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Comparative analysis of clinical and biological characteristics of COVID-19 patients: A retrospective cohort study

  • Abir Yahyaoui
    Correspondence
    Corresponding author. Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco.
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Abdessamad Amrani
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Amjad Idrissi
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Sabrina Belmahi
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Oumaima Nassiri
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Boutaina Mouhoub
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Elhoucine Sebbar
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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  • Siham Hamaz
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco

    Infectious Diseases, Immunohematology and Cellular Therapy Laboratory, Mohammed VI University Hospital, Oujda, Morocco
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  • Mohammed Choukri
    Affiliations
    Central Laboratory, Mohammed VI University Hospital, Oujda, Morocco

    Faculty of Medicine and Pharmacy of Oujda, Mohammed First University, Oujda, Morocco
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Open AccessPublished:November 24, 2022DOI:https://doi.org/10.1016/j.cegh.2022.101184

      Highlights

      • The most represented age group in our series was 50–70 years.
      • Hypertension, diabetes and obesity were noted in the majority of patients in the severe group.
      • Logistic regression analyses identified several predictors of serious outcomes such as C-reactive protein, procalcitonin, ferritin, and D-dimer.
      • The optimal thresholds predictive of severity were 105 mg/l for C-reactive protein, 0.13 ng/ml for procalcitonin, and 669.5 μg/l for ferritin.

      Abstract

      Background

      Coronavirus disease (COVID-19), caused by a betacoronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly evolved into a pandemic since it was first reported in December 2019. thus, SARS-CoV-2 has become a major global public health issue.

      Objective

      The objective of this work is to compare demographics, comorbidities, clinical symptoms, biology and imaging findings between severe and non-severe COVID-19 patients and to identify clinical and biological risk factors and biomarkers for the development of severe COVID-19 as well as predictive thresholds for severity in order to best rationalize management and decrease the morbidity and mortality caused by this condition.

      Patients and methods

      This is a single-center retrospective study, from June 25 to December 31, 2021, on 521 patients at the level of the unit COVID-19 of the central laboratory of the Mohammed VI University Hospital Center Oujda, then classified into two groups according to the severity of the disease.

      Results

      Out of a total of 521 patients, a severe group including 336 cases (64.5%) and a non-severe group with 185 cases (35.5%). Hypertension, diabetes and obesity were noted in the majority of patients. Severe COVID-19 cases had higher C-reactive protein, procalcitonin, D-dimer, ferritin, elevated white blood cell count, and lower lymphocyte count than non-severe cases with a significant difference between the two groups. The areas under the curve (AUC) for C-reactive protein, procalcitonin and D-dimer were 0.886, 0.708, and 0.736 respectively. The optimal thresholds predictive of severity were 105 mg/l for C-reactive protein, 0.13 ng/ml for procalcitonin, 7420/μl for white blood cell count, and 0.55 mg/l for D-dimer.

      Conclusion

      Comparison of the proportion of clinical, biological and radiological data between severe and non-severe cases of COVID-19, as well as identification of biomarkers for the development of severe form in the present study, will allow optimal streamlining of management with rapid triage of patients.

      Keywords

      1. Introduction

      COVID-19 (Coronavirus Disease 2019) is the most critical health crisis of the decade with a significant rate of morbidity and mortality worldwide.
      • Gulati A.
      • Pomeranz C.
      • Qamar Z.
      • et al.
      A comprehensive review of manifestations of novel coronaviruses in the context of deadly COVID-19 global pandemic.
      It is an emerging anthropozoonosis-like infectious disease caused by an enveloped, non-segmented, polarity-positive RNA virus belonging to the order Nitrovirals, family Coronaviridae and subgroup Betacoronavirus. First discovered in late December 2019, in the city of Wuhan, China and named SARS-CoV-2 (Severe Acute Respiratory Syndrome CoronaVirus-2) by ICTV (International Committee On Taxonomy of Viruses) due to its phylogenetic proximity to SARS-CoV responsible for the SARS epidemic in 2003.
      • Lu H.
      • Stratton C.W.
      • Tang Y.-W.
      Outbreak of pneumonia of unknown etiology in Wuhan, China: the mystery and the miracle.
      The rapidity and extent of viral spread worldwide led the World Health Organization (WHO) to officially declare the SARS-CoV-19 outbreak a pandemic on March 11, 2020.,
      • Sohrabi C.
      • Alsafi Z.
      • O'Neill N.
      • et al.
      World Health Organization declares global emergency: a review of the 2019 novel coronavirus (COVID-19).
      Given the rapid spread of Covid-19, we determined that an updated case analysis could help identify the defining clinical features, concomitant comorbidities, biology and imaging findings of severe cases in our population, as well as compare the proportion of these data between the severe and non-severe group, which is useful for rapid patient triage and improved prognosis. This study aims to investigate and analyze the epidemiological, clinical, biological, and radiological characteristics and prognosis related to mild to severe infection of patients infected with 2019-nCoV during this pandemic to determine appropriate management strategies in advance.

