UNASSIGNED: Haematological abnormalities are common among tuberculosis patients but there is dearth of information on their value as prognostic markers in Multidrug resistant tuberculosis patients. This study examined the association between complete blood count variables and drug resistant tuberculosis.
UNASSIGNED: Nighty (90) consenting adults comprising 30 Drug Resistant Tuberculosis patients (DR-TB), 30 Drug susceptible tuberculosis patients (DS-TB) and 30 healthy participants were recruited in this study. Ethical approval was obtained from Oyo State Ministry of Health Institutional Review Board while patients\' demographic data were collected using structured questionnaire. Five milliliters (5mL) of blood samples were collected in EDTA bottle. Haematological parameters were analysed using impedance technique and Mindary-BG5380 5-part automated system.
UNASSIGNED: The mean hemoglobin levels were significantly lower in DR-TB patients (11.70 ± 2.73 g/dL) than in DS-TB patients (8.33 ± 9.56 fL), with a mean difference of -3.37 ± 12.29 g/dL. The mean MCH and MCHC levels were also slightly lower in DR-TB patients (26.17 ± 3.44 pg and 30.41 ± 1.92 g/dL, respectively), but the differences were not statistically significant. The WBC count was similar in both groups (8.20 ± 3.80 × 10^9 /L and 8.45 ± 3.63 × 10^9 /L, respectively).
UNASSIGNED: The mean hemoglobin levels were significantly lower in DR-TB patients than in DS-TB patients which may be due to the increased inflammation associated with DR-TB. The WBC count was similar in both groups, suggesting that the immune system is responding similarly to the infection in both DR-TB and DS-TB patients.
UNASSIGNED: In the meantime, healthcare providers should be aware of these potential differences and use them to inform their diagnosis and treatment of patients with tuberculosis.

UNASSIGNED: Inflammation is integral to diabetes pathogenesis. The novel hematological inflammatory biomarker, platelet to white blood cell ratio (PWR), is linked with various conditions such as chronic kidney disease and stroke. However, the association of this novel clinical indicator with diabetes still remains unclear, which is investigated in this study.
UNASSIGNED: A total of 10,973 Chinese participants were included and grouped according to the tertiles of PWR (T1, T2, and T3 groups). Diagnosis of prediabetes and diabetes adhered to American Diabetes Association criteria. Binary logistic regression was adopted to assess the relationship between PWR and both diabetes and prediabetes. The dose-response relationship of PWR and diabetes was examined using restricted cubic spline regression. Subgroup and interaction analyses were conducted to investigate potential covariate interactions.
UNASSIGNED: Individuals with higher PWR had better lifestyles and lipid profiles (all P < 0.05). After adjusting for all the covariates, the T2 group had a 0.83-fold (95% CI: 0.73-0.93, P < 0.01) risk of diabetes and that for the T3 group was 0.68-fold (95% CI: 0.60-0.78. P < 0.001). Dose-response analysis identified non-linear PWR-diabetes associations in the general population and females (both P < 0.05), but absent in males. Participants with prediabetes in the T2 and T3 groups had lower risks of diabetes (OR = 0.80 for the T2 group, P < 0.001 and 0.68 for the T3 group, P < 0.001) in the full models. All the sensitivity analysis support consistent conclusions.
UNASSIGNED: An increase in PWR significantly correlates with reduced diabetes risks. A non-linear PWR-diabetes relationship exists in the general population and females, but not in males. The correlation between PWR and diabetes indicates that PWR holds potentials in early identification and prevention of diabetes.

