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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 45  |  Issue : 2  |  Page : 97-104

Longitudinal assessment of the impact of tuberculosis infection and treatment on monocyte–lymphocyte ratio, neutrophil–lymphocyte ratio, and other white blood cell parameters


1 Department of Medical Laboratory Science, Faculty of Health Sciences and Technology, Nnamdi Azikiwe University, Anambra State, Nigeria
2 Department of Haematology, Faculty of Medicine, College of Health Sciences, Nnamdi, Nnamdi Azikiwe University, Anambra State, Nigeria
3 Department of Pharmacology and Therapeutics, Faculty of Medicine, College of Health Sciences, Nnamdi Azikiwe University, Anambra State, Nigeria

Date of Submission27-Dec-2019
Date of Acceptance22-Jan-2020
Date of Web Publication29-Dec-2020

Correspondence Address:
Chizoba O Okeke
Department of Medical Laboratory Science, Faculty of Health Sciences and Technology, College of Health Sciences, Nnamdi Azikiwe University, Nnewi Campus P.M.B. 5001 Anambra State
Nigeria
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejh.ejh_62_19

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  Abstract 


Context Tuberculosis (TB) is a major infectious disease usually marked by alterations in white blood cell (WBC) parameters which are known to play a major role in the normal body response to infections.
Aim The aim was to assess the impact of TB infection and treatment on monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and other WBC parameters in TB individuals before and in the course of therapy.
Settings and design This was a longitudinal follow-up study that included 60 TB-infected individuals, age 18 and 80 years. The TB individuals were recruited at Mile-Four Hospital Abakaliki before initiation of therapy and followed up at 2 months and 6 months into treatment.
Materials and methods TB diagnosis was done using both Ziehl–Neelsen acid fast bacilli test and GeneXpert Mycobacterium tuberculosis/rifampicin assay. Whole blood collected in dipotassium ethylenediamine tetraacetic acid was used for the measurement of total white blood cell count and differential white cell count (neutrophil, lymphocyte, monocyte, eosinophil) and packed cell volume. The MLR and NLR were calculated. Statistical Package for the Social Sciences (SPSS), version 22 was used for statistical analysis.
Results The findings showed that total white cell count, neutrophil count, lymphocyte count, eosinophil count, and monocyte count (×109/l) were all significantly decreased after 2-month treatment compared with the pretreatment values (P<0.05) and all except monocyte was significantly increased after 6-month treatment (P<0.05). There was a significant decrease in NLR and MLR after 2 months of treatment that was maintained after 6 months of treatment. Moreover, the packed cell volume (l/l) increased significantly after 2 months of treatment and decreased significantly after 6 months of treatment.
Conclusion TB is associated with significant changes in NLR, MLR, and other WBC parameters which might be possible markers to explore as a prognostic index in TB disease.

Keywords: monocyte–lymphocyte ratio, neutrophil–lymphocyte ratio, tuberculosis, white blood cells


How to cite this article:
Okeke CO, Amilo GI, Ifeanyichukwu MO, Obi EO. Longitudinal assessment of the impact of tuberculosis infection and treatment on monocyte–lymphocyte ratio, neutrophil–lymphocyte ratio, and other white blood cell parameters. Egypt J Haematol 2020;45:97-104

How to cite this URL:
Okeke CO, Amilo GI, Ifeanyichukwu MO, Obi EO. Longitudinal assessment of the impact of tuberculosis infection and treatment on monocyte–lymphocyte ratio, neutrophil–lymphocyte ratio, and other white blood cell parameters. Egypt J Haematol [serial online] 2020 [cited 2021 Jul 31];45:97-104. Available from: http://www.ehj.eg.net/text.asp?2020/45/2/97/305406




  Introduction Top


Mycobacterium tuberculosis (MTB) is the bacterium that is known to cause tuberculosis (TB), which is an infectious disease that generally affects the lungs in cases of pulmonary TB, and other parts of the body in cases of extrapulmonary TB [1]. TB infection may be asymptomatic in most cases in which it is said to be latent or with obvious symptoms in which case it is said to be active. About 10% of latent infections progress to active disease which, if left untreated, kills about half of those infected [1]. It is thought that one-third of the world’s population has been infected with TB with new infections occurring in about 1% of the population each year [2]. In 2016, there were more than 10 million cases of active TB which resulted in 1.3 million deaths with more than 95% of deaths occurred in developing countries such as Nigeria [3].

