Experiential Relationship between Malaria Parasite Density and Some Haematological Parameters in Malaria Infected Male Subjects in Port Harcourt, Nigeria

Abstract

This study examined the experiential relationship between the parasite density and haematological parameters in male patients with Plasmodium falciparum infection in Port Harcourt, Nigeria reporting to malaria clinics. A total of one hundred and thirty-six (136) male patients were recruited. QBC haematological analysis, QBC malaria parasite specie identification and quantification and thin blood film for differential leucocytes count was used. The mean values of the haematological parameters in each quartile of parasite densities were determined using Microsoft Excel statistical package. Regression analysis was employed to model the experiential relationship between parasite density and haematological parameters. All regression relationships were tested and the relationship with the highest coefficient of determination (R2) was accepted as the valid relationship. The relationships tested included linear, polynomial, exponential, logarithmic and power relationships. The X- axis of the regression graphs stand for the parasite density while Y-axis stands for the respective haematological parameters Neutrophil count had a negative exponential relationship with the parasite density and is related to the parasite density by a polynomial equation model: ynm = -7E-07x2 - 0.0003x + 56.685. The coefficient of determination (R2) was 0.6140. This means that the rate of change of the parasitemia will depend on the initial value of the neutrophil. As the neutrophil increases, the parasitemia will tend to decrease in a double, triple and quadruple manner. The relationship between lymphocyte count, monocyte count and eosinophil count and parasite density was logarithmic and expressed by the following linear equation models: ylm = -2.371ln(x) + 37.296, ymm = 0.6965ln(x) + 5.7692 and yem = 0.9334ln(x) + 4.1718 in the same order. Their respective high coefficients of determination (R2) were 0.8027, 0.8867 and 0.9553. This logarithmic relationship means that each doubling of monocyte count and eosinophil count will cause the same amount of increase in parasitemia whereas each doubling of lymphocyte count will cause the same amount of decrease in parasitemia. The best fitting regression model for total white cell count (WBC), haemoglobin concentration, packed cell volume (PCV)(haematocrit) and mean cell haemoglobin concentration (MCHC) and parasite density was a linear model and expressed by the following linear equation models: yWBCm = 1.2314x + 8533.8, yHbm = -0.0014x + 13.004, yPCVm = -0.0046x + 41.443 and yMCHCm = -0.0008x + 32.336. Their respective coefficients of determination are 0.7397, 0.6248, 0.9758 and 0.8584. This linear relationship means that as the parasite density is increasing that there is a corresponding decrease in haemoglobin concentration, PCV and MCHC and a corresponding increase in total white cell count. The best fitting regression model between platelet count and parasite density is a power model with a very high coefficient of determination (R2=0.9938) and expressed by: yPltm = 278047x-0.122. These equation...

Hematological changes in Eleginops maclovinus during an experimental Caligus rogercresseyi infestation

“…In both the infested and basal (uninfested) groups, we found that lymphocytes are the most abundant leukocytes in the peripheral blood; however, eosinophils were scarce in the uninfested fishes but abundant in the infested ones, which correlates with other studies in fishes (ALVAREZ-PELLITERO, 2008;EZE EVELYN et al, 2012;PIERRARD et al, 2012;RUANE et al, 2000;SILVA-SOUZA et al, 2000). Neutrophils decrease steadily during the 4 weeks of infestation, which is consistent with a study by Tavares-Dias et al (2008).…”

Impact of malaria diagnostic refresher training programme on competencies and skills in malaria diagnosis among medical laboratory professionals: evidence from Ghana 2015–2019

“…On the other hand, microscopy is the gold standard in malaria diagnosis as it is able to detect low parasitaemia threshold of 100 parasites per microlitre of blood in the thin film and about 50 parasites per microlitre of blood in the thick film [ 5 ]; identify and describe species and stages, quantify parasite density and is also used for treatment response monitoring. The sensitivity and specificity of this diagnostic tool is however of great concern as skilled laboratory professionals trained in microscopy are needed to give reliable results [ 7 ]. Accurate diagnosis of malaria is important in reducing misdiagnosis of the disease and helps in identifying other fatal non-malarial causes of infection, reducing wastage of and possible resistance to antimalarial drugs and enables the effective management of febrile patients [ 8 ].…”

Association of Parasite Density and Hematological Parameters of Plasmodium vivax- and Plasmodium falciparum-infected Patients Attending Merauke General Hospital, Papua, Indonesia

“…An inverse correlation between the parasite densities with the lymphocyte count in P. falciparum infection and positive correlations of the parasite density with neutrophil and platelet counts in P. vivax and P. falciparum infection were reported by studies in Ghana and South Ethiopia [3], [7]. A mathematical model study also designated good relationships of the parasite density with neutrophil, lymphocyte, monocyte, and eosinophil count in P. falciparum infection [17]. Despite those discordances, insignificant correlations of parasite density, in both species, with hemoglobin concentration, leukocyte count, and monocyte count, in this study, agree with the previous studies [3], [7].…”