This study was performed to analyze fingertip capillary blood sampling in pediatric patients using microcapillary blood collection tubes and microhematocrit tubes and to compare the blood cell analysis results obtained via these two blood collection methods. Finger capillary blood was collected from 110 outpatients using microcapillary blood collection tubes and microhematocrit tubes and complete blood count analysis was performed with a Sysmex XS-900i hematology analyzer and manual microscopy for blood cell morphology. Paired data was evaluated for agreement and bias using the microhematocrit samples as the reference group and the samples from the microcapillary blood collection tubes as the observation group. The two blood collection methods demonstrated good agreement for measuring red blood cell (RBC) parameters (i.e., RBC, Hb, Hct, MCV, MCH and MCHC), wherein the relative bias was > allowable total error (TEa) in 0.91%, 1.82%, 11.82%, 1.82%, 0.91% and 8.18% of the parameter measures, respectively. According to industry requirements, the proportion of samples meeting the acceptable bias level should be > 80%. Additionally, the estimated biases at each medical decision level were within clinically acceptable levels for RBC, Hb, Hct, and MCV. However, the proportion of WBC and PLT counts with relative bias > TEa was 25.45% and 35.45%, respectively. Furthermore, the relative bias of the WBC count at the medical decision level of 0.5 × 109/L and that of the PLT counts at the medical decision levels of 10 × 109/L and 50 × 109/L were clinically significant. Bland-Altman analysis further showed a mean bias of 0.66 × 109/L (95% LoA, - 0.79 to 2.11) for the WBC count and 39 × 109/L (95% LoA, - 46 to 124) for the PLT count from the blood samples collected in the microcapillary blood collection tubes compared with the counts of those collected in the microhematocrit tubes. Neutrophil, monocyte, lymphocyte, eosinophil, and PLT counts increased significantly in the microcapillary blood collection tubes compared with those in the microhematocrit tubes, along with an elevated number of instrument false alarms (P < 0.05). The two capillary blood collection devices exhibit performance differences. Therefore, clinicians should pay attention to the variation in results caused by different blood collection methods.

The Coronavirus Disease 2019 (COVID-19) has caused a global health crisis. Mortality predictors in critically ill patients remain under investigation. A retrospective cohort study included 201 patients admitted to the intensive care unit (ICU) due to COVID-19. Data on demographic characteristics, laboratory findings, and mortality were collected. Logistic regression analysis was conducted with various independent variables, including demographic characteristics, clinical factors, and treatment methods. The study aimed to identify key risk factors associated with mortality in an ICU. In an investigation of 201 patients comprising non-survivors (n = 80, 40%) and Survivors (n = 121, 60%), we identified several markers significantly associated with ICU mortality. Lower Interleukin 6 and White Blood Cells levels at both 24- and 48-hours post-ICU admission emerged as significant indicators of survival. The study employed logistic regression analysis to evaluate risk factors for in-ICU mortality. Analysis results revealed that demographic and clinical factors, including gender, age, and comorbidities, were not significant predictors of in-ICU mortality. Ventilator-associated pneumonia was significantly higher in Survivors, and the use of antibiotics showed a significant association with increased mortality risk in the multivariate model (OR: 11.2, p = 0.031). Our study underscores the significance of monitoring Il-6 and WBC levels within 48 hours of ICU admission, potentially influencing COVID-19 patient outcomes. These insights may reshape therapeutic strategies and ICU protocols for critically ill patients.

BACKGROUND: The immune response dynamics in COVID-19 patients remain a subject of intense investigation due to their implications for disease severity and treatment outcomes. We examined changes in leukocyte levels, eosinophil activity, and cytokine profiles in patients hospitalized with COVID-19.
METHODS: Serum samples were collected within the first 10 days of hospitalization/confirmed infection and analyzed for eosinophil granule proteins (EGP) and cytokines. Information from medical records including comorbidities, clinical symptoms, medications, and complete blood counts were collected at the time of admission, during hospitalization and at follow up approximately 3 months later.
RESULTS: Serum levels of eotaxin, type 1 and type 2 cytokines, and alarmin cytokines were elevated in COVID-19 patients, highlighting the heightened immune response (p < 0.05). However, COVID-19 patients exhibited lower levels of eosinophils and eosinophil degranulation products compared to hospitalized controls (p < 0.05). Leukocyte counts increased consistently from admission to follow-up, indicative of recovery.
CONCLUSIONS: Attenuated eosinophil activity alongside elevated chemokine and cytokine levels during active infection, highlights the complex interplay of immune mediators in the pathogenesis COVID-19 and underscores the need for further investigation into immune biomarkers and treatment strategies.

