<?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.2021.112019</article-id><article-id pub-id-type="publisher-id">OJNeph-109436</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>
 
 
  Peripheral Arterial Disease among Patient Undergoing Maintenance Hemodialysis in Dakar (Senegal)
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Habin</surname><given-names>Yabama Aida Lengani</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>Mouhamadou</surname><given-names>Moustapha Cissé</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hamadoun</surname><given-names>Yattara</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Alassane</surname><given-names>Mbaye</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gérard</surname><given-names>Coulibaly</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>Joseph</surname><given-names>Salvador Mingou</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>El</surname><given-names>Hadj Fary Ka</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>Abdou</surname><given-names>Niang</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>Abdoul</surname><given-names>Kane</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Boucar</surname><given-names>Diouf</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff3"><addr-line>Departement of Nephrology, University Hospital of Point G, Bamako, Mali</addr-line></aff><aff id="aff5"><addr-line>Cheikh Anta Diop University, Dakar, Sénégal</addr-line></aff><aff id="aff1"><addr-line>Departement of Nephrology, University Hospital Yalgado Ouédraogo, Ouagadougou, Burkina Faso</addr-line></aff><aff id="aff2"><addr-line>Departement of Nephrology, University Hospital Aristide le Dantec, Dakar, Sénégal</addr-line></aff><aff id="aff4"><addr-line>Departement of Cardiology, National Hospital Grand Yoff, Dakar, Sénégal</addr-line></aff><pub-date pub-type="epub"><day>23</day><month>04</month><year>2021</year></pub-date><volume>11</volume><issue>02</issue><fpage>242</fpage><lpage>251</lpage><history><date date-type="received"><day>26,</day>	<month>February</month>	<year>2021</year></date><date date-type="rev-recd"><day>24,</day>	<month>May</month>	<year>2021</year>	</date><date date-type="accepted"><day>27,</day>	<month>May</month>	<year>2021</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>
 
 
  Background: Peripheral arterial disease (PAD) is common in patients with chronic kidney disease (CKD). It is a surrogate marker of generalized atherosclerosis. In sub-Saharan Africa, PAD remains understudied in CKD. Ankle-brachial index (ABI) is a non-invasive and cost-effective tool to diagnose PAD. 
  Objectives: Our aim was to determine the prevalence and associated risk factors for PAD in hemodialysis patients. 
  Patients and Methods: We conducted a cross-sectional study from July 1 to December 31, 2012 in the department of Nephrology of the University Hospital Aristide le Dantec of Dakar. All consenting patients, aged above 18 years, on hemodialysis for at least 6 months were included. ABI measurements were performed using a handled pulse doppler. PAD was defined as an ABI of &lt;0.9 or the history of surgical revascularization and/or amputation due to vascular disease. The patients were divided into two groups according to the presence or not of PAD. Standard blood tests and anthropometrical parameters were recorded. 
  Results: A total of 53 patients with a mean age of 49.15 &#177; 15.18 were included. The sex ratio was 0.70. Hypertension (83.01%), low HDL-cholesterol (26.41%) and cigarette smoking (20.75%) were the main cardiovascular risk factors. Prevalence of PAD was 47.16%. Among patients with PAD, 52% had no suggestive symptoms. Lower pre-dialysis (p = 0.0384) and post-dialysis (p = 0.0447) diastolic blood pressure (BP) were significantly associated with PAD. The conventional risk factors (tobacco consumption, diabetes, alcohol consumption, dyslipidemia, hypertension, age), iPTH and CRP levels were not correlated with PAD. 
  Conclusion: PAD is common among patients undergoing maintenance hemodialysis in Senegal. Early diagnosis and management of PAD should be routinely performed in CKD patients.