The pathogenesis of TB infection is linked to the intense local inflammatory response that accompanies infection with MTB. An important feature of inflammation is the accumulation of white blood cells (WBCs) (most of which are phagocytes) at the site of injury. The main phagocytes involved in acute inflammation are the neutrophils. Large numbers of neutrophils reach the site of injury first, sometimes within an hour after injury or infection. After the neutrophils, often 24–28 h after inflammation begins comes the monocytes, which eventually mature into cell-eating macrophages. Macrophages usually become more prevalent at the site of injury only after days or weeks and are a cellular hallmark of chronic inflammation. In general, acute inflammation is mediated by granulocytes, whereas chronic inflammation is mediated by mononuclear cells such as monocytes and lymphocytes.

According to the research by Ngahane et al. [4] the most common abnormalities found among TB patients were lymphopenia (22.1%), neutrophilia (14.2%), monocytosis (23.5%), while monocyte-to-lymphocyte ratio (MLR) and neutrophil-to-lymphocyte ratio (NLR) were significantly higher in the patient group compared with the control group and were fairly predictive of active TB. Immune cells, both monocytes and lymphocytes, have well-defined roles in innate as well as acquired immunity. Monocytes are central mediators of the immune response. Inflammatory stimuli mainly affect the numbers of monocytes in the peripheral blood, which contributes to changes in MLR [5]. TB is considered to be one of the most imperative causes of monocytosis which settles as the infection resolves [6]. Monocytosis is commonly seen in TB because when the microorganism enters the body it is engulfed by alveolar macrophages. Some microorganisms escape the defense mechanisms and succeed to endure, resulting in infection with production of chemoattractant substances which then invites other leukocytes and results in unopposed production of monocytes [7]. The changes in lymphocyte count in TB patients are still controversial, increasing in some cases while decreasing in others and returning to normal with anti-TB therapy [8].

Monocytes are the target cells for mycobacterial proliferation whereas lymphocytes provide resistance to the spread of infection causing mycobacterial clearance, so it is reasonable to suggest that MLR can also be used as a prognostic tool in TB [7]. In line with this, several studies suggest that the MLR is a cheap, readily available, and reproducible test with potential for predicting clinical outcomes of patients with solid tumors and hematological malignancy [9-12]. Similarly, according to Yoon et al. [13] the NLR is a convenient marker of inflammation. It is a readily calculable laboratory marker used to evaluate systemic inflammation. Therefore, the NLR is thought to have stronger discriminative power for predicting bacteremia compared with discrimination based on neutrophilia or lymphocytopenia alone [13].

Although recent studies have focused on the prognostic value of lymphocytes, monocytes, and calculated ratios in cancer and infected patients [14-17], most of the studies were based on comparisons between infected and control groups, thus the relevance of a follow-up study to assess the changes in these immune cells in TB-infected patients and possible utility as a prognostic marker for treatment.


  Materials and methods Top


Study area

This study was carried out at the TB Center of Mile-Four Hospital, Abakaliki Ebonyi State. Mile-Four Hospital is a renowned Catholic Mission Hospital known as a special Tuberculosis and Leprosy Referral Center. It is located in Abakaliki, the capital of Ebonyi State, Southeastern Nigeria and serves patients of high, middle, and lower socioeconomic status.

Study design

This is a prospective follow-up study designed to assess the impact of TB infection and on MLR, NLR, and other WBC parameters by measuring them in TB-infected individuals before and during treatment.

