<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">OJNeph</journal-id><journal-title-group><journal-title>Open Journal of Nephrology</journal-title></journal-title-group><issn pub-type="epub">2164-2842</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ojneph.2020.102008</article-id><article-id pub-id-type="publisher-id">OJNeph-99340</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Hematological Disorders during Chronic Kidney Disease Stages 3 to 5 Non-Dialysed in Cameroon
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Francois</surname><given-names>Folefack Kaze</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mathurin</surname><given-names>Pierre Kowo</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Irene</surname><given-names>Nintcheu Wagou</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mahamat</surname><given-names>Maimouna</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hermine</surname><given-names>Danielle Menye Ebana Fouda</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Marie</surname><given-names>Patrice Halle</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Department of Internal Medicine and Specialties, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, 
Yaoundé, Cameroon</addr-line></aff><aff id="aff2"><addr-line>Higher Institute of Health Sciences, Bangangté, Cameroon</addr-line></aff><aff id="aff3"><addr-line>Department of Clinical Sciences, Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon</addr-line></aff><pub-date pub-type="epub"><day>02</day><month>04</month><year>2020</year></pub-date><volume>10</volume><issue>02</issue><fpage>61</fpage><lpage>72</lpage><history><date date-type="received"><day>5,</day>	<month>March</month>	<year>2020</year></date><date date-type="rev-recd"><day>31,</day>	<month>March</month>	<year>2020</year>	</date><date date-type="accepted"><day>3,</day>	<month>April</month>	<year>2020</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Introduction: Haematological disorders are common complications of chronic kidney disease (CKD) leading by anemia which increase with the severity of the disease. Objective: Assess the haematological profile of CKD patients stages 3 to 5 non-dialysed seen at the first nephrology consultation in Cameroon. 
  Patients and Methods: A hospital-based cross-sectional study was conducted from February to July 2018 at the nephrology unit of the Yaounde University Teaching Hospital and Douala General Hospital. All adults’ (≥18 years old) patients who provided a written informed consent and attended their first nephrology consultation with a nephrologist diagnosis of CKD stages 3 to 5 non-dialysed were included. Clinical and paraclinical data (serum creatinine, full blood count, reticulocytes count, iron status, vitamin B12 and folates count, and bleeding time) were collected. Parametric, non-parametric and correlations tests were used to compare variables. 
  Results: We included 105 (59% males) participants with a mean age of 55.2 &#177; 13.6 years divided into 20 (19%), 36 (34.3%) and 49 (46.7%) respectively in stage G3, G4 and G5 of CKD. The profile of hematological abnormalities was anemia (86.7%), leucopenia (15.2%), hyperleucocytosis (6.7%), thrombopenia (23.8%), thrombocytosis (3.8%) and prolonged bleeding time (13.3%) without any association with the stage of CKD (p &gt; 0.05). The pattern of anemia was mainly normocytic and normochromic (59.3%) and aregenerative (92.3%) with iron deficiency found in 23 (21.9%) participants. There was no case of vitamin B12 and folates deficiency. Prolonged bleeding time was observed in 14 (13.3%) participants with a weak correlation between platelets count and bleeding time (r = 0.122). 
  Conclusion: We observed that aregenerative normocytic normochromic anemia is the leading haematological abnormality during CKD in this setting. None of the full blood count parameters was associated with CKD stages and there was a week correlation between bleeding time and platelet count.
