<?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.2024.142019</article-id><article-id pub-id-type="publisher-id">OJNeph-133115</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>
 
 
  Acute Kidney Injury in the Nephrology Department of the Brazzaville University Hospital: Epidemiological, Clinical and Evolutionary Aspects
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Daniel</surname><given-names>Tony Eyeni Sinomono</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>Gael</surname><given-names>Honal Mahoungou</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>Eric</surname><given-names>Gabdzali Ngab&amp;#233;</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>Audrey</surname><given-names>Missamou</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>Mavi</surname><given-names>Bouloupy</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>Richard</surname><given-names>Loumingou</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Department of Nephrology, Adolphe Ciss&amp;amp;#233; General Hospital, Pointe Noire, Congo</addr-line></aff><aff id="aff1"><addr-line>Department of Nephrology, Brazzaville University Hospital, Brazzaville, Congo</addr-line></aff><pub-date pub-type="epub"><day>02</day><month>04</month><year>2024</year></pub-date><volume>14</volume><issue>02</issue><fpage>196</fpage><lpage>215</lpage><history><date date-type="received"><day>4,</day>	<month>March</month>	<year>2024</year></date><date date-type="rev-recd"><day>12,</day>	<month>May</month>	<year>2024</year>	</date><date date-type="accepted"><day>15,</day>	<month>May</month>	<year>2024</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>
 
 
  &lt;b&gt;Introduction: &lt;/b&gt;Acute kidney injury (AKI) is defined as a sudden and reversible deterioration in renal function. It is a life-threatening condition in hospitalized patients. Our objectives were to determine the prevalence of AKI in a nephrology department, list the causes, describe the evolutionary profile and identify the factors associated with death. &lt;b&gt;Patients and &lt;/b&gt;&lt;b&gt;Methods&lt;/b&gt;&lt;b&gt;: &lt;/b&gt;We reviewed the records of patients hospitalised between 1 January 2016 and 31 October 2020 in the nephrology department of Brazzaville University Hospital. We included patients aged at least 18 years whose discharge diagnosis included the item &amp;#8220;AKI&amp;#8221;. Study variables were socio-demographic data, clinical and paraclinical signs, stage and type of AKI, etiology and evolutionary profile. &lt;b&gt;Results: &lt;/b&gt;Of the 1823 patients hospitalised, 244 (13.38%) were hospitalised for AKI. Of these, 60.2% were boys and 39.8% girls, with an average age of 47 &amp;#177; 19 years. The average consultation time was 10 &amp;#177; 6.5 days. AKI was stage 3 in 69.57% of cases. It was functional, organic and obstructive in the order of 55.28%, 36.02% and 8.69%. Dialysis was indicated in 62 patients (38.51%) and performed in 24 patients (14.9%). In-hospital mortality was 27.95%, with an average hospital stay of 9.6 &amp;#177; 5.8 days. Metabolic acidosis and anemia were the main causes of death in 14.28% and 4.35% of patients respectively. Factors associated with death were male sex, socioeconomic level, coma, indication for dialysis and absence of dialysis, with a p &lt; 0.05. &lt;b&gt;Concl&lt;/b&gt;&lt;b&gt;u&lt;/b&gt;&lt;b&gt;sion: &lt;/b&gt;AKI is more common in young adult males. Mortality is relatively low. Improving prognosis requires early management and access to dialysis.
 
</p></abstract><kwd-group><kwd>AKI</kwd><kwd> Epidemiology</kwd><kwd> Diagnosis</kwd><kwd> Evolution</kwd><kwd> Brazzaville</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Acute Kidney Injury (AKI) is defined as a sudden and potentially reversible deterioration in renal function resulting in a rise in plasma creatinine, due to the kidney’s inability to eliminate waste products from nitrogen metabolism and maintain the body’s fluid and electrolyte balance [<xref ref-type="bibr" rid="scirp.133115-ref1">1</xref>] . It can occur in people with normal renal function or in patients with pre-existing chronic kidney disease [<xref ref-type="bibr" rid="scirp.133115-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref3">3</xref>] . It is a life-threatening diagnostic and therapeutic emergency [<xref ref-type="bibr" rid="scirp.133115-ref4">4</xref>] . The problem with AKI is not its recognition, which is made easier by the contribution of biology, but rather the search for its etiology, which determines the way it is managed. It is one of the causes of in-hospital morbidity and mortality [<xref ref-type="bibr" rid="scirp.133115-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref6">6</xref>] . However, little is known about its incidence in hospitals, due to a contradictory definition, which is the corollary of the variability of diagnostic criteria, and an abundant and discordant literature [<xref ref-type="bibr" rid="scirp.133115-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref8">8</xref>] . In Europe and North America, its incidence in hospitals is estimated at between 200 and 400 cases per million population [<xref ref-type="bibr" rid="scirp.133115-ref9">9</xref>] . In the United Kingdom, according to Racha and Challiner, the incidence of AKI is 25.4%, two-thirds of which develop in hospitals [<xref ref-type="bibr" rid="scirp.133115-ref10">10</xref>] . In the United States, in a national multicenter survey carried out in 2006 in nearly 500 hospitals, the incidence of AKI was 1.9% [<xref ref-type="bibr" rid="scirp.133115-ref11">11</xref>] .</p><p>In Asia, specifically in China, it was 31.6% in 2009 [<xref ref-type="bibr" rid="scirp.133115-ref12">12</xref>] .</p><p>In Africa, the studies available on AKI are often hospital-based and single center. In Rabat, Morocco, for example, the hospital incidence rate was 20% [<xref ref-type="bibr" rid="scirp.133115-ref13">13</xref>] . In Burkina Faso, it was 18.4% [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] , and 52% in Mali and the Democratic Republic of Congo [<xref ref-type="bibr" rid="scirp.133115-ref15">15</xref>] . In the Republic of Congo, studies of AKI in adults are rare, although a study carried out in intensive care units in Pointe Noire and Brazzaville reported a prevalence of AKI of 20%, with a case fatality rate of 37% [<xref ref-type="bibr" rid="scirp.133115-ref16">16</xref>] . With the aim of contributing to the improvement of the management of AKI in hospitalised patients, we carried out this study with the general objective of determining the epidemiological, diagnostic, therapeutic and evolutionary aspects of AKI in the nephrology department of the CHU-B and more specifically to determine: the frequency of AKI in nephrology, its aetiologies, the evolutionary profile and to identify the factors associated with death.