Study population

Individuals confirmed to be positive for pulmonary TB by sputum-smear acid fast bacilli (AFB) by Ziehl–Neelsen stain and GeneXpert MTB/rifampicin (RIF) assay were recruited for the study. The baseline samples were collected before initiation of therapy (pretreatment) and the participants were followed up in the course of treatment and samples were collected after 2 months and 6 months of therapy. TB treatment regimen generally involves a 6-month treatment that is divided into two phases of treatment namely, 2 months of intensive phase in which the patients are given four fixed-dose combination (RIF, isoniazid, pyrazinamide, and ethambutol hydrochloride) and the continuation phase in which the patients are given RIF and isoniazid only for 4 months.

Sampling technique

The TB-infected individuals were recruited before the initiation of therapy by purposive sampling technique in which individuals who meet the inclusion criteria were recruited consecutively until the sample size was attained.

Sample size determination

Sample size was calculated using G*Power software (version 3.0.10, Universitat Dusseldorf Germany). Power analysis for repeated measures analysis of variance with three measurements was conducted in G*Power to determine a sufficient sample size using an alpha of 0.05, a power of 0.90, and a medium effect size (f=0.25). Based on these assumptions, the calculated sample size of 58 has 90% power to detect a difference of 0.25 at a significance level of 0.05.

Inclusion criteria

Patients of both sex, who are positive for active pulmonary MTB.

Exclusion criteria

The following individuals were excluded from the study; pregnant women, those who had blood transfusion in the previous 3 months, those that withheld their consent before or in the course of the study, women on oral contraceptives, smokers, those on herbal concoctions, those that have other known clinical diseases such as cancer, HIV, diabetes, chronic infections, chronic kidney, and liver disease.

Ethical consideration and informed consent

Ethical approval was obtained from the ethics committee of Federal Teaching Hospital Abakaliki (FETHA) and permission was sought and obtained from the management of Mile-Four Hospital Abakaliki before sample collection. The reason for the research was explained to prospective participants and those who gave informed consent was recruited into the study and confidentiality was ensured.

Sample collection

Blood sample collection

All the necessary precautions on sample collection and processing of blood samples were observed. A measure of 3 ml of blood was collected from each patient dispensed into bottles containing dipotassium salt of ethylenediamine tetraacetic acid (K2-EDTA) at a concentration of 1.5 mg/ml of blood and used for total, differential white cell count and packed cell volume (PCV).

Sputum for tuberculosis diagnosis

Two sputum samples (consisting of one spot sample and one early morning sample) were collected in a wide-mouth container from the patients is required for AFB test as well as for the automated GeneXpert MTB/RIF real-time nucleic acid amplification test for rapid and simultaneous detection of TB and RIF resistance.

Methods of sample analysis

Ziehl–Neelsen technique for Mycobacterium tuberculosis diagnosis

A piece of clean stick was used to transfer and spread sputum materials evenly covering an area of about 15–20 mm diameter on a glass slide. The smear was air-dried and labeled. The slide with the smear uppermost was rapidly passed three times through the flame of a Bunsen burner and allowed to cool. The slide containing the smear was placed on a slide rack and the smear covered with Carbol fuchsin stain. The stain was heated until vapor just begins to rise. The heated stain was allowed to remain on the slide for 5 min. The stain was washed off with clean water and then covered with 3% v/v acid alcohol for 5 min or until the smear is sufficiently decolorized, that is pale pink. The slide was washed off with clean water. The smear was covered with methylene blue stain for 1–2 min and then washed off with clean water. The back of the slide was wiped clean and placed in a draining rack for the smear to air-dry. The smear was examined microscopically using the ×100 oil immersion objective. Scanning of the smear was done systematically and when any definite red bacillus is seen, it was reported as AFB positive. AFB appear as red, straight, or as slightly curved rods, occurring singly or in small groups. Cells and background material appear blue.

