<?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.2022.124042</article-id><article-id pub-id-type="publisher-id">OJNeph-121679</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>
 
 
  COVID-19 Infection and Acute Kidney Injury: About 43 Cases Report Collected at the Nephrology Department of the Farah Polyclinic in Abidjan
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Badomta</surname><given-names>Dolaama</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>Serge</surname><given-names>Didier Konan</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>Sery</surname><given-names>Patrick Diopoh</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>Mohamed</surname><given-names>Alex Moudachirou</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>Komlan</surname><given-names>Georges Tona</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>Eyram</surname><given-names>Yoan Makafui Amekoudi</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>Mawufemo</surname><given-names>Claude Tsevi</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>Kouamé</surname><given-names>Hubert Yao</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff3"><addr-line>Nephrology Department, Teaching Hospital of Kara, Lome, Togo</addr-line></aff><aff id="aff2"><addr-line>Nephrology Department, Teaching Hospital of Treichville, Treichville, Cote d’Ivoire</addr-line></aff><aff id="aff1"><addr-line>Farah Polyclinic, Abidjan, Cote d’Ivoire</addr-line></aff><aff id="aff4"><addr-line>Nephrology and Hemodialysis Department, Teaching Hospital of Sylvanus Olympio, Lome, Togo</addr-line></aff><pub-date pub-type="epub"><day>26</day><month>10</month><year>2022</year></pub-date><volume>12</volume><issue>04</issue><fpage>410</fpage><lpage>425</lpage><history><date date-type="received"><day>24,</day>	<month>September</month>	<year>2022</year></date><date date-type="rev-recd"><day>4,</day>	<month>December</month>	<year>2022</year>	</date><date date-type="accepted"><day>7,</day>	<month>December</month>	<year>2022</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: Acute kidney injury (AKI) is one of the increasingly described complications of coronavirus infection. 
  Objectives: To identify factors associated with death in patients with acute kidney injury (AKI) during Coronavirus disease (COVID-19) in Abidjan, C?te d’Ivoire. 
  Material and Method: This was a monocentric retrospective analytical study of all patients over 18 years of age with AKI during COVID-19 at the Farah Polyclinic in Abidjan, C?te d’Ivoire. AKI was defined and ranked according to Kidney Disease Improving Global Outcomes (KDIGO) 2012. The data were collected from the medical record and processed using RStudio. 
  Results: Forty-three cases were collected. The average age was 58.5 12 years. The sex ratio (M/F) was 4.4. The main comorbidities were high blood pressure (60.4%) and diabetes (37.2%). AKI was at KDIGO stage 3 in 58%, KDIGO 2 in 21% and KDIGO 1 in 21%. The diagnosis of acute tubular necrosis was retained in 44.2% of patients followed by acute functional kidney injury in 32.6%. Hemodialysis was initiated in 48.8% of cases. The main indication of dialysis was anuria (46.6%). In total, 55.8% of patients died. Factors associated with death were KDIGO stage (p = 0.049), and invasive ventilation (p &lt; 0.001) associated with the risk of death in univariate analysis. 
  Conclusion: Mortality is high in patients with AKI during COVID-19 infection. 
 
</p></abstract><kwd-group><kwd>Coronavirus</kwd><kwd> Acute Kidney Injury</kwd><kwd> Abidjan</kwd><kwd> 2020</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>A new pathogen emerging since November 2019, SARS-CoV-2 (Severe Acute Respiratory Syndrome CoronaVirus-2) is a virus responsible for Coronavirus disease (COVID-19) [<xref ref-type="bibr" rid="scirp.121679-ref1">1</xref>]. The virus has spread to the world, including Africa. It is responsible for systemic damage, including kidney damage, resulting in high mortality [<xref ref-type="bibr" rid="scirp.121679-ref2">2</xref>]. Indeed, this kidney involvement is associated with the occurrence of major complications independently of comorbidities and other risk factors. The mechanisms and type of kidney involvement during infection with the new coronavirus are numerous [<xref ref-type="bibr" rid="scirp.121679-ref3">3</xref>].</p><p>Currently, several studies showed that the mortality rate of COVID-19 patients with acute kidney injury is high, ranging from 8% to 23% [<xref ref-type="bibr" rid="scirp.121679-ref2">2</xref>]. One study indicated that 6.7% of patients with SARS-CoV-2 may develop impaired kidney function, and the mortality rate for those with acute kidney injury is 91.7% [<xref ref-type="bibr" rid="scirp.121679-ref4">4</xref>].</p><p>In Africa, several studies were conducted on kidney disease during COVID-19 [<xref ref-type="bibr" rid="scirp.121679-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.121679-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.121679-ref7">7</xref>]. Few studies were conducted in C&#244;te d’Ivoire. Hence this work, whose main objective is to determine the factors associated with death in patients with acute kidney injury during COVID-19. Specifically, it involved describing the demographic, clinical, para-clinical characteristics of patients with acute kidney injury during COVID-19, describing the evolution and prognosis of patients with acute kidney injury during COVID-19, and identifying factors associated with the death of patients with acute kidney injury during COVID-19.</p></sec><sec id="s2"><title>2. Patients and Methods</title><sec id="s2_1"><title>2.1. Pattern, Framework, Population and Period of Study</title><p>This is an analytical retrospective study covering the period from March 1, 2020 to April 30, 2021. Patients were monitored monthly for 03 months. The Farah Polyclinic in Abidjan, the only center where we were able to obtain the data exploitation authorizations, served as a framework for our study.</p><p>The nephrology-dialysis service consists of 2 resident nephrologists, 1 resident nurse, 2 temporary nurses and 4 nursing assistants. The hemodialysis unit has 6 hemodialysis generators, 1 of which in the resuscitation department. Activities include clinical nephrology, conventional hemodialysis and consultations.</p><p>The source population consisted of positive COVID-19 patients seen in consultation or hospitalization for nephrological advice in the face of increased creatinine.</p></sec><sec id="s2_2"><title>2.2. Inclusion and Non-Inclusion Criteria</title><p>We included patients with acute kidney injury during coronavirus disease. The date of inclusion was the date of diagnosis of acute kidney injury.</p><p>Chronic kidney injury patients with hemodialysis and patients transferred to another hospital were not included.</p></sec><sec id="s2_3"><title>2.3. Data Collection</title><p>The data were collected from patients files by the nephrologists. They were collected using a standardized survey form.</p></sec><sec id="s2_4"><title>2.4. Variables Studied</title><p>The variables collected were:</p><p>• Socio-demographic data: age (years), gender;</p><p>• Clinical data: comorbidities, systolic and diastolic blood pressure (mmHg), temperature in degree Celsius, respiratory rate (per minute), pulsed oxygen saturation (%);</p><p>• Biological data: hemoglobin levels (g/dl), uremia (g/l), creatinine (mg/l), kalemia (mmol/l), CPR reactive C protein in mg/L;</p><p>• Radiological data: alveolar opacities, interstitial, pleurisy;</p><p>• Data from the positive diagnosis of Coronavirus infection;</p><p>• Type of renal involvement: based on data from the clinic;</p><p>• Patient progression: death or not, recovery of kidney function.