</p></sec><sec id="s2"><title>2. Patients and Methods</title><sec id="s2_1"><title>2.1. Type and Period of Study</title><p>This is a retrospective study. It covered the period from 01 January 2016 to 31 October 2020, i.e. 04 years and 10 months. Our study was carried out in the nephrology and dialysis department of the Brazzaville University Hospital Centre (B-UHC).</p></sec><sec id="s2_2"><title>2.2. Study Population</title><p>The study population consisted of all patients hospitalised on the ward during the study period. We included all patients over 18 years of age hospitalised on the ward whose discharge diagnosis included the item ARF. We excluded patients with chronic renal failure (CRF), and patients whose records were absent and/or unusable.</p></sec><sec id="s2_3"><title>2.3. Sampling</title><p>The sampling method was exhaustive. Our data sources were hospital registers and inpatient medical records. The variables studied were: sociodemographic (age, sex, socioeconomic level*, occupation) clinical (reason for hospitalization, time to consultation, history, type of AKI: pre-renal, renal, post-renal), biological (creatininaemia, urea, kalaemia, natremia, calcaemia, phosphaemia), diagnostic (stage of AKI according to the KDIGO 2012 classification**, type of AKI and its etiology), therapeutic (indications for dialysis) and evolutionary (recovery of renal function, death, chronicity). AKI was staged according to the 2012 classification of AKI by KDIGO (Kidney Disease international Global Outcomes), reported in <xref ref-type="table" rid="table1">Table 1</xref>.</p><p>The socio-economic level was classified into three groups based on professional status:</p><p>1) High socio-economic level: senior executives of the State or the private sector, import-export traders, army officers;</p><p>2) Average socio-economic level: made up of agents of the State or the private sector with a level of education equivalent to secondary school, traders, army non-commissioned officers;</p><p>3) Low socio-economic level: made up of workers, laborers, farmers, soldiers and the unemployed.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> KDIGO 2012 classification of acute renal failure [<xref ref-type="bibr" rid="scirp.133115-ref17">17</xref>] </title></caption><table><tbody><thead><tr><th align="center" valign="middle" >State</th><th align="center" valign="middle" >Creatinine</th><th align="center" valign="middle" >Urinary volume</th></tr></thead><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >&gt;0.3 mgl dl.</td><td align="center" valign="middle" >&lt;0.5 ml/kg/h for 6 - 12 h</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >1.5 - 1.9 times basal creatinine</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >2.0 - 2.9 times basal creatinine</td><td align="center" valign="middle" >&lt;0 - 5 ml/kg/h for &gt;12 h.</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >3.0 times basal creatinine</td><td align="center" valign="middle" >&lt;0.3 ml/kg/h for &gt;24 h.</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Creatinine greater than</td><td align="center" valign="middle" >Anuria for &gt;12 h.</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >4.0 mg l dl</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Start TRR.</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Less than 18 years old TFG</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >&lt;35 ml/min/1.73 m<sup>2</sup></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int. 2012; 2(1): 1-138.</p></sec><sec id="s2_4"><title>2.4. Ethical Considerations</title><p>Our study was retrospective, so data were collected with respect for patient anonymity and confidentiality.</p></sec><sec id="s2_5"><title>2.5. Statistical Analysis</title><p>The data were entered using Microsoft Excel 2016 and analysed using R version 2016 and Microsoft Excel 2016. Statistical indices were calculated, including those for central tendency (numbers, percentages) and dispersion (arithmetic mean, standard deviation). The quantitative data are presented in the form of mean&#177; standard deviation. We began by carrying out a descriptive study of the different variables associated with AKI, followed by a univariate study to identify the risk factors for death. To do this, the Odd Ratio (OR) and its confidence interval (CI) were calculated. The significance threshold was set at 95%. Confounding factors were identified. In order to identify confounding factors, the results were adjusted using the logit method, with significance at p &lt; 0.05.</p><p>The data were entered using Microsoft Excel 2016 and analysed using R software version 4.0.3. Statistical indices were calculated, including those for central tendency (numbers, percentages) and dispersion (arithmetic mean, standard deviation). Quantitative data are presented in the form of mean &#177; standard deviation, and qualitative data in the form of numbers and percentages. A univariate study was used to identify the risk factors associated with death. To do this, Odds Ratios (OR) and their confidence intervals (CI) were calculated. An adjustment for sex was made in the multivariate analysis by integrating the factors associated with death. The significance threshold for comparisons was set at p &lt; 0.05.</p><p>In total, we consulted 1823 patient files. <xref ref-type="fig" rid="fig1">Figure 1</xref> shows the flow chart for selecting the files selected for the study.</p></sec></sec><sec id="s3"><title>3. Results</title><sec id="s3_1"><title>3.1. Socio-Demographic Characteristics</title><sec id="s3_1_1"><title>3.1.1. Frequency</title><p>A total of 1823 patients were hospitalised in the nephrology department during the study period, 244 of them for AKI, representing a hospital frequency of 13.4%.</p></sec><sec id="s3_1_2"><title>3.1.2. Age, Sex, Socio-Economic Level</title><p>The mean age was 47 &#177; 19 years, with extremes of 18 and 91 years. The distribution of patients by age group is shown in <xref ref-type="table" rid="table2">Table 2</xref>.</p><p>There were 97 men (60.2%) and 64 women (39.8%), giving a sex ratio of 1.51.</p><p>Male patients had a mean age of 48&#177;18.6 years and female patients had a mean age of 45 &#177; 18.5 years.</p><p>There were 104 single patients (64.58%), 37 married patients (23%), 19 widowed patients (11.8%) and one divorced patient (0.62%).</p><p>The <xref ref-type="table" rid="table3">Table 3</xref> pr&#233;sents the socio-economic level of the patients.