 
</p></abstract><kwd-group><kwd>Hematologic Disorders</kwd><kwd> Chronic Kidney Disease</kwd><kwd> Cameroon</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Chronic kidney disease (CKD) is a worldwide public health problem with 8% to 10% prevalence in adult population [<xref ref-type="bibr" rid="scirp.99340-ref1">1</xref>]. CKD is highly prevalent in Africa affecting 15.8% of adults overall and 10% to 14.2% in Cameroon [<xref ref-type="bibr" rid="scirp.99340-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref4">4</xref>]. Haematological disorders are among complications of CKD which increase with the severity of the disease [<xref ref-type="bibr" rid="scirp.99340-ref5">5</xref>]. Anemia is the most common haematological complication of CKD with increasing prevalence associated to the progressive decline of glomerular filtration rate (GFR) [<xref ref-type="bibr" rid="scirp.99340-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref8">8</xref>]. It’s a predictor of all cause and cardiovascular morbi-mortality as well as reduction of quality of life [<xref ref-type="bibr" rid="scirp.99340-ref9">9</xref>]. The occurrence of anemia during CKD is multifactorial involving uremic and context specific factors. Despite the reduction of endogenous production of erythropoietin as a main pathophysiological factor of anemia, other contributing factors include deficiency in iron, B12 vitamins and folates, shortened red blood cell lifespan, blood loss, “uremic environment”, hyperparathyroidism, inflammation, aluminum toxicity and hypothyroidism [<xref ref-type="bibr" rid="scirp.99340-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref11">11</xref>]. Moreover, Sub-Saharan Africa (SSA) specific factors like nutritional deficiencies, hemoglobinopathies and infectious diseases contribute to the burden of anemia and the pattern modification in this setting [<xref ref-type="bibr" rid="scirp.99340-ref6">6</xref>]. CKD is associated with malnutrition, inflammation and atherosclerosis which can explain the modification of the total and differential white blood cell count [<xref ref-type="bibr" rid="scirp.99340-ref12">12</xref>]; this modification leads to the suggested use of the ratio of neutrophil-to-lymphocyte count as an alternative to measure inflammation in CKD patients [<xref ref-type="bibr" rid="scirp.99340-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref14">14</xref>]. The progression of CKD is associated with bleeding which is unrelated to platelet count; it is more linked to platelet reactivity which is best explored by bleeding time [<xref ref-type="bibr" rid="scirp.99340-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref16">16</xref>].</p><p>A study in our setting in patients on maintenance hemodialysis revealed that 79% had anemia at baseline which was predominantly microcytic and hypochromic in 43% of them [<xref ref-type="bibr" rid="scirp.99340-ref17">17</xref>]. We therefore undertook this study aiming to assess the hematological profile of CKD patients seen at the first nephrology consultation in two referral hospitals of Cameroon.</p></sec><sec id="s2"><title>2. Patients and Methods</title><sec id="s2_1"><title>2.1. Study Design and Setting</title><p>This was a hospital-based cross-sectional study of 6-month duration (February to July 2018), conducted at the nephrology unit of the Yaounde University teaching hospital (YUTH) and the Douala General Hospital (DGH) which are two tertiary hospitals in the Cameroon. This study received administrative authorization from the YUTH and DGH, and was approved by the ethic committee of the Higher Institute of Health Sciences, Bangangt&#233;, Cameroon.