</p></sec><sec id="s2_5"><title>2.5. Operational Definition</title><p>The positive diagnosis of coronavirus infection was made on the basis of positive PCR or positive IgM serology or CT lesions in favor (areas of frosted glass, which correspond to a moderate increase in the density of the pulmonary parenchyma secondary to edema, bilateral and multifocal, rather peripheral and rather in the lower and posterior regions).</p><p>The diagnosis of acute kidney injury was made and classified according to the Kidney Diseases Improving Global Outcomes (KDIGO) 2012 [<xref ref-type="bibr" rid="scirp.121679-ref8">8</xref>].</p><p>High blood pressure was defined as a systolic blood pressure greater than 140 mmHg and/or a diastolic blood pressure greater than 90 mmHg.</p><p>Low blood pressure: systolic blood pressure less than 90 mmHg.</p><p>Respiratory distress was defined as a breathing rate greater than 20 cycles per minute with or without oxygen saturation of less than 90%.</p><p>Anemia was defined as hemoglobin levels below 12 g/dl in women and below 13 g/dl in men.</p><p>Hyperkalemia is defined by a kalemia greater than 5.3 mmol/l and hypokalemia by a kalemia less than 3.5 mmol/l.</p><p>Severe uremia is defined as uremia greater than 2 g/l.</p></sec><sec id="s2_6"><title>2.6. Data Analysis</title><p>The data was analyzed using R Studio software version 1.4.1717. The aim was to present the means, standard deviation, minimum, maximum for quantitative variables and percentages for binary and qualitative variables.</p><p>A univariate analysis by comparison of groups according to the main judgment criterion was performed by applying the Pearson Chi-2 test for categorical variables or the exact Fischer test for continuous variables. The significance threshold was set at p-value below 0.05.</p><p>Univariate and multivariate logistic regression was performed in order to investigate the associated factors. The explanatory variables were certain socio-demographic, clinical and biological variables. Variables statistically associated with death in univariate analysis with a degree of significance p 0.20 were introduced into the initial model. Multivariate analysis estimated the odd-ratio (OR) and its 95% confidence interval for each selected variable. After obtaining the final model, interactions were sought between the various variables of the final model by including interaction terms (product of the two variables concerned) in the model and by checking their non significance. The adequacy of the model was verified based on the R<sup>2</sup> value.</p></sec><sec id="s2_7"><title>2.7. Ethical and Administrative Considerations</title><p>The authorizations from the medical director of the Farah Polyclinic and the head of the Nephrology-Dialysis unit at the Farah Polyclinic were obtained. Anonymity was respected.</p></sec></sec><sec id="s3"><title>3. Results</title><sec id="s3_1"><title>3.1. Descriptive Analysis</title><p>A total of 43 patients met the including criteria during the study period. The majority (58%) were classified as Stage 3 according to the KDIGO classification (<xref ref-type="fig" rid="fig1">Figure 1</xref>). The average age was 58.5 12 years with extremes of 32 and 88 years. The most observed age group was between 60 and 70 years (32.5%). The Male/Female sex ratio was 4.4.</p><p>The comorbidities found were high blood pressure in 58.1% of cases and diabetes in 34.9% of cases.</p><p>The diagnosis of Coronavirus infection was made in 11.6% of cases with RT-PCR, 74.4% with CT lesions and 14% with positive Covid IgM serology.</p><p>Only 1 patient had low blood pressure and 6 (14%) had grade 1 or 2 high blood pressure. Respiratory distress was present in 60.5% of patients and fever 16.3% of patients. The mean hemoglobin level was 10.8 g/dl with extremes of 5.2 and 16.3 g/dl. The average CRP was 30.81 mg/l. All patients had a CRP greater than 6 mg/l of which 4 (9.3%) had a CRP &lt; 30 mg/l, 8 (18.6%) between 30 - 60 mg/l and 27 (62.8%) a CRP 60 mg/l. Uremia and creatinine were averaging 1.9 g/L (extremes of 0.4 g/L and 4.8 g/L) and 78.7 mg/L (extremes of 15 mg/L and 240 mg/L), respectively. The mean kalemia was 4.6 mmol/l (extremes of 2 mmol/l and 6.9 mmol/l).</p><p>For the pleuropulmonary lesions on CT, they were represented by pleurisy, alveolar pneumonia and interstitial pneumonia respectively in 46.5%, 69.8% and 97.7%. The type of renal involvement was dominated by acute tubular necrosis in 44.2% of cases followed by acute functional kidney injury in 32.6% of cases. It was undetermined in 23.3%.</p><p>The treatments received were antibiotics (93%), corticosteroids (65.1%), anticoagulants (65.1%), vasoactive amines (34.9%), non-invasive ventilation (9.3%), invasive ventilation (44.2%) and hemodialysis (48.8%). Indications of hemodialysis were dominated by anuria (35%) and hyperkalemia (35%), followed by severe uremia (25%) and PAO (5%).</p><p>There is a statistically significant difference by KDIGO stage in gender (p = 0.01), kidney involvement type (p = 0.001), hemodialysis treatment (p = 0.006) and kidney function evolution (p = 0.02) (<xref ref-type="table" rid="table1">Table 1</xref>). In terms of gender, there were more women in the KDIGO 2 stage (55.6%), whereas men predominated in the KDIGO 1 (100%) and KDIGO 3 stages (84%). In terms of type of kidney involvement, the majority of KDIGO 1 patients (55.6%) had functional kidney injury; stage 2 was also dominated by functional kidney injury in 44.4% of cases; however, stage 3 had a high proportion of acute tubular necrosis (68%). Sixty-eight (68%) of KDIGO 3 patients had been hemodialysis (<xref ref-type="table" rid="table1">Table 1</xref>). Stages 1 and 3 had the highest proportion of deaths, respectively 77.8% and 60%, in contrast to stage 2, which had a higher proportion (44.4%) of kidney function recovery (<xref ref-type="table" rid="table1">Table 1</xref>).</p></sec><sec id="s3_2"><title>3.2. Factors Associated with the Risk of Death</title><p>In univariate analysis, age (p = 0.0109), respiratory distress (p = 0.01), KDIGO stage (p = 0.049), vasoactive amines (p = 0.0068) and invasive ventilation (p &lt; 0.001) were associated with the risk of death (<xref ref-type="table" rid="table2">Table 2</xref>). In multivariate analysis, KDIGO stage 2 (OR = 0.14 [CI = 0 - 0.1]; p = 0.0148), KDIGO Stage 3 (OR = 0.7; 95% CI = 0 - 0.1; p = 0.0492) were protector factor associated to death. Invasive ventilation (OR = 22.5; 95% CI = 8.7 - 207.7; p = 0.0120) was associated with the risk of death (<xref ref-type="table" rid="table2">Table 2</xref>). Survival was better in KDIGO 2 patients but the difference was not significant (p = 0.082) (<xref ref-type="fig" rid="fig2">Figure 2</xref>). According to Kaplan Meyer curve, the probability of survival was better when the patient had not benefited from invasive ventilation (p = 0.0007) (<xref ref-type="fig" rid="fig3">Figure 3</xref>).</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Patients general characteristics</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Characteristics</th><th align="center" valign="middle" >Total (N = 43)</th><th align="center" valign="middle" >KDIGO 1 (n = 9)</th><th align="center" valign="middle" >KDIGO 2 (n = 9)</th><th align="center" valign="middle" >KDIGO 3 (n = 25)</th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >Age</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><td align="center" valign="middle" >0.9116</td></tr><tr><td align="center" valign="middle" >&lt;60 years</td><td align="center" valign="middle" >79% (34/43)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >66.7% (6/9)</td><td align="center" valign="middle" >52% (13/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≥60 years</td><td align="center" valign="middle" >21% (9/43)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >48% (12/25)</td><td align="center" valign="middle" ></td></tr><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><td align="center" valign="middle" >0.01403</td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >79% (34/43)</td><td