 
</p></abstract><kwd-group><kwd>Ankle Brachial Index</kwd><kwd> Peripheral Arterial Disease</kwd><kwd> Hemodialysis</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Peripheral arterial disease (PAD) refers to stenosis or occlusion of the arteries of the lower limbs. It is a marker of generalized atherosclerosis. PAD is common in patients with chronic kidney disease (CKD) [<xref ref-type="bibr" rid="scirp.109436-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref2">2</xref>]. The high prevalence of traditional cardiovascular risk factors such as hypertension (HTN), diabetes mellitus, tobacco use, dyslipidemia, age and the existence of uremia-related cardiovascular risk factors are responsible for an accelerated atherosclerosis in CKD [<xref ref-type="bibr" rid="scirp.109436-ref1">1</xref>]. Ankle brachial index (ABI) is a simple, non-invasive method to diagnose PAD. In comparison to angiography, the gold standard for detecting atherosclerosis in the lower limbs arteries, low ABI (&lt;0.9) has good sensitivity (between 69% and 79%) and excellent specificity (between 83% to 99%) [<xref ref-type="bibr" rid="scirp.109436-ref3">3</xref>]. PAD is associated with increased cardiovascular and overall morbidity and deaths in the general population and among hemodialysis patients [<xref ref-type="bibr" rid="scirp.109436-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>]. In a study by Ono et al. [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>], the risk for cardiovascular mortality was 5.9-fold higher in dialysis patients with low ABI (&lt;0.9).</p><p>PAD remains one of the least studied atherosclerosis markers. Yet, it is the most common manifestation of atheromatous cardiovascular disease compared to coronary artery disease and ischemic stroke in patients with CKD [<xref ref-type="bibr" rid="scirp.109436-ref6">6</xref>]. ABI testing can help in early detection of PAD and for monitoring PAD’s progression, which may improve patient’s survival. There are little data on PAD in hemodialysis patients in sub-Saharan Africa. The aim of this study was to determine the prevalence of PAD in chronic hemodialysis patients and to study its relationship with some cardiovascular risk factors (CVRF).</p></sec><sec id="s2"><title>2. Patients and Methods</title><sec id="s2_1"><title>2.1. Patients and Study Design</title><p>This cross-sectional study was conducted for 6 months, from 1 July to 31 December 2012, in nephrology department of the University Hospital Aristide Le Dantec (CHU-ALD) of Dakar (Senegal). We included all patients aged 18 and over, on maintenance hemodialysis for at least 6 months, who consent to participate in the study. Subjects who had bilateral amputation of lower limbs, bilateral arteriovenous fistula or with atrial fibrillation were not included [<xref ref-type="bibr" rid="scirp.109436-ref7">7</xref>].</p></sec><sec id="s2_2"><title>2.2. Anthropometry and Blood Pressure</title><p>Socio-demographic characteristics, co-morbid conditions, behavioral measures (smoking history, alcohol consumption), clinical and biological data were noted.</p><p>Current smokers were deﬁned as patients who currently smoked and had smoked more than 100 cigarettes in their lifetimes [<xref ref-type="bibr" rid="scirp.109436-ref8">8</xref>]. Former smokers were defined as patients who smoked more than 100 cigarettes in their lifetimes in the past [<xref ref-type="bibr" rid="scirp.109436-ref8">8</xref>].</p><p>Alcohol drinking was deﬁned as consuming at least one beverage containing alcohol each week over the previous year [<xref ref-type="bibr" rid="scirp.109436-ref8">8</xref>]. Anthropometric measures included weight and height.</p><p>Body mass index (BMI) was calculated by dividing “dry” weight in kilograms by the square of height in meters. Predialysis and postdialysis systolic and diastolic blood pressure (BP) were measured in seated patients by qualified medical staff on the non-carrier arm of the arteriovenous fistula after at least a 5 minutes rest. The systolic BP and diastolic BP considered were the respective calculated average systolic BP and diastolic BP of the month prior to data collection for each patient. Mean arterial pressure (MAP) was calculated based on the formula MAP = diastolic BP + 1/3 (systolic BP - diastolic BP) and the pulse pressure (PP) using the formula PP = systolic BP - diastolic BP. Hypertension (HTN) was defined as systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg, or the current use of antihypertensive medication [<xref ref-type="bibr" rid="scirp.109436-ref8">8</xref>].</p></sec><sec id="s2_3"><title>2.3. Laboratory Parameters</title><p>Blood tests including hemoglobin level, hematocrit, white blood cell counts, serum albumin, urea nitrogen, creatinine, glucose, calcium, phosphate, intact parathyroid hormone (iPTH), sodium, potassium, total cholesterol, high-density lipoprotein cholesterol (HDL-cholesterol), low-density lipoprotein cholesterol (LDL-cholesterol), triglycerides, C reactive protein (CRP)) were performed using standard laboratory methods. The total cholesterol to high-density lipoprotein cholesterol (HDL-C) ratio was calculated.