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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">wjcd</journal-id>
      <journal-title-group>
        <journal-title>World Journal of Cardiovascular Diseases</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2164-5337</issn>
      <issn pub-type="ppub">2164-5329</issn>
      <publisher>
        <publisher-name>Scientific Research Publishing</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.4236/wjcd.2025.1512055</article-id>
      <article-id pub-id-type="publisher-id">wjcd-148037</article-id>
      <article-categories>
        <subj-group>
          <subject>Article</subject>
        </subj-group>
        <subj-group>
          <subject>Medicine</subject>
          <subject>Healthcare</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Prevalence and Predictive Factors of Heart Failure in Patients Hospitalized in the Medical-Surgical Cardiology Department of the Donka National Hospital in Conakry</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Kone</surname>
            <given-names>Alpha</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Samoura</surname>
            <given-names>Sana</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Bah</surname>
            <given-names>Mamadou Mariame Bassirou</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Falana</surname>
            <given-names>Amal Kamal</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Barry</surname>
            <given-names>Ibrahima Sory</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Mansare</surname>
            <given-names>Abel</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Diakite</surname>
            <given-names>Souleymane</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Sylla</surname>
            <given-names>Ibrahima Sory</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Onivogui</surname>
            <given-names>Zézé</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Balde</surname>
            <given-names>Elhadj Yaya</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Beavogui</surname>
            <given-names>Mariame</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name name-style="western">
            <surname>Balde</surname>
            <given-names>Mamadou Dadhi</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1"><label>1</label> Medical-Surgical Cardiology Department, Donka National Hospital, Conakry, Guinea </aff>
      <aff id="aff2"><label>2</label> Cardiology Department of Friendly Sino-Guinean, Conakry, Guinea </aff>
      <aff id="aff3"><label>3</label> Faculty of Health Sciences and Technologies, University Gamal Abdel Nasser of Conakry, Conakry, Guinea </aff>
      <aff id="aff4"><label>4</label> Cardiology Department, Ignace Deen National Hospital, Conakry, Guinea </aff>
      <aff id="aff5"><label>5</label> Abidjan National Police Hospital, Abidjan, Cote d’Ivoire </aff>
      <author-notes>
        <fn fn-type="conflict" id="fn-conflict">
          <p>The authors declare no conflicts of interest regarding the publication of this paper.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub">
        <day>08</day>
        <month>12</month>
        <year>2025</year>
      </pub-date>
      <pub-date pub-type="collection">
        <month>12</month>
        <year>2025</year>
      </pub-date>
      <volume>15</volume>
      <issue>12</issue>
      <fpage>631</fpage>
      <lpage>637</lpage>
      <history>
        <date date-type="received">
          <day>27</day>
          <month>10</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>14</day>
          <month>12</month>
          <year>2025</year>
        </date>
        <date date-type="published">
          <day>17</day>
          <month>12</month>
          <year>2025</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>© 2025 by the authors and Scientific Research Publishing Inc.</copyright-statement>
        <copyright-year>2025</copyright-year>
        <license license-type="open-access">
          <license-p> This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link> ). </license-p>
        </license>
      </permissions>
      <self-uri content-type="doi" xlink:href="https://doi.org/10.4236/wjcd.2025.1512055">https://doi.org/10.4236/wjcd.2025.1512055</self-uri>
      <abstract>