GeneXpert method for detection of Mycobacterium tuberculosis and rifampicin resistance (GeneXpert Mycobacterium tuberculosis/rifampicin)

The assay consists of a single-use multichambered plastic cartridge preloaded with liquid buffers and lyophilized reagent beads necessary for sample processing. DNA extraction and heminested real-time PCR were done. Sputum samples were treated with the sample reagent (containing NaOH and isopropanol). The sample reagent was added in the ratio of 2 : 1 to the sputum sample and the closed specimen container was manually agitated twice during 15 min of incubation at room temperature. Two milliliters of the treated sample was transferred into the test cartridge; the cartridge was loaded into the GeneXpert instrument and an automatic step will complete the remaining assay steps. The assay cartridge also contained lyophilized Bacillus globigii spores which served as an internal sample processing and PCR control. The spores were automatically resuspended and processed during the sample processing step and the resulting B. globigii DNA was amplified during the PCR step. The standard user interface indicates the presence or absence of MTB, the presence or absence of RIF resistance, and a semiquantitative estimate of MTB concentration (high, medium, low, and very low). Assays that are negative for MTB and also negative for B. globigii internal control was reported as invalid.

Total white cell count as described by Lewis et al. [18].

A 1 : 20 dilution of well–mixed EDTA blood was made by adding 20 μl of blood to 0.38 ml of Turks solution in a small glass tube. The tube was corked and the diluted blood sample mixed. Using a capillary tube the chamber was loaded with the sample. Precaution was taken not to overfill the chamber. The chamber was left undisturbed for 2 min to allow the white cells to settle. Using ×40 objective, the cells in the four large corners were counted.

The number of white cells obtained was reported after using the calculation

Total number of cells counted×dilution factor×106.

Area×depth (volume) counted.

Differential white cell count as described by Lewis et al. [18].

Thin blood films were made from EDTA anticoagulated blood. The air-dried slides were covered with Leishman stain using a dropper and was left for 3 min. Twice the volume of pH 6.8 buffered water was added and allowed to further stain for 10 min. The stain was washed off; the back of the slide wiped clean and was placed on a draining rack to dry. Using oil immersion, the slide was viewed and white cells differentiated and counted.

Statistical analysis

The Statistical Package for the Social Sciences (IBM SPSS Inc., Illinois, Chicago, USA), version 22 was used in the statistical analysis. Data were expressed as mean±SD. Comparison of multiple repeated measurements (at pretreatment, 2 months, and 6 months) was carried out using the one way repeated measures analysis of variance. P values less than 0.05 were considered statistically significant.


  Results Top


[Table 1] shows that there was a significant decrease in total white cell count (×109/l) after 2 months (5.41±1.61) and 6 months TB treatment (6.59±2.61) compared with the pretreatment value (10.27±4.94) (P<0.05) and a significant increase below the pretreatment value after 6-month treatment when compared with 2 months (P<0.05). Similarly, there was a significant decrease in NLR after 2-month TB treatment (1.26±0.33) and 6-month treatment (1.32±0.41) compared with the pretreatment values (1.67±0.79) (P<0.05), but no significant difference at 6 months compared with 2 months (P>0.05). Also, there was a significant decrease in MLR after 2-month TB therapy (0.08±0.04) and 6-month treatment (0.08±0.06) compared with the pretreatment value (0.11±0.08) (P<0.05), but no significant difference at 6 months compared with 2 months (P>0.05). However, there was a significant increase in PCV (l/l) after 2 months of TB treatment (0.36±0.05) compared with the pretreatment value (0.33±0.05) (P<0.05) and a significant decrease after 6 months of treatment (0.31±0.06) compared with 2 months of treatment (P<0.05), but no significant difference was observed at 6 months compared with the pretreatment (P>0.05).
Table 1 Comparison of mean values of parameters at pretreatment, after 2-months and 6-months of tuberculosis treatment