</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Breakdown of patients by age group (in years)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >[18 - 30]</td><td align="center" valign="middle" >42</td><td align="center" valign="middle" >26.1</td></tr><tr><td align="center" valign="middle" >[31 - 45]</td><td align="center" valign="middle" >39</td><td align="center" valign="middle" >24.2</td></tr><tr><td align="center" valign="middle" >[46 - 60]</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >21.1</td></tr><tr><td align="center" valign="middle" >[61 - 75]</td><td align="center" valign="middle" >37</td><td align="center" valign="middle" >23</td></tr><tr><td align="center" valign="middle" >&gt;75</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >5.6</td></tr></tbody></table></table-wrap><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Distribution of socio-economic level</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >Low socio-economic level</td><td align="center" valign="middle" >94</td><td align="center" valign="middle" >58.4</td></tr><tr><td align="center" valign="middle" >Average socioeconomic level</td><td align="center" valign="middle" >57</td><td align="center" valign="middle" >35.4</td></tr><tr><td align="center" valign="middle" >High socio-economic level</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >6.2</td></tr></tbody></table></table-wrap></sec></sec><sec id="s3_2"><title>3.2. Clinical Features</title><sec id="s3_2_1"><title>3.2.1. Reason for Hospitalisation</title><p>The reasons for hospitalisation are shown in <xref ref-type="table" rid="table4">Table 4</xref>.</p></sec><sec id="s3_2_2"><title>3.2.2. Consultation Period</title><p>The average time elapsed between the onset of symptoms and hospitalization was 10 &#177; 6.5 days, with extremes of 1 and 30 days.</p></sec><sec id="s3_2_3"><title>3.2.3. Background</title><p>The background is shown in <xref ref-type="table" rid="table5">Table 5</xref>.</p></sec><sec id="s3_2_4"><title>3.2.4. Diuresis</title><p>Diuresis was preserved in 86 patients (53.4%) and oligoanuria was noted in 75 patients (46.6%).</p></sec></sec><sec id="s3_3"><title>3.3. Biological Characteristics</title><sec id="s3_3_1"><title>3.3.1. Serum Creatinine and Urea</title><p>The mean serum creatinine was 701 &#177; 564 μmol/l (range 147 and 3397 μmol/l). <xref ref-type="fig" rid="fig2">Figure 2</xref> illustrates the distribution of patients according to serum creatinine levels.</p><p>The mean azotemia level was 1.8 &#177; 1.4 g/l (range 0.1 to 5.5 g/l). Azotemia was noted in 53 cases (34%).</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Breakdown by reason for hospitalization</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >Consciousness disorders</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >17.4</td></tr><tr><td align="center" valign="middle" >Edema</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >12.4</td></tr><tr><td align="center" valign="middle" >Vomiting</td><td align="center" valign="middle" >17</td><td align="center" valign="middle" >10.4</td></tr><tr><td align="center" valign="middle" >Convulsive seizures</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >10.1</td></tr><tr><td align="center" valign="middle" >Diarrhoea</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >6.8</td></tr><tr><td align="center" valign="middle" >Anuria</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >6.8</td></tr><tr><td align="center" valign="middle" >Fever</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >5.6</td></tr><tr><td align="center" valign="middle" >Lumbar fossa pain</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >5</td></tr><tr><td align="center" valign="middle" >Abdominal pain</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >4.3</td></tr><tr><td align="center" valign="middle" >Haematuria</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >2.5</td></tr><tr><td align="center" valign="middle" >Hoquet</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.8</td></tr><tr><td align="center" valign="middle" >Physical asthenia</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.8</td></tr><tr><td align="center" valign="middle" >Urinary irritation syndrome</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.8</td></tr><tr><td align="center" valign="middle" >Severe anaemia</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >1.2</td></tr><tr><td align="center" valign="middle" >Joint pain</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.6</td></tr><tr><td align="center" valign="middle" >Digestive haemorrhage</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.6</td></tr></tbody></table></table-wrap><table-wrap id="table5" ><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> Medical history</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >HBP</td><td align="center" valign="middle" >47</td><td align="center" valign="middle" >29.2</td></tr><tr><td align="center" valign="middle" >Diabetes mellitus</td><td align="center" valign="middle" >26</td><td align="center" valign="middle" >16.2</td></tr><tr><td align="center" valign="middle" >Long-term use of NSAIDs</td><td align="center" valign="middle" >24</td><td align="center" valign="middle" >15</td></tr><tr><td align="center" valign="middle" >HIV</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >7.5</td></tr><tr><td align="center" valign="middle" >Heart disease</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >3.1</td></tr><tr><td align="center" valign="middle" >Stroke</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >3.1</td></tr><tr><td align="center" valign="middle" >Tuberculosis</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >2.5</td></tr><tr><td align="center" valign="middle" >Cirrhosis of the liver</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.86</td></tr><tr><td align="center" valign="middle" >Benign tumours</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.86</td></tr><tr><td align="center" valign="middle" >Homozygous sickle cell disease</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.62</td></tr><tr><td align="center" valign="middle" >Other</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >6.8</td></tr></tbody></table></table-wrap><p>*Poly Blood transfusion (4); systemic lupus erythematosus (2); treatment with injectable aminoglycosides (2); Kaposi’s sarcoma (1); nephrotic syndrome (1).</p></sec><sec id="s3_3_2"><title>3.3.2. Electrolytic Disorders</title><p>The blood ionogram revealed: a mean natraemia of 139 &#177; 6.6 meq/l (extremes: 130 and 158 meq/l). Hyponatremia was found in 51 cases (31.7%) and hypernatremia in 21 cases (13%); mean kalaemia was 3.8 &#177; 1.3 meq/l with extremes of 0.74 and 7 mEq/l. Hypokalaemia was noted in 69 patients (42.8%), moderate hyperkalaemia in 28 cases (17.4%) and threatening hyperkalaemia in 2 cases (1.2%).