Chest computed tomography for outcome prediction in laboratory-confirmed COVID-19: A retrospective analysis of 38,051 cases

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Abstract

BACKGROUND: In the current epidemiological situation, computed tomography (CT) of chest organs plays an important role in disease diagnosis. Clinical and CT data allow physicians to quickly establish the probability of the presence and prognosis of patients with coronavirus disease 2019 (COVID-19).

AIMS: This study aimed to predict outcomes in patients with laboratory-confirmed COVID-19 based on chest CT and a semi-quantitative visual pulmonary lesion grading system (CT 0–4).

MATERIALS AND METHODS: A retrospective analysis of the Unified Medical Information and Analytical Service and Unified Radiological Information Service records from March 01, 2020 to July 30, 2020 was performed. The inclusion criteria were as follows: patients diagnosed with U07.1 (laboratory-verified coronavirus infection) from March 01, 2020 to July 30, 2020 and referred for a chest CT by a physician with suspected community-acquired pneumonia caused by COVID-19; the maximum period between laboratory verification and CT was not more than five days. The observation period for each patient was at least till 30 days from the date of CT. CT was performed in 48 medical organizations providing primary medical care to adults in Moscow. The exclusion criterion was a negative reverse transcription-polymerase chain reaction results by July 30, 2020. The CT 0–4 scale is recommended for use in the Russian Federation to estimate the volume of lung parenchyma lesions when COVID-19 is suspected.

RESULTS: The total sample volume was 38,051 patients. In this study, the risk of death was three times higher for CT-4 than for CT-0. In the Kaplan–Meier survival curve, the survival rate of patients in the CT-3 category was almost three times lower (hazard ratio = 2.94) than in the CT 0–2 categories; in addition, the higher the initial category of CT, the lower the risk of deterioration. The time for hospitalization decreased with the increase in the CT grade.

CONCLUSION: The visual CT 0–4 scale can be used to predict outcomes, such as hospitalizations and deaths, in patients suspected of COVID-19 who underwent chest CT in primary health care.

About the authors

Sergey P. Morozov

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Email: morozov@npcmr.ru
ORCID iD: 0000-0001-6545-6170
SPIN-code: 8542-1720

MD, PhD

Russian Federation, Moscow

Valeria Yu. Chernina

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Email: v.chernina@npcmr.ru
ORCID iD: 0000-0002-0302-293X
SPIN-code: 8896-8051

MD

Russian Federation, Moscow

Andreevich I. Blokhin

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Email: i.blokhin@npcmr.ru
ORCID iD: 0000-0002-2681-9378
SPIN-code: 3306-1387

MD

Russian Federation, Moscow

Victor A. Gombolevskiy

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

Author for correspondence.
Email: g_victor@mail.ru
ORCID iD: 0000-0003-1816-1315
SPIN-code: 6810-3279

MD, PhD, MPH

Russian Federation, Moscow

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Supplementary files

Supplementary Files
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1. JATS XML
2. Figure 1. Sampling process flowchart.

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3. Figure 2. Overall survival curves for CT1-4 grades (p < 0.0001)

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4. Figure 3. Kaplan–Meier curves for the time to deterioration by one or more grades relative to the baseline (p < 0.0001).

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5. Figure 4. Kaplan–Meier curves for the time from the baseline CT to hospitalization (p < 0.0001)

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6. Video-presentation
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Copyright (c) 2020 Morozov S.P., Chernina V.Y., Blokhin A.I., Gombolevskiy V.A.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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