Confidence Intervals ; Cross-Sectional Studies ; Erythrocyte Volume ; Humans ; Incidence ; Odds Ratio ; Osteophyte ; blood ; epidemiology ; Risk Factors ; Severity of Illness Index

OBJECTIVES: We conducted this study to evaluate the diagnostic value of hematologic markers for moderate to severe obstructive sleep apnea syndrome (OSAS). METHODS: We performed the study using medical records from our sleep disorders center. We collected information regarding obstructive apnea-hypopnea index (oAHI), age, sex, body mass index, and complete blood counts with differential counts [white blood cell (WBC) count, neutrophil count, lymphocyte count, red blood cell distribution width (RDW), mean platelet volume, platelet count, platelet distribution width (PDW), neutrophil-lymphocyte ratio, and platelet-lymphocyte ratio]. We excluded patients who were younger than 2 years, older than 14 years, obese/underweight, and those who had a hematologic or severe medical illness. RESULTS: We assessed records from 57 patients (7.98±3.25 years old, 35 men). We classified the subjects into three groups based on their oAHI scores, as follows: normal (oAHI < 1), mild OSAS (1≤oAHI < 5), and moderate/severe OSAS (oAHI≥5). Using a multivariate multinomial logistic regression model (pseudo R²=0.33), we found significant differences among the groups in RDW [moderate/severe OSAS vs. mild OSAS, adjusted odds ratio (OR): 8.77, p-value: 0.03], PDW (mild OSAS vs. normal, adjusted OR: 1.05, p-value: 0.04), and WBC (moderate/severe OSAS vs. normal, adjusted OR: 1.42, p-value: 0.03). CONCLUSIONS: RDW, PDW, and WBC had diagnostic value for moderate/severe OSAS in our study. Further prospective and validation studies are required to develop a screening tool for moderate/severe OSAS in children and adolescents.
Adolescent ; Blood Cell Count ; Blood Cells ; Blood Platelets ; Body Mass Index ; Child ; Erythrocyte Indices ; Erythrocytes ; Humans ; Logistic Models ; Lymphocyte Count ; Mass Screening ; Mean Platelet Volume ; Medical Records ; Neutrophils ; Odds Ratio ; Platelet Count ; Prospective Studies ; Sleep Apnea Syndromes ; Sleep Apnea, Obstructive ; Sleep Wake Disorders

Platelet distribution width (PDW) is an index for platelet size variation. In this study, we analysed the correlation between PDW values obtained using two different hematology analysers that employ different measurement methods. Complete blood cell parameters including PDW for 153 healthy individuals were measured using both, ADVIA 2120i (Simens AG, Germany) and XN-3000 (Sysmex, Japan). The PDW values measured using the two hematology analysers showed a moderate correlation (r=0.661, P<0.001), while the hemoglobin, mean corpuscular volume, red blood cell distribution width values and white blood cell and platelet counts showed strong correlations (r >0.900, P<0.001). PDW obtained using XN-3000 showed a strong correlation with mean platelet volume, whereas PDW obtained using ADVIA 2120i did not. The reference values in this group were 40.0%–64.2% in ADVIA 2120i and 9.0–16.0 fL in XN-3000. In conclusion, PDW values obtained using ADVIA 2120i and XN-3000 are not interchangeable. In laboratories equipped with more than one hematology analyser, a particular analyser should be used consistently for monitoring a particular patient.
Blood Cells ; Blood Platelets* ; Erythrocyte Indices ; Erythrocytes ; Hematology* ; Humans ; Leukocytes ; Mean Platelet Volume ; Platelet Count ; Reference Values

