For this retrospective case-control study, the medical records of 299 COVID-19 RT-PCR– positive patients who presented themselves to the emergency department of the UZ Brussel between March 7 and May 3, 2020, were extracted from the database of the radiology department. All emergency department symptomatic patients of all ages with positive RT-PCR results were included. Demographic and clinical differences between these two groups were evaluated.
For each participant, the following registered variables were collected from medical records: age, gender, ethnicity, and symptoms. These symptoms included cough, dyspnea, thoracic pain, anosmia, dysgeusia, fever, muscle pain, fatigue, rhinitis, sore throat, headache, diarrhea, anorexia, confusion, and sudden fall. Comorbidities, including AHT, HD, DM, smoking, COPD, malignancy, and chronic kidney disease, were also considered. In addition, ACEI or ARB treatment, RT-PCR results, and CT findings were encoded appropriately.
All patients were scanned on an Apex Revolution CT (GE Healthcare, Milwaukee, USA). The non‐contrast CT thorax scan protocol consisted of a spiral acquisition (pitch = 1), a rotation time of 0.35 s, and an auto kVp and mA selection (average dose length product = 149 mGy.cm). Two radiologists analyzed the CT scan images, with one of them having more than a decade of experience in radiology.
The CT severity score—as established in prior studies16—was based on the extent of lung abnormalities in each lobe. The CT severity score, with a maximum total score of 25, was calculated by totaling the individual scores for each lobe. Scores 0, 1, 2, 3, 4, and 5 correspond to 0–4%, 5–25%, 26–49%, 50–75%, and >75% of the lobe affected, respectively (Table 1).
Table 1. The CT severity score per lobe, with a maximum total score of 25.
Score
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1
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2
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3
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4
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5
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The extent of lung abnormalities
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0–4%
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5–25%
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26–49%
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50–75%
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>75%
|
The clinical severity scoring of RT-PCR–positive patients was divided into four classes based on the Chinese guidelines that the National Health Commission and State Administration of Traditional Chinese Medicine introduced on March 3, 2020. Class I, or mild type, includes symptomatic patients with negative CT scans. Class II, or common type, consists of symptomatic patients with positive CT scans. Class III, or severe type, comprises patients who fulfilled at least one of the following criteria: respiratory distress, a respiratory rate ≥ 30 times per minute, an SaO2 ≤ 93%, or a PaO2/FiO2 < 300 mmHg at any given time during admission. Finally, Class IV, or critical type, includes patients with shock, respiratory failure requiring mechanical ventilation, and other organ failure requiring ICU monitoring and treatment (Table 2).
The institutional review board of UZ Brussel (ethics committee BUN 2020/106) approved this retrospective case-control study. Written informed consent was waived. IBM SPSS Statistics for Windows Version 23.0 (Armonk, NY: IBM Corp) was used for statistical analysis. The ACEI or ARB users were compared with the non-users according to age, gender, ethnicity, comorbidities, and symptom frequency using Pearson’s Chi-square test and Fisher’s exact test. The Mann-Whitney U test was performed to compare the age distribution between the two groups. The optimal cut-off value of the CT severity score to detect a clinical severe- critical type was defined by calculating Youden’s J index on the cut points that an ROC curve analysis yielded. For this purpose, we considered the mild and common patients one group and the severe and critical patients the other group.
In addition, a cumulative logistic regression was conducted to create a model wherein the potential confounding factors of age, gender, ethnicity, and comorbidities were considered.
In this model, the cumulative odds ratio of ACEI or ARB users for having a higher clinical severity score of COVID-19 infection was determined. A binomial logistic regression was also conducted to determine the association between ACEI or ARB use and having a severe CT score. To evaluate the association between ACEI or ARB use and the current mortality outcome, a Poisson logistic regression was performed, using the standard 𝝰 = 0.05 cut-off and a 95% confidence interval (CI).