      2. Materials and methods

      2.1 Participants and data sources

      Data collection was retrospective and monocentric. Data were examined by accessing computerized medical records of patients hospitalized in the dedicated COVID-19 wards of the Mohammed VI University Hospital Center (CHU) of Oujda, Morocco, during the period from June 25 to December 31, 2021. Information recorded included demographics, medical history, general, respiratory, digestive and neurosensory symptoms. Laboratory results were collected including standard blood counts (white blood cells, lymphocytes), biochemical markers such as C-reactive protein, procalcitonin, ferritin, d-dimers, urea and creatinine. Additional data collected included chest CT and prognosis (favorable outcome, secondary worsening, or death). We divided our sample into two distinct populations: severe form with 336 cases, and non-severe form, with 185 cases. The criteria of severity in our study based on WHO recommendations were defined as follows: (a) the presence of respiratory symptomatology on admission made of dyspnea, polypnea or desaturation ≤90% with chest imaging signs suggestive of COVID-19 infection and/or (b) acute respiratory distress syndrome (ARDS) secondary worsening and transfer to intensive care unit (ICU) for ventilation and/or (c) death. The criteria of non-severity included general (fever, asthenia, myalgias), respiratory (cough, dyspnea, odynophagia, anosmia, agueusia) and other symptoms without signs of severe COVID-19. hemodynamic repercussions.
      • World Health Organization
      Living Guidance for Clinical Management of COVID-19: Living Guidance.

      2.2 Inclusion and exclusion criteria

      We included in our study all patients with a positive RT-PCR result admitted to the COVID-19 unit at CHU Mohammed VI Oujda and whose records were complete and we excluded from our study patients who were not hospitalized at the CHU Mohammed VI Oujda during the defined period as well as patients whose SARS-CoV-2 infection was not confirmed.

      2.3 Statistical methods

      All data were analyzed by IBM SPSS (Statistical Package for the Social Sciences) version 23.0. Categorical variables were expressed as frequency and percentage and continuous variables as mean, interquartile range, or median. Multivariate analysis was performed to compare between the two groups of patients with severe and non-severe COVID-19, using a two-tailed Student T test or the Mann-Whitney test. Categorical variables were compared using the CHI-2 test, although Fisher's exact test was used when data were limited. The value of the optimal biomarker cutoffs was calculated using the Receiver Operating Characteristic curve (ROC). The relative risk and confidence interval were defined at 95%. The significance level of p < 0.05 was used to define the significance of the observed differences.

      3. Results

      3.1 Demographic characteristics

      The median age of the patients was 64 years with a range of 17–100 years. The most represented age group in our series was 50–70 years with a percentage of 46.6%, followed by the age group over 70 years with a percentage of 31.9%. The group of patients between 20 and 50 years of age represented 20.9% of cases. While patients under 20 years of age represented only 0.6% of cases. In the severe group, the median age of patients was 66 ± 13.5 years, whereas the median age of patients in the non-severe group was 51 ± 14.6 years. Thus, the median age was significantly lower in the non-severe patients than in the severe patients (p = 0.035), suggesting that middle-aged and elderly people were more susceptible to infections, whereas young healthy adults were less susceptible. The sex ratio (M/F) was 1.76 in the severe patients and 0.36 in the non-severe patients. However, there was a male predominance in the severe group of patients (p = 0.021). The results of the demographic characteristics of our two patient groups are summarized in Table 1.
      Table 1Description and statistical analysis of demographic characteristics and comorbidities in severe and non-severe COVID-19 patients hospitalized at Mohammed VI University Hospital, Oujda.
      FeaturesTotal n = 521Non-severe group n = 336Severe group n = 185P value
      Demographics:
      Age: median (SD)64 ± 16,351 ± 14,666 ± 13,50,035
      Gender: N (%)
      Male272(52,2)154(45,8)118(63,8)0,021
      Woman249(47,8)182(54,2)67(36,2)
      Sex-ratio (M/F)0,841,76
      Comorbidities: N (%)
      HTA252(48,4)106(31,5)146(78,9)0,028
      Diabetes1796(37,6)88(26,2)108(58,4)0,005
      Obesity201(38,6)56(16,7)145(78,4)0,002
      Chronic lung disease67(12,8)35(10,4)32(17,3)0,019
      Cardiovascular pathology86(16,5)22(6,5)64(34,6)0,026
      Chronic kidney disease24(4,6)7(2,1)17(9,2)0,001
      Hematological disease15(2,9)10(3)5(2,7)0,148
      Neoplasia12(2,3)8(2,4)4(2,2)0,169
      Hypothyroidism13(2,5)4(1,2)9(4,9)0,384
      Rheumatic pathology15(2,9)7(2,1)8(4,3)0,118
      Dyslipidemia12(2,3)5(1,5)7(2,7)0,231
      Neurological pathology17(3,3)9(2,7)8(4,3)0,154