</p><p>The mean calcaemia was 99 &#177; 4.4 mg/l with extremes of 80 and 110 mg/l. Hypocalcaemia was noted in 2 cases (1.2%) and hypercalcaemia (n = 1, 0.6%).</p><p>The mean serum phosphorus level was 34 &#177; 4.7 mg/l, with extremes ranging from 29 to 40 mg/l. Four of the patients had normal blood phosphorus levels.</p></sec><sec id="s3_3_3"><title>3.3.3. HIV infection</title><p>Twenty-three patients (14.3%) were HIV-positive, of whom 12 (7.6%) knew their HIV-positive status and 11 were diagnosed during hospitalization.</p></sec></sec><sec id="s3_4"><title>3.4. Staging of Acute Renal Failure (KDIGO 2012)</title><p>The distribution of patients by stage of renal failure is shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>.</p></sec><sec id="s3_5"><title>3.5. Type of Acute Renal Failure</title><p>The distribution of the type of acute renal failure is illustrated in <xref ref-type="fig" rid="fig4">Figure 4</xref>.</p></sec><sec id="s3_6"><title>3.6. Indication for Dialysis</title><p>Haemodialysis was indicated in 62 patients (38.5%) The indications for haemodialysis were:</p><p>&#183; Uremic encephalopathy: n = 32 (20%).</p><p>&#183; Persistent anuria (&gt;24 hours): n = 11 (6.8%).</p><p>&#183; Acute pulmonary Edema (APE) refractory to diuretic treatment: n = 10 (6.2%).</p><p>&#183; Severe metabolic acidosis unresponsive to conservative measures in 7 patients (4.35%).</p><p>&#183; Severe hyperkalaemia: n = 2 (1.2%).</p><p>Only 24 patients (14.9%) were able to undergo dialysis.</p></sec><sec id="s3_7"><title>3.7. Evolution</title><p>The average length of hospital stay was 9.6 &#177; 5.8 days (extremes: 1 and 28 days). One hundred and four patients were hospitalised for 10 days or less.</p><p><xref ref-type="table" rid="table6">Table 6</xref> shows the evolution of patients during hospitalization.</p><p>The average age of patients who died was 50 &#177; 22 years (extremes: 18 and 91 years). The breakdown by cause of death is shown in <xref ref-type="table" rid="table7">Table 7</xref>.</p></sec><sec id="s3_8"><title>3.8. Risk Factors for Death</title><p>The <xref ref-type="table" rid="table8">Table 8</xref> shows in analysis univariate analysis the relationship between the socio-demographic characteristics and death, in univariate analysis.</p><sec id="s3_8_1"><title>3.8.1. Relationship between Co-Morbidities and Death</title><p><xref ref-type="table" rid="table9">Table 9</xref> shows the relationship between comorbidities and death in univariate analysis.</p><table-wrap id="table6" ><label><xref ref-type="table" rid="table6">Table 6</xref></label><caption><title> Breakdown by development</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >Full kidney Function recovery</td><td align="center" valign="middle" >86</td><td align="center" valign="middle" >53.4</td></tr><tr><td align="center" valign="middle" >Deceased</td><td align="center" valign="middle" >45</td><td align="center" valign="middle" >27.9</td></tr><tr><td align="center" valign="middle" >Chronic Kidney Failure</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >13</td></tr><tr><td align="center" valign="middle" >Unknown (escapees)</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >5.6</td></tr></tbody></table></table-wrap><table-wrap id="table7" ><label><xref ref-type="table" rid="table7">Table 7</xref></label><caption><title> Breakdown of patients by cause of death</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Cause of death</th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >%</th></tr></thead><tr><td align="center" valign="middle" >Uremic encephalopathy</td><td align="center" valign="middle" >23</td><td align="center" valign="middle" >14.3</td></tr><tr><td align="center" valign="middle" >Septic shock</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >10</td></tr><tr><td align="center" valign="middle" >Hypovolaemic shock</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.8</td></tr><tr><td align="center" valign="middle" >APE</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.8</td></tr></tbody></table></table-wrap><p>APE: Acute Pulmonary Edema.</p><table-wrap id="table8" ><label><xref ref-type="table" rid="table8">Table 8</xref></label><caption><title> Relationship between socio-demographic characteristics and death</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Deceased n = 45 n (%)</th><th align="center" valign="middle" >Living n = 107 n (%)</th><th align="center" valign="middle" >OR [95% CI]</th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></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" >F</td><td align="center" valign="middle" >10 (22.2)</td><td align="center" valign="middle" >50 (46.7)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >M</td><td align="center" valign="middle" >35 (77.8)</td><td align="center" valign="middle" >57 (53.3)</td><td align="center" valign="middle" >3.1 [1.38 - 6.82]</td><td align="center" valign="middle" >0.005</td></tr><tr><td align="center" valign="middle" >Socio-economic level</td><td align="center" valign="middle" ></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" >Low</td><td align="center" valign="middle" >21 (46.7)</td><td align="center" valign="middle" >70 (65.4)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Elevated</td><td align="center" valign="middle" >7 (15.6)</td><td align="center" valign="middle" >4 (3.74)</td><td align="center" valign="middle" >5.8 [1.56 - 21.9]</td><td align="center" valign="middle" >0.01</td></tr><tr><td align="center" valign="middle" >Medium</td><td align="center" valign="middle" >17 (37.8)</td><td align="center" valign="middle" >33 (30.8)</td><td align="center" valign="middle" >1.7 [0.80 - 3.68]</td><td align="center" valign="middle" >0.172</td></tr><tr><td align="center" valign="middle" >Admission procedure</td><td align="center" valign="middle" ></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" >Referral</td><td align="center" valign="middle" >15 (33.3)</td><td align="center" valign="middle" >44 (41.1)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Intra-hospital transfer</td><td align="center" valign="middle" >30 (66.7)</td><td align="center" valign="middle" >63 (58.9)</td><td align="center" valign="middle" >1.4 [0.67 - 2.90]</td><td align="center" valign="middle" >0.377</td></tr></tbody></table></table-wrap><table-wrap id="table9" ><label><xref ref-type="table" rid="table9">Table 9</xref></label><caption><title> Relationship between comorbidities and death in univariate analysis</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Deceased n = 45 n (%)</th><th align="center" valign="middle" >Living n = 107 n (%)</th><th