BACKGROUND: Hemolytic specimens contain components that interfere with clinical laboratory results. We evaluated previously published hemolysis indices (HI) and developed an algorithm for differentiating between mechanical hemolysis and immune-mediated hemolysis based on complete blood count (CBC). METHODS: Sixty-three residual EDTA (ethylenediamine tetraacetic acid)-anticoagulated blood specimens were obtained during regular health check-ups, and each specimen was divided into 3 aliquots (A control, B, and C group). Aliquots B and C were mechanically hemolysed by 2 and 5 aspirations, respectively, using a 25-gauge needle before testing; aliquot A was analysed immediately without hemolysis. Additionally, we collected 36 specimens from patients suspected of having immune-mediated hemolysis after thorough reviewing their various laboratory results including direct antiglobulin test. We compared CBC parameters between the groups (A, B, C, D [B+C], and E [immune-mediated hemolysis group]). RESULTS: Our HI scoring system using the sum of red blood cell ghosts, measured hemoglobin-calculated hemoglobin, mean corpuscular hemoglobin concentration-corpuscular hemoglobin concentration mean, and mean platelet volume rather than mean corpuscular hemoglobin, effectively identified mechanical hemolysis; the results were similar to those of previous studies. Furthermore, the HI score using the sum of mean corpuscular volume, red cell distribution width, hemoglobin distribution width, polymorphonuclear %, and neutrophil % differentiated mechanical hemolysis from immune-mediated hemolysis (cut-off, 9; sensitivity, 91.7%; specificity, 92.9%; area under the receiver operating characteristic curve, 0.965 [95% confidence interval, 0.924–0.988]). CONCLUSIONS: The newly developed algorithm may provide effective screening for detecting hemolysis and differential diagnosis of mechanical hemolysis and immune-mediated hemolysis based on CBC results.
Aspirations (Psychology) ; Blood Cell Count ; Coombs Test ; Diagnosis, Differential* ; Edetic Acid ; Erythrocyte Indices ; Erythrocytes ; Hemolysis* ; Humans ; In Vitro Techniques* ; Mass Screening ; Mean Platelet Volume ; Needles ; Neutrophils ; ROC Curve ; Sensitivity and Specificity

In the field of orofacial surgery, a red blood cell transfusion (RBCT) is occasionally required during double jaw and oral cancer surgery. However, the question remains whether the effect of RBCT during the perioperative period is beneficial or harmful. The answer to this question remains challenging. In the field of orofacial surgery, transfusion is performed for the purpose of oxygen transfer to hypoxic tissues and plasma volume expansion when there is bleeding. However, there are various risks, such as infectious complications (viral and bacterial), transfusion-related acute lung injury, ABO and non-ABO associated hemolytic transfusion reactions, febrile non-hemolytic transfusion reactions, transfusion associated graft-versus-host disease, transfusion associated circulatory overload, and hypersensitivity transfusion reaction including anaphylaxis and transfusion-related immune-modulation. Many studies and guidelines have suggested RBCT is considered when hemoglobin levels recorded are 7 g/dL for general patients and 8-9 g/dL for patients with cardiovascular disease or hemodynamically unstable patients. However, RBCT is occasionally an essential treatment during surgeries and it is often required in emergency cases. We need to comprehensively consider postoperative bleeding, different clinical situations, the level of intra- and postoperative patient monitoring, and various problems that may arise from a transfusion, in the perspective of patient safety. Since orofacial surgery has an especially high risk of bleeding due to the complex structures involved and the extensive vascular distribution, measures to prevent bleeding should be taken and the conditions for a transfusion should be optimized and appropriate in order to promote patient safety.
Acute Lung Injury ; Anaphylaxis ; Cardiovascular Diseases ; Emergencies ; Erythrocyte Transfusion* ; Erythrocytes* ; Graft vs Host Disease ; Hemorrhage ; Humans ; Hypersensitivity ; Jaw ; Monitoring, Physiologic ; Mouth Neoplasms ; Oxygen ; Patient Safety ; Perioperative Period ; Plasma Volume ; Transfusion Reaction

OBJECTIVETo investigate the effect of occupational exposure to toluene diisocyanate (TDI) on the workers' health.

METHODSA total of 76 workers exposed to TDI (exposure group) and 64 management staff members (control group) were selected from a factory as the study subjects. Area sampling was performed for the place with exposure to TDI according to the method in GBZ 159-2004 Specifications of air sampling for hazardous substances monitoring in the workplace, and gas chromatography was applied to measure the concentration of TDI in workplace air. The workers' personal information was collected with questionnaire, pulmonary ventilation function was determined with a portable spirometer, hematological parameters were analyzed by automatic blood analyzer and blood chemistry analyzer, and the indicators of oxidative damage and energy metabolism were measured by the reagent kit provided by Nanjing Jiancheng Bioengineering Institute. SPSS 17 software was applied for statistical analysis.

RESULTSThe exposure group had significantly lower forced vital capacity (FVC), forced expiratory volume in 1 second(FEV1.0), and FEV1.0/FVC ratio than the control group (P <0.05). Compared with the control group, the exposure group had significantly higher red blood cell count, platelet distribution width, mean platelet volume, lymphocyte count, and neutrophil count(P<0.01), and significantly lower activities of lactate dehydrogenase(LDH), superoxide dismutase, and succinodehydrogenase (SDH)(P <0.01). In the exposure group, the length of exposure was negatively correlated with the activities of SDH and LDH in the serum (r=-0.319, P <0.05; r=-0.239, P <0.05), and the length of exposure was not found to be correlated with the activity of SOD and pulmonary function indices.