align="center" valign="middle" >100% (9//9)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >84% (21/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >21% (9/43)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >16% (4/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Comorbidities</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><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hypertension</td><td align="center" valign="middle" >58% (25/43)</td><td align="center" valign="middle" >77.8% (7/9)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >56% (14/25)</td><td align="center" valign="middle" >0.4014</td></tr><tr><td align="center" valign="middle" >Diabetes</td><td align="center" valign="middle" >34.9% (15/43)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >24% (6/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Heart diseases</td><td align="center" valign="middle" >14% (6/43)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >12 (3/25)</td><td align="center" valign="middle" >0.143</td></tr><tr><td align="center" valign="middle" >Clinical signs</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><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hypotension</td><td align="center" valign="middle" >2.3% (1/43)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >11,1% (1/9)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0.4186</td></tr><tr><td align="center" valign="middle" >Fever</td><td align="center" valign="middle" >16.3% (7/43)</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >20% (5/25)</td><td align="center" valign="middle" >0.5102</td></tr><tr><td align="center" valign="middle" >Respiratory distress</td><td align="center" valign="middle" >60.5% (26/43)</td><td align="center" valign="middle" >66.7% (6/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >68% (17/25)</td><td align="center" valign="middle" >0.7039</td></tr><tr><td align="center" valign="middle" >Biological signs</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><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hemoglobin &lt; 12 g/dl</td><td align="center" valign="middle" >37.2% (16/43)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >32% (8/25)</td><td align="center" valign="middle" >0.4717</td></tr><tr><td align="center" valign="middle" >Hyperkalemia</td><td align="center" valign="middle" >27.9% (12/43)</td><td align="center" valign="middle" >11.1% (1/9)</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >36% (9/25)</td><td align="center" valign="middle" >0.3357</td></tr><tr><td align="center" valign="middle" >Uremia (g/l)</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><td align="center" valign="middle" >0.1875</td></tr><tr><td align="center" valign="middle" >&lt;2</td><td align="center" valign="middle" >51.2% (22/43)</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >60% (15/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≥2</td><td align="center" valign="middle" >48.8% (21/43)</td><td align="center" valign="middle" >77.8% (7/9)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >40% (10/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >CT lesions</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><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Interstitial</td><td align="center" valign="middle" >51.2% (22/43)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >56% (14/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Alveolar</td><td align="center" valign="middle" >18.6% (8/43)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >24% (6/25)</td><td align="center" valign="middle" >0.5941</td></tr><tr><td align="center" valign="middle" >Pleurisy</td><td align="center" valign="middle" >46.5% (20/43)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >52% (13/25)</td><td align="center" valign="middle" >0.7667</td></tr><tr><td align="center" valign="middle" >Type of kidney involvement</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><td align="center" valign="middle" >0.00124</td></tr><tr><td align="center" valign="middle" >ATN</td><td align="center" valign="middle" >44.2% (19/43)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >68% (17/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >FKI</td><td align="center" valign="middle" >32.6% (14/43)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >20% (5/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Not determined</td><td align="center" valign="middle" >23.3% (10/43)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >12% (3/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Duration of the 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><td align="center" valign="middle" >0.4306</td></tr><tr><td align="center" valign="middle" >&lt;7 days</td><td align="center" valign="middle" >14% (6/43)</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >16% (4/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≥7 days</td><td align="center" valign="middle" >86% (37/43)</td><td align="center" valign="middle" >77.8% (7/9)</td><td align="center" valign="middle" >100% (9/9)</td><td align="center" valign="middle" >84% (21/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Treatment</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><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Antibiotics</td><td align="center" valign="middle" >93% (40/43)</td><td align="center" valign="middle" >100% (9/9)</td><td align="center" valign="middle" >100% (9/9)</td><td align="center" valign="middle" >88% (22/25)</td><td align="center" valign="middle" >0.5624</td></tr><tr><td align="center" valign="middle" >Anticoagulants</td><td align="center" valign="middle" >65.1% (28/43)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >76% (19/25)</td><td align="center" valign="middle" >0.1872</td></tr><tr><td align="center" valign="middle" >Corticosteroids</td><td align="center" valign="middle" >65.1% (28/43)</td><td align="center" valign="middle" >44.4% (4/9)</td><td align="center" valign="middle" >77.8% (7/9)</td><td align="center" valign="middle" >68% (17/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Vasoactive amines</td><td align="center" valign="middle" >34.9% (15/43)</td><td align="center" valign="middle" >55.6% (5/9)</td><td align="center" valign="middle" >11.1% (1/9)</td><td align="center" valign="middle" >36% (9/25)</td><td align="center" valign="middle" >0.1501</td></tr><tr><td align="center" valign="middle" >Invasive ventilation</td><td align="center" valign="middle" >44.2% (19/43)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >52% (13/25)</td><td align="center" valign="middle" >0.3454</td></tr><tr><td align="center" valign="middle" >Hemodialysis</td><td align="center" valign="middle" >48.8% (21/43)</td><td align="center" valign="middle" >11.1% (1/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >68% (17/25)</td><td align="center" valign="middle" >0.00685</td></tr><tr><td align="center" valign="middle" >Evolution</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><td align="center" valign="middle" >0.02758</td></tr><tr><td align="center" valign="middle" >Death</td><td align="center" valign="middle" >55.8% (24/43)</td><td align="center" valign="middle" >77.8% (7/9)</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >60% (15/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Chronic</td><td align="center" valign="middle" >16.3% (7/43)</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >33.3% (3/9)</td><td align="center" valign="middle" >8% (2/25)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Recovery</td><td align="center" valign="middle" >27.9% (12/43)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >44.4 (%4/9)</td><td align="center" valign="middle" >32% (8/25)</td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>ATN: Acute Tubular Necrosis, FKI: Functional Kidney Injury.