</p></sec><sec id="s2_2"><title>2.2. Data Collection</title><p>Final year undergraduate medical student collected consecutively data of all adults’ (≥18 years old) patients who provided a written informed consent and attended their first nephrology consultation with a nephrologist diagnosis of CKD stage 3 to 5 non-dialysed. We excluded patients with active bleeding, history of blood transfusion within 3 months of enrolment, and on oral iron, erythropoietin stimulating agents, anticoagulant and antiplatelet therapy. We used data entry form to collect during face-to-face interview patient’s information’s. Socio-demographic characteristics include age, gender and employment status. Clinical data were baseline nephropathy, comorbidities, weight, height, blood pressure and capillary glucose measurements. Blood samples were collected for serum creatinine, full blood count, reticulocytes count, iron status, vitamin B12 and folates count, and bleeding time. Full blood count includes red blood cell, white blood cell, platelet, haemoglobin, haematocrit, mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH) and MCH concentration (MCHC) whereas iron status was assess with serum iron, serum ferritin and transferrin saturation (TSAT).</p></sec><sec id="s2_3"><title>2.3. Definitions and Calculations</title><p>We calculated the body mass index (BMI, kg/m<sup>2</sup>) as weight (kg)/height (m) * height (m), and ranked participants as normal weight for 20 ≤ BMI &lt; 25 kg/m<sup>2</sup>, overweight for 25 ≤ BMI &lt; 30 kg/m<sup>2</sup> or obese for BMI ≥ 30 kg/m<sup>2</sup>. Hypertension was diagnosed in the presence of systolic (SBP) ≥ 140 mmHg and/or a diastolic blood pressure (DBP) ≥ 90 mmHg on two consecutive occasions two weeks apart, or ongoing use of BP lowering medications. Diabetes mellitus was defined as repeated fasting glycemia ≥ 126 mg/dl or use of glucose control agents. Estimated glomerular ﬁltration rate (eGFR, mL/min) was based on the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) equation [<xref ref-type="bibr" rid="scirp.99340-ref18">18</xref>]. Serum creatinine from Jaffe reaction (SCr<sub>Jaffe</sub>) was converted to standardized serum creatinine (SCr<sub>Standardized</sub>) to be used in CKD-EPI formula, via the formula SCr<sub>Standardized</sub> = 0.95 * SCr<sub>Jaffe</sub> − 0.10 [<xref ref-type="bibr" rid="scirp.99340-ref19">19</xref>]. Kidney Disease: Improving Global Outcomes (KDIGO) guidelines were used to classified CKD into G3 (eGFR: 30 - 59); G4 (eGFR: 15 - 29) and G5 (eGFR &lt; 15) [<xref ref-type="bibr" rid="scirp.99340-ref20">20</xref>]. For the purpose of the study, anemia was defined by haemoglobin level &lt; 13.5 g/dL for men and &lt;12 g/dL for women. Microcytosis and macrocytosis were defined respectively by MCV &lt; 80 and &gt;100 fl. Hypochromia and normochromia were defined by MCH &lt; 27 and ≥27 pg respectively. Anemia was regenerative and aregenerative when reticulocytes count was respectively above and less than 120,000/mm<sup>3</sup>. Absolute iron deficiency was defined as TSAT &lt; 20% and serum ferritin &lt; 100 ng/mL while functional iron deficiency was defined as TSAT &lt; 20% and serum ferritin &gt; 100 ng/mL. Vitamine B12 deficiency was defined by a serum level &lt; 150 ng/L whereas hypervitaminose B12 was &gt;950 ng/L. Folates deficiency was serum level &lt; 5 &#181;g/L and high when &gt;15 &#181;g/L. Hyperleucocytosis referred to WBC ≥ 10,000/mm<sup>3</sup> whereas leucopenia was WBC ≤ 4000/mm<sup>3</sup>. Thrombocytosis was defined as platelet count ≥ 450,000/mm<sup>3</sup> while thrombopenia was platelet count ≤ 150,000/mm<sup>3</sup>. Bleeding time was prolonged when &gt;5 minutes.</p></sec><sec id="s2_4"><title>2.4. Statistical Analysis</title><p>Statistical analysis was performed using the SPSS&#174; version 18 software for Windows (SPSS, Chicago, IL, USA). Means and standard deviations and percentages were used to express results. Chi-square test and equivalents, and Student t-test and non-parametric equivalents were used to compare qualitative and quantitative variables. Correlation between variables was performed using the Pearson and Spearman’s correlation tests. The level of significance was set at p &lt; 0.05.