        <p><bold>Objective</bold>: To determine the prevalence and predictive factors of heart failure in patients hospitalized in the medical surgical department in Donka National Hospital. <bold>Materials and</bold><bold>Method</bold><bold>:</bold> This was a descriptive and analytical cross-sectional study over period of 6 months (July 01 to December 31, 2020) that included patients hospitalized for heart failure in whom informed consent was obtained. The statistical analyzes were carried out by the epi-info software in version 7.2. The qualitative and quantitative variables were compared by the chi-square test. A value of p &lt; 0.05 was retained as significant. <bold>Results:</bold> One hundred and fifteen (115) patients were collected in our study with a hospital prevalence of 72.17% (83 cases) of HF. The average age was 52 ± 18 years. A female predominance is noted with an M/F ratio = 0.84. The main CVRDs were hypertension, diabetes and age. The CI was global in 66.27% of cases. ECG signs were dominated by arrhythmias, conduction disturbances, and LVH. Cardiomegaly is noted in 70% of cases (p &lt; 0.01). On TTE, LVEF was impaired in 43.55% of cases. The mean length of stay was 12.5 ± 7. The bivariate analysis allowed us to identify several predictive factors positively correlated with the occurrence of HF, namely: hypertension (p &lt; 0.0003), diabetes (p &lt; 0.0000), tobacco (p &lt; 0.0023), the association of hypertension/age (p &lt; 0.0076) and/or diabetes (p &lt; 0.0270) and comorbidities such as pulmonary disease (p &lt; 0.0270), anemia (p &lt; 0.0214) and ischemic attack (p &lt; 0.0029). <bold>Conclusion:</bold> Heart failure is a major public health problem. Early identification and management of predictive factors can significantly reduce the morbidity and mortality of HF.</p>
      </abstract>
      <kwd-group kwd-group-type="author-generated" xml:lang="en">
        <kwd>Predictors</kwd>
        <kwd>Heart Failure</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec1">
      <title>1. Introduction</title>
      <p>Heart failure (HF) is a clinical syndrome characterized by typical symptoms that may be accompanied by signs caused by structural and/or functional cardiac abnormalities, resulting in reduced cardiac output and/or elevated intracardiac pressures at rest or during stress [<xref ref-type="bibr" rid="B1">1</xref>].</p>
      <p>It is linked to a defect in filling or ejecting blood, resulting in the appearance of clinical symptoms, the main ones being dyspnea and lower limb edema (congestion) [<xref ref-type="bibr" rid="B2">2</xref>]. The epidemiology of heart failure is now well understood. Its evolution has been distinguished in recent years by a steady increase in its prevalence, estimated at 40 million individuals worldwide, representing 1% to 2% of the adult population in developed countries. Two main factors explain this trend: the aging of the population and the growing improvement in management burden of cardiovascular diseases, the ultimate stage of which is heart failure [<xref ref-type="bibr" rid="B3">3</xref>][<xref ref-type="bibr" rid="B4">4</xref>]. In Canada, a decrease in average temperature of 10˚C over a week or less (which is common in Quebec) increases the risk of being hospitalized or dying from the main cause of HF by approximately 7% in people over 65 years of age [<xref ref-type="bibr" rid="B5">5</xref>]. In France, a proven history of heart failure, impaired renal function, age or an increase in N-terminal-proBNP were the factors that predicted hospitalization for HF [<xref ref-type="bibr" rid="B6">6</xref>]. In sub-Saharan Africa, the factors identified as positively correlated with the occurrence of HF, apart from advanced age, were the presence of cardiovascular risk factors (CVRF) or not, large electrocardiographic territories and comorbidities such as infection, anemia and renal failure [<xref ref-type="bibr" rid="B7">7</xref>][<xref ref-type="bibr" rid="B8">8</xref>]. There are few studies in Guinea on the predictive factors of heart failure. </p>
      <p>The objective of our study was to determine the factors linked to the occurrence of failure in patients hospitalized in the medical-surgical cardiology department of the Donka National Hospital, Conakry University Hospital.</p>
    </sec>
    <sec id="sec2">
      <title>2. Methods</title>
      <p><bold>Study Overview:</bold> We conducted a descriptive and analytical cross-sectional study at the Medical-Surgical Cardiology Department of Donka National Hospital, from July 1 to December 31, 2020, involving 115 patients.</p>