</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Factors associated with the risk of death</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >n</th><th align="center" valign="middle" >Death</th><th align="center" valign="middle" >Univariate analysis</th><th align="center" valign="middle" >p-value</th><th align="center" valign="middle" >Multivariate model</th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >Age (ans)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.0109*</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.0666</td></tr><tr><td align="center" valign="middle" >&lt;60</td><td align="center" valign="middle" >22</td><td align="center" valign="middle" >36.4% (8/22)</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" >≥60</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >76.2% (16/21)</td><td align="center" valign="middle" >5.6 [1.56 - 22.9]</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >2.8 [1.14 - 19.3]</td><td align="center" valign="middle" ></td></tr><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" >0.4431</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >44.4% (4/9)</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" >Male</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >58.8% (20/34)</td><td align="center" valign="middle" >1.7 [0.4 - 8.3]</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" >Comorbidities</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><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" >25</td><td align="center" valign="middle" >56% (14/25)</td><td align="center" valign="middle" >1.0 [0.3 - 3.4]</td><td align="center" valign="middle" >0.9</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Diabetes</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >46.7% (7/15)</td><td align="center" valign="middle" >0.5 [0.1 - 2]</td><td align="center" valign="middle" >0.3787</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Clinical signs</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><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hypotension</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >0.4418</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Fever</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >85.7% (6/7)</td><td align="center" valign="middle" >6.8 [1 - 137]</td><td align="center" valign="middle" >0.09</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Respiratory distress</td><td align="center" valign="middle" >26</td><td align="center" valign="middle" >73.1% (19/26)</td><td align="center" valign="middle" >19 [2.7 - 39]</td><td align="center" valign="middle" >0.01*</td><td align="center" valign="middle" >1.36 [1.5 - 3.8]</td><td align="center" valign="middle" >0.7917</td></tr><tr><td align="center" valign="middle" >Biological signs</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><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Haemoglobin &lt; 12 g/dl</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >62.5% (10/16)</td><td align="center" valign="middle" >1.5 [0.4 - 5.7]</td><td align="center" valign="middle" >0.4978</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Hyperkalemia</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >75% (9/12)</td><td align="center" valign="middle" >3 [0.7 - 15.7]</td><td align="center" valign="middle" >0.1517</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Uremia (g/l)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.4332</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&lt;2</td><td align="center" valign="middle" >22</td><td align="center" valign="middle" >50% (11/22)</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" >≥2</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >61.9% (13/21)</td><td align="center" valign="middle" >1.6 [0.4 - 5.6]</td><td align="center" valign="middle" >0.4332</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >CRP (mg/l)</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><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&lt;30</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >&#188; (25%)</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" >[30 - 60[</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >3/8 (37.5%)</td><td align="center" valign="middle" >1.8 [0.1 - 46.2]</td><td align="center" valign="middle" >0.6670</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >≥60</td><td align="center" valign="middle" >27</td><td align="center" valign="middle" >19/27 (70.4%)</td><td align="center" valign="middle" >7.1 [0.7 - 156.8]</td><td align="center" valign="middle" >0.1102</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >CT lesions</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><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Interstitial</td><td align="center" valign="middle" >42</td><td align="center" valign="middle" >57.1% (24/42)</td><td align="center" valign="middle" >+</td><td align="center" valign="middle" >0.9944</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Alveolar</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >63.3% (19/30)</td><td align="center" valign="middle" >2.8 [0.7 - 11.2]</td><td align="center" valign="middle" >0.1375</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Pleurisy</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >55% (11/20)</td><td align="center" valign="middle" >0.9 [0.3 - 3.1]</td><td align="center" valign="middle" >0.9202</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >KDIGO stage</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.04964</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >77.8% (7/9)</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" >2</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >22.2% (2/9)</td><td align="center" valign="middle" >0.08 [0 - 0.6]</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.14 [0 - 0.1]</td><td align="center" valign="middle" >0.0148*</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >25</td><td align="center" valign="middle" >60% (15/25)</td><td align="center" valign="middle" >0.4 [1.1 - 2.2]</td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.7 [0 - 0.1]</td><td align="center" valign="middle" >0.0492*</td></tr><tr><td align="center" valign="middle" >Type of kidney involvement</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.5374</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >FKI</td><td align="center" valign="middle" >14</td><td align="center" valign="middle" >42.8% (6/14)</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" >NTA</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >60% (6/10)</td><td align="center" valign="middle" >2.2 [0.6 - 9.8]</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" >Not determined</td><td align="center" valign="middle" >19</td><td align="center" valign="middle" >63.2% (12/19)</td><td align="center" valign="middle" >2 [0.3 - 11.1]</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" >Duration of the 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" >0.5953</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >&lt;7 days</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >66.7% (4/6)</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" >≥7 days</td><td align="center" valign="middle" >37</td><td align="center" valign="middle" >54.1% (20/37)</td><td align="center" valign="middle" >0.6 [0.1 - 3.4]</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" >Treatment</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><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Antibiotics</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >52.5% (21/40)</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >0.2425</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Anticoagulants</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >60.7% (17/28)</td><td align="center" valign="middle" >1.7 [0.4 - 6]</td><td align="center" valign="middle" >0.3787</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Corticosteroids</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >53.6% (15/28)</td><td align="center" valign="middle" >0.7 [0.2 - 2.7]</td><td align="center" valign="middle" >0.6861</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Vasoactive amines</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >86.7% (13/15)</td><td align="center" valign="middle" >10 [2.2 - 72.7]</td><td align="center" valign="middle" >0.0068*</td><td align="center" valign="middle" >0.6 [0.2 - 3.9]</td><td align="center" valign="middle" >0.2975</td></tr><tr><td align="center" valign="middle" >Invasive ventilation</td><td align="center" valign="middle" >19</td><td align="center" valign="middle" >89.5% (17/19)</td><td align="center" valign="middle" >20 [4.4 - 154.7]</td><td align="center" valign="middle" >&lt;0.001*</td><td align="center" valign="middle" >22.5 [8.7 - 207.7]</td><td align="center" valign="middle" >0.0120*</td></tr><tr><td align="center" valign="middle" >Hemodialysis</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >52.4% (11/21)</td><td align="center" valign="middle" >0.7 [0.2 - 2.5]</td><td align="center" valign="middle" >0.6581</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>ATN: Acute Tubular Necrosis; FKI: Functional Kidney Injury.