Effects of short-term exposure to ambient air pollution on systemic immunological and inflammatory biomarkers in rural population have not been adequately characterized. From May to July 2021, 5816 participants in rural villages of northern Henan Province, China, participated in this cross-sectional study. Blood biomarkers of systemic inflammation were determined including peripheral white blood cells (WBC), eosinophils (EOS), basophils (BAS), monocytes (MON), lymphocytes (LYM), neutrophils (NEU), neutrophil-lymphocyte ratio (NLR), and serum high-sensitivity C-reactive protein (hs-CRP). The concentrations of ambient fine particulate matter (PM2.5), PM10, nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were assessed up to 7 days prior to the blood draw. A generalized linear model was used to analyze the associations between air pollution exposure and the above-mentioned blood biomarkers. Significantly positive associations were revealed between PM2.5, CO and WBC; CO, O3 and LYM; PM2.5, PM10, SO2, CO and NEU; PM2.5, PM10, SO2, CO and NLR; PM2.5, PM10, SO2, NO2, CO, O3 and hs-CRP. Meanwhile, negative associations were found between SO2 and WBC; PM2.5, PM10, NO2, CO, or O3 and EOS; PM2.5, SO2, or CO and BAS; SO2, NO2 or O3 and MON; PM2.5, PM10, SO2, or NO2 and LYM. Moreover, men, individuals with normal body mass index (BMI), current smokers, and those older than 60 years were found vulnerable to air pollution effects. Taken together, short-term exposure to air pollution was associated with systemic inflammatory responses, providing insight into the potential mechanisms for air pollution-induced detrimental systemic effects in rural residents.

Sysmex DI-60 enumerates and classifies leukocytes. Limited research has evaluated the performance of Sysmex DI-60 in abnormal samples, and most focused on leukopenic samples. We evaluate the efficacy of DI-60 in determining white blood cell (WBC) differentials in normal and abnormal samples in different WBC count. Peripheral blood smears (n = 166) were categorised into normal control and disease groups, and further divided into moderate and severe leucocytosis, mild leucocytosis, normal, mild leukopenia, and moderate and severe leukopenia groups based on WBC count. DI-60 preclassification and verification and manual counting results were assessed using Bland-Altman and Passing-Bablok regression analyses. The Kappa test compared the concordance in the abnormal cell detection between DI-60 and manual counting. DI-60 exhibited notable overall sensitivity and specificity for all cells, except basophils. The correlation between the DI-60 preclassification and manual counting was high for segmented neutrophils, band neutrophils, lymphocytes, and blasts, and improved for all cell classes after verification. The mean difference between DI-60 and manual counting for all cell classes was significantly high in moderate and severe leucocytosis (WBC > 30.0 × 109/L) and moderate and severe leukopenia (WBC < 1.5 × 109/L) groups. For blast cells, immature granulocytes, and atypical lymphocytes, the DI-60 verification results were similar to the manual counting results. Plasma cells showed poor agreement. In conclusion, DI-60 demonstrates consistent and reliable analysis of WBC differentials within the range of 1.5-30.0 × 109. Manual counting was indispensable in examining moderate and severe leucocytosis samples, moderate and severe leukopenia samples, and in enumerating of monocytes and plasma cells.

Hepatitis B virus (HBV) damages liver cells through abnormal immune responses. Mitochondrial metabolism is necessary for effector functions of white blood cells (WBCs). The aim was to investigate the altered counts and mitochondrial mass (MM) of WBCs by two novel indicators of mitochondrial mass, MM and percentage of low mitochondrial membrane potential, MMPlow%, due to chronic HBV infection. The counts of lymphocytes, neutrophils and monocytes in the HBV infection group were in decline, especially for lymphocyte (p = 0.034) and monocyte counts (p = 0.003). The degraded MM (p = 0.003) and MMPlow% (p = 0.002) of lymphocytes and MM (p = 0.005) of monocytes suggested mitochondrial dysfunction of WBCs. HBV DNA within WBCs showed an extensive effect on mitochondria metabolic potential of lymphocytes, neutrophils and monocytes indicated by MM; hepatitis B e antigen was associated with instant mitochondrial energy supply indicated by MMPlow% of neutrophils; hepatitis B surface antigen, antiviral therapy by nucleos(t)ide analogues and prolonged infection were also vital factors contributing to WBC alterations. Moreover, degraded neutrophils and monocytes could be used to monitor immune responses reflecting chronic liver fibrosis and inflammatory damage. In conclusion, MM combined with cell counts of WBCs could profoundly reflect WBC alterations for monitoring chronic HBV infection. Moreover, HBV DNA within WBCs may be a vital factor in injuring mitochondria metabolic potential.