CONCLUSIONTDI can induce inflammatory response and lung ventilation function impairment in workers exposed to TDI, as well as oxidative stress and imbalance of energy metabolism. Therefore, it can cause damage to workers' health, and protective measures should be enhanced.

Case-Control Studies ; Erythrocyte Count ; Forced Expiratory Volume ; Humans ; Inflammation ; physiopathology ; L-Lactate Dehydrogenase ; blood ; metabolism ; Leukocyte Count ; Lung ; physiopathology ; Occupational Exposure ; adverse effects ; Pulmonary Ventilation ; Succinate Dehydrogenase ; blood ; metabolism ; Superoxide Dismutase ; metabolism ; Toluene 2,4-Diisocyanate ; adverse effects ; Vital Capacity

BACKGROUND: In this study, we assessed whether red blood cell distribution width (RDW) was associated with all-cause mortality in patients on peritoneal dialysis (PD) and evaluated its prognostic value. METHODS: This study included 136 patients who had RDW levels at PD initiation from January 2007 to January 2014 at the Presbyterian Medical Center and Seoul St. Mary's Hospital. We divided these patients into 2 groups (survivors vs. nonsurvivors), compared their clinical characteristics, and analyzed the predictors of survival. RESULTS: The study included 79 men and 57 women, with a mean age of 54 years (range, 15-85 years). The mean follow-up duration was 32 months (range, 1-80 months). Of 136 patients, 14 died during the follow-up period. When clinical characteristics of survivors (n = 122) and nonsurvivors (n = 14) were compared, no differences were identified, with the exception of serum albumin, total iron-binding capacity (TIBC), left ventricular ejection fraction, total leukocyte count, and RDW value. Survivors had higher serum albumin (3.4 ± 0.5 vs. 3.0 ± 0.5 g/dL, P < 0.001) and left ventricular ejection fraction (56.8 ± 9.8 vs. 48.7 ± 12.8, P = 0.040) and lower TIBC (213.4 ± 40.9 vs. 252.8 ± 65.6, P = 0.010), total leukocyte counts (6.9 × 103/μL vs. 8.6 × 103/μL, P = 0.009), and serum RDW values (13.9 ± 1.7 vs. 16.0 ± 1.8, P < 0.001). Patients with high RDW levels (≥ 14.8) showed significantly higher all-cause mortality than patients with low RDW levels (< 14.8, P < 0.001). In multivariate-adjusted Cox analysis, RDW and TIBC at the start of PD were independent risk predictors for all-cause mortality. CONCLUSION: RDW could be an additive predictor for all-cause mortality in patients on PD.
Erythrocyte Indices ; Erythrocytes* ; Female ; Follow-Up Studies ; Humans ; Leukocyte Count ; Male ; Mortality* ; Peritoneal Dialysis* ; Protestantism ; Seoul ; Serum Albumin ; Stroke Volume ; Survivors

BACKGROUND: The XN-series (Sysmex, Japan) is the new hematology analyzer from Sysmex, with new channels to improve the accuracy of differential leukocyte count and platelet count in the low cell count range. We evaluated the analytical performance and low white blood cell (WBC) mode of the XN-2000. METHODS: Precision, linearity, and carryover were evaluated for the analyzer. We analyzed the accordance of complete blood count (CBC), reticulocyte count, and differential leukocyte count between the XN-2000 and XE-2100 (Sysmex), using 200 samples from normal controls and patients. For 80 samples with a WBC count <1.5x10(9) cells/L, the low WBC mode was evaluated by comparing the automated count with a manual differential count as the reference. RESULTS: The coefficients of variation of precision were <5% for most CBC parameters and <10% for differential leukocyte count. All results obtained with the XN-2000 showed good correlation with those obtained with the XE-2100. The correlation coefficients (r) were >0.9800 for all CBC parameters except mean corpuscular hemoglobin concentration, mean platelet volume, and platelet distribution width, and >0.9900 for differential leukocyte count except monocytes and basophils. The low WBC mode provided accurate counts for neutrophils and lymphocytes, with r>0.9300 for samples with a WBC count of 0.1-1.5x10(9) cells/L. CONCLUSIONS: The XN-2000 showed good analytical performance and correlation with the existing model, the XE-2100. The XN-2000 provided accurate results for differential leukocyte count in samples with a WBC count of 0.1-1.5x10(9) cells/L, and reduced manual slide reviews.
Basophils ; Blood Cell Count ; Blood Platelets ; Cell Count ; Erythrocyte Indices ; Hematology* ; Humans ; Leukocyte Count* ; Leukocytes ; Lymphocytes ; Mean Platelet Volume ; Monocytes ; Neutrophils ; Platelet Count ; Reticulocyte Count