</p></sec></sec><sec id="s3"><title>3. Results</title><p>Characteristics of study population</p><p>As presented in <xref ref-type="table" rid="table1">Table 1</xref>, we included 105 participants with a mean age of 55.2 &#177; 13.6 years, 62 (59%) men and 53 (50.5%) overweight/obese; they were divided into 20 (19%), 36 (34.3%) and 49 (46.7%) respectively in stage G3, G4 and G5 of CKD. Hypertension (47.6%) and Diabetes (31.4%) were the leading baseline nephropathy as shown in <xref ref-type="fig" rid="fig1">Figure 1</xref>. Asthenia (69.5%), dizziness (58.1%) and palor (42.8%) were the main clinical signs reported in participants, <xref ref-type="fig" rid="fig2">Figure 2</xref>.</p><p>Distribution of hematoligical parameters</p><p>The haematologic parameters of study population are presented in <xref ref-type="table" rid="table2">Table 2</xref>. As shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>, anemia was the main haematological abnormality observed</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Socio-demographic and clinical characteristics of study population</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >N (%)</th></tr></thead><tr><td align="center" valign="middle" >Total</td><td align="center" valign="middle" >105 (100)</td></tr><tr><td align="center" valign="middle" >Mean age &#177; SD (years)</td><td align="center" valign="middle" >55.2 &#177; 13.6</td></tr><tr><td align="center" valign="middle" >Sex</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >43 (41)</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >62 (59)</td></tr><tr><td align="center" valign="middle" >Employment</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >45 (42.9)</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >60 (57.1)</td></tr><tr><td align="center" valign="middle" >GFR categories</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >G3</td><td align="center" valign="middle" >20 (19)</td></tr><tr><td align="center" valign="middle" >G4</td><td align="center" valign="middle" >36 (34.3)</td></tr><tr><td align="center" valign="middle" >G5</td><td align="center" valign="middle" >49 (46.7)</td></tr><tr><td align="center" valign="middle" >Comorbidities</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hypertension</td><td align="center" valign="middle" >86 (81.9)</td></tr><tr><td align="center" valign="middle" >Diabetes</td><td align="center" valign="middle" >37 (35.2)</td></tr><tr><td align="center" valign="middle" >Gout</td><td align="center" valign="middle" >19 (18.1)</td></tr><tr><td align="center" valign="middle" >HCV infection</td><td align="center" valign="middle" >11 (10.5)</td></tr><tr><td align="center" valign="middle" >HBV infection</td><td align="center" valign="middle" >4 (3.8)</td></tr><tr><td align="center" valign="middle" >HIV infection</td><td align="center" valign="middle" >4 (3.8)</td></tr><tr><td align="center" valign="middle" >Mean BMI &#177; SD (kg/m<sup>2</sup>)</td><td align="center" valign="middle" >25.9 &#177; 5.1</td></tr><tr><td align="center" valign="middle" >Overweight</td><td align="center" valign="middle" >34 (32.4)</td></tr><tr><td align="center" valign="middle" >Obese</td><td align="center" valign="middle" >20 (19)</td></tr><tr><td align="center" valign="middle" >Mean SBP &#177; SD (mmHg)</td><td align="center" valign="middle" >155.6 &#177; 25.9</td></tr><tr><td align="center" valign="middle" >Mean DBP &#177; SD (mmHg)</td><td align="center" valign="middle" >89.9 &#177; 15.1</td></tr><tr><td align="center" valign="middle" >Uncontrolled hypertension</td><td align="center" valign="middle" >74 (70.5)</td></tr><tr><td align="center" valign="middle" >Mean glycemia &#177; SD (mg/dl)</td><td align="center" valign="middle" >144 &#177; 23.5</td></tr><tr><td align="center" valign="middle" >Uncontrolled glycemia</td><td align="center" valign="middle" >21 (56.7)</td></tr></tbody></table></table-wrap><p>BMI—body mass index; DBP—diastolic blood pressure; GFR—glomerular filtration rate; HBV—hepatitis B virus; HCV—hepatitis C virus; HIV—human immunodeficiency virus; SBP—systolic blood pressure; SD—standard deviation.