</p><p>Diabetes was defined as fasting glucose ≥ 1.26 g/l or random blood glucose ≥ 2 g/l, and/or the use of insulin or oral hypoglycemic agents [<xref ref-type="bibr" rid="scirp.109436-ref8">8</xref>].</p><p>Blood urea nitrogen measured before hemodialysis session (C<sub>0</sub>) and after hemodialysis session (C<sub>t</sub>) was used to calculate the urea reduction ratio (URR) [<xref ref-type="bibr" rid="scirp.109436-ref9">9</xref>]: URR = (C<sub>0</sub> − C<sub>t</sub>)/C<sub>O</sub>. In hemodialysis patients, URR ≥ 65% and Kt/V ≥ 1.2 indicates adequate minimum HD and URR ≥ 70% and Kt/V ≥ 1.4 indicates adequate optimal HD [<xref ref-type="bibr" rid="scirp.109436-ref9">9</xref>].</p></sec><sec id="s2_4"><title>2.4. ABI Measurement</title><p>ABI measurement was conducted the day after hemodialysis session, by the same trained physician to eliminate interobserver variability. ABI was determined using a sphygmomanometer and a manual Doppler (Hadeco, ES-100V3, Kawasaki, Japan) with an 8 MHz probe. After a rest period of 5 to 15 minutes in the supine position, the patient’s systolic BP was registered in posterior tibial artery and dorsalis pedis artery of the right and left lower limb, and in the brachial artery of the arm without arteriovenous fistula. The sphygmomanometer cuff above the ankle was inflated to 20 mmHg after the disappearance of the Doppler signal, and then deflated very slowly until it reappeared. The value of the pressure in mmHg at the time of the reappearance of the Doppler signal was noted as the systolic pressure of the recorded artery. ABI was calculated by the ratio of the lower value of the ankle systolic pressure divided by the systolic pressure of the arm without the dialysis blood access [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref11">11</xref>].</p><p>ABI was normal when between 0.9 and 1.4 [<xref ref-type="bibr" rid="scirp.109436-ref3">3</xref>]. It was considered low when it was below 0.9 [<xref ref-type="bibr" rid="scirp.109436-ref3">3</xref>]. PAD was defined by the history of surgical revascularization and/or amputation of limb, and/or ABI &lt; 0.9 [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>].</p></sec><sec id="s2_5"><title>2.5. Dialysis Parameters</title><p>The majority of patients underwent their routine hemodialysis sessions 3 times a week using a Fresenius 4008S machine. Each hemodialysis session was performed for 4 hours using a polysulfone dialysis membrane. The flow rate of the dialysate was 500 ml/min and the blood flow was variable (between 250 and 350 mL/min). Anticoagulation of the extracorporeal circuit was performed with low molecular weight heparin for all patients.</p></sec><sec id="s2_6"><title>2.6. Statistical Analysis</title><p>Statistical analyses were performed with SPSS (Statistical Package for Social Science), version 16.0. Continuous variables were expressed as mean &#177; standard deviation (SD) and categorical variables, in count and percentage (%). For comparison of patients with or without PAD, Stutent’s t test was used to compare mean values and Chi<sup>2</sup> test was used to compare difference in prevalence rates. p-value &lt; 0.05 was considered significant.</p></sec></sec><sec id="s3"><title>3. Results</title><sec id="s3_1"><title>3.1. General Characteristics of the Study Population</title><p><xref ref-type="table" rid="table1">Table 1</xref> shows the distribution of demographic characteristics, clinical, and laboratory parameters for the entire study population and for patients with and without PAD.</p><p>Fifty-three patients, with a mean age of 49.15 &#177; 15.18 (18 - 81 years) were included in the study. There were 22 men (41.5%) and 31 women (58.5%). Forty-four patients (83 %) were hypertensive, 11 (20. 75%) were former smokers with an average consumption of 14.35 &#177; 17.13 packs/years, and 2 (3.8%) patients were diabetic. None of patients drank alcohol. Four patients (7.5%) had a history of stroke. The etiologies of ESRD were hypertension (51%), glomerulonephritis (15%) and polycystic kidney disease (7.5%). The mean duration in hemodialysis was 4.24 &#177; 2. 89 years (0.91 - 12.91 years). The mean interdialytic weight gain was 2.10 &#177; 0.80 Kg (0.145 - 4.16 Kg). Dialysis sessions were twice a week for 5 (9.4%) patients who had an average interdialytic weight gain of 2.64 &#177; 0.68 Kg (1.56 - 3.35 Kg). URR and Kt/V were low in respectively 2 (3.8%) and 6 (11.32%) patients.