UNASSIGNED: Due to high inter-observer variability the 2015 International Council for Standardization in Haematology (ICSH) recommendations state to count band neutrophils as segmented neutrophils in the white blood cell (WBC) differential. However, the inclusion of bands as a separate cell entity within the WBC differential is still widely used in hematology laboratories in Croatia. The aim of this multicentric study was to assess the degree of inter-observer variability in enumerating band neutrophils within the WBC differential among Croatian laboratories.
UNASSIGNED: Seven large Croatian hospital laboratories from different parts of the country participated in the study. In each of 7 participating laboratories, one blood smear, that was flagged by the analyzer as possibly having bands, was evaluated by all personnel participating in the analysis of hematology samples. Between-observer manual smear reproducibility was expressed as coefficient of variation (CV) and calculated using the following formula: CV (%) = (standard deviation (SD)/mean value) x 100%.
UNASSIGNED: The CVs (%) and relative band neutrophil counts in participating laboratories were as follows: 15.4% (16-24), 19.2% (16-32), 19.5% (17-40), 21.1% (17-44), 35.0% (8-26), 51.9% (3-29), and remarkably high 62.4% (12-59). For segmented neutrophils CVs were lower, ranging from 7.4% to 32.2%. The CVs did not correlate with the number of staff members in each hospital (P = 0.293).
UNASSIGNED: This study revealed very high variability in enumerating band neutrophil count in the blood smear differential among all participants, thus prompting a need for action on a national level.

Blood cell ratios are a standard clinical index for the assessment of inflammation. Although a large number of epidemiological investigations have shown that inflammation is a potential risk factor for the development of coronary heart disease (CHD), there is not sufficient and direct evidence to confirm the relationship between blood cell ratios and CHD. Therefore, this study aimed to elucidate the effect of blood cell ratios on the incidence of coronary heart disease. This 10-year national study included data from 24,924 participants. The independent variable was blood cell ratios, and the dependent variable was coronary heart diseases (yes or no). The relationship between blood cell ratios and coronary heart disease was verified using baseline characteristic analysis, multivariate logistic regression analysis, smoothed fitted curves, and subgroup analysis. This study found that in multiple logistic regression analysis showed significant positive correlation between monocyte counts × meutrophil counts/lymphocyte counts (SIRI) (OR = 1.495; 95% CI = 1.154-1.938), monocyte-lymphocyte ratio (MLR) (OR = 3.081; 95% CI = 1.476-6.433) and the incidence of CHD; lymphocyte-monocyte ratio (LMR) (OR = 0.928;95% CI = 0.873-0.987), monocyte-lymphocyte ratio (PLR) (OR = 0.997;95% CI = 0.994-1.000) showed negative correlation with CHD. The smoothed curve fitting shows a nonlinear relationship between SIRI, LMR, PLR, and CHD, with an inverted U-shaped curve between SIRI and CHD, an L-shaped angle between LMR and CHD, and a U-shaped curve between PLR and CHD, respectively. Their inflection points are 1.462, 3.75, and 185.714, respectively. SIRI has an inverted U-shaped curve with coronary heart disease, suggesting that low levels of SIRI increase the risk of CHD; LMR with an L-shaped curve with CHD, and PLR with a U-shaped curve with CHD, suggesting that the risk of CHD can be prevented when LMR and PLR are reduced to a certain level. This has positive implications for the prevention and treatment of CHD.