</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Haematological parameters of study population</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Parameters</th><th align="center" valign="middle" >Mean (standard deviation)</th></tr></thead><tr><td align="center" valign="middle" >RBC (&#215;10<sup>12</sup>/L)</td><td align="center" valign="middle" >3.5 (0.8)</td></tr><tr><td align="center" valign="middle" >Haematocrit (%)</td><td align="center" valign="middle" >28 (6)</td></tr><tr><td align="center" valign="middle" >Haemoglobin (g/dL)</td><td align="center" valign="middle" >9.4 (2.3)</td></tr><tr><td align="center" valign="middle" >MCV (fl)</td><td align="center" valign="middle" >82 (9)</td></tr><tr><td align="center" valign="middle" >MCH (pg)</td><td align="center" valign="middle" >26 (3)</td></tr><tr><td align="center" valign="middle" >MCHC (g/dL)</td><td align="center" valign="middle" >29 (4)</td></tr><tr><td align="center" valign="middle" >Reticulocytes (10<sup>9</sup>/L)</td><td align="center" valign="middle" >53 (11)</td></tr><tr><td align="center" valign="middle" >Serum iron (mmol/L)</td><td align="center" valign="middle" >12.3 (4.3)</td></tr><tr><td align="center" valign="middle" >Serum ferritin (ng/L)</td><td align="center" valign="middle" >342.6 (98.1)</td></tr><tr><td align="center" valign="middle" >TSAT (%)</td><td align="center" valign="middle" >25.6 (6.5)</td></tr><tr><td align="center" valign="middle" >Vitamine B12 (ng/L)</td><td align="center" valign="middle" >769.2 (265.6)</td></tr><tr><td align="center" valign="middle" >Folates (&#181;g/L)</td><td align="center" valign="middle" >11.1 (2.2)</td></tr><tr><td align="center" valign="middle" >WBC (&#215;10<sup>9</sup>/L)</td><td align="center" valign="middle" >5.9 (2.3)</td></tr><tr><td align="center" valign="middle" >Platelets (&#215;10<sup>9</sup>/L)</td><td align="center" valign="middle" >215.6 (61.2)</td></tr><tr><td align="center" valign="middle" >Bleeding time (minutes)</td><td align="center" valign="middle" >3.7 (1.1)</td></tr></tbody></table></table-wrap><p>MCH—mean corpuscular haemoglobin; MCHC—mean corpuscular haemoglobin concentration; MCV—mean corpuscular volume; RBC—Red blood cell; TSAT—transferrin saturation coefficient; WBC—White blood cell.</p><p>in 91 (86.7%) participants. His prevalence increases with the progression of CKD with 75% in G3, 83.3% in G4 and 93.9% in G5 without statistical significance among GFR categories of CKD (p &gt; 0.05). The patterns of anemia presented in <xref ref-type="fig" rid="fig4">Figure 4</xref> revealed that it was mainly normocytic and normochromic in 54 (59.3%) patients and aregenerative in 84 (92.3%) of them. Only anemic participants had iron deficiency found in 23 (21.9%) participants. Absolute and functional iron deficiency was observed in 13 (56.5%) and 10 (43.5%) participants</p><p>respectively. None of the participants have vitamin B12 deficiency while 71 (67.6%) patients had hypervitamin B12. Folates levels were within normal limits.</p><p>Leucopenia was present in 16 (15.2%) participants while hyperleucocytosis was observed in 7 (6.7%), <xref ref-type="fig" rid="fig4">Figure 4</xref>. Leucopenia was observed 5 (31.2%), 6 (37.5%) and 5(31.2%) participants respectively in G3, G4 and G5 of CKD GFR categories without statistically significance difference (p &gt; 0.05). Equivalents figures for hyperleucocytosis were 2 (28.6%), 3 (42.8%) and 2 (28.6%) participants respectively in G3, G4 and G5 of CKD GFR categories (p &gt; 0.05).</p><p>There was thrombopenia and thrombocytosis in 25 (23.8%) and 4 (3.8%) participants respectively, <xref ref-type="fig" rid="fig4">Figure 4</xref>. The prevalence of thrombopenia increased with the severity of CKD in 6 (24%), 8 (32%) and 11(44%) participants respectively in CKD G3, G4 and G5 without statistical significance with CKD GFR categories (p &gt; 0.05). Equivalents figures were 2 (50%), 1 (25%) and 1 (25%) for thrombocytosis (p &gt; 0.05).