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[Table 2] shows a significant decrease in absolute neutrophil count (×109/l) after 2 months of TB treatment (2.87±0.97) and 6 months of treatment (3.54±1.54) compared with the pretreatment value (6.11±3.62) (P<0.05) and a slight, but significance increase after 6 months of therapy compared with the value after 2 months of therapy (P<0.05). Similarly, the mean absolute lymphocyte count (×109/l) decreased significantly after 2 months of TB treatment (2.39±0.85) and 6 months of treatment (2.68±1.07) when compared with the pretreatment value (3.73±1.90) (P<0.05), but there was no significant different after 6 months of treatment when compared with the value after 2 months of treatment (P>0.05). Also, there was a significant decrease in absolute monocyte count (×109/l) after 2 months of TB therapy (0.17± 0.09) and 6 months of therapy (0.20±0.14) compared with the pretreatment value (0.38±0.28) (P<0.05). However, no significant difference was observed after 6 months of therapy when compared with the value after 2 months of therapy (P>0.05). Moreover, there was a statistically significant decrease in absolute eosinophil count (×109/l) after 2 months of TB therapy (0.03±0.01) compared with the pretreatment value (0.06±0.02) (P<0.05), and a significant increase after 6 months of therapy (0.06±0.02) when compared with the value after 2 months of treatment (P<0.05). But there was no significant difference after 6 months of treatment when compared with the value at pretreatment (P>0.05).
Table 2 Comparison of mean values of white cell parameters at pretreatment, after 2 months and 6 months of tuberculosis treatment

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  Discussion Top


The NLR is a convenient marker of inflammation because it is a readily calculable laboratory marker used to evaluate systemic inflammation [13]. This explains the significantly higher NLR at pretreatment obtained in this study since TB infection is marked by inflammation. The laboratory and clinical utility of NLR has been established in various studies. de Jager et al [19] demonstrated that NLR was superior to C-reactive protein level, WBC, and neutrophil counts for predicting bacteremia in an emergency care unit. Yoon et al. [13] also discovered that the NLR has a stronger discriminative power for predicting bacteremia compared with neutrophilia or lymphocytopenia alone. The significant decrease observed after 2-month and 6-month treatment agrees with the findings of Iqbal et al. [7] of a significant decrease in NLR in patients undergoing treatment because neutrophilia and lymphopenia improves with settlement of inflammation and appropriate treatment. According to Ayed et al. [20], the peripheral blood NLR has been reported to correlate with the prognosis of many acute or chronic infectious diseases. This was confirmed in their study in which the mean value of NLR was significantly higher in the poor prognosis group. They concluded that high NLR was an independent risk factor for predicting poor prognosis in extrapulmonary TB patients. Drawing from their conclusion, the implication of the finding in our study of a decrease in NLR after 2-month and 6-month treatment shows a good prognosis for TB patients. Thus, the response of the patients to therapy was appropriate as expected.

According to Iqbal et al. [7], MLR gives an index of the relationship of the processes of TB infection to those of resistance because an increase of the monocytes (which are target cells for mycobacterial proliferation) is an index of dissemination of the disease and the increase of lymphocytes (which provide resistance to the spread of infection causing mycobacterial clearance) is an index of resistance. This implies that MLR is high when the disease is active and normal or low when the patient had good combative powers. This makes it a good prognostic tool in TB infection [5]. This study shows a significant increase in MLR at pretreatment when the infection was at its peak. There was also a significant decline after 2 months of treatment and the decrease continued after 6 months of treatment showing a good response to therapy. This finding agrees with that of Iqbal et al. [7]. They found that the MLR significantly decreased after the initiation phase and 2 months of maintenance phase of treatment from the baseline value. They concluded that TB is associated with increased MLR, which declines and returns to normal with antituberculous therapy. Manna et al. [16] also came up with a similar finding. They discovered that patients with active TB disease had a very high MLR, as compared with cured TB patients and additional analysis showed that the MLR value decreased close to the normal range after antimycobacterial therapy. It can be concluded from our finding in relation to previous similar findings that MLR can be considered as an independent prognostic marker and a reliable tool to evaluate treatment success in TB infection.