</p></sec></sec><sec id="s4"><title>4. Discussion</title><p>We report 43 cases of AKI on Covid 19 infection. In Ghana, Afriyie-Mensah and al. found 36.4% of ARF [<xref ref-type="bibr" rid="scirp.121679-ref9">9</xref>] in a population of 22 patients infected with covid 19 and not having pre-existing kidney injury. Ketfi found 10.7% hypercreatinemia (serum creatinine greater than 14 mg/l) in Algeria [<xref ref-type="bibr" rid="scirp.121679-ref10">10</xref>] in a population of 86 patients. Arrocha had reported 37.8% of AKI in a population of 82 patients in Bolivia [<xref ref-type="bibr" rid="scirp.121679-ref11">11</xref>]. All of these single-center studies reported less than 100 cases of AKI during COVID-19 with different methodologies.</p><p>The average age in our series was 58 years. Gupta [<xref ref-type="bibr" rid="scirp.121679-ref12">12</xref>] and Chan [<xref ref-type="bibr" rid="scirp.121679-ref13">13</xref>] in the USA reported an average age of 62 and 71 in 2 different series. Ibrahim [<xref ref-type="bibr" rid="scirp.121679-ref14">14</xref>] had found an average age of 65 years and Rubin [<xref ref-type="bibr" rid="scirp.121679-ref15">15</xref>] had found 61 years in Bordeaux (France). The age group most represented in Gupta in the United States was over 80. At Afriyie-Mensah in Ghana, 63.6% were at least 60 years old. Guti&#233;rrez in Spain [<xref ref-type="bibr" rid="scirp.121679-ref16">16</xref>] found that those over 65 represented 91.8% of the population. There is a clear predominance of the elderly.</p><p>The male/female sex ratio was 4 in Bordeaux (Rubin and et al.) [<xref ref-type="bibr" rid="scirp.121679-ref15">15</xref>], 2 in Nigeria (Ibrahim and et al.) [<xref ref-type="bibr" rid="scirp.121679-ref14">14</xref>], 9.4 in India (Sampathkumar and et al.) [<xref ref-type="bibr" rid="scirp.121679-ref17">17</xref>], and 2.5 in the USA in Gupta’s series. Male predominance was also reported in our study. Male gender is already identified as a factor associated with the occurrence of an AKI during Covid [<xref ref-type="bibr" rid="scirp.121679-ref18">18</xref>] [<xref ref-type="bibr" rid="scirp.121679-ref19">19</xref>]. One hypothesis was the overexpression of ACE2 in male subjects [<xref ref-type="bibr" rid="scirp.121679-ref20">20</xref>]. Androgenic hormones would also play a role in increasing the expression of ACE2 [<xref ref-type="bibr" rid="scirp.121679-ref21">21</xref>].</p><p>High blood pressure was a comorbidity present in 60.4% of patients. The prevalence of hypertension was 71.7% in the USA [<xref ref-type="bibr" rid="scirp.121679-ref12">12</xref>], 16.7% in Nigeria [<xref ref-type="bibr" rid="scirp.121679-ref14">14</xref>] and 59% in India [<xref ref-type="bibr" rid="scirp.121679-ref17">17</xref>]. Gutierrez reported that 57.9% of his population had hypertension. The prevalence of hypertension was superimposed on ours except in the Nigerian study. There is probably an underestimation of high blood pressure cases in Nigeria where data were collected at interrogation in patients hospitalized in Intensive Care. Hypertension was identified as a risk factor for AKI during Covid [<xref ref-type="bibr" rid="scirp.121679-ref22">22</xref>]. Nevertheless, Hypertension is often accompanied by many factors [<xref ref-type="bibr" rid="scirp.121679-ref22">22</xref>].</p><p>Diabetes was a variable proportion in the studies. It was 37.2% in our series against 52.1% in Gupta in the USA [<xref ref-type="bibr" rid="scirp.121679-ref12">12</xref>] and Gutierrez 26.7%. It was comparable to that of Hirsch (43.3%) [<xref ref-type="bibr" rid="scirp.121679-ref23">23</xref>] and Chan (31%) [<xref ref-type="bibr" rid="scirp.121679-ref13">13</xref>]. There is strong expression of ACE2 in the kidneys of diabetic subjects [<xref ref-type="bibr" rid="scirp.121679-ref24">24</xref>].</p><p>Afriyie-Mensah and Arrocha found a clear predominance of respiratory distress with 90.9% and 98.7% respectively. This is superimposed on our results. The vast majority of lung damage is caused by COVID [<xref ref-type="bibr" rid="scirp.121679-ref25">25</xref>].</p><p>The mean hemoglobin was 10.8 g/dl and 12.3 g/dl in the Chan series [<xref ref-type="bibr" rid="scirp.121679-ref13">13</xref>]. Anemia was present in 53.5% of our patients compared to 16% in Ibrahim [<xref ref-type="bibr" rid="scirp.121679-ref14">14</xref>]. Anemia was present in 50.6% of patients in the Marques and al. series in Portugal. These results are superimposed on ours (74.4%). Anemia, common during Covid, is aggravated by the onset of kidney injury [<xref ref-type="bibr" rid="scirp.121679-ref26">26</xref>].</p><p>CRP levels were variable: 175 mg/L in Gupta [<xref ref-type="bibr" rid="scirp.121679-ref12">12</xref>] and 12.7 mg/L in Chan [<xref ref-type="bibr" rid="scirp.121679-ref13">13</xref>]. This is much lower than our result, related to the delay in management. CRP increases as the infection progresses [<xref ref-type="bibr" rid="scirp.121679-ref27">27</xref>]. It is a factor in the severity of Covid infection [<xref ref-type="bibr" rid="scirp.121679-ref28">28</xref>]. Inflammatory syndrome with high CRP was consistent in all our patients as in Marques (92.1%). COVID-19 is responsible for a significant inflammatory syndrome; inflammatory syndrome is also a prognostic factor.</p><p>The proportion of stage 3 patients in Arrocha in Bolivia [<xref ref-type="bibr" rid="scirp.121679-ref11">11</xref>] was 24.8% and 30% in Rubin [<xref ref-type="bibr" rid="scirp.121679-ref15">15</xref>] respectively, which is less than 58% in our series.</p><p>ATN accounted for 60.7% of patients. On renal biopsies performed, ATN lesions coexisted with several other lesions and were present in 70.6% of patients [<xref ref-type="bibr" rid="scirp.121679-ref29">29</xref>]. In another series, Sharma found 100% ATN lesions [<xref ref-type="bibr" rid="scirp.121679-ref30">30</xref>]. The predominance of ATN is related to the physio-pathology, which associates in a large proportion an effective hypovolemia, a rhabdomyolysis [<xref ref-type="bibr" rid="scirp.121679-ref31">31</xref>].</p><p>The majority of our patients (93%) were on antibiotics. Although no treatment showed efficacy, there is overuse of antibiotics without formal evidence of bacterial infection. This cannot be without negative effects.</p><p>Hemodialysis was initiated in 48.8% of patients. In the other series, it represented respectively 6.6% for Gupta [<xref ref-type="bibr" rid="scirp.121679-ref12">12</xref>], 29% for Chan [<xref ref-type="bibr" rid="scirp.121679-ref13">13</xref>] and 40% for Arrocha [<xref ref-type="bibr" rid="scirp.121679-ref11">11</xref>]. Gupta had patients with single-organ failure, with intensive care management early. On the other hand, Chan and Arrocha had a population distribution superimposed on ours. The indications of dialysis had not been specified in the series. In ours, it was dominated by anuria (46.6%).