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Comparison of baseline and clinical characteristics of patients with PAD and without PAD</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Characteristics</th><th align="center" valign="middle"  colspan="3"  >Peripheral arterial disease</th></tr></thead><tr><td align="center" valign="middle" >Yes (n = 25)</td><td align="center" valign="middle" >No (n = 28)</td><td align="center" valign="middle" >p-value</td></tr><tr><td align="center" valign="middle" >Age (years)</td><td align="center" valign="middle" >52.52 &#177; 15.08</td><td align="center" valign="middle" >46.14 &#177; 14.89</td><td align="center" valign="middle" >0.1278</td></tr><tr><td align="center" valign="middle" >Female gender (%)</td><td align="center" valign="middle" >16 (64%)</td><td align="center" valign="middle" >15 (53.6%)</td><td align="center" valign="middle" >0.2209</td></tr><tr><td align="center" valign="middle" >Duration of dialysis (years)</td><td align="center" valign="middle" >4.15 &#177; 2.38</td><td align="center" valign="middle" >4.32 &#177; 3.33</td><td align="center" valign="middle" >0.8334</td></tr><tr><td align="center" valign="middle" >Diabetes</td><td align="center" valign="middle" >1 (4%)</td><td align="center" valign="middle" >1 (3.57%)</td><td align="center" valign="middle" >0.4674</td></tr><tr><td align="center" valign="middle" >Stroke</td><td align="center" valign="middle" >2 (8%)</td><td align="center" valign="middle" >2 (7.15%)</td><td align="center" valign="middle" >0.4165</td></tr><tr><td align="center" valign="middle" >Coronary artery disease</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >1 (3.57%)</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" >Cause of ESRD (%)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hypertension</td><td align="center" valign="middle" >13 (52%)</td><td align="center" valign="middle" >14 (50%)</td><td align="center" valign="middle" >0.4422</td></tr><tr><td align="center" valign="middle" >Glomerulonephritis</td><td align="center" valign="middle" >3 (12%)</td><td align="center" valign="middle" >5 (17.85%)</td><td align="center" valign="middle" >0.2761</td></tr><tr><td align="center" valign="middle" >Polycystic kidney disease</td><td align="center" valign="middle" >1 (4%)</td><td align="center" valign="middle" >3 (10.7%)</td><td align="center" valign="middle" >0.1778</td></tr><tr><td align="center" valign="middle" >Diabetes mellitus</td><td align="center" valign="middle" >1 (4%)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" >Others diagnoses</td><td align="center" valign="middle" >2 (8%)</td><td align="center" valign="middle" >4 (14.3%)</td><td align="center" valign="middle" >0.2572</td></tr><tr><td align="center" valign="middle" >Unknown</td><td align="center" valign="middle" >5 (20%)</td><td align="center" valign="middle" >2 (7.15%)</td><td align="center" valign="middle" >0.1004</td></tr><tr><td align="center" valign="middle" >Height (cm)</td><td align="center" valign="middle" >168.12 &#177; 10.12</td><td align="center" valign="middle" >170.17 &#177; 8.63</td><td align="center" valign="middle" >0.4298</td></tr><tr><td align="center" valign="middle" >Weight (Kg)</td><td align="center" valign="middle" >62.54 &#177; 15</td><td align="center" valign="middle" >61.60 &#177; 13.87</td><td align="center" valign="middle" >0.8136</td></tr><tr><td align="center" valign="middle" >BMI (kg/m&#178;)</td><td align="center" valign="middle" >21.88 &#177; 3.75</td><td align="center" valign="middle" >21.10 &#177; 3.66</td><td align="center" valign="middle" >0.4474</td></tr><tr><td align="center" valign="middle" >Inter-dialytic weight gain (Kg)</td><td align="center" valign="middle" >2.08 &#177; 0.88</td><td align="center" valign="middle" >2.31 &#177; 0.72</td><td align="center" valign="middle" >0.3006</td></tr><tr><td align="center" valign="middle" >Smoking status</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Current smoker (%)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" >Former smokers (%)</td><td align="center" valign="middle" >6 (24%)</td><td align="center" valign="middle" >5 (17.85%)</td><td align="center" valign="middle" >0.3012</td></tr><tr><td align="center" valign="middle" >Tobacco (packs/year)</td><td align="center" valign="middle" >14.5 &#177; 20.91</td><td align="center" valign="middle" >14.2 &#177; 14.93</td><td align="center" valign="middle" >0.9792</td></tr><tr><td align="center" valign="middle" >Pre-dialysis blood pressure (mmHg)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Systolic BP</td><td align="center" valign="middle" >137.76 &#177; 19.08</td><td align="center" valign="middle" >142.07 &#177; 19.84</td><td align="center" valign="middle" >0.4252</td></tr><tr><td align="center" valign="middle" >Diastolic BP</td><td align="center" valign="middle" >78.12 &#177; 11.04</td><td align="center" valign="middle" >84.39 &#177; 10.43</td><td align="center" valign="middle" >0.0384</td></tr><tr><td align="center" valign="middle" >PP</td><td align="center" valign="middle" >59.64 &#177; 14.86</td><td align="center" valign="middle" >57.67 &#177; 12.61</td><td align="center" valign="middle" >0.6039</td></tr><tr><td align="center" valign="middle" >MAP</td><td align="center" valign="middle" >97.96 &#177; 12.46</td><td align="center" valign="middle" >103.64 &#177; 13.01</td><td align="center" valign="middle" >0.1117</td></tr><tr><td align="center" valign="middle" >Post-dialysis blood pressure (mmHg)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Systolic BP</td><td align="center" valign="middle" >135.12 &#177; 21.76</td><td align="center" valign="middle" >141.67 &#177; 23.29</td><td