      3.2 Comorbidities

      The proportion of comorbidities in severe cases was remarkably higher than in non-severe cases. Statistical analysis showed that in both groups the prevalent comorbidity was arterial hypertension (severe cases: 78.9%, non-severe: 31.5%, p = 0.028), followed by diabetes (severe cases: 58.4%, non-severe: 26.2%, p = 0.005) and obesity (severe cases: 78.4%, non-severe: 16.7%, p = 0.002) 17.3% of severe cases had a chronic pulmonary pathology versus 10.4% with a significant difference p = 0.019. Cardiovascular pathology was found in 34.6% of patients with severe COVID-19 versus 6.5% in the non-severe group (p = 0.026). Chronic kidney disease was present in 9.2% of severe cases versus 2.1% of non-severe cases (p = 0.001). Other pathologies were included in the history of COVID-19 patients with a non-significant difference. These results are summarized in Table 1. In total, 21.1% of patients had no medical history, 33.2% had only one, 24.4% of patients had two, and 21,3% had three or more medical histories.

      3.3 Clinical manifestations

      Clinical symptoms are summarized in Table 2. Dry cough (90%), asthenia (82.7%), myalgia (72.7%), fever (63.5%), anosmia-agueusia (54.7%) were the most common symptoms. Dyspnea was present in 50.5% and 75.1% of severe COVID-19 patients. Odynophagia, headache, digestive signs and arthralgia were less frequent. In all, 0.8% of patients had only one symptom, 1.5% had two symptoms, 2.7% had three symptoms and 95% had more than three symptoms.
      Table 2Description and statistical analysis of the clinical symptoms of COVID-19 in severe and non-severe patients hospitalized at Mohammed VI University Hospital, Oujda.
      Clinical symptomsTotal n = 521 N (%)Non-severe group n = 336 N (%)Severe group n = 185 N (%)P value
      Cough469(90)304(90,5)165(89,2)0,042
      Fever331(63,5)189(56,2)142(76,7)0,008
      Dyspnea264(50,7)125(37,2)139(75,1)0,001
      Asthenia431(82,7)277(82,4)154(83,2)0,026
      Myalgias379(72,7)243(72,3)136(73,5)0,037
      Anosmia-Agueusia285(54,7)162(48,2)123(66,5)0,001
      Odynophagia165(31,7)114(33,9)51(27,6)0,081
      Headaches184(35,3)155(46,1)29(15,7)0,165
      Nausea-Vomiting60(11,5)35(10,4)25(13,5)0,179
      Diarrhea119(22,8)76(22,6)43(23,2)0,367
      Arthralgia12(2,3)5(1,5)7(3,8)0,088