align="center" valign="middle" >OR [95% CI]</th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >HTA</td><td align="center" valign="middle" ></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" >No</td><td align="center" valign="middle" >31 (68,9)</td><td align="center" valign="middle" >77 (72,0)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >14 (31.1)</td><td align="center" valign="middle" >30 (28.0)</td><td align="center" valign="middle" >1.2 [0.54 - 2.48]</td><td align="center" valign="middle" >0.702</td></tr><tr><td align="center" valign="middle" >Diabetes mellitus</td><td align="center" valign="middle" ></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" >No</td><td align="center" valign="middle" >37 (82.2)</td><td align="center" valign="middle" >93 (86.9)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >8 (17.8)</td><td align="center" valign="middle" >14 (13.1)</td><td align="center" valign="middle" >1.4 [0.56 - 3.71]</td><td align="center" valign="middle" >0.461</td></tr><tr><td align="center" valign="middle" >HIV</td><td align="center" valign="middle" ></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" >No</td><td align="center" valign="middle" >43 (95.6)</td><td align="center" valign="middle" >98 (91.6)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >2 (4.4)</td><td align="center" valign="middle" >9 (8.41)</td><td align="center" valign="middle" >0.5 [0.10 - 2.44]</td><td align="center" valign="middle" >0.424</td></tr><tr><td align="center" valign="middle" >Heart disease</td><td align="center" valign="middle" ></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" >No</td><td align="center" valign="middle" >45 (100)</td><td align="center" valign="middle" >102 (95.3)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >5 (4.67)</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >0.168</td></tr><tr><td align="center" valign="middle" >Cirrhosis of the liver</td><td align="center" valign="middle" ></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" >No</td><td align="center" valign="middle" >44 (97.8)</td><td align="center" valign="middle" >106 (99.1)</td><td align="center" valign="middle" >Ref.</td><td align="center" valign="middle" >Ref.</td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >1 (2.2)</td><td align="center" valign="middle" >1 (0.9)</td><td align="center" valign="middle" >2.4 [0.15 - 39.4]</td><td align="center" valign="middle" >0.592</td></tr></tbody></table></table-wrap></sec><sec id="s3_8_2"><title>3.8.2. Multivariate Analytical Study</title><p>In multivariate analysis, after adjustment for sex, the factors associated with death are shown in <xref ref-type="table" rid="table1">Table 1</xref>0.</p><table-wrap id="table10" ><label><xref ref-type="table" rid="table1">Table 1</xref>0</label><caption><title> Risk factors for death in multivariate analysis</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Dependent: DEATH</th><th align="center" valign="middle" >OR (multivariable)</th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >F</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >M</td><td align="center" valign="middle" >2.5 [1.11 - 6.09]</td><td align="center" valign="middle" >0.032</td></tr><tr><td align="center" valign="middle" >Socio-economic level</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Low</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" >Elevated</td><td align="center" valign="middle" >5.4 [1.41 - 23.69]</td><td align="center" valign="middle" >0.016</td></tr><tr><td align="center" valign="middle" >Medium</td><td align="center" valign="middle" >1.7 [0.75 - 3.81]</td><td align="center" valign="middle" >0.201</td></tr><tr><td align="center" valign="middle" >Awareness</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td></tr><tr><td align="center" valign="middle" >Coma</td><td align="center" valign="middle" >3.2 [1.48 - 6.95]</td><td align="center" valign="middle" >0.003</td></tr><tr><td align="center" valign="middle" >Blood urea</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&lt;2.5</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≥2.5</td><td align="center" valign="middle" >1.1 [0.38 - 2.88]</td><td align="center" valign="middle" >0.913</td></tr><tr><td align="center" valign="middle" >Indication for dialysis</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >4 [ 1.54 - 10.19]</td><td align="center" valign="middle" >0.005</td></tr></tbody></table></table-wrap></sec></sec></sec><sec id="s4"><title>4. Discussion</title><sec id="s4_1"><title>4.1. Analysis of the Methodology</title><p>In Congo-Brazzaville, studies of AKI are still rare, despite the problems it poses for vital and functional prognosis in the short and medium term. The available studies are sector-based and do not provide an overall hospital prevalence rate. Ekat MH et al. carried out a descriptive and analytical study in 2013 on the prevalence and factors associated with acute renal failure in newly HIV-positive patients in Brazzaville [<xref ref-type="bibr" rid="scirp.133115-ref18">18</xref>] ; Missamou A et al. carried out a retrospective study on ARF during and after childbirth in 2017 [<xref ref-type="bibr" rid="scirp.133115-ref16">16</xref>] and Moyen E et al. carried out a study in 2019 on acute renal failure exclusively in the paediatric wards of the Brazzaville University Hospital [<xref ref-type="bibr" rid="scirp.133115-ref19">19</xref>] .</p><p>We conducted a retrospective analytical study with the aim of contributing to improving the management of AKI in the nephrology department of B-UHC.</p><p>This methodological choice was justified by the need to obtain hospital data on AKI, in particular from a department specialising in the management of kidney disease, thereby supplementing the sectoral data already available.</p><p>There are undoubtedly a number of pitfalls in this study. The first relates to the fact that the study was only carried out in a hospital department, which would obviously reduce the power of the observations and make it difficult to extrapolate the results to the general population. The second relates to the retrospective nature of the study, which generates bias in terms of lost to follow-up and data collection. During data collection, we found a large number of files that could not be used (n = 51). The exclusion of patients with chronic renal failure was justified by the fact that many of these patients do not have regular follow-up, since the diagnosis of AKI on a chronic background is made during post-hospital follow-up [<xref ref-type="bibr" rid="scirp.133115-ref20">20</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref21">21</xref>] . Despite these limitations, we were able to carry out our work within the defined period, and the results obtained were discussed with the data in the literature.