      <p><bold>Inclusion Criteria:</bold> Patients hospitalized with signs of right-sided, left-sided, or global HF during the study period and who provided their consent were included.</p>
      <p><bold>Data Collection</bold>: The following parameters were analyzed: epidemiological data, CVRF, comorbidities, patient clinical characteristics, clinical presentation of heart failure, electrocardiographic, radiological, and echocardiographic abnormalities, and progression during hospitalization under conventional treatment.</p>
      <p><bold>Statistical Analysis:</bold> Statistical analysis was performed using Epi info software, version 7.2. Quantitative variables were expressed as mean plus or minus standard deviation. Qualitative variables were expressed as number and percentage. The Chi-square test was used for our association tables with any p &lt; 0.005 considered statistically significant.</p>
    </sec>
    <sec id="sec3">
      <title>3. Results</title>
      <p>During our study period, we recorded a hospital prevalence of 72.17% (83 cases) related to HF out of 115 hospitalizations. The mean age of our patients was 52 ± 19.80 years, the majority of whom were women (54.22%), with a sex ratio of 0.84. The main cardiovascular risk factors encountered were: hypertension (85.54%), diabetes (59.04%), and age (54.22%). Dyspnea was the most representative functional sign in our study (96.38%), particularly in stages III-IV of NHYA, followed by OMI (80.72%). Clinically, 66.27% of patients were admitted for congestive heart failure, 18.07% for left heart failure, and 15.66% for right heart failure. Bronchopneumopathy was the most representative comorbidity (44.57%), followed by anemia (43.37%) and CA/AF (24.10%). All our patients underwent an electrocardiogram. On chest X-ray, cardiomegaly was present in 70% of cases. Transthoracic echocardiography by the Simpson method found an altered LVEF in 43.55% of cases, preserved in 40.12% of cases and moderately altered in 16.13% of cases.</p>
      <p>The average length of stay of our patients was 12.5 ± 7. The evolution was favorable in 86.75% (72 cases) and the remaining 11 cases had an evolution punctuated by complications (unfavorable). The bivariate analysis between patients with or without insufficiency and the predictive factors studied revealed a statistically significant link with hypertension (p &lt; 0.0003), diabetes (p &lt; 0.0000), smoking (p &lt; 0.0023), the association of hypertension and age (p &lt; 0.0076) and/or diabetes (p &lt; 0.0270) and comorbidities such as anemia (p &lt; 0.0214), bronchopneumopathy (p &lt; 0.0270) and ischemic attack (p &lt; 0.0029). Unlike age (p &lt; 0.21), menopause or dyslipidemia and certain comorbidities such as renal failure, AC/AF or hypertensive crisis (p not significant) (<bold>T</bold><bold>ables 1-4</bold>).</p>
      <p><bold>Table 1</bold><bold>.</bold> Patient frequency by CVRF.</p>
      <table-wrap id="tbl1">
        <label>Table 1</label>
        <table>
          <tbody>
            <tr>
              <td>Comorbidities</td>
              <td>Frequency</td>
              <td>Percentage</td>
            </tr>
            <tr>
              <td>Anemia</td>
              <td>36</td>
              <td>43.37</td>
            </tr>
            <tr>
              <td>microcytic hypochromic</td>
              <td>28</td>
              <td>33.73</td>
            </tr>
            <tr>
              <td>macrocytic hypochromic</td>
              <td>06</td>
              <td>9.64</td>
            </tr>
            <tr>
              <td>Pulmonary disease</td>
              <td>37</td>
              <td>44.57</td>
            </tr>
            <tr>
              <td>Hypertensive crisis</td>
              <td>18</td>
              <td>21.69</td>
            </tr>
            <tr>
              <td>Arrythmia</td>
              <td>31</td>
              <td>37.35</td>
            </tr>
            <tr>
              <td>Atrial Fibrillation</td>
              <td>20</td>
              <td>24.10</td>
            </tr>
            <tr>
              <td>Ventricular extrasystoles</td>
              <td>11</td>
              <td>13.25</td>
            </tr>
            <tr>
              <td>Renal Faillure</td>
              <td>8</td>
              <td>9.64</td>
            </tr>
            <tr>
              <td>Ischemia crisis</td>
              <td>10</td>