align="center" valign="middle" >0.2968</td></tr><tr><td align="center" valign="middle" >Diastolic BP</td><td align="center" valign="middle" >75.44 &#177; 10.18</td><td align="center" valign="middle" >81.96 &#177; 12.58</td><td align="center" valign="middle" >0.0447</td></tr><tr><td align="center" valign="middle" >PP</td><td align="center" valign="middle" >59.68 &#177; 16.36</td><td align="center" valign="middle" >59.71 &#177; 14.63</td><td align="center" valign="middle" >0.9944</td></tr><tr><td align="center" valign="middle" >MAP</td><td align="center" valign="middle" >95.32 &#177; 13.01</td><td align="center" valign="middle" >101.89 &#177; 15.44</td><td align="center" valign="middle" >0.1022</td></tr><tr><td align="center" valign="middle" >Antihypertensive medications, n (%)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >RAAS blockers use</td><td align="center" valign="middle" >21 (75%)</td><td align="center" valign="middle" >20 (80%)</td><td align="center" valign="middle" >0.3321</td></tr><tr><td align="center" valign="middle" >Calcium channel blocker use</td><td align="center" valign="middle" >12 (48%)</td><td align="center" valign="middle" >15 (53.6%)</td><td align="center" valign="middle" >0.3484</td></tr><tr><td align="center" valign="middle" >β-blockers use</td><td align="center" valign="middle" >14 (50%)</td><td align="center" valign="middle" >14 (56%)</td><td align="center" valign="middle" >0.3373</td></tr><tr><td align="center" valign="middle" >Statins use</td><td align="center" valign="middle" >7 (28%)</td><td align="center" valign="middle" >6 (21.43%)</td><td align="center" valign="middle" >0.2986</td></tr><tr><td align="center" valign="middle" >Aspirin use</td><td align="center" valign="middle" >5 (20%)</td><td align="center" valign="middle" >7 (25%)</td><td align="center" valign="middle" >0.3417</td></tr><tr><td align="center" valign="middle" >ABI</td><td align="center" valign="middle" >0.78 &#177; 0.08</td><td align="center" valign="middle" >1.06 &#177; 0.10</td><td align="center" valign="middle" >&lt;0.0001</td></tr></tbody></table></table-wrap><p>ABI: ankle-brachial index; BMI: body mass index; BP: blood pressure; ESRD: end stage renal disease; MAP: mean arterial pressure; PP: pulse pressure; RAAS: renin-angiotensin-aldosterone system.</p></sec><sec id="s3_2"><title>3.2. PAD Prevalence and Associated Factors</title><p>The mean ABI was 0.92 &#177; 0.17 (0.51 - 1.3). The prevalence of PAD was 47.16% (25 patients). Of these, 12 (48%) patients had intermittent claudication with nonpalpable distal pulses in 7 (28%) patients. Women with PAD were older than men (53.43 &#177; 14.51 years vs. 50.88 &#177; 16.83 years, p = 0.5904).</p><p>Compared with patient without PAD, patients with PAD were older (52.52 &#177; 15.08 years vs. 46.14 &#177; 14.89 years), with a higher proportion of women (64% vs 53.6%) but the statistical differences were not significant (<xref ref-type="table" rid="table1">Table 1</xref>). Pre-dialysis and post-dialysis diastolic BP were significantly lower (78.12 &#177; 11.04 mmHg vs 84.39 &#177; 10.43 mmHg, p = 0.0384 and 75.44 &#177; 10.18 mmHg vs. 81.96 &#177; 12.58 mmHg, p = 0.0447 respectively) in PAD patients. Significant differences were not found between the two groups of patients regarding hemodialysis duration, systolic BP, PP, MAP and BMI (<xref ref-type="table" rid="table1">Table 1</xref>).</p><p>Serum albumin, total cholesterol, HDL-cholesterol and LDL-cholesterol were almost similar in the two groups (<xref ref-type="table" rid="table2">Table 2</xref>). PAD patients had higher blood levels of iPTH, CRP and triglycerides, without significant differences (p &gt; 0.05) (<xref ref-type="table" rid="table2">Table 2</xref>).</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Laboratory parameters among patients with PAD and without PAD</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Laboratory parameters</th><th align="center" valign="middle"  colspan="3"  >Peripheral arterial disease</th></tr></thead><tr><td align="center" valign="middle" >Yes (n = 25)</td><td align="center" valign="middle" >No (n = 28)</td><td align="center" valign="middle" >p-value</td></tr><tr><td align="center" valign="middle" >Urea (mg/dL)</td><td align="center" valign="middle" >1.21 &#177; 0.47</td><td align="center" valign="middle" >1.07 &#177; 0.42</td><td align="center" valign="middle" >0.2574</td></tr><tr><td align="center" valign="middle" >Creatinine (mg/L)</td><td align="center" valign="middle" >84.47 &#177; 50.91</td><td align="center" valign="middle" >86.56 &#177; 36.38</td><td align="center" valign="middle" >0.8631</td></tr><tr><td align="center" valign="middle" >Sodium (mEq/L)</td><td align="center" valign="middle" >138.72 &#177; 3.69</td><td align="center" valign="middle" >139.44 &#177; 3.62</td><td align="center" valign="middle" >0.4373</td></tr><tr><td align="center" valign="middle" >Potassium (mEq/L)</td><td align="center" valign="middle" >4.79 &#177; 0.92</td><td align="center" valign="middle" >4.82 &#177; 0.97</td><td align="center" valign="middle" >0.9088</td></tr><tr><td