</p></sec><sec id="s4_2"><title>4.2. Socio-Demographic Characteristics</title><p>AKI is a major threat to the vital prognosis of hospitalised patients, depending on the circumstances in which it occurs [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] . Our study shows that one in seven hospitalised patients (13.38%) in the nephrology department of Brazzaville University Hospital presented with AKI. Our data are in line with the sub-Saharan literature, which reveals a prevalence in nephrology departments of between 10 and 15%. Samak&#233; M et al. in 2018 in Mali found a prevalence of 11.88% in the internal medicine department of the Fousseyni Daou Hospital in Kayes [<xref ref-type="bibr" rid="scirp.133115-ref22">22</xref>] . In Uganda, the prevalence of AKI in the adult medical wards of Mulago National Referral Hospital was 16% in 2013, according to Basagha P et al [<xref ref-type="bibr" rid="scirp.133115-ref23">23</xref>] . Our data and others from sub-Saharan Africa are similar to those from Europe such as the French study conducted in 2011 by Lakhal K where the prevalence was 14% [<xref ref-type="bibr" rid="scirp.133115-ref24">24</xref>] .</p><p>AKI is more frequent in an adult hospital ward; in fact, comparing our data with those of Moyen E et al., the prevalence of AKI in the 4 paediatric wards of B-UHC was 10 times less frequent [<xref ref-type="bibr" rid="scirp.133115-ref19">19</xref>] . However, despite the specialised nature of renal disease management, AKI is less frequent in nephrology than in an intensive care unit, since Missamou et al. in 2018 found a prevalence of AKI of 20% in the intensive care units of B-UHC and A Ciss&#233; Hospital in Pointe Noire Ciy [<xref ref-type="bibr" rid="scirp.133115-ref16">16</xref>] . In our study, 60.2% of patients were male. The same finding was noted in various studies such as that of Lengani A et al. where the predominance of males was 61.98% [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] ; and Hatem O et al. in Saudi Arabia, who found a male predominance of 62% [<xref ref-type="bibr" rid="scirp.133115-ref25">25</xref>] . At any age, AKI is more frequent in males, since our data also concur with those of Moyen E et al [<xref ref-type="bibr" rid="scirp.133115-ref19">19</xref>] who also reported a male predominance in children. In univariate and multivariate analysis, male sex was a risk factor for death from AKI in our study (0.05). This could be explained by hormonal factors.</p><p>AKI patients in the nephrology department are young. The age group most affected was between 18 and 30 (26.08%). Elderly patients were very poorly represented, with only 5.6% over 75 years of age. Our data are in line with those of other African studies, where the average age varies between 40 and 55. In Morocco in 2013, Failal I et al. found a mean age of 45.8 years [<xref ref-type="bibr" rid="scirp.133115-ref26">26</xref>] . Samak&#233; M et al in Mali in 2018 [<xref ref-type="bibr" rid="scirp.133115-ref22">22</xref>] and Masewu A et al in the DRC [<xref ref-type="bibr" rid="scirp.133115-ref15">15</xref>] reported an average age of 51.61 and 51.9 respectively. This can be explained by the fact that the African population, and the Congolese population in particular, is predominantly young. The African population is predominantly young [<xref ref-type="bibr" rid="scirp.133115-ref27">27</xref>] . Our data and those in the African literature differ from those in Europe, where the average age is between 60 and 80, with a peak in the over 75s [<xref ref-type="bibr" rid="scirp.133115-ref28">28</xref>] . In fact, due to better health coverage and better-equipped modern medical facilities, life expectancy in the West is higher than in Africa [<xref ref-type="bibr" rid="scirp.133115-ref29">29</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref31">31</xref>] . Elderly subjects are also at risk of AKI, due to a senile decline in the perception of thirst and higher cardiovascular risk factors [<xref ref-type="bibr" rid="scirp.133115-ref32">32</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref33">33</xref>] . Patients with a low socio-economic level were the most represented (58.39%). The data is similar to that observed in the literature. Lengani A et al. reported in 2010 a proportion of 55.4% of patients with a low socio-economic status [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] . This finding is explained by the fact that the majority of the Congolese population is active in the end on their behalf [<xref ref-type="bibr" rid="scirp.133115-ref34">34</xref>] .</p></sec><sec id="s4_3"><title>4.3. Clinical Characteristics</title><p>The delay in consultation was 10 &#177; 6.5 days in our study population. The late recourse to modern health structures is linked to the multiple traditional treatments (herbal medicine) and therapeutic manipulations at the level of secondary health centers [<xref ref-type="bibr" rid="scirp.133115-ref35">35</xref>] .</p><p>Disturbed consciousness was the main reason for hospitalisation (17.39%). This finding in our study sample is similar to that observed in Algeria by Hanba M et al [<xref ref-type="bibr" rid="scirp.133115-ref36">36</xref>] and in the Republic of Congo by Missamou M et al [<xref ref-type="bibr" rid="scirp.133115-ref16">16</xref>] . This high frequency of patients hospitalised for disturbance of consciousness may be related to uremic encephalopathy as a result of a delay in consulting specialised facilities, but may also be part of a multivisceral failure.</p></sec><sec id="s4_4"><title>4.4. Co-Morbidities and AKI</title><p>Hypertension was common in our patients (29.19%). This figure was slightly higher than that of Lengani A et al. where the proportion of hypertension was 10.7% [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] . Diabetes mellitus was the second most common medical history (<xref ref-type="table" rid="table6">Table 6</xref>). It was observed in 26 patients (16.15%). This finding is similar to that of Hanba M et al., who reported a proportion of diabetic subjects of 11.3% [<xref ref-type="bibr" rid="scirp.133115-ref36">36</xref>] . Hypertension and diabetes mellitus are the world’s leading non-transmissible chronic diseases and are the cause of significant morbidity and mortality. Several studies have reported a high incidence of AKI in hypertensive and diabetic patients. However, despite their significant morbidity and mortality, these two diseases did not influence death in our study.