According to Yoon et al. [13], the physiological immune responses of circulating leukocytes to various stressful events and inflammation are characterized by an increased neutrophil count and decreased lymphocyte count and an increase in total white blood cell (TWBC) particularly when caused by a bacterial infection. This generally agrees with the findings of this study at pretreatment except in the lymphocyte count where a significant increase was found as well. The TWBC counts at pretreatment, after 2 months and 6 months of treatment in this study were within the reference range. This agrees with the findings of Iqbal et al. [21]. However, a statistically significant higher TWBC was observed at pretreatment compared with the value after 2 months and 6 months of treatment. This agrees with that of Veenstra et al. [6] who posited that this increase in total leukocyte count resulted from an immune reaction taking place in response to foreign antigen (TB), resulting in increased cytokine levels which they suggested caused further proliferation of WBCs. Veenstra et al. [6] also found a decreased TWBC with treatment, which aligns with the finding of a significant decrease after 2 months and 6 months of therapy compared with the value at pretreatment in this study. This response of TWBC with treatment could point to its possible utility as a surrogate marker of treatment response in TB patients.

This study found that the value of neutrophil count was higher at pretreatment. The first line of defense against any foreign organism is innate immunity characterized by phagocytosis mediated by neutrophils and macrophages and the neutrophils play a vital role in granuloma formation that characterizes TB disease [4]. Iqbal et al. [21] corroborated this by stating that innate immune response of the body against the antigen (TB) could result in an elevated neutrophil count. Rekha et al. [22] and Kashinkunti [23] also stated that neutrophilia is generally seen in the acute phase of TB infection. These may explain the significantly higher neutrophil count observed at pretreatment. Similarly, this finding also agrees with the Iqbal et al. [21] study which reported a significant neutrophilia (increase in neutrophils) that improved (decreased) with treatment, which aligns with the significant decrease observed in our study after 2 months and 6 months of treatment. The significant decrease that started after 2 months of treatment could be as a result of decreased production due to therapy, bone marrow invasion, or malnutrition in TB patients that may result in decreased hematopoiesis. Whatever was the reason for the decrease after 2 months of treatment the condition obviously improved by the sixth month, thus the significant increase after 6 months of treatment compared with the value after 2 months.

The finding of our study showed a significant higher absolute lymphocyte count at pretreatment followed by a significant decline after 2 months and 6 months of treatment. Previous studies have reported conflicting findings on lymphocyte count in TB patients, some research findings reported an increase in lymphocyte count and others a decrease in lymphocyte count with return to normal values with therapy [6],[8],[24]. Iqbal et al. [21] reported lymphopenia in half (50%) of the patients at the time of diagnosis which later improved with initial treatment and Veenstra et al. [6] found that absolute lymphocyte count of patients at diagnosis was significantly depressed at diagnosis, but counts were no longer significantly decreased at the end of treatment. Both of these disagree with the findings of this study in which there was an increase at pretreatment that decreased after 2 months and 6 months of treatment. This decrease observed in this study may be due to the accumulation of lymphocytes at the site of infection leading to a decreased number in peripheral blood as posited by Djoba et al. [25]. It may also have a link to the therapy administered at 2 months (initiation phase) and 6 months (continuation phase).

According to Naranbhai et al. [14], monocytes/macrophages are one of the major effector cells in protecting the host against MTB infection. They are central mediators of the immune response and inflammatory stimuli mainly affect the numbers of monocytes in the peripheral blood [5]. The finding of a significantly higher monocyte count in this study at pretreatment is in line with the findings of Veenstra et al. [6] that TB infection causes monocytosis which then settles as the infection resolves. This increase in monocytes commonly seen in TB infection is because the microorganism is engulfed by alveolar macrophages after entering the body, but some evade the defense mechanism resulting in infection that leads to the production of chemoattractant substances that mobilize other leukocytes and unopposed production of monocytes. The decrease in monocyte count in this study after 2 months and 6 months of treatment is also in line with the significantly decreased level observed at the end of treatment by Veenstra et al. [6] after a significantly elevated level at diagnosis. Although Veenstra et al. [6] stated that monocytes are important components of the innate immune response to mycobacterial infection, the cause of the significant decrease in treated patients is unknown. We posit that the cause of the decrease that started after 2 months of treatment could be the anti-TB therapy. However, according to Iqbal et al. [21], it may be due to malnutrition because TB is a disease that affects those from low socioeconomic society that prevails more in poor and malnourished individuals. According to França et al. [26], malnutrition leads to inappropriate and altered immunological response that results in altered monocyte production and differentiation. The application of this assertion fully to the findings of this study is doubtful since the monocyte count was higher at pretreatment.