align="center" valign="middle" >Calcium (mg/L)</td><td align="center" valign="middle" >91.06 &#177; 18.68</td><td align="center" valign="middle" >92.99 &#177; 8.23</td><td align="center" valign="middle" >0.6221</td></tr><tr><td align="center" valign="middle" >Phosphate (mg/L)</td><td align="center" valign="middle" >38.85 &#177; 16.68</td><td align="center" valign="middle" >44.16 &#177; 14.84</td><td align="center" valign="middle" >0.2256</td></tr><tr><td align="center" valign="middle" >iPTH(pg/mL)</td><td align="center" valign="middle" >625.58 &#177; 666.13</td><td align="center" valign="middle" >599.23 &#177; 425.26</td><td align="center" valign="middle" >0.8629</td></tr><tr><td align="center" valign="middle" >Hemoglobin (g/dL)</td><td align="center" valign="middle" >9.34 &#177; 1.73</td><td align="center" valign="middle" >9.35 &#177; 1.74</td><td align="center" valign="middle" >0.9834</td></tr><tr><td align="center" valign="middle" >Hematocrit (%)</td><td align="center" valign="middle" >29.06 &#177; 5.34</td><td align="center" valign="middle" >29.72 &#177; 5.91</td><td align="center" valign="middle" >0.6729</td></tr><tr><td align="center" valign="middle" >White blood cell counts (thousand/mL)</td><td align="center" valign="middle" >5908.4 &#177; 2041.94</td><td align="center" valign="middle" >5497.14 &#177; 1523.28</td><td align="center" valign="middle" >0.4066</td></tr><tr><td align="center" valign="middle" >Albumin (g/L)</td><td align="center" valign="middle" >40.70 &#177; 5.49</td><td align="center" valign="middle" >41.72 &#177; 5.60</td><td align="center" valign="middle" >0.5071</td></tr><tr><td align="center" valign="middle" >CRP (mg/L)</td><td align="center" valign="middle" >16.78 &#177; 33.31</td><td align="center" valign="middle" >11.37 &#177; 18.56</td><td align="center" valign="middle" >0.4622</td></tr><tr><td align="center" valign="middle" >Fasting glucose (g/L)</td><td align="center" valign="middle" >0.90 &#177; 0.12</td><td align="center" valign="middle" >0.91 &#177; 0.10</td><td align="center" valign="middle" >0.7422</td></tr><tr><td align="center" valign="middle" >Total cholesterol (g/L)</td><td align="center" valign="middle" >1.97 &#177; 0.45</td><td align="center" valign="middle" >1.91 &#177; 0.44</td><td align="center" valign="middle" >0.6260</td></tr><tr><td align="center" valign="middle" >HDL-cholesterol (g/L)</td><td align="center" valign="middle" >0.44 &#177; 0.16</td><td align="center" valign="middle" >0.47 &#177; 0.10</td><td align="center" valign="middle" >0.4116</td></tr><tr><td align="center" valign="middle" >LDL-cholesterol (g/L)</td><td align="center" valign="middle" >1.34 &#177; 0.44</td><td align="center" valign="middle" >1.35 &#177; 0.38</td><td align="center" valign="middle" >0.9296</td></tr><tr><td align="center" valign="middle" >Triglycerides (g/L)</td><td align="center" valign="middle" >1.22 &#177; 0.99</td><td align="center" valign="middle" >0.89 &#177; 0.34</td><td align="center" valign="middle" >0.1032</td></tr><tr><td align="center" valign="middle" >Total cholesterol/HDL ratio</td><td align="center" valign="middle" >4.87 &#177; 1.66</td><td align="center" valign="middle" >4.27 &#177; 1.31</td><td align="center" valign="middle" >0.1481</td></tr><tr><td align="center" valign="middle" >URR (%)</td><td align="center" valign="middle" >74.51 &#177; 9.0</td><td align="center" valign="middle" >79.86 &#177; 10.27</td><td align="center" valign="middle" >0.0506</td></tr><tr><td align="center" valign="middle" >Kt/V</td><td align="center" valign="middle" >1.46 &#177; 0.47</td><td align="center" valign="middle" >1.68 &#177; 0.63</td><td align="center" valign="middle" >0.1598</td></tr></tbody></table></table-wrap><p>iPTH: intact parathyroid hormone; URR: urea reduction ratio. Creatinine (mg &#215; 8.8 = &#181;mol/L).</p></sec></sec><sec id="s4"><title>4. Discussion</title><p>In this study, PAD prevalence was 47.16%. This was higher than those reported by other authors [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref15">15</xref>] especially when we compared some risk factors like age, diabetes mellitus and smoking (<xref ref-type="table" rid="table3">Table 3</xref>). PAD prevalence in hemodialysis patients varies from 17% to 48% [<xref ref-type="bibr" rid="scirp.109436-ref1">1</xref>]. This large variability can be partly explained by the diagnostic criteria of PAD, which differ from one study to another. In some studies [<xref ref-type="bibr" rid="scirp.109436-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref15">15</xref>], PAD was diagnosed at a clinical stage of the disease, based on data from patients’ medical records (presence or history of intermittent claudication, gangrene, history of revascularization, or limb amputation). However, 40% of PAD patients are asymptomatic [<xref ref-type="bibr" rid="scirp.109436-ref16">16</xref>]. In other studies, such as ours [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref17">17</xref>], PAD diagnosis was made at a subclinical stage by measuring the ABI. But in CKD, diabetes, or in elderly subjects, the presence of mediacalcosis resulted in abnormally normal or high ABI. Hence, the calculation of toe-brachial index (TBI) was combined with ABI in some studies to minimize this bias [<xref ref-type="bibr" rid="scirp.109436-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref18">18</xref>] (<xref ref-type="table" rid="table3">Table 3</xref>): the toe blood vessels are less prone to mediacalosis-related stiffening.