</p><p>In several studies, such as Lengani’s, heart disease was observed in 11% of cases [<xref ref-type="bibr" rid="scirp.133115-ref15">15</xref>] . In our study population, the incidence of heart disease was 3.11%. Stroke was observed in 3.1% of our study population. This result is similar to that reported by Eswarappa in India (2.8%) [<xref ref-type="bibr" rid="scirp.133115-ref37">37</xref>] .</p><p>Patients with heart disease, particularly those with a collapse of the ventricular ejection fraction, are at risk of AKI [<xref ref-type="bibr" rid="scirp.133115-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref38">38</xref>] , as are patients hospitalised for stroke [<xref ref-type="bibr" rid="scirp.133115-ref16">16</xref>] . In our study, the low frequency of these two comorbidities may be explained by the location of the study: “a nephrology department”. Patients hospitalised for heart disease or stroke are managed in other departments. ARF is managed in these departments in collaboration with the nephrologists. A transfer is considered when the AKI is severe.</p></sec><sec id="s4_5"><title>4.5. Severity of AKI</title><p>More than 2/3 of AKI were at stage 3 of the KDIGO 2012 classification; explaining a high mean creatinine level (701 &#177; 564 μmol/l). This high frequency of severe AKI has also been found in other African studies. Lengani H et al. found that 73.33% of AKI were severe [<xref ref-type="bibr" rid="scirp.133115-ref39">39</xref>] . The delay in diagnosis and the limited technical resources could explain the large number of patients seen at stage 3. These data are in contrast to those from Europe and even Eastern Europe, where the frequency of severe AKI is lower, as reported by Yang Li et al. (28.6% of severe AKI) in China.</p><p>[<xref ref-type="bibr" rid="scirp.133115-ref40">40</xref>] and Conan in France (28.6%) [<xref ref-type="bibr" rid="scirp.133115-ref41">41</xref>] , despite the multicenter nature of these studies. The differences observed in the severity of AKI patients admitted to hospital are thought to be linked to the level of the healthcare system.</p></sec><sec id="s4_6"><title>4.6. AKI and Dialysis</title><p>In our study population, the indications for dialysis were high among patients with AKI hospitalised in nephrology (38.51%). However, access to dialysis was poor, with only 24 patients (14.9%) receiving dialysis. Our results are similar to those of Mokoli MV et al. in the DRC, who reported a high frequency of dialysis indications of around 45% in 320 patients hospitalised for AKI in nephrology; of these, only 17.8% were able to benefit from dialysis [<xref ref-type="bibr" rid="scirp.133115-ref42">42</xref>] . In 2008, Sayer I et al. observed a dialysis frequency of 18% [<xref ref-type="bibr" rid="scirp.133115-ref43">43</xref>] and Ben Ariba Y et al. reported a proportion of 8.1% of patients having benefited from dialysis in Tunis in 2017 [<xref ref-type="bibr" rid="scirp.133115-ref44">44</xref>] . The low accessibility to dialysis in our study could be explained by the absence of dialysis generators in the nephrology and dialysis department of Brazzaville University Hospital Center during the period of our study to date [<xref ref-type="bibr" rid="scirp.133115-ref45">45</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref46">46</xref>] . In Brazzaville the</p><p>Haemodialysis sessions for hospitalised patients are carried out in private dialysis centres, which create 2 obstacles: on the one hand, the high price of a session which is not affordable for everyone, and on the other, the selection of haemodynamically stable patients who can afford to travel outside hospital. However, results superior to ours have been described in Europe. Lins RL et al. reported an accessibility rate of 36.5% for patients requiring dialysis in Belgium in 2004 [<xref ref-type="bibr" rid="scirp.133115-ref47">47</xref>] , where renal replacement techniques are more accessible, as in many European countries [<xref ref-type="bibr" rid="scirp.133115-ref48">48</xref>] . The indications for dialysis vary according to the data in the literature, but all authors agree on certain absolute indications [<xref ref-type="bibr" rid="scirp.133115-ref49">49</xref>] .</p><p>Uremic encephalopathy and persistent anuria resistant to diuretics after 24 hours were the main indications for dialysis in our study series in the order of 19.89% and 6.82%. Elouaer Y et al. found t hat severe acidosis, APE and uremic syndrome were the main indications for haemodialysis in 27.4%, 24.3% and 16.5% [<xref ref-type="bibr" rid="scirp.133115-ref50">50</xref>] . This difference in results is due to the clinical severity on admission resulting in a delay in diagnosis, since the average duration between the onset of symptoms and arrival at hospital was high, in the order of 10 &#177; 6.5 days.</p></sec><sec id="s4_7"><title>4.7. Evolution</title><p>The outcome of AKI depends on the etiology, the speed with which it is managed and the quality of the technical support available, in particular access to a dialysis unit. Complete recovery of renal function was high in our study (53.4%). Complete recovery of renal function during AKI is a known fact according to various African studies. Ghezaiel H et al. in 2012 [<xref ref-type="bibr" rid="scirp.133115-ref51">51</xref>] , Samak&#233; M et al. in 2020 in Mali [<xref ref-type="bibr" rid="scirp.133115-ref22">22</xref>] , Haffane L et al. in 2012 in Morocco (Rabat) [<xref ref-type="bibr" rid="scirp.133115-ref52">52</xref>] , Lengani A et al. in Burkina Faso in 2010 (41.3%) [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] reported a recovery of Renal Function in the order of 63%, 49.3%, 49.5% and 41.3%. The high recovery rate in these studies as in our case can be explained by the fact that extra-renal purification is not indicated in the majority of patients, by the young age of patients, by the low number of cases of polypathology (comorbidities), and by the fact that the main cause of AKI is functional; an origin for which the management consists, among other things, of adequate and early filling, and therefore does not require a special heavy technical platform.</p><p>The course of AKI may also be marked by complications, including CKD and death [<xref ref-type="bibr" rid="scirp.133115-ref53">53</xref>] . Progression to CKD was relatively low in this study (13%). This figure is similar to that reported in Morocco by Haffane L et al. (18%) [<xref ref-type="bibr" rid="scirp.133115-ref52">52</xref>] .