              <td>12.05</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p><bold>Table 2</bold><bold>.</bold> Patient frequency by comorbidities.</p>
      <table-wrap id="tbl2">
        <label>Table 2</label>
        <table>
          <tbody>
            <tr>
              <td>Cardiovascular risk factors</td>
              <td>Frequency</td>
              <td>Percentage</td>
            </tr>
            <tr>
              <td>HTA</td>
              <td>71</td>
              <td>85.54</td>
            </tr>
            <tr>
              <td>Diabetis</td>
              <td>49</td>
              <td>59.04</td>
            </tr>
            <tr>
              <td>Age</td>
              <td>45</td>
              <td>54.22</td>
            </tr>
            <tr>
              <td>Menopause</td>
              <td>25</td>
              <td>30.12</td>
            </tr>
            <tr>
              <td>Alcohol</td>
              <td>6</td>
              <td>7.23</td>
            </tr>
            <tr>
              <td>Obesity</td>
              <td>6</td>
              <td>7.23</td>
            </tr>
            <tr>
              <td>tobacco</td>
              <td>5</td>
              <td>6.02</td>
            </tr>
            <tr>
              <td>Dyslipidemia</td>
              <td>4</td>
              <td>4.82</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p><bold>Table 3</bold><bold>.</bold> Patient distribution by LVEF (N = 62 out of 83, or 74.70%).</p>
      <table-wrap id="tbl3">
        <label>Table 3</label>
        <table>
          <tbody>
            <tr>
              <td>
                <bold>Ejection Fraction</bold>
              </td>
              <td>
                <bold>frequency</bold>
              </td>
              <td>
                <bold>percentage</bold>
              </td>
            </tr>
            <tr>
              <td>Reduced</td>
              <td>27</td>
              <td>43.55</td>
            </tr>
            <tr>
              <td>Moderately reduced</td>
              <td>10</td>
              <td>16.13</td>
            </tr>
            <tr>
              <td>preserved</td>
              <td>25</td>
              <td>40.32</td>
            </tr>
            <tr>
              <td>TOTAL</td>
              <td>62</td>
              <td>100.00</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p><bold>Table 4</bold><bold>.</bold> Distribution of patients with or without heart failure and predictive factors.</p>
      <table-wrap id="tbl4">
        <label>Table 4</label>
        <table>
          <tbody>
            <tr>
              <td rowspan="2">Predictive Factors</td>
              <td colspan="2">IC</td>
              <td rowspan="2">Total</td>
              <td rowspan="2">p-value</td>
            </tr>
            <tr>
              <td>OUI</td>
              <td>NON</td>
            </tr>
            <tr>
              <td>Diabetis</td>
              <td>49</td>
              <td>4</td>
              <td>53</td>
              <td>0.0000</td>
            </tr>
            <tr>
              <td>HTA</td>
              <td>71</td>
              <td>16</td>
              <td>87</td>
              <td>0.0003</td>
            </tr>
            <tr>
              <td>Ménopause</td>
              <td>25</td>
              <td>13</td>
              <td>38</td>
              <td>0.3133</td>
            </tr>
            <tr>
              <td>Tobacco</td>
              <td>5</td>
              <td>9</td>
              <td>14</td>
              <td>0.0023</td>
            </tr>
            <tr>
              <td>Age</td>
              <td>59</td>
              <td>26</td>
              <td>85</td>
              <td>0.2156</td>
            </tr>
            <tr>
              <td>HTA/Diabetes</td>
              <td>37</td>
              <td>6</td>
              <td>43</td>
              <td>0.0270</td>
            </tr>
            <tr>
              <td>HTA/Age</td>
              <td>35</td>
              <td>4</td>
              <td>39</td>
              <td>0.0076</td>
            </tr>
            <tr>
              <td>Anemia</td>
              <td>28</td>
              <td>3</td>
              <td>31</td>
              <td>0.0214</td>
            </tr>
            <tr>
              <td>AF</td>
              <td>20</td>
              <td>9</td>
              <td>29</td>
              <td>0.10</td>
            </tr>
            <tr>