</p><p>On the other hand, ABI measurement protocols vary dependent on studies, making it difficult to compare results. For the calculation of ABI, the lowest, highest or average systolic BP of the ankle can be used [<xref ref-type="bibr" rid="scirp.109436-ref3">3</xref>]. Using the lowest systolic pressure in lower limb, as in our study, or the mean systolic BP of the posterior tibial arteries, allows to increase the sensitivity and the reproducibility of the measurements but overestimates the severity of PAD in asymptomatic patients [<xref ref-type="bibr" rid="scirp.109436-ref3">3</xref>].</p><p>Age, hypertension, diabetes mellitus, smoking and dyslipidemia are known risk factors for PAD [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref19">19</xref>]. Among those risk factors, diabetes mellitus and smoking have been identified as the most potent [<xref ref-type="bibr" rid="scirp.109436-ref16">16</xref>]. In our study, PAD subjects were on average older (52.52 &#177; 15.08 years vs 46.14 &#177; 14.89) but diabetes prevalence was low (4%). As reported by Ono et al. [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>], we found significant lower diastolic BP in PAD patients.</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Prevalence of PAD according to some studies</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Authors</th><th align="center" valign="middle" >PAD assessment</th><th align="center" valign="middle" >PAD (%)</th><th align="center" valign="middle" >Mean age (years)</th><th align="center" valign="middle" >HTN (%)</th><th align="center" valign="middle" >Diabetes (%)</th><th align="center" valign="middle" >Smokers (%)</th></tr></thead><tr><td align="center" valign="middle" >Our study, 2012</td><td align="center" valign="middle" >ABI</td><td align="center" valign="middle" >47.1</td><td align="center" valign="middle" >49.15 &#177; 15.18</td><td align="center" valign="middle" >83</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >20.75</td></tr><tr><td align="center" valign="middle" >Ohtake et al. [<xref ref-type="bibr" rid="scirp.109436-ref18">18</xref>] , 2011</td><td align="center" valign="middle" >ABI/TBI</td><td align="center" valign="middle" >47.2</td><td align="center" valign="middle" >67.8 &#177; 12.2</td><td align="center" valign="middle" >95.8</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >14.4</td></tr><tr><td align="center" valign="middle" >Adragao et al. [<xref ref-type="bibr" rid="scirp.109436-ref17">17</xref>] , 2012</td><td align="center" valign="middle" >ABI</td><td align="center" valign="middle" >41</td><td align="center" valign="middle" >65.6 &#177; 15</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >22</td></tr><tr><td align="center" valign="middle" >Chen et al. [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>] , 2016</td><td align="center" valign="middle" >ABI</td><td align="center" valign="middle" >18.6/52.8*</td><td align="center" valign="middle" >59.3</td><td align="center" valign="middle" >91.3</td><td align="center" valign="middle" >58.2</td><td align="center" valign="middle" >19.9</td></tr><tr><td align="center" valign="middle" >Matsuzawa et al. [<xref ref-type="bibr" rid="scirp.109436-ref13">13</xref>] , 2015</td><td align="center" valign="middle" >ABI/TBI</td><td align="center" valign="middle" >38.1</td><td align="center" valign="middle" >66 &#177; 11</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >48.6</td><td align="center" valign="middle" >57.6</td></tr><tr><td align="center" valign="middle" >Ono et al. [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>] , 2003</td><td align="center" valign="middle" >ABI</td><td align="center" valign="middle" >16.5</td><td align="center" valign="middle" >60.6 &#177; 12.5</td><td align="center" valign="middle" >79</td><td align="center" valign="middle" >33.8</td><td align="center" valign="middle" >41.4</td></tr><tr><td align="center" valign="middle" >O’Hare et al. [<xref ref-type="bibr" rid="scirp.109436-ref14">14</xref>] , 2002</td><td align="center" valign="middle" >Symptomatic disease**</td><td align="center" valign="middle" >24</td><td align="center" valign="middle" >60 &#177; 16</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >43</td><td align="center" valign="middle" >47</td></tr><tr><td align="center" valign="middle" >Sebastianski et al. [<xref ref-type="bibr" rid="scirp.109436-ref15">15</xref>] , 2014</td><td align="center" valign="middle" >Symptomatic disease**</td><td align="center" valign="middle" >19.1</td><td align="center" valign="middle" >60.3 &#177; 15.6</td><td align="center" valign="middle" >87.2</td><td align="center" valign="middle" >51.4</td><td align="center" valign="middle" >58.4</td></tr></tbody></table></table-wrap><p>ABI: ankle-brachial index; HTN: hypertension; PAD: peripheral arterial disease; TBI: toe-brachial index. *African-americans, **: claudication symptoms, absent foot pulses, gangrene, previous vascular intervention or previous amputation due to vascular disease.