Total Leucocyte Count

A decade ago, Assicot et al reported that elevated levels of PCT could reliably discriminate between fever due to bacterial infections and other non-infectious causes 4 . Considering the need for a reliable biochemical marker of infection, we decided to evaluate levels of PCT in 70 patients of suspected bacterial infection of various grades. CRP levels were also evaluated, in order to do a comparative study. Total leucocyte count being an inexpensive test, was also added to the comparative study. 30 patients who had no evidence of infection were taken as controls.

Background: Dengue infections are public health concerns in India, where they occur in epidemics and have a high mortality in the advanced stages. Clinical features are nonspecific, and diagnosis is supported by lab features. One of these lab tests include total leucocyte count-easily available, simple and cost effective which is useful in small rural set ups for early diagnosis and prognosis of dengue. The aim of this study is to analyse the total leucocyte count patterns in dengue and assess its utility as early marker of dengue and prognosticator of severe dengue.

The immune system expresses an adaptive response in all the vertebrates against invading microorganisms. The role of immune system is to sustain host defense mechanisms and maintain homeostasis. The Long acting oxytetracycline administered at 20 and 40 mg/kg body weight mg/kg body weight through intramuscular route in wistar albino rats. Sheep RBC used as antigen. The present study was conducted to study the hematological parameters like Total Leucocyte count (TLC) in rats. There was no significant (P>0.05) difference in TLC values in antigen plus long acting oxytetracycline low dose (Group VII) and high dose (Group VIII). There was decrease in the TLC values in treated groups (Group VII and VIII) when compared to antigen (Group V) and

Acute appendicitis often poses a diagnostic dilemma to the operating surgeon because of the multiple aetiologies of acute abdomen and the varied clinical presentation among different categories of patients. Total leucocyte count (TLC) is a useful investigation in diagnosing acute appendicitis. It is an indirect marker of inflammation and bacterial infection. Patients with acute, uncomplicated appendicitis usually present with a total leucocyte count ranging from 10,000 to 18,000. 1 Reports show the finding

[4,27]. A relatively high positive correlation has been established between absolute values of TLC and CD4 count [27] or between changes in TLC and CD4 cell count [28]. A range of TLC cutoffs have been used and reported as predictors of CD4 < 200 cells/µl. These cutoffs range from 1000 cells/µl with a specificity of 98% and a sensitivity of 53% to 1,400 cells/µl with a sensitivity of 73% and a specificity of 88%[4,29]. In another study, a TLC cutoff of 1,200 cells/µl was modeled with hemoglobin to improve sensitivity[30]. Our study explored the use of TLC in predicting CD4 count that would be readily available even in underserved resource-poor settings. Our study demonstrated that TLC could be used to predict CD4 count in healthy HIV negative adults, its application in various formats, both before and during HAART use in HIV patients need to be explored. The laboratory parameter most studied as a potential alternative to CD4 count is the total lymphocyte count (TLC). This is calculated by multiplying the total white blood cell count (wbc) by the lymphocyte percentage. The relatively low cost of this method, and the wider availability of necessary laboratory equipment make it an attractive parameter for resource-limited settings. The lymphocyte percentage of total wbc, which is necessary to calculate the TLC, is most accurate if determined within a few hours of phlebotomy. Many hematology workstations in resource-limited settings are unable to meet this stringent criterion, and there are unavoidable excursions in ambient temperature that accelerate the degradation of laboratory samples. As such, TLC calculations are prone to error. Another factor that can unravel potential correlation between TLC and CD4 count is that TLC captures both B and T cell subsets. Accordingly, a person with low CD4 count could have relatively high TLC if high amounts of B cells are expressed due to immune hyperactivation from exposure to the wide variety of circulating antigens in sub- Saharan Africa.

Comparison of effect of trial drug on total leucocyte count within and between the three groups in terms of mean difference with standard deviation using paired t test and one way ANOVA [r]

Abstract- The haematological parameters such as Total Erythrocyte Count (TEC), Total Leucocyte Count and Differential leucocyte count (TLC and DLC), Haemoglobin Content (Hb), Packed Cell Volume (PCV), the Erythrocyte constants like Mean Corpuscular Volume (MCV), Mean Corpuscular Haemoglobin (MCH) and Mean Corpuscular Haemoglobin Concentration (MCHC) and Enzymes (AST/SGOT and ALT/SGPT) were estimated in the fish Oreochromis mossambicus exposed to sub-lethal concentration (10ppm) of FAME (Flubendiamide 480 SC) pesticide for four weeks. Studies in fish exposed to this chemical pesticide (amide derivative) indicated significant reduction in the blood parameters except WBC throughout the experiment. Total leucocytes showed significant increase throughout the experiment. The enzyme profile showed significant increase after 4weeks of exposure confirming the significant impact of the pesticide on the organism.