      3.4 Biological results

      The results of the biological workups obtained are summarized in Table 3. The median white blood cells count was higher in the severe cases (9 versus 7.9 × 10⁹/L, p = 0.001). Hyper leukocytosis was noted in 38.9% of the severe population. The median lymphocyte count was lower in severe patients than in patients with a non-severe form (0.8 versus 1.1 × 10⁹/L, p = 0.002). Lymphopenia was found in 60% of severe patients, consistent with the main feature of the viral infection. However, median C-reactive protein and procalcitonin were significantly higher in severe patients than in non-severe patients (218 versus 61 mg/L, p = 0.001) and (0.24 versus 0.11 ng/mL, p = 0.024) respectively. The median ferritin level was higher in the severe group (936 versus 519 μg/L) with p = 0.001. Logistic regression analyses identified several predictors of serious outcomes in multivariate analysis, such as C-reactive protein (OR: 2.024,[95% CI: 1.016–2.023], p: 0.001), procalcitonin (OR: 1.063, [95% CI: 1.025–1.084], p: 0.027), ferritin (OR: 1.055, [95% CI: 1.032–1.063], p: 0.042), and D-dimer (OR: 1.975, [95% CI: 1.927–2.026], p: 0.019) were significantly related to patients with severe COVID-19. To study the specificity and sensitivity of the biomarkers, we used the ROC curve (Fig. 1), which allowed us to specify the area under the curve of each biomarker, called AUC (Area Under the Curve). The AUC of the curve of the biomarker studied must be greater than or equal to 0.5. Thus, the closer the AUC value is to 1, the better the test studied. As described in Table 4 and Fig. 1, the calculated AUCs are presented as follows: for C-reactive protein (CRP): 0.886, procalcitonin: 0.708, D-dimer: 0.736, ferritin: 0.673 and white blood cells (WBC): 0.603. Biomarkers with AUCs less than or equal to 0.5 were excluded from the next step (lymphocytes). The optimal thresholds predictive of severity were 105 mg/l for C-reactive protein, 0.13 ng/ml for procalcitonin, 669.5 μg/l for ferritin, 7420/μl for white blood cell count, and 0.55 mg/l for D-dimer.
      Table 3Description and statistical analysis of biological parameters in severe and non-severe COVID-19 patients hospitalized at Mohammed VI University Hospital, Oujda.
      Laboratory resultsTotal n = 521 Median (Interval)Non-severe group n = 336 Median (Interval)Severe group n = 185 Median (Interval)P value
      C-reactive protein (mg/l)102(0,19–615)61(0,19–269)218(76–615)0,001
      Procalcitonin (ng/ml)0,15(0,01–66)0,11(0,01–15)0,24(0,12–66)0,024
      Ferritin (μg/l)659(9,07–40000)519(9,07–1981)936(122–40000)0,001
      D-Dimer (mg/l)0,28(0,01–85,5)0,17(0,01–15,5)0,62(0,01–85,5)0,062
      Creatinine (μmol/l)71(26–1179)70,2(33,4–675)73,4(26,1–1179)0,055
      Urea (mmol/l)5,8(1–46,1)5,5(1,5–46,1)6,3(1–45,3)0,053
      Lymphocytes (.109/l)1(0,2–6,4)1,1(0,2–6,4)0,8(0,2–4,5)0,002
      White blood cells (.109/l)7,9(0,3–30,5)7,41(0,3–30,5)9(0,32-29,3)0,001
      Table 4Logistic regression adjusted for biological parameters.
      Laboratory resultsOR*95% CIP value
      C-reactive protein (mg/l)2,0241,016–2,0230,001
      Procalcitonin (ng/ml)1,0631,025–1,0840,027
      Ferritin (μg/l)1,0551,032–1,0630,042
      D-dimer (mg/l)1,9751,927–2,0260,019
      Creatinine (μmol/l)0,0290,003–1,0370,421
      Urea (mmol/l)0,9860,405–2,3960,387
      Lymphopenia (109/l)0,0421,014–1,0590,063
      White blood cells (.109/l)1,0211,018–1,0440,076

      3.5 Radiological findings

      Representative radiological findings in the two groups of patients with severe and non-severe COVID-19 are provided in Table 5. Of 435 chest scans performed at the time of admission, 83.5% revealed abnormalities suggestive of COVID-19. The most common radiological findings on chest scan were ground-glass opacity (47%), Crazy Paving appearance (43.9%) and parenchymal condensation (42.2%). Pulmonary embolism was found in 24.9% of severe patients compared to 3.3% of non-severe patients, which 44% had high level of D-Dimers. The predominant parenchymal involvement was that of more than 75% in 35.5% of the population.
      Table 5Description and statistical analysis of radiological abnormalities and lung involvement in severe and non-severe COVID-19 patients hospitalized at Mohammed VI University Hospital, Oujda.
      Imaging resultsTotal n = 521 N (%)Non-severe group n = 336 N (%)Severe group n = 185 N (%)P value
      ground-glass opacities245(47)73(21,7)172(93,3)0,001
      Crazy paving229(43,9)124(36,9)105(56,8)0,001
      Parenchymal condensation220(42,2)79(23,5)141(76,2)0,001
      Pulmonary embolism57(10,9)11(3,3)46(24,9)0,015
      Parenchymal damage:
      less than 10%.37(7,1)32(9,5)5(2,7)0,001
      10–25%.68(13)48(14,3)20(10,8)
      25–50%.105(20,1)64(19)41(22,2)
      50–75%143(27,4)55(16,4)81(43,8)
      more than 75% of the total185(35,5)42(12,5)133(71,9)

      3.6 Patient prognosis

      6.3% of the patients in the series died from complications of this infection. This mortality rate could be attributed to the fact that they were all hospitalized patients in a third level of health with critical conditions than most of the other patients infected in this COVID-19 pandemic.