</p><p>For dyslipidemia, the lipid fractions associated with PAD differ from one study to another. In some reports, high LDL cholesterol levels [<xref ref-type="bibr" rid="scirp.109436-ref13">13</xref>] or low HDL cholesterol levels [<xref ref-type="bibr" rid="scirp.109436-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref13">13</xref>] were the most significant fractions, while in another [<xref ref-type="bibr" rid="scirp.109436-ref14">14</xref>], high total cholesterol and high triglycerides levels, identified in the univariate analysis were not confirmed in the multivariate analysis. Thus, current data support the total cholesterol/HDL cholesterol ratio that was most correlated with PAD in the general population [<xref ref-type="bibr" rid="scirp.109436-ref19">19</xref>]. Like other authors [<xref ref-type="bibr" rid="scirp.109436-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref20">20</xref>], we did not find significant correlation between PAD and blood levels of total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides or iPTH.</p><p>We observed a higher prevalence of PAD in women, which is consistent with the literature data [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref19">19</xref>]. In developing countries, PAD tends to be more frequent among women in the general population, while in developed countries, the prevalence of PAD seemed to be similar between men and women [<xref ref-type="bibr" rid="scirp.109436-ref19">19</xref>].</p><p>Inflammation plays an important role in the occurrence of PAD [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref19">19</xref>]. In our study, both CRP levels and white blood cell counts were higher in the PAD-patients group, but without significant difference.</p><p>Other reasons could also explain this high prevalence. Apart from traditional CVRF, PAD is associated with non-traditional CVRF such as fibrinogen, myeloperoxidase, glycated hemoglobin, insulin resistance and alkaline phosphatase [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>]. These new CVRF are common in chronic renal failure patients and have not been studied in this work. In addition, black subjects have a higher PAD prevalence compared to other ethnic groups [<xref ref-type="bibr" rid="scirp.109436-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref21">21</xref>]. For African-Americans, poor access to health care services due to low socio-economic status, poor quality of life and genetic factors could account for the high morbidity. In sub-Saharan Africa, difficulty for populations to access healthcare services due to the lack of sufficient human resources and limitation of the technical healthcare platforms is a reality.</p><p>PAD is a powerful predictor of cardiovascular and global mortality in hemodialysis patients [<xref ref-type="bibr" rid="scirp.109436-ref5">5</xref>]. Diagnosing it earlier could be integrated into strategies for preventing cardiovascular and global morbidity and mortality in this population by establishing therapeutic means such as smoking cessation, regular physical activity practice by hemodialysis patients with a good tolerance to efforts, and by initiating drug therapy with statins and/or antiplatelet agents (aspirin, clopidogrel) [<xref ref-type="bibr" rid="scirp.109436-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.109436-ref16">16</xref>]. In patients with end stage chronic kidney disease (CKD), screening for PAD is recommended at the initiation of dialysis [<xref ref-type="bibr" rid="scirp.109436-ref1">1</xref>].</p></sec><sec id="s5"><title>5. Conclusion</title><p>In the present study we found a high PAD prevalence amounting to 47.16% with more than half of patients (52%) who were clinically asymptomatic. Also, screening for PAD should be systematic in groups of patients at high cardiovascular risk as in hemodialysis patients. This study had several limitations: a relatively small number of patients, the use of the smallest ankle systolic BP for the calculation of ABI and the fact that we did not study non-traditional cardiovascular risk factors.</p></sec><sec id="s6"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s7"><title>Cite this paper</title><p>Lengani, H.Y.A., Ciss&#233;, M.M., Yattara, H., Mbaye, A., Coulibaly, G., Mingou, J.S., Ka, E.H.F., Niang, A., Kane, A. and Diouf, B. (2021) Peripheral Arterial Disease among Patient Undergoing Maintenance Hemodialysis in Dakar (Senegal). Open Journal of Nephrology, 11, 242-251. https://doi.org/10.4236/ojneph.2021.112019</p></sec></body><back><ref-list><title>References</title><ref id="scirp.109436-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Herzog, C., Asinger, R., Berger, A., Charytan, D., D&amp;iacute;ez, J., Hart, R., et al. 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