</p><p>Invasive ventilation was used in 79.1% of patients in Gupta, 68.2% of patients in Arrocha. In contrast, Afriyie-Mensah had 4.5% of patients with mechanical ventilation and Kanay had 16.4% of patients. Gupta and Arrocha had more severe patients with at least two-organ failure in intensive care. The study populations of Afriyie-Mensah and Kanay were low (28 and 22 patients respectively), which may be a selection bias. In addition, they were carried out in Africa where invasive ventilation in public hospitals is limited [<xref ref-type="bibr" rid="scirp.121679-ref32">32</xref>].</p><p>In Gupta, 6.6% had received therapeutic-dose anticoagulants. In contrast, we found a higher proportion of patients who received anticoagulant therapy. Coagulopathy described during COVID-19 infection motivated the use of anticoagulants. In addition, the majority of patients had high D-dimers motivating the prescription of anticoagulants before imaging to rule out venous thromboembolic disease.</p><p>The proportion of patients on vasoactive amines was 34.9%. This is superimposed on the result of Guti&#233;rrez (46.1%) in Spain [<xref ref-type="bibr" rid="scirp.121679-ref16">16</xref>]. COVID-19 is responsible for a sepsis that can develop into a state of shock requiring the use of vasoactive amines [<xref ref-type="bibr" rid="scirp.121679-ref33">33</xref>].</p><p>Corticosteroids were used in 65.1% of patients. Afriyie-Mensah and Guti&#233;rrez reported a percentage of corticosteroid use of 72.7% and 48.6%, respectively. The inflammation described in COVID-19 motivated the use of corticosteroids and was proposed by the WHO in severe patients [<xref ref-type="bibr" rid="scirp.121679-ref34">34</xref>] [<xref ref-type="bibr" rid="scirp.121679-ref35">35</xref>].</p><p>Death occurred in 55.8% of our patients. The percentage of deaths was 63.3% for Gupta [<xref ref-type="bibr" rid="scirp.121679-ref12">12</xref>], 46.4% for Hirsch [<xref ref-type="bibr" rid="scirp.121679-ref23">23</xref>], 50% for Chan [<xref ref-type="bibr" rid="scirp.121679-ref13">13</xref>] and Arrocha [<xref ref-type="bibr" rid="scirp.121679-ref11">11</xref>], respectively. However, it was high (90.3%) in Ibrahim [<xref ref-type="bibr" rid="scirp.121679-ref14">14</xref>] and low (21%) in Rubin [<xref ref-type="bibr" rid="scirp.121679-ref15">15</xref>]. There was a high mortality rate.</p><p>Hirsch and et al. [<xref ref-type="bibr" rid="scirp.121679-ref23">23</xref>] found that there was a statistically significant difference between age, male gender, race, Latino ethnicity, type of insurance, comorbidities (hypertension, diabetes), treatments used (antihypertensives, mechanical ventilation, inotropes, vasoactive amines), duration of hospitalization and KDIGO stage in univariate analysis. We did not find the same results, probably because of methodological limitations and missing data.</p><p>In our work, age over 60 years was associated with the risk of death in univariate analysis but not confirmed in multivariate analysis, probably due to the small number of our study population. Kolhe also found that age over 65 [<xref ref-type="bibr" rid="scirp.121679-ref36">36</xref>] was associated with a high risk of death. On the other hand, in his study, heart failure, respiratory failure and history of cancer were risk factors for death in patients with AKI during COVID-19. High age is known as a factor fragility and poor prognosis of COVID-19 [<xref ref-type="bibr" rid="scirp.121679-ref17">17</xref>].</p><p>Cheng found that elevated proteinuria and hematuria were factors associated with the risk of death in COVID-19 patients with AKI [<xref ref-type="bibr" rid="scirp.121679-ref1">1</xref>]. In Spain, systemic inflammatory response syndrome (OR = 2.4) and the occurrence of acute respiratory distress syndrome (OR = 2.8) were associated with the occurrence of death in COVID-19 patients with AKI [<xref ref-type="bibr" rid="scirp.121679-ref16">16</xref>].</p><p>In a study in Spain, artificial ventilation (OR = 5.9) and corticosteroid therapy (OR = 1.7) were associated with the onset of death in COVID-19 patients with AKI [<xref ref-type="bibr" rid="scirp.121679-ref16">16</xref>]. This was a study of 794 COVID-19 patients with AKI. We also found that invasive ventilation was associated with a high risk of death. Invasive ventilation has been identified as a death factor in COVID-19 patients [<xref ref-type="bibr" rid="scirp.121679-ref37">37</xref>]. Casas-Aparicio [<xref ref-type="bibr" rid="scirp.121679-ref38">38</xref>] in Mexico differed by KDIGO stage in symptoms such as rhinorrhea (p &lt; 0.02), cough (p &lt; 0.02), obesity (p = 0.04), mechanical ventilation (p = 0.01) and albuminemia (p = 0.02). Mortality was more common in KDIGO 3 (79.3%) and KDIGO 2 (68.7%) patients compared to KDIGO 1 (25%) with p = 0.004. Alfano in Italy [<xref ref-type="bibr" rid="scirp.121679-ref39">39</xref>] found no association between the KDIGO stage and the risk of death. In contrast, Xiao [<xref ref-type="bibr" rid="scirp.121679-ref40">40</xref>] in China found that the KDIGO stage was associated with the risk of dying with more deaths in stages 2 and 3 (64.3% of deaths versus 7.3% of deaths in stage 1). Blood [<xref ref-type="bibr" rid="scirp.121679-ref41">41</xref>] in China as well, in an ICU study, found that stage 3 was associated with the risk of death in patients with ARF during Covid (OR = 5.33 CI = 1.15 - 24.65, p &lt; 0.01). The difference between our results and those of the literature could be explained by the lack of diuresis in our study and the small study population. It is accepted that KDIGO stage 3 is a factor of death during insufficiencies. It is recognized that stage KDIGO 3 is a factor of death during acute renal failure, regardless of cause [<xref ref-type="bibr" rid="scirp.121679-ref8">8</xref>].</p></sec><sec id="s5"><title>5. Limitations of the Study</title><p>The absence of some information in patient records related to the retrospective nature of our study influenced our comments.</p><p>Our work took place in a private institution not specialized in nephrology. Creatinine was not always dosed at intake. In addition, the diuresis data were missing. The diagnosis of COVID-19 infection was based on imaging or positive IgM serology or positive PCR. The diagnosis of kidney injury was based on evolutionary arguments. No renal biopsy was performed.</p><p>The conclusions of our study are therefore difficult to generalize, because they are based on a single center and on a small number of cases.</p></sec><sec id="s6"><title>6. Conclusions</title><p>Mortality is high in COVID-19 patients with acute kidney injury. The factors associated with this are the advanced age of fragile patients and the severity of clinical signs justifying invasive ventilation. This raises the problem of systematic screening of patients in order to initiate early management, before the onset of respiratory distress.</p><p>What is already known on this topic: The coronavirus is responsible of kidney failure.</p><p>What this study adds: Prognosis and factor associated to death in Cote d’Ivoire.</p></sec><sec id="s7"><title>Acknowledgements</title><p>Our thanks to the director of the Farah Polyclinic in Abidjan.</p></sec><sec id="s8"><title>Contribution of the Authors</title><p>Dolaama Badomta collected data, performed data analysis and wrote the manuscript.</p><p>Konan Serge Didier and Diopoh Sery Patrick brought relevant criticism for the drafting of the research protocol, corrected the manuscript.</p><p>Moudachirou Mohamed Alex drafted the research protocol and participated in the data collection.</p><p>Tona Komlan Georges was involved in the data capture and editing of the descriptive analysis.</p><p>Amekoudi Eyram Yoan Makafui and Tsevi Mawufemo Claude reread the manuscript in order to bring relevant criticism concerning the method, the bibliographic review.