Hydrocephalus 55.5% 33% Death due to disease 44.4% - The CSF examination parameters for the two groups are listed in table 2. The HIV positive group had a lower total leucocyte count (23 cells/mm 3 ) with a predominance of neutrophils. Plasma cells were invariably noted in the differential count. The glucose levels were within normal range whereas the protein was raised. This group had a high antigen titre (>1:256). In stark comparison, the HIV negative group had a significant leucocytosis (96.3 cells/mm 3 ) with lymphocyte predominance. The eosinophils were relatively more compared to the first group. The CSF protein and glucose concentration were within normal range. The antigen titres were also low.

Results in the present study showed that cigarette smoker young men and control group differed significantly on the basis of TLC, Neutrophil and Eosinophil counts. The results related to Total Leucocyte Count (TLC), Differential leucocyte Count (DLC) and Platelet Count in control group was observed to be within the physiological limits [6]. In the present study, Total Leucocyte Counts (TLC) was found elevated in cigarette smoking young men compared with that of non-smoking age-matched young men. R. W. Howell in 1970 reported mean white cell count in heavy smokers to be strikingly higher than in non-smokers [7]. This type of findings of high white cell counts in heavy smokers has been confirmed in France [8] and in the U.S.A. [9]. Similar findings were observed in pregnant women in England by McGarry in 1974 [10]. Elevated Total Leucocyte Count (TLC) in smoker in this study is in agreement with the findings of other investigators like Burney S W, L Bonus (1972) [11]; Corre F.J., Lellouch, and D. Schwartz (1971) [8]; Sutek K., and W Jedrzejczak (1973) [12].

 Bleeker et al in 2001 conducted study among 231febrile children aged 1-36months and showed 25%prevalence of serious bacterial infection in the study population. The study also suggested clinical parameters like temperature <36.7℃ or more than or equal to 40℃, presence of retractions, poor peripheral perfusion, fever duration at presentation, age, poor micturition ,presence of vomiting as significant predictors (ROC area 0.750) . Laboratory parameters like total leucocyte count, C reactive protein values and presence of >70WBC in urine (ROC area 0.83) are suggested as independent laboratory predictors of serious bacterial infection. The risk stratification for presence of serious bacterial infections in such children ranged from 6% to 92% 7.

Where, PI is parasite index, PC is the number of para- sites counted in the blood smear, WBC is the number of white blood cells counted in the blood smear, TLC is the patients’ total leucocyte count (either ‘assumed’ or ‘measured’). Leishman’s stained peripheral blood smears were examined under Olympus CH20i microscope and PIs were determined independently by three microsco- pists. Using a manual tally counter, number of parasites and WBCs in corresponding microscopic fields were counted. If ten or more parasites were noted in up to 200 WBCs counts, further counting was stopped, other- wise counting continued up until 500 WBCs [8]. A mean of three consecutive PIs was used for further analysis.

Objectives: To observe the duration for normalization of the Total Leucocyte Count (TLC) with adjuvant Granulocyte-Colony Stimulating Factor (G-CSF) treatment in leukopenic neonatal sepsis, and to compare the neutrophilic response to G-CSF in neutropenic vs non-neutropenic subgroups Methods: This prospective cohort study was carried out at the Neonatal Intensive Care Unit at Military Hospital Rawalpindi (NICU) from 1st August 2015 to 25th January 2017. Fifty one newborns with sepsis and leucopenia were sampled judgmentally from a population of 5666 admitted to NICU during the study period. The sample was then divided into neutropenic (exposed) and non-neutropenic (non-exposed) subgroups on basis of the absolute neutrophil count (ANC). Adjuvant G-CSF was given to all subjects and stopped once TLC normalized. SPSS v22 was used to calculate mean G-CSF treatment duration and rise in ANC. A Pearson correlation coefficient and simple linear regression were computed to assess the relationship between pre-GCSF ANC and the duration of treatment with GCSF. Comparison of subgroups with respect to rise in ANC was done using independent samples T-test.

Mean ages of occurrence of obesity and metabolic syndrome were much higher than the mean age of the control group. As expected, increase in BMI was associated with corresponding increase in waist circumference and body fat content. In one-way ANOVA, F-statistic was particularly high for waist circumference, body fat content, TLC and absolute neutrophil count. Overall, there was statistically significant variation between the groups. There was a progressive increase in the values of the following parameters as the BMI increased: Waist Circumference (WC), Fasting Plasma Glucose (FPG), Body Fat % (BF), Total Leucocyte Count (TLC), Absolute Neutrophil Count (ANC) and ratios (N/l & dNLR). Most of these parameters showed positive correlation which was statistically significant (p=<0.05 to <0.0001) [Table/Fig-3]. Among the haematological parameters, TLC and ANC showed the strongest correlations with BMI, WC, BF and FPG.

