Chest CT Total Severity Score on Admission to Predict In-Hospital Mortality in Patients with Acute and Chronic Renal Impairment with COVID-19 Infection

BACKGROUND AND AIMS COVID-19 is an infection that has spread widely and quickly over the world, resulting in a pandemic with substantial consequences for the sociopolitical environment and healthcare delivery systems. The aim of this study was to explore the clinical, laboratory characteristics and chest CT severity score in patients with renal impairment who died with COVID-19 infection. METHOD This retrospective study examined the electronic clinical and laboratory data of consecutive patients aged 18 years and older, with serum creatinine > 2 mg/dL who tested positive for COVID-19 and admitted to Mansoura University Hospital between June 2020 and May 2021. CT scans of the chest were retrospectively examined by one reviewer with 10 years’ experience in thoracic imaging for the following characteristics based on the Fleischner Society Nomenclature recommendations: ground-glass opacity (GGO), consolidation, nodules, crazy-paving pattern, subpleural lines, bronchial wall thickening, lymph node enlargement and pleural effusion.  We attempted to measure the magnitude of the abnormalities by the total severity score to assess the severity of lung parenchymal involvement. The total severity score was primarily a numeric score that assessed the existence of GGOs, consolidation or mixed GGOs in each of the five lobes of both lungs. Each lobe will be rated from 0 to 4 points based on the percentage of the involved lobe: (0) = 0%, (1) = 1–25%, (2) = 26–50%, (3) = 51–75% or (4) = 76–100%. The overall score, which varies from 0 to 20, is the sum of the points from each lobe. Death events were collected, and the ROC curve analysis for CT severity score was used to determine the best cutoff that predict mortality. RESULTS Of a total 100 patients, 54 were males, with a mean age of 60 ± 15 years. Sixty patients died. Mortality was higher in those with acute renal impairment (P = .033) than chronic kidney disease. Non-survivors had higher respiratory rate (P = .000), C-reactive protein (CRP) (P = .003), ICU admission (P = .000), oxygen supply needs (P = .005), pulmonary consolidation (P = .000) and crazy paving pattern (P = .000). Furthermore, non-survivors had higher CT chest total severity score (P = .000).  Univariate regression analysis showed increasing odds of in-hospital mortality associated with increased respiratory rate (OR 1.149, 95% CI 1.057–1.248, P = .001), total bilirubin (OR 2.532, 95% CI 1.099–5.836, P = .029), lactate dehydrogenase (OR 1.001, 95% CI 1.000–1.003, P = .018), CRP (OR 1.010, 95% CI 1.002–1.017, P = .012), invasive mechanical ventilation (OR 7.667, 95% CI 2.118–27.755, P = .002), predominant pattern of pulmonary consolidation (OR 21.714, 95% CI 4.799–98.261, P = .000) and high CT chest total severity score (OR 2.082, 95% CI 1.579–2.745, P = .000) . The optimum cut-off value of CT chest total severity score to predict in-hospital mortality was 8.5 with a sensitivity of 86.7% and a specificity of 87.5% (Figure 1).FIGURE 1: ROC curve for CT chest total severity score sensitivity and specificity to predict mortality in patients with renal impairment with COVID-19 infection. CONCLUSION In-hospital mortality is high in patients with renal impairment with COVID-19 infection especially those with acute renal impairment. High bilirubin, predominant pattern of pulmonary consolidation and CT chest total severity score are the most significant predictors of mortality in these patients. CT chest total severity score on admission ≥8.5 could effectively predict in-hospital mortality in these patients.

Chest CT Total Severity Score on Admission to Predict In-Hospital Mortality in COVID-19 Patients with Acute and Chronic Renal Impairment.