</p><p>In-hospital mortality was observed in 45 patients (27.9%), including 35 men and 10 women, which is high. The death rate observed in our work is the same as that observed in the African literature. Mokoli MV et al. in the DRC found a case fatality rate of 29.4% [<xref ref-type="bibr" rid="scirp.133115-ref42">42</xref>] ; Lengani A et al reported 24% [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] . Lower mortality rates were reported in Mali by Samak&#233; M et al. at 12.4% [<xref ref-type="bibr" rid="scirp.133115-ref22">22</xref>] . This variable mortality rate from one study to another is justified by the severity of the clinical picture on admission, the etiology, associated comorbidities and the need for dialysis.</p><p>In the study by Mokoli MV et al. in the DRC, septic shock (26.6%), uremic encephalopathy (25.5%), hyperkaliemia (18%) and anemia (10.6%) were the main causes of death [<xref ref-type="bibr" rid="scirp.133115-ref42">42</xref>] . Our study showed that uremic encephalopathy was the main cause of death (14.3%).</p><p>We recorded an evasion rate of 5.6%. This choice can be justified on the one hand by a lack of knowledge of the pathology within the population due to a lack of information, and on the other hand by the high cost of dialysis once it is indicated.</p></sec><sec id="s4_8"><title>4.8. Factors Associated with Death</title><p>Among the risk factors associated with death found in univariate analysis were: coma (p = 0.004), blood urea (p = 0.014) and indication for dialysis (p &lt; 0.001). These risk factors for death have been found in intra-hospital African studies [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.133115-ref42">42</xref>] .</p><p>The literature reports that coma is a risk factor associated with an increase in death in ARF patients. Mokoli MV et al., in the Democratic Republic of Congo, found coma to be a risk factor for death (OR = 3.7, p = 0.002) [<xref ref-type="bibr" rid="scirp.133115-ref42">42</xref>] . This result was also found in multivariate analysis in our study, where the proportion of deaths in patients with coma on admission was 45.1% and 21.8% in patients with normal consciousness (p = 0.003). And the risk of death in patients with coma on admission was 3 times greater than in patients with normal consciousness. Blood urea, which is indicative of high protein catabolism, was a risk factor found in univariate analysis in this study (OR = 1.3, p = 0.014). Unlike the study by Mokoli MV et al. in which blood urea was a multivariate predictor of death (OR = 1, p = 0.035) [<xref ref-type="bibr" rid="scirp.133115-ref42">42</xref>] and Chertow GM in 2006 in California in the USA [<xref ref-type="bibr" rid="scirp.133115-ref53">53</xref>] , our study excluded this factor in the multivariate study (p = 0.913). Blood urea and coma reflect the severity of AKI. Severe AKI accounted for more than 2/3 of our sample. Patients with severe AKI appropriate management. This severity indicates the need for urgent haemodialysis, which is not widely available in our context (only 14.9% of urgent dialysis indications were implemented). Mortality was higher in patients requiring ESRD (56.9%) than in those for whom ESRD was not indicated (12.8%). The risk of death in patients for whom haemodialysis was indicated was multiplied by 3.90 (p = 0.05). Dialysis remains the key to improving vital prognosis in the management of AKI.</p><p>In our study, the proportion of deaths in men was 77.8% compared with 22.2% in women, with a statistically significant difference (p = 0.005), and the risk of death in men was 3 times higher than in women. This finding was confirmed in multivariate analysis (OR = 2.52; p = 0.032). Conversely, in most studies, gender does not appear to be associated with death. Masewu A et al. reported a non-significant difference in the DRC (p = 0.32). [<xref ref-type="bibr" rid="scirp.133115-ref11">11</xref>] and in East Asia (China), Yang Li et al. report a p = 0.80 [<xref ref-type="bibr" rid="scirp.133115-ref40">40</xref>] .</p><p>Also in our work, the high socio-economic level in multivariate analysis was significantly associated with death (OR = 5.43, p = 0.016). This finding seems to be confirmed in the work of Lengani A et al. [<xref ref-type="bibr" rid="scirp.133115-ref14">14</xref>] in Burkina Faso with a significant statistical difference (p = 0.005). This trend in socio-economic level could be explained by the lack of health coverage in our country and by the fact that functional causes are the primary cause of AKI, even though in the study by Lengani et al, this cause comes in 2nd place after organic causes. Gastroenteritis, the main cause of AKI in our sample, is a reason for hospitalization, particularly in affluent patients. In middle-class and especially disadvantaged patients, it is often treated by self-medication and simple oral rehydration at home. These patients are more likely to consult a doctor for this symptom if they have an associated co-morbidity, such as HIV, or signs of severity [<xref ref-type="bibr" rid="scirp.133115-ref54">54</xref>] .</p><p>With the exception of blood urea, multivariate analysis confirmed all the above risk factors. The failure to confirm blood urea as a risk factor for death from AKI in our study may be explained by the importance of dialysis indications in the risk of death. Whatever the indication for emergency dialysis, because of the presence of severe AKI, blood urea remained high. The mean blood urea level in our study was 1.8 &#177; 1.4 g/l.</p></sec></sec><sec id="s5"><title>5. Conclusions</title><p>AKI is a medical emergency, and its frequency is high in the nephrology department of Brazzaville University Hospital. Young people between the ages of 18 and 30 are the most affected, with males predominating. Etiologies were dominated by functional causes. The severe form (KDIGO 2012 stage 3) was the most common, with a high case fatality rate. The factors associated with death were male gender, socioeconomic level, coma and the need for dialysis.</p><p>The problems posed by this condition in the Congo are essentially linked to treatment. Biological and morphological tests, medical treatment and follow-up are expensive. Haemodialysis, which is indicated for severe forms of the disease, is non-existent in hospital departments and expensive in private centres, thus limiting the overall management of patients.</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>Eyeni Sinomono, D.T., Mahoungou, G.H., Gandzali Ngab&#233;, E., Missamou, A., Bouloupy, M. and Loumingou, R. (2024) Acute Kidney Injury in the Nephrology Department of the Brazzaville University Hospital: Epidemiological, Clinical and Evolutionary Aspects. Open Journal of Nephrology, 14, 196-215. https://doi.org/10.4236/ojneph.2024.142019</p></sec></body><back><ref-list><title>References</title><ref id="scirp.133115-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Bellomo, R., Kellum, J.A. and Ronco, C. 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