key: cord-0968013-xwelf2nb
authors: Ruch, Yvon; Kaeuffer, Charlotte; Ohana, Mickael; Labani, Aissam; Fabacher, Thibaut; Bilbault, Pascal; Kepka, Sabrina; Solis, Morgane; Greigert, Valentin; Lefebvre, Nicolas; Hansmann, Yves; Danion, François
title: CT lung lesions as predictors of early death or ICU admission in COVID-19 patients
date: 2020-07-24
journal: Clin Microbiol Infect
DOI: 10.1016/j.cmi.2020.07.030
sha: c11adbfb56de8378b083577ab58bab09643a7f2c
doc_id: 968013
cord_uid: xwelf2nb

OBJECTIVE: The main objective of this study was to investigate the prognostic value of early systematic chest computed tomography (CT) with quantification of lung lesions in coronavirus disease 2019 (COVID-19) patients. METHODS: We studied 572 patients diagnosed with COVID-19, confirmed using polymerase chain reaction for whom a chest CT was performed at hospital admission. Visual quantification was used to classify patients as per the percentage of lung parenchyma affected by COVID-19 lesions: normal CT, 0%–10%, 11%–25%, 26%–50%, 51%–75%, and >75%. The primary endpoint was severe disease, defined by death or intensive care unit admission in the 7 days following admission. RESULTS: The mean patient age was 66.0 ± 16.0 years, and 343/572 (60.0%) were men. The primary endpoint occurred in 206/572 (36.0%) patients. The extent of lesions on initial CT was independently associated with prognosis (odds ratio = 2.35, 95% confidence interval 1.24–4.46; p <0.01). Most patients with lung involvement >50% developed severe disease (66/95, 69.5%), compared to patients with lung involvement of 26%–50% (70/171, 40.9%) and ≤25% (70/306, 22.9%) (p <0.01 and p <0.01, respectively). None (0/14) of the patients with normal CT had severe disease. CONCLUSION: Chest CT findings at admission are associated with bad outcome in COVID-19 patients.

Chest computed tomography (CT) has shown promise as a diagnostic modality for coronavirus 24 disease 2019 (COVID-19) [1, 2] . Initial studies have described a stereotypical time course with 25 successive radiological stages with ground-glass opacities (GGO) as the main initial lesion [3, 4] . 26

Quantitative CT lung analysis has demonstrated good association with patient prognosis in 27 those with non-COVID-19 acute respiratory distress syndrome [5] . From March 2020, patients 28 admitted to the Strasbourg University Hospital with the suspicion of COVID-19 were managed 29 using a specific protocol, including reverse-transcription polymerase chain reaction (RT-PCR) 30 on respiratory samples and a systematic chest CT to improve the triage of patients. We aimed 31 to determine the early prognostic value of systematic chest CT with quantification of lung 32 lesions performed at the time of admission in COVID-19 patients. 33 34

We conducted a retrospective study of prospectively collected data. All consecutive patients 36 aged ≥18 years, with COVID-19 confirmed using RT-PCR and a chest CT performed with 37 quantitative evaluation of the lesions, hospitalised at the Strasbourg University Hospital in 38

March 2020 were enrolled in this cohort study. Patients for whom the CT was realised ≥48 39 hours after admission were excluded. Non-contrast enhanced chest CT images were acquired 40 on an 80-row scanner (Aquilion Prime SP, Canon Medical Systems), with parameters based on 41 the patient's morphotype (tension 100-135kV and maximum mAs 2-50) [6] . Images were 42 reconstructed with a slice-thickness of 1 mm in mediastinal and parenchymal windows using 43 an iterative reconstruction algorithm (AIDR-3D, Canon Medical Systems) and read on 44 dedicated workstations with multiplanar and maximum intensity projection reconstructions. 45

CT angiography was performed secondarily for patients suspected of pulmonary embolism. 46

Visual quantification of the lung lesions was performed at the time of the CT by two different 47 radiologists who were blinded to the patients' clinical condition. Evaluations were made 48 independently, but discrepancies were resolved in consensus. The CT images were classified as 49 per the percentage of the whole lung parenchyma affected by COVID-19 lesions-GGO and/or 50 consolidations-in the following six groups: normal CT (no lesion), minimal (0%-10%), 51 moderate (11%-25%), important (26%-50%), severe (51%-75%), and critical (>75%) [7] . To 52 simplify the analysis of clinical data, the patients were divided into three subgroups: ≤25%, 26-53 50%, and >50%. 54

The primary endpoint was early severe disease, defined as death or intensive care unit (ICU) 55 admission in the seven days after hospital admission. Statistical analyses were performed using 56 the R software (version 3.5.2). This study was approved by the Ethics Committee of Strasbourg 57

University Hospital (N°CE-2020-51). Oral informed consent was obtained from all the patients. There were no significant differences in the prevalence of comorbidities based on the extent of 68 the lesions on CT (Table 1) . Patients with lung involvement >50% had significantly higher C-69 reactive protein (CRP) level and neutrophil count, lower lymphocyte count, and more 70 consolidations on CT compared to those with lung involvement ≤25% (p <0.01, for each 71 comparison). Finally, 16/95 (16.8%) patients with lung involvement >50% were diagnosed with 72 pulmonary embolism. 73