</p><p>Prolonged bleeding time was observed in 14 (13.3%) participants divided into 4 (28.6%), 4 (28.6%) 6 (42.8%) respectively for G3, G4 and G5 of CKD GFR categories without any statistical significance with the category (p &gt; 0.05). Among participants with prolonged bleeding time, 10 (71.4%) had thrombopenia. There was a weak correlation between platelets count and bleeding time (r = 0.122).</p></sec><sec id="s4"><title>4. Discussion</title><p>This study revealed that anemia was the main hematological abnormality, mainly aregenerative, in nearly 9 out of 10 participants with increase prevalence associated to the CKD progression. Anemia was normocytic and normochronic in nearly 60% of cases with iron deficiency observed in more than one out of five participants. There was no case of vitamin B12 and folates deficiency. Leucopenia was present in 15% and thrombopenia in nearly 1 out of 4 patients. Prolonged bleeding time was observed in 13% with a weak correlation with platelets count and bleeding time.</p><p>The haematological profile observed in this study is closed to similar studies in this setting [<xref ref-type="bibr" rid="scirp.99340-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref21">21</xref>]. There was a high prevalence of anemia increasing with the disease progression in our study similar to previous study in this setting compare to other study which can be explain by context specific factors, higher prevalence of unemployed participants and lack of social security program [<xref ref-type="bibr" rid="scirp.99340-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref17">17</xref>]. The main pattern of anemia was normocytic and normochromic similar to the south African study [<xref ref-type="bibr" rid="scirp.99340-ref8">8</xref>]; this highlight the reduction of erythropoietin secretion as the main pathophysiological factors of anemia in CKD. Microcytic hypochromic pattern was the second most common anemia profile which can be explained by specific factors like nutritional deficiencies, hemoglobinopathies and infectious diseases in this setting [<xref ref-type="bibr" rid="scirp.99340-ref6">6</xref>]. There was a high prevalence of iron deficiency, predominantly absolute, close to previous results in similar setting which can be explain by the high prevalence of hemoglobinopathies and infectious disease in SSA [<xref ref-type="bibr" rid="scirp.99340-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref22">22</xref>]. We did not report any deficiency in vitamin B12 and folates which correlate well with few case of macrocytic anemia; this suggest that complete blood count could be enough to indicate these parameters deficiency in our setting with no social insurance policy and higher prevalence of unemployment hence limitating exhaustive work up.</p><p>We reported a high prevalence of leucopenia compare to hyperleucocytosis without any correlation with CKD progression as reported elsewhere [<xref ref-type="bibr" rid="scirp.99340-ref8">8</xref>]. The hyperleucocytosis could be related to the inflammation which occurs during CKD in the context of malnutrition, inflammation and atherosclerosis syndrome [<xref ref-type="bibr" rid="scirp.99340-ref12">12</xref>]. However, we did not assess the neutrophil/lymphocytes ratio and C reactive protein (CRP) which can permit us to evaluate inflammation in such patients [<xref ref-type="bibr" rid="scirp.99340-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref14">14</xref>]. The predominance of leucopenia could be related to the physiologic conditions in this high risk infectious environment [<xref ref-type="bibr" rid="scirp.99340-ref23">23</xref>].</p><p>Thrombopenia was more prevalent without any correlation with CKD categories as observed in previous studies [<xref ref-type="bibr" rid="scirp.99340-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref22">22</xref>]. There was a weak correlation between platelet count and bleeding time suggesting the platelet reactivity abnormality during CKD [<xref ref-type="bibr" rid="scirp.99340-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.99340-ref16">16</xref>].