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Published on: December 19, 2020
Evaluating the Association Between Comorbidities and COVID-19 Severity Scoring on Chest CT Examinations Between the
Pranav Ajmera1, Amit Kharat2, Satvik Dhirawani1
1Radiology, Dr. DY Patil Medical College, Hospital and Research Centre, Pune, IND.
Insights
The first and second waves of COVID-19 showed similar radiological severity, but the second wave disproportionately affected younger individuals and more females. Comorbidities increased disease severity in both waves.
Area of Science:
- Radiology and Imaging
- Infectious Diseases
- Public Health
Background:
- Coronavirus disease 2019 (COVID-19) has caused millions of deaths globally.
- The specific demographic impact of different COVID-19 waves remains unclear.
- Computed Tomography Severity Scores (CT-SS) can quantify COVID-19 lung involvement.
Purpose of the Study:
- To compare the radiological severity of the first and second COVID-19 waves using CT-SS.
- To analyze demographic differences in COVID-19 severity between the two waves.
- To assess the impact of comorbidities on COVID-19 severity across waves.
Main Methods:
- Retrospective, cross-sectional, observational study.
- Inclusion of 301 patients from the first wave (June-Oct 2020) and 1,001 from the second wave (Feb-Apr 2021).
- Analysis of CT-SS using artificial intelligence (U-net with Xception encoder) and SPSS, examining age, gender, and comorbidities.
Main Results:
- No statistically significant difference in mean CT-SS between the two COVID-19 waves.
- The most affected age group in the second wave was younger by nearly a decade.
- Females were more afflicted in the second wave; comorbidities like hypertension and diabetes increased severity.
Conclusions:
- Radiological severity of COVID-19 did not differ significantly between the first and second waves.
- Demographic patterns of COVID-19 infection varied between the waves, with younger age and higher female affliction in the second.
- No demographic group is low-risk; heterogeneous disease manifestation necessitates broad public health vigilance.
Abstract:
Background Coronavirus disease 2019 (COVID-19) has accounted for over 352 million cases and five million deaths globally. Although it affects populations across all nations, developing or transitional, of all genders and ages, the extent of the specific involvement is not very well known. This study aimed to analyze and determine how different were the first and second waves of the COVID-19 pandemic by assessing computed tomography severity scores (CT-SS). Methodology This was a retrospective, cross-sectional, observational study performed at a tertiary care Institution. We included 301 patients who underwent CT of the chest between June and October 2020 and 1,001 patients who underwent CT of the chest between February and April 2021. All included patients were symptomatic and were confirmed to be COVID-19 positive. We compared the CT-SS between the two datasets. In addition, we analyzed the distribution of CT-SS concerning age, comorbidities, and gender, as well as their differences between the two waves of COVID-19. Analysis was performed using the SPSS version 22 (IBM Corp., Armonk, NY, USA). The artificial intelligence platform U-net architecture with Xception encoder was used in the analysis. Results The study data revealed that while the mean CT-SS did not differ statistically between the two waves of COVID-19, the age group most affected in the second wave was almost a decade younger. While overall the disease had a predilection toward affecting males, our findings showed that females were more afflicted in the second wave of COVID-19 compared to the first wave. In particular, the disease had an increased severity in cases with comorbidities such as hypertension, diabetes mellitus, bronchial asthma, and tuberculosis. Conclusions This assessment demonstrated no significant difference in radiological severity score between the two waves of COVID-19. The secondary objective revealed that the two waves showed demographical differences. Hence, we iterate that no demographical subset of the population should be considered low risk as the disease manifestation was heterogeneous.
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