              <td>Pulmonary disease</td>
              <td>37</td>
              <td>6</td>
              <td>43</td>
              <td>0.0270</td>
            </tr>
            <tr>
              <td>Renal Faillure</td>
              <td>8</td>
              <td>3</td>
              <td>11</td>
              <td>1.0000</td>
            </tr>
            <tr>
              <td>Ischemia crisis</td>
              <td>10</td>
              <td>12</td>
              <td>22</td>
              <td>0.0029</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
    </sec>
    <sec id="sec4">
      <title>4. Discussion</title>
      <p>Our study shows that certain cardiovascular risk factors and some comorbidities are frequently associated with the occurrence of heart failure in patients with heart failure in the Medical-Surgical Cardiology Department of Donka National Hospital. They appear more frequent in certain pathologies. Furthermore, this work suggests that the more numerous these CVRFs and/or comorbidities are, the more they worsen the prognosis of heart failure patients. HF was present in 72.17% of cases. Our result is higher than that of Senegal [<xref ref-type="bibr" rid="B9">9</xref>], which found 14.28%, but lower than that of Burkina Faso [<xref ref-type="bibr" rid="B10">10</xref>], which was 84.5%. This study allowed us to demonstrate that the frequency of heart failure remains high in hospitalized patients in the Medical-Surgical Cardiology Department of Donka National Hospital. The average age of our patients was 52 ± 19.80 years. This corroborates the data in the literature which states that advanced age constitutes a risk factor for the occurrence of cardiovascular diseases.</p>
      <p>In our study series, we recorded a female predominance of 54.22% against 45.78% with a sex ratio M/F of 0.84. Hassane B M <italic>et al.</italic> also reported a female predominance in Mali [<xref ref-type="bibr" rid="B11">11</xref>]. This can be explained by the predominance of the female sex in the general Guinean population. From the point of view of cardiovascular risk factors for heart failure patients, hypertension was at the top with 85.54% followed by diabetes 59.04% and age 54.22%. Arterial hypertension remains the leading cause of HF in our countries due to its high incidence, poor screening and insufficient control [<xref ref-type="bibr" rid="B12">12</xref>]. Comorbidities were dominated by bronchopneumopathy, anemia (microcytic hypochromic in particular) and AC/AF, <italic>i.e.</italic> 44.57%, 43.37% and 24.10% respectively.</p>
      <p>The most frequent comorbidities in the study of Adoubi KA <italic>et al.</italic> [<xref ref-type="bibr" rid="B13">13</xref>] were hypertension, anemia and renal dysfunction (respectively 48%, 43.7% and 41.3%). This can be explained by poor socio-economic conditions and therapeutic non-compliance. Furthermore, the predictive factors identified positively correlated with the occurrence of heart failure in our study were: hypertension, diabetes, smoking, the association of hypertension + age and/or diabetes and comorbidities such as anemia, bronchopneumopathy and ischemic attack. Our data are comparable to those of Benin [<xref ref-type="bibr" rid="B8">8</xref>] and Morocco [<xref ref-type="bibr" rid="B14">14</xref>]. This can be explained by the change in lifestyle and dietary habits, the lack of therapeutic education, the absence of universal health coverage and non-compliance with the low-sodium diet in the elderly. The implementation of the best prophylactic measures, early screening of cardiovascular risk factors and/or comorbidities and prevention of predictive factors could delay the onset of HF in people at risk and improve their clinical condition.</p>
    </sec>
    <sec id="sec5">
      <title>5. Conclusion</title>
      <p>Heart failure is a major public health problem and is increasingly becoming a concern for health authorities in sub-Saharan Africa. Early identification and management of predictive factors can significantly reduce morbidity and mortality from heart failure.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <title>References</title>
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          <mixed-citation publication-type="other">Manuel, D., <italic>et al.</italic> (2013) Emergency Management of Heart Failure Situations. University of Lorraine, 30 p.</mixed-citation>
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