</p></sec><sec id="s5"><title>5. Strength and Limitations</title><p>The main limitations of this study are the lack of CRP and assessment of neutrophil/lymphocytes ratio which could help to better assess inflammation status. However, this is on our knowledge the only published study in Central Africa assessing haematological profile of CKD patients. It therefore provides lacking data in non-dialysed CKD patients and completes the previous one in patients on maintenance haemodialysis [<xref ref-type="bibr" rid="scirp.99340-ref17">17</xref>].</p></sec><sec id="s6"><title>6. Conclusion</title><p>We observed that aregenerative normocytic normochromic anemia is the leading haematological abnormality during CKD in this setting suggesting the role of nutritional deficiencies, hemoglobinopathies and infectious diseases. None of the full blood count parameters was associated with CKD categories and there was a week correlation between bleeding time and platelet count.</p></sec><sec id="s7"><title>Acknowledgements</title><p>We thank the Yaounde University Teaching Hospital’s and Douala General Hospital’s laboratory technicians.</p></sec><sec id="s8"><title>Ethics Approval and Consent to Participate</title><p>This study received administrative authorization from the Yaounde University Teaching Hospitals, and was approved by the ethic committee of the Higher Institute of Health Sciences, Bangangt&#233;, Cameroon and all participants provided a written informed consent before enrolment.</p></sec><sec id="s9"><title>Consent for Publication</title><p>All authors gave their approval for publication.</p></sec><sec id="s10"><title>Conflicts of Interest</title><p>The authors report no conflicts of interest.</p></sec><sec id="s11"><title>Funding</title><p>The authors did not receive any fund for this study.</p></sec><sec id="s12"><title>Authors’ Contribution Statement</title><p>Study conception—FFK, INW, MPK.</p><p>Clinical data collection and supervision—FFK, INW, MM, MPK.</p><p>Acquisition and validation of the biological data—FFK, HDFME, INW, MM.</p><p>Data analysis—FFK, MPH.</p><p>Data interpretation—FFK, MPH.</p><p>Manuscript drafting—FFK, MPH.</p><p>Critical revision of the manuscript—HDFME, INW, MM, MPK.</p></sec><sec id="s13"><title>Availability of Data and Materials</title><p>Data and materials are available with corresponding author which is the principal investigator. They can be consulted at anytime upon request. However, the ethical clearance and the inform consent form did mention that patient data could be shared to a third party.</p></sec><sec id="s14"><title>Cite this paper</title><p>Kaze, F.F., Kowo, M.P., Wagou, I.N., Maimouna, M., Fouda, H.D.M.E. and Halle, M.P. (2020) Hematological Disorders during Chronic Kidney Disease Stages 3 to 5 Non-Dialysed in Cameroon. Open Journal of Nephrology, 10, 61-72. https://doi.org/10.4236/ojneph.2020.102008</p></sec><sec id="s15"><title>List of Abbreviations</title><p>BMI—Body Mass Index; CKD—Chronic Kidney Disease; CKD-EPI—Chronic Kidney Disease Epidemiology Collaboration; CRP—C Reactive Protein; DBP—Diastolic Blood Pressure; GFR—Glomerular Filtration Rate; HBV—Hepatitis B Virus; HCV—Hepatitis C Virus; HIV—Human Immunodeficiency Virus; KDIGO—Kidney Disease: Improving Global Outcomes; MCH—Mean Corpuscular Haemoglobin; MCHC—Mean Corpuscular Haemoglobin Concentration; MCV—Mean Corpuscular Volume; SBP—Systolic Blood Pressure; TSAT—Transferrin Saturation Coefficient; WBC—White Blood Cell.</p></sec></body><back><ref-list><title>References</title><ref id="scirp.99340-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">World Kidney Day (2020). https://www.worldkidneyday.org/facts/chronic-kidney-disease</mixed-citation></ref><ref id="scirp.99340-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Kaze, A.D., Ilori, T., Jaar, B.G. and Echouffo-Tcheugui, J.B. 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