Overall, 206/572 (36.0%) patients met the criteria for early severe disease, including 55/572 74 (9.6%) who died. Extent of lesions on the initial CT was associated with severe disease (Figure  75 1, A Figure S2 ). 83

The median time between the onset of the symptoms and CT was 7 days (interquartile range 84 6.0). This duration was shorter in patients with normal CT or minimal lesions (Figure 1, B) . 85

None of the patients with minimal lesions and symptoms for more than ten days have 86 developed severe disease, while 10/12 (83.3%) of those with minimal lesions and severe 87 disease presented with symptoms for five days or less (Figure 1, C) . 88 89

Our study has shown that visual quantification of CT lung lesions was associated with early 91 death or ICU admission in hospitalised patients, especially in patients with lung involvement 92 >50%. 93

Several risk factors for severe COVID-19 have been reported, such as older age, male sex, and 94 chronic diseases [8, 9] . The chest CT has shown benefit in COVID-19 pneumonia diagnosis; 95 however, its interest as a prognosis factor remains unclear [1] . Based on a study on 134 COVID-96 19 patients, Liu and al. showed that CT quantification of pneumonia lesions can predict early 97 progression to severe illness [10] . 98

Although our study has employed one of the largest cohorts on COVID-19 imaging, it has some 99 limitations. We chose to evaluate early prognosis with the outcome on day seven; a longer 100 endpoint may have increased the number of patients with severe disease. However, most 101 deaths and ICU admissions occurred within seven days after admission in our study, and peak 102 lung involvement was reached before two weeks of evolution in previous studies [3, 11] . 103 Furthermore, we performed visual quantification, while other studies have used dedicated 104 software to quantify lung lesions [10, 11] . Although this makes our evaluation dependent on 105 the experience of radiologists, this facilitates its generalisation to centres that are not 106 equipped with such software. 107

Four radiological stages have been described, with progressive extent of GGO and the 108 secondary onset of consolidations [3,12]. The higher CRP level, neutrophilia and lymphopenia 109 in our severe patients suggested an inflammatory profile that appears to be associated with 110 lung consolidations and subsequent worsening of their respiratory condition [13] . 111

Consolidations were associated with poor outcome, as previously described [14] . Patients with 112 lung involvement >50% were significantly more diagnosed with pulmonary embolism. This 113 higher risk of thrombosis in patients with severe COVID-19 has been reported, even if the 114 pathophysiology remains unclear with several mechanisms possibly involved [15] . 115

The timing between the onset of the symptoms and performance of CT was lower for patients 116 with lung involvement ≤25%, indicating that these patients could have presented at an earlier 117 disease stage. However, this difference was only of 1 day, raising a question about its clinical 118 relevance. Fourteen patients (2.4%) had no lesions on the initial chest CT, among whom 10/14 119 had symptoms for three days or less, as previously reported [1, 2] . None of these patients died 120 or was admitted to ICU, suggesting that normal CT at the time of hospital admission could 121 predict good prognosis. 122

In conclusion, in addition to its diagnostic value, chest CT could predict severe COVID-19 123 pneumonia as visual quantification of the lesions appears to be associated with early 124

prognosis. Whether this strategy should be systematically implemented remains to be 125 evaluated in further studies. Lactate (mmol/L) 0.9 ± 0.5 (n = 186)

1.1 ± 0.7 (n = 123)

1.2 ± 0.9 (n = 83) <0.01 CT, computed tomography; ICU, intensive care unit In order to ease visualisation, noise was randomly added to each point. Curves were fitted through points with the locally weighted scatterplot smoothing (LOESS) method using the 'ggplot2' R package. Shaded area represents the standard error.

COVID-19) in China: A Report of 1014 Cases

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A 154 predictive factor for patients with acute respiratory distress syndrome: CT lung 155 volumetry of the well-aerated region as an automated method

Ultra-low-dose 158 unenhanced chest CT: Prospective comparison of high kV/low mA versus low kV/high mA 159 protocols

COVID-19 patients 162 and the radiology department -advice from the European Society of Radiology (ESR) and 163 the European Society of Thoracic Imaging (ESTI)

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Risk Factors Associated With Acute 170 Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 171 Pneumonia in Wuhan, China

CT quantification of pneumonia 174 lesions in early days predicts progression to severe illness in a cohort of COVID-19 175 patients

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Radiological findings from 81 patients 180 with COVID-19 pneumonia in Wuhan, China: a descriptive study

COVID-19: 183 consider cytokine storm syndromes and immunosuppression

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Data are given in n (%) or median ± interquartile range, otherwise specified COVID-19: coronavirus disease

SpO2: peripheral oxygen saturation. a Only 10/29 pulmonary embolisms were diagnosed at admission; b Defined as intensive care unit admission or death

The inferential analysis for the categorical data was performed using the χ² test or Fisher's exact test (2x3 comparison), as per the theoretical size of the samples. Continuous data were compared using a nonparametric test