Back

Chest CT findings and outcomes of COVID-19 in second wave: A cross-sectional study in a tertiary care centre in Northern India

Cheema, T.; Saroha, A.; Kumar, A.; Panda, P. K.; Saxena, S.

2023-03-18 infectious diseases
10.1101/2023.03.17.23287423 medRxiv
Show abstract

IntroductionThe COVID-19 pandemic has posed a serious threat to global health, with developing nations like India being amongst the worst affected. Chest CT scans play a pivotal role in the diagnosis and evaluation of COVID-19, and certain CT features may aid in predicting the prognosis of COVID-19 illness. MethodsThis was a single-centre, hospital-based, cross-sectional study conducted at a tertiary care centre in Northern India during the second wave of the COVID-19 pandemic from May-June 2021. The study included 473 patients who tested positive for COVID-19. A high-resolution chest CT scan was performed within five days of hospitalization, and patient-related information was extracted retrospectively from medical records. Univariable and Multivariable analysis was done to study the predictors of poor outcome. ResultsA total of 473 patients were included in the study, with 75.5% being males. The mean total CT score was 29.89 {+/-} 9.06. Fibrosis was present in 17.1% of patients, crazy paving in 3.6%, pneumomediastinum in 8.9%, and pneumothorax in 3.6%. Males had a significantly higher total score, while the patients who survived (30.00 {+/-} 9.55 vs 35.00 v 6.21, p value - <.001), received Steroids at day 2 (28.04 {+/-} 9.71 vs 31.66 {+/-} 7.12, p value - 0.002) or Remdesivir had lower total scores (28.04 {+/-} 9.71 vs 31.66 {+/-} 7.12, p-value - 0.002). Total CT score (aHR 1.05, 95% CI 1.02 - 1.08, p - 0.001), pneumothorax (aHR 1.38, 95 % CI 0.67 - 2.87, p - 0.385), pneumomediastinum (aHR 1.20, 95% CI 0.71 - 2.03, p=0.298) and cardiovascular accident (CVA, aHR 4.75, 95% CI 0.84 - 26.72, p - 0.077) were associated with increased mortality, but the results were not significant after adjusting with other variables on multiple regression analysis. ConclusionThis study identifies several radiological parameters, including fibrosis, crazy paving, pneumomediastinum, and pneumothorax, that are associated with poor prognosis in COVID-19. These findings highlight the role of CT thorax in COVID-19 illness and the importance of timely identification and interventions in severe and critical cases of COVID-19 to reduce mortality and morbidity.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.