</p><p>Yao Kouam&#233; Hubert was involved in drafting the protocol, writing the results, correcting the manuscript.</p></sec><sec id="s9"><title>Conflicts of Interest</title><p>The authors declare no conflict of interest.</p></sec><sec id="s10"><title>Ethical Considerations</title><p>The authorizations of the medical director of the Farah Polyclinic and the head of the Nephrology-Dialysis unit at the Farah Polyclinic have been taken. Patient anonymity was respected.</p></sec><sec id="s11"><title>Cite this paper</title><p>Dolaama, B., Konan, S.D., Diopoh, S.P., Moudachirou, M.A., Tona, K.G., Amekoudi, E.Y.M., Tsevi, M.C. and Yao, K.H. (2022) COVID-19 Infection and Acute Kidney Injury: About 43 Cases Report Collected at the Nephrology Department of the Farah Polyclinic in Abidjan. Open Journal of Nephrology, 12, 410-425. https://doi.org/10.4236/ojneph.2022.124042</p></sec></body><back><ref-list><title>References</title><ref id="scirp.121679-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Cheng, Y., Luo, R., Wang, K., Zhang, M., Wang, Z., Dong, L., et al. (2020) Kidney Disease Is Associated with In-Hospital Death of Patients with COVID-19. Kidney International, 97, 829-838. https://doi.org/10.1016/j.kint.2020.03.005</mixed-citation></ref><ref id="scirp.121679-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Martinot, M., Eyriey, M., Gravier, S., Bonijoly, T., Mohseni-Zadeh, M., Braumeisen, C., et al. (2020) Facteur de risque d’évolution défavorable et manifestations extra-pulmonaires au cours du COVID-19. Médecine et Maladies Infectieuses, 50, S81. https://doi.org/10.1016/j.medmal.2020.06.161</mixed-citation></ref><ref id="scirp.121679-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Darriverre, L., Fieux, F. and De La Jonquière, C. (2020) Acute Renal Failure during COVID-19 Epidemic. Le Praticien En Anesthesie Reanimation, 24, 207-211.https://doi.org/10.1016/j.pratan.2020.07.004</mixed-citation></ref><ref id="scirp.121679-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Martinez-Rojas, M.A., Vega-Vega, O. and Bobadilla, N.A. (2020) Is the Kidney a Target of SARS-CoV-2? American Journal of Physiology-Renal Physiology, 318, F1454-F1462. https://doi.org/10.1152/ajprenal.00160.2020</mixed-citation></ref><ref id="scirp.121679-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Karray, R., Jamoussi, A., Ayed, S., Lakhdhar, D., Rachdi, E, Khelil, J.B., et al. (2020) Surmortalité de l’insuffisance rénale aigu&amp;euml; oligoanurique au cours de la COVID-19: étude prospective tunisienne. Néphrologie &amp; Thérapeutique, 16, 312.https://doi.org/10.1016/j.nephro.2020.07.170</mixed-citation></ref><ref id="scirp.121679-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">Peleg, Y., Kudose, S., D’Agati, V., Siddall, E., Ahmad, S., Nickolas, T., et al. (2020) Acute Kidney Injury Due to Collapsing Glomerulopathy Following COVID-19 Infection. Kidney International Reports, 5, 940-945.https://doi.org/10.1016/j.ekir.2020.04.017</mixed-citation></ref><ref id="scirp.121679-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Cheruiyot, I., Henry, B., Lippi, G., Kipkorir, V., Ngure, B., Munguti, J., et al. (2020) Acute Kidney Injury is Associated with Worse Prognosis in COVID-19 Patients: A Systematic Review and Meta-Analysis. Acta Biomedica: Atenei Parmensis, 91, e2020029.</mixed-citation></ref><ref id="scirp.121679-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Eknoyan, G., Lameire, N., Eckardt, K. and Kasiske, B. (2012) Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney International Supplements, 2, 1-138.</mixed-citation></ref><ref id="scirp.121679-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Afriyie-Mensah, J., Aboagye, E.T., Ganu, V.J., Bondzi, S., Tetteh, D., Kwarteng, E., et al. (2021) Clinical and Therapeutic Outcomes of COVID-19 Intensive Care Units (ICU) Patients: A Retrospective Study in Ghana. Pan African Medical Journal, 38, Article 107. https://doi.org/10.11604/pamj.2021.38.107.27131</mixed-citation></ref><ref id="scirp.121679-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Ketfi, A., Chabati, O., Chemali, S., Mahjoub, M., Gharnaout, M., Touahri, R., et al. (2020) Profil clinique, biologique et radiologique des patients Algériens hospitalisés pour COVID-19: Données préliminaires. Pan African Medical Journal, 35, Article 77. https://doi.org/10.11604/pamj.supp.2020.35.2.23807</mixed-citation></ref><ref id="scirp.121679-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Lucana, G.G.A. and Casas, R. (2021) POS-003 Acute Kidney Injury in Critically Ill Patients with COVID-19 Experience of a ICU Bolivian Center Reference. Kidney International Reports, 6, S1-S2. https://doi.org/10.1016/j.ekir.2021.03.009</mixed-citation></ref><ref id="scirp.121679-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Gupta, S., Coca, S.G., Chan, L., Melamed, M.L., Brenner, S.K., Hayek, S.S., et al. (2021) AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19. Journal of the American Society of Nephrology, 32, 161-176. https://doi.org/10.1681/ASN.2020060897</mixed-citation></ref><ref id="scirp.121679-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Chan, L., Chaudhary, K., Saha, A., Chauhan, K., Vaid, A., Zhao, S., et al. (2021) AKI in Hospitalized Patients with COVID-19. Journal of the American Society of Nephrology, 32, 151-160. https://doi.org/10.1681/ASN.2020050615</mixed-citation></ref><ref id="scirp.121679-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Ibrahim, O.R., Oloyede, T., Gbadamosi, H., Musa, Y., Aliu, R., Bello, S.O., et al. (2021) Acute Kidney Injury in COVID-19: A Single—Center Experience in Nigeria. Anaesthesia. Pain &amp; Intensive Care, 25, 470-477.</mixed-citation></ref><ref id="scirp.121679-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Rubin, S., Orieux, A., Prevel, R., Carrié, C., Dewitte, A., Camou, F., et al. (2020) Caractérisation de l’insuffisance rénale aigu&amp;euml; chez les patients de réanimation atteints du COVID-19. Néphrologie &amp; Thérapeutique, 16, 247.https://doi.org/10.1016/j.nephro.2020.07.005</mixed-citation></ref><ref id="scirp.121679-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Gutiérrez-Abejón, E., Martín-García, D., Tamayo, E., álvarez, F.J. and Herrera-Gómez, F. (2021) Clinical Profile, Pharmacological Treatment, and Predictors of Death among Hospitalized COVID-19 Patients with Acute Kidney Injury: A Population-Based Registry Analysis. Frontiers in Medicine (Lausanne), 8, Article ID: 657977. https://doi.org/10.3389/fmed.2021.657977</mixed-citation></ref><ref id="scirp.121679-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Sampathkumar, H.H., Rajiv, A., Kumar, S., Sampathkumar, D., Kumar, S., et al. (2021) Incidence, Risk Factors and Outcome of COVID-19 Associated AKI—A Study from South India. Journal of the Association of Physicians of India, 69, 11-12.