Aim: To identify the predictors of in-hospital mortality in patients with coronavirus disease of 2019 (COVID-19) and acute renal impairment (ARI) or chronic kidney disease (CKD), and to evaluate the performance and inter-reader concordance of chest CT total severity scores (TSSs). Methods: This retrospective single-center study was conducted on symptomatic COVID-19 patients with renal impairment (either acute or chronic) and a serum creatinine of >2 mg/dL at the time of admission. The patients' demographic characteristics, clinical data, and laboratory data were extracted from the clinical computerized medical records. All chest CT images obtained at the time of hospital admission were analyzed. Two radiologists independently assessed the pulmonary abnormalities and scored the severity using CT chest total severity score (TSS). Univariate logistic regression analysis was used to determine factors associated with in-hospital mortality. A receiver operating characteristic (ROC) curve analysis was performed for the TSS in order to identify the cut-off point that predicts mortality. Bland-Altman plots were used to evaluate agreement between the two radiologists assessing TSS. Results: A total of 100 patients were included, with a mean age of 60 years, 54 were males, 53 had ARI, and 47 had CKD. In terms of in-hospital mortality, 60 patients were classified in the non-survivor group and 40 were classified in the survivor group. The mortality rate was higher for those with ARI compared to those with CKD (p = 0.033). The univariate regression analysis showed an increasing odds of in-hospital mortality associated with higher respiratory rate (OR 1.149, 95% CI 1.057-1.248, p = 0.001), total bilirubin (OR 2.532, 95% CI 1.099-5.836, p = 0.029), lactate dehydrogenase (LDH) (OR 1.001, 95% CI 1.000-1.003, p = 0.018), CRP (OR 1.010, 95% CI 1.002-1.017, p = 0.012), invasive mechanical ventilation (MV) (OR 7.667, 95% CI 2.118-27.755, p = 0.002), a predominant pattern of pulmonary consolidation (OR 21.714, 95% CI 4.799-98.261, p < 0.001), and high TSS (OR 2.082, 95% CI 1.579-2.745, p < 0.001). The optimum cut-off value of TSS used to predict in-hospital mortality was 8.5 with a sensitivity of 86.7% and a specificity of 87.5%. There was excellent interobserver agreement (ICC > 0.9) between the two independent radiologists in their quantitative assessment of pulmonary changes using TSS. Conclusions: In-hospital mortality is high in COVID-19 patients with ARI/CKD, especially for those with ARI. High serum bilirubin, a predominant pattern of pulmonary consolidation, and TSS are the most significant predictors of mortality in these patients. Patients with a higher TSS may require more intensive hospital care. TSS is a reliable and helpful auxiliary tool for risk stratification among COVID-19 patients with ARI/CKD.

Comparison of chest CT severity scoring systems for COVID-19.

PURPOSE: To compare the diagnostic performance and inter-observer agreement of five different CT chest severity scoring systems for COVID-19 to find the most precise one with the least interpretation time. METHODS AND MATERIALS: This retrospective study included 85 patients (54 male and 31 female) with PCR-confirmed COVID-19. They underwent CT to assess the severity of pulmonary involvement. Three readers were asked to assess the pulmonary abnormalities and score the severity using five different systems, including chest CT severity score (CT-SS), chest CT score, total severity score (TSS), modified total severity score (m-TSS), and 3-level chest CT severity score. Time consumption on reporting of each system was calculated. RESULTS: Two hundred fifty-five observations were reported for each system. There was a statistically significant inter-observer agreement in assessing qualitative lung involvement using the m-TSS and the other four quantitative systems. The ROC curves revealed excellent and very good diagnostic accuracy for all systems when cutoff values for detection severe cases were > 22, > 17, > 12, and > 26 for CT-SS, chest CT score, TSS, and 3-level CT severity score. The AUC was very good (0.86), excellent (0.90), very good (0.89), and very good (0.86), respectively. Chest CT score showed the highest specificity (95.2%) in discrimination of severe cases. Time consumption on reporting was significantly different (< 0.001): CT-SS > 3L-CT-SS > chest CT score > TSS. CONCLUSION: All chest CT severity scoring systems in this study demonstrated excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. CT-SS and TSS had the highest specificity and least time for interpretation. KEY POINTS: • All chest CT severity scoring systems discussed in this study revealed excellent inter-observer agreement and reasonable performance to assess COVID-19 in relation to the clinical severity. • Chest CT scoring system and TSS had the highest specificity. • Both TSS and m-TSS consumed the least time compared to the other three scoring systems.