Though it is a common knowledge that eosinophils play a major role in parasitic infections of which TB is not one, according to Tocheny et al. [27] eosinophils have comparable phagocytic function to neutrophils and an overlapping repertoire of granular contents capable of limiting bacterial growth. This may explain the similar pattern of response we found in neutrophils and eosinophils in our study. The significant higher eosinophils at pretreatment may also be relative to the findings of Tocheny et al. [27] that MTB directly affects eosinophil degranulation, and eosinophils are able to contribute to MTB-driven inflammation. They also reported that eosinophils are being actively recruited to the lung in response to MTB in vivo. This may suggest that the decrease observed after 2 months of therapy may be due to this mobilization of eosinophils to the lungs away from the peripheral circulation. The decrease may also be due to the chemotherapeutic effects of the initiation phase drugs. However, the significant increase after 6 months of treatment implies that the cause of the decrease in the second month did not continue till the sixth month.This study showed a significantly lower PCV at pretreatment compared with the value after 2 months of treatment. Although there was no obvious anemia, the finding of a decreased PCV is supported by the report that anemia is one of the most common findings seen in TB patients and is considered to be responsible for poor prognosis [28]. According to Iqbal et al. [21], more than three-fourth of TB patients present with normocytic normochromic or iron-deficiency anemia. Iron-deficiency anemia that decreases host capacity in defending against foreign antigen resulting in impaired immune response is the most seen in TB patients [29]. Iron is a growth factor required by MTB for growth and survival, which prevents the release of iron from the reticuloendothelial system and due to reduced/nonavailability of iron to the bone marrow, there is reduced erythropoiesis resulting in anemia. Lee et al. [30] reported suppression of erythropoietin secretion under the effect of inflammatory mediators in TB patients. The significant increase in PCV observed after 2 months of treatment may be explained by the findings of Iqbal et al. [21] that with effective therapy, anemia improved in TB patients after the completion of initiation phase of therapy. Similarly, the decline after 6 months of treatment may suggest that the continuation phase therapy may have a suppressing effect on erythropoiesis in line with the findings of Oyer and Schlossberd [31] that pharmacological agents (drugs) used for TB treatment may cause hematological changes.


  Conclusion and recommendations Top


TB infection is marked by an initial increase in white cell parameters (TWBC count, neutrophil count, lymphocyte count, monocyte count, eosinophil count, NLR, and MLR) in TB patients after infection (before initiation of therapy) that decreases with anti-TB treatment. This implies that they could be a good prognostic index in TB patients. It is therefore recommended that white cell parameters especially NLR and MLR should be considered for prognostic monitoring of TB treatment, especially since they are affordable, cost effective, and routinely assessed parameters.

Also, PCV is increased by the initiation phase therapy and decreased by the continuation phase therapy. Thus, iron supplements may be required during the continuation phase (3–6 months) of anti-TB therapy because of the decrease in PCV observed.

Acknowledgements

Management of Mile-Four Hospital Abakaliki Ebonyi State, Nigeria, Sct Ogamde Sunday and Mr Elias Ekpe research assistants that played a role in sample collection and separation and administration of questionnaires.

This study was carried out in collaboration between all authors. Chizoba O. Okeke, Grace I. Amilo, Martin O. Ifeanyichukwu played a major part in the design and conception of the study. Ejeatuluchukwu O. Obi also contributed to the conception of the study. All authors contributed to the experimental process, data acquisition, and interpretation. Chizoba O. Okeke wrote the protocol and the first draft of the manuscript, managed the literature searches, and Chizoba O. Okeke and Martin O. Ifeanyichukwu managed the statistical analysis. All authors revised and approved the final manuscript.

Financial support and sponsorship

Grant for this research was provided by the Tertiary Education Trust Fund (TETFUND), Nigeria.

Conflicts of interest

There are no conflicts of interest.



 
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