</mixed-citation></ref><ref id="scirp.121679-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Biswas, M., Rahaman, S., Biswas, T.K., Haque, Z. and Ibrahim, B. (2021) Association of Sex, Age, and comorbidities with mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis. Intervirology, 64, 36-47.https://doi.org/10.1159/000512592</mixed-citation></ref><ref id="scirp.121679-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Rapp, J.L., Lieberman-Cribbin, W., Tuminello, S. and Taioli, E. (2021) Male Sex, Severe Obesity, Older Age, and Chronic Kidney Disease are Associated with COVID-19 Severity and Mortality in New York City. Chest, 159, 112-115.https://doi.org/10.1016/j.chest.2020.08.2065</mixed-citation></ref><ref id="scirp.121679-ref20"><label>20</label><mixed-citation publication-type="other" xlink:type="simple">Maksimowski, N.A., Scholey, J.W. and Williams, V.R. (2021) Network (NEPTUNE) NSS. Sex and Kidney ACE2 Expression in Primary Focal Segmental Glomerulosclerosis: A Neptune Study. PLOS ONE, 16, e0252758. https://doi.org/10.1371/journal.pone.0252758</mixed-citation></ref><ref id="scirp.121679-ref21"><label>21</label><mixed-citation publication-type="other" xlink:type="simple">Yanes Cardozo, L.L., Rezq, S., Pruett, J.E. and Romero, D.G. (2021) Androgens, the kidney, and COVID-19: An Opportunity for Translational Research. American Journal of Physiology-Renal Physiology, 320, F243-F248. https://doi.org/10.1152/ajprenal.00601.2020</mixed-citation></ref><ref id="scirp.121679-ref22"><label>22</label><mixed-citation publication-type="other" xlink:type="simple">Shi, Y., Yu, X., Zhao, H., Wang, H., Zhao, R. and Sheng, J. (2020) Host Susceptibility to Severe COVID-19 and Establishment of a Host Risk Score: Findings of 487 Cases outside Wuhan. Critical Care, 24, Article No. 108.https://doi.org/10.1186/s13054-020-2833-7</mixed-citation></ref><ref id="scirp.121679-ref23"><label>23</label><mixed-citation publication-type="other" xlink:type="simple">Hirsch, J.S., Ng, J.H., Ross, D.W., Sharma, P., Shah, H.H. and Barnett, R.L., et al. (2020) Acute Kidney Injury in Patients Hospitalized with COVID-19. Kidney International, 98, 209-218. https://doi.org/10.1016/j.kint.2020.05.006</mixed-citation></ref><ref id="scirp.121679-ref24"><label>24</label><mixed-citation publication-type="other" xlink:type="simple">Gilbert, R.E., Caldwell, L., Misra, P.S., Chan, K., Burns, K.D., Wrana, J.L., et al. (2020) Overexpression of the SARS-CoV-2 Receptor, ACE-2, in Diabetic Kidney Disease: Implications for Kidney Injury in COVID-19. Canadian Journal of Diabetes, 45, 162-166.</mixed-citation></ref><ref id="scirp.121679-ref25"><label>25</label><mixed-citation publication-type="other" xlink:type="simple">Ritchie, H., Ortiz-Ospina, E., Beltekian, D., Mathieu, E., Hasell, J., Macdonald, B., et al. (2020) Coronavirus Pandemic (COVID-19). Our World in Data. https://ourworldindata.org/covid-vaccinations?country=CIV</mixed-citation></ref><ref id="scirp.121679-ref26"><label>26</label><mixed-citation publication-type="other" xlink:type="simple">Han, S.S., Baek, S.H., Ahn, S.Y., Chin, H.J., Na, K.Y., Chae, D.-W., et al. (2015) Anemia Is a Risk Factor for Acute Kidney Injury and Long-Term Mortality in Critically Ill Patients. The Tohoku Journal of Experimental Medicine, 237, 287-295. https://doi.org/10.1620/tjem.237.287</mixed-citation></ref><ref id="scirp.121679-ref27"><label>27</label><mixed-citation publication-type="other" xlink:type="simple">Benotmane, I., Perrin, P., Gautier-Vargas, G., Bassand, X., Bedo, D., Baldacini, C., et al. (2020) Prédiction de la sévérité de la COVID-19 par les biomarqueurs du syndrome de relargage cytokinique au sein d’une population de transplantés rénaux. Néphrologie &amp; Thérapeutique, 16, 259-260. https://doi.org/10.1016/j.nephro.2020.07.031</mixed-citation></ref><ref id="scirp.121679-ref28"><label>28</label><mixed-citation publication-type="other" xlink:type="simple">Admou, B. (2021) COVID-19 et marqueurs immunologiques pertinents. Pan African Medical Journal, 39, 40. https://doi.org/10.11604/pamj.2021.39.40.23481</mixed-citation></ref><ref id="scirp.121679-ref29"><label>29</label><mixed-citation publication-type="other" xlink:type="simple">Akilesh, S., Nast, C.C., Yamashita, M., Henriksen, K., Charu, V., Troxell, M.L., et al. (2021) Multicenter Clinicopathologic Correlation of Kidney Biopsies Performed in COVID-19 Patients Presenting with Acute Kidney Injury or Proteinuria. American Journal of Kidney Diseases, 77, 82-93. https://doi.org/10.1053/j.ajkd.2020.10.001</mixed-citation></ref><ref id="scirp.121679-ref30"><label>30</label><mixed-citation publication-type="other" xlink:type="simple">Sharma, P., Uppal, N.N., Wanchoo, R., Shah, H.H., Yang, Y., Parikh, R., et al. (2020) COVID-19-Associated Kidney Injury: A Case Series of Kidney Biopsy Findings. Journal of the American Society of Nephrology, 31, 1948-1958. https://doi.org/10.1681/ASN.2020050699</mixed-citation></ref><ref id="scirp.121679-ref31"><label>31</label><mixed-citation publication-type="other" xlink:type="simple">Batlle, D., Soler, M.J., Sparks, M.A., Hiremath, S., South, A.M., Welling, P.A., et al. (2020) Acute Kidney Injury in COVID-19: Emerging Evidence of a Distinct Pathophysiology. Journal of the American Society of Nephrology, 31, 1380-1383.https://doi.org/10.1681/ASN.2020040419</mixed-citation></ref><ref id="scirp.121679-ref32"><label>32</label><mixed-citation publication-type="other" xlink:type="simple">Daou, M. (2021) Evaluation de la pratique de la ventilation mécanique dans le service de réanimation du CHU Gabriel Toure. Thesis, USTTB, Beijing.</mixed-citation></ref><ref id="scirp.121679-ref33"><label>33</label><mixed-citation publication-type="other" xlink:type="simple">Bonny, V., Maillard, A., Mousseaux, C., Plaais, L. and Richier, Q. (2020) COVID-19: Physiopathologie d’une maladie à plusieurs visages. La Revue de Médecine Interne, 41, 375-389. https://doi.org/10.1016/j.revmed.2020.05.003</mixed-citation></ref><ref id="scirp.121679-ref34"><label>34</label><mixed-citation publication-type="other" xlink:type="simple">Manus, J.-M. (2020) OMS: COVID-19, cortico&amp;iuml;des mode d’emploi. Revue Francophone Laboratoires, 526, 9. https://doi.org/10.1016/S1773-035X(20)30285-9</mixed-citation></ref><ref id="scirp.121679-ref35"><label>35</label><mixed-citation publication-type="other" xlink:type="simple">Lellou, S., Bouhadda, M., Sahnoun, L., Dali, Y.N. and Bouatam, S. (2021) Place des cortico&amp;iuml;des dans la prise en charge du COVID-19. à propos de 25 cas. Revue des Maladies Respiratoires Actualités, 13, 141. https://doi.org/10.1016/j.rmra.2020.11.297</mixed-citation></ref><ref id="scirp.121679-ref36"><label>36</label><mixed-citation publication-type="other" xlink:type="simple">Kolhe, N.V., Fluck, R.J., Selby, N.M., Taal, M.W. (2020) Acute Kidney Injury Associated with COVID-19: A Retrospective Cohort Study. PLOS Medicine, 17, e1003406. https://doi.org/10.1371/journal.pmed.1003406</mixed-citation></ref><ref id="scirp.121679-ref37"><label>37</label><mixed-citation publication-type="other" xlink:type="simple">Alvarez-Garcia, J., Lee, S., Gupta, A., Cagliostro, M., Joshi, A.A., Rivas-Lasarte, M., et al. (2020) Prognostic Impact of Prior Heart Failure in Patients Hospitalized with COVID-19. Journal of the American College of Cardiology, 76, 2334-2348. https://doi.org/10.1016/j.jacc.2020.09.549</mixed-citation></ref><ref id="scirp.121679-ref38"><label>38</label><mixed-citation publication-type="other" xlink:type="simple">Casas-Aparicio, G.A., León-Rodríguez, I., Alvarado De La Barrera, C., González-Navarro, M., Peralta-Prado, A.B., Luna-Villalobos, Y., et al. (2021) Acute Kidney Injury in Patients with Severe COVID-19 in Mexico. PLOS ONE, 16, e0246595. https://doi.org/10.1371/journal.pone.0246595</mixed-citation></ref><ref id="scirp.121679-ref39"><label>39</label><mixed-citation publication-type="other" xlink:type="simple">Alfano, G., Ferrari, A., Fontana, F., Mori, G., Magistroni, R., Meschiari, M., et al. (2021) Incidence, Risk Factors and Outcome of Acute Kidney Injury (AKI) in Patients with COVID-19. Clinical and Experimental Nephrology, 25, 1203-1214. https://doi.org/10.1007/s10157-021-02092-x</mixed-citation></ref><ref id="scirp.121679-ref40"><label>40</label><mixed-citation publication-type="other" xlink:type="simple">Xiao, G.H., Hu, H.B., Wu, F., Sha, T., Zeng, Z.H., Huang, Q.B., et al. (2021) Acute Kidney Injury in Patients Hospitalized with COVID-19 in Wuhan, China: A Single-Center Retrospective Observational Study. Journal of Southern Medical University, 41, 157-163.</mixed-citation></ref><ref id="scirp.121679-ref41"><label>41</label><mixed-citation publication-type="other" xlink:type="simple">Sang, L., Chen, S., Zheng, X., Guan, W., Zhang, Z., Liang, W., et al. (2020) The Incidence, Risk Factors and Prognosis of Acute Kidney Injury in Severe and Critically Ill Patients with COVID-19 in Mainland China: A Retrospective Study. BMC Pulmonary Medicine, 20, Article No. 290. https://doi.org/10.1186/s12890-020-01305-5</mixed-citation></ref></ref-list></back></article>