Hemoglobin, Total Leucocyte count, Differential Leucocyte count, Platelet count, ESR, Peripheral smear Tuberculosis Mantoux test- Negative X-ray chest- Normal Sputum for AFB- Negative[r]

Materials and methods: Our study was carried out in 48 pregnant women in their third trimester of pregnancy. Blood collected was analyzed for complete hemogram, including haemoglobin (Hb), differential count(DC), total leucocyte count (TLC) , red blood cell count (RBC), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC), red cell distribution width (RDW), hemoglobin distribution width (HDW), serum ferritin and serum transferrin receptors (sTfR).

cause the escalating of leucocyte cells. One of them was caused by polluted aquatic environment. This was supported by the research conducted by Mazrouh et al. (2015), it explained that a very clear growing number of leucocytes in fish samples collected were caused by pollutants. In line with the opinion of Maftuch et al. (2017), that pollutants increased haemorrhage which resulted in fish organs damage. An intensification in the number of lymphocytes, monocytes, and neutrophils was thought to be the reason for the increasing total number of leucocytes. Another reason that could increase the number of leucocytes was bacterial infection.

To determine whether iron overload affected hematological profile, the value resulted from hematology analyzer (18 indices) was analyzed.An iron overload model was successfully established by injecting with iron dextran and was able to modify hematology change. Iron overload treatments exaggerated the leucocyte, platelet, and erythrocyte indicesvalue. A dynamic tendency of leucocyte absolute cell number and differential cell count of each group of iron treatment was shown in Figure 1. In line with the increased dosage of iron treatment, there was a decreasing tendencyof total white blood cell, monocyte, and lymphocyte number within groups, while an increasing trend showed in absolute and differential cell count of granulocyte subset. There was a significantly different effect of iron treatment on differential monocyte count among the groups, using Kruskal- Wallis, X 2 =6.59, P<0.05. Post hoc pairwise

Decreases in the red blood cells could also be as a result of internal bleeding caused by damaged kidney. Similar findings supporting the present study were recorded for Heteroclarias exposed to sub lethal concentrations of Cd 2+ (Kori-Siakpere et al., 2006). In fish, the white blood cells respond to various stressors including infections and chemical irritants (Christensen et al., 1978). The significant increase of lymphocytes, total leucocytes was observed in fish exposed to CdCl 2 . Increased TLC has been suggested due to stimulated

The two different contaminated canned foods (milk and meat) samples were collected from the Tiruchirappalli general market during October 2015 for microbiological analysis. The 1 ml of milk and 1 g of meat contaminated canned foods were mixed in peptone waters and were inoculated into the selective medium by spared plate method. The mean level of TVC, TCC, TSTC, TPC, TBC, TSYC, TSSC and TKC counts in canned milk sample were 12.4 x 10 2 , 3.4 x 10 2 , 1.1 x 10 2 , 0.84 x 10 2 , 2.7 x 10 2 , To low too count (TLTC), 0.72 x 10 2 , 0.57 x 10 2 , respectively. But, the mean level of Total viable count (TVC), Total coliforms count (TCC), Total Streptococci count (TSTC), Total Pseudomonas count (TPC), Total Bacillus count (TBC), Total Staphylococcus count (TSYC), Total Salmonella and Shigella count (TSSC) and Total Klebsiella count (TKC) counts in canned meat sample were 11.4 x 10 3 , 7.8 x 10 2 , 3.1 x 10 2 , 1.4 x 10 2 , 4.3 x 10 2 , 0.98 x 10 2 , 1.2 x 10 2 , 0.81 x 10 2 , respectively. The microbial load was high in meat food product than the milk product. The microbial load was high in meat food product than the milk product due to the nutrient richness and that can be support the growth of microorganisms. Among the bacterial parameters, total coliforms and Bacillus counts were high in both the samples while low level of Staphylococcus was observed. Hence, this study recommended that the canned food materials were analyzed at each stage of food processing.

CNNA & MNB The levels of ascitic PMN count, proteins and total serum bilirubin in SBP, CNNA and MNB are shown in [Table/Fig 3]. The ascitic fluid PMN count was raised in SBP and CNNA cases as compared to that in the MNB cases (P<0.05 ).The protein level was significantly decreased in SBP cases as compared to that in the CNNA cases (P<0.05). The levels were further more increased in MNB cases as compared to that in the CNNA cases (P<0.05). Serum bilirubin levels were raised in SBP cases as compared to that in the CNNA cases (P<0.05). The levels were lower in MNB cases as compared to that in the CNNA cases (P<0.05).