      4. Discussion

      We report in this study a cohort of 521 patients with RT-PCR confirmed 2019-nCoV infection hospitalized at the Mohammed VI University Hospital Oujda and divided into two groups: COVID-19 severe and non-severe. Our study aims to determine the clinical, biological, and imaging characteristics of patients with COVID-19, assess risk factors for severe outcomes, and identify biomarkers and thresholds predictive of severity. Severe cases of COVID-19 increased with age.
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      Clinical and laboratory characteristics of severe and non-severe patients with COVID-19: a retrospective cohort study in China.
      . Nevertheless, special attention should be paid to patients with an increase in these biological parameters.
      • Martinot M.
      • Eyriey M.
      • Gravier S.
      • et al.
      Predictors of mortality, ICU hospitalization, and extrapulmonary complications in COVID-19 patients.
      In accordance with several studies, lung CT images could manifest different suggestive abnormalities in COVID-19 patients with different time course and disease severity. In our study, the most frequent radiological signs found in severe patients were ground glass opacities, parenchymal condensation and crazy paving. The extension of the lesions was dominated by the critical form by more than 75% in the severe group. This was consistent with similar studies.
      • Sun P.
      • Qie S.
      • Liu Z.
      • Ren J.
      • Li K.
      • Xi J.
      Clinical characteristics of hospitalized patients with SARS-CoV-2 infection: a single arm meta-analysis.
      • Li K.
      • Wu J.
      • Wu F.
      • et al.
      The clinical and chest CT features associated with severe and critical COVID-19 pneumonia.
      • Wu J.
      • Wu X.
      • Zeng W.
      • et al.
      Chest CT findings in patients with coronavirus disease 2019 and its relationship with clinical features.
      • Ng M.-Y.
      • Lee E.Y.P.
      • Yang J.
      • et al.
      Imaging profile of the COVID-19 infection: radiologic findings and literature review.
      The pathophysiology of pulmonary embolism during SARS-CoV-2 infection is multi-causal. Returning to the clinical and biological timeline of the course of this disease, the rapid worsening of respiratory symptoms is accompanied by an extremely marked elevation of proinflammatory cytokines.
      • Zhou F.
      • Yu T.
      • Du R.
      • et al.
      Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study.
      ,
      • Connors J.M.
      • Levy J.H.
      Thromboinflammation and the hypercoagulability of COVID-19.
      ,
      • Ye Q.
      • Wang B.
      • Mao J.
      The pathogenesis and treatment of the 'Cytokine Storm’ in COVID-19.
      This acute inflammatory phenomenon can affect coagulation and fibrinolysis and amplify hypercoagulability.
      • Jackson S.P.
      • Darbousset R.
      • Schoenwaelder S.M.
      Thromboinflammation: challenges of therapeutically targeting coagulation and other host defense mechanisms.
      This explains the increased rates of pulmonary emboli during SARS-CoV-2 infection, which were significantly higher in our study in the severe group.
      • Hékimian G.
      • Lebreton G.
      • Bréchot N.
      • Luyt C.-E.
      • Schmidt M.
      • Combes A.
      Severe pulmonary embolism in COVID-19 patients: a call for increased awareness.
      ,
      • Gervaise A.
      • Bouzad C.
      • Peroux E.
      • Helissey C.
      Acute pulmonary embolism in non-hospitalized COVID-19 patients referred to CTPA by emergency department.
      Hence the approach adopted by our hospital based on early anticoagulation.

      5. Conclusion

      There is a significant difference between severe and non-severe COVID-19 patients in terms of demographic characteristics, clinical manifestations, comorbidities, and biological and radiological characteristics. These factors have been associated with disease deterioration and are critical insights that must be carefully considered to reduce mortality from this condition. Furthermore, the determination of biological thresholds predictive of severity and the association of several markers correlated with the epidemiological, clinical, and radiological aspect, offers a broad-spectrum guidance to clinicians to rapidly identify patients with severe COVID-19, classify them, and transport them to specialized centers to initiate appropriate management.

      Ethical approval

      Access to patient data was authorized by the Mohammed VI University Hospital and approved by the head of the department. Taking into account the retrospective design of this study and the context of emerging infectious diseases, the requirement for patient consent was waived. Data anonymity was respected in our database in accordance with national and international guidelines.

      Funding sources

      This research did not receive any specific funding from public, commercial, or non-profit funding agencies.

      Declaration of competing interest

      The authors declare that they have no conflicts of interest in this case series.

      Acknowledgements

      We would like to thank the medical and paramedical teams of the Mohammed VI University Hospital, Oujda, for their significant involvement in the care of the patients included in our study and for their successful management during this pandemic COVID-19.

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