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Biomarker evaluation for prognostic stratification of patients with COVID-19: the added value of quantitative chest CT.

ABSTRACT: Aim: Pulmonary disease burden and biomarkers are possible predictors of outcomes in patients with COVID-19 and provide complementary information. In this study, the prognostic value of adding quantitative chest computed tomography (CT) to a multiple biomarker approach was evaluated among 148 hospitalized patients with confirmed COVID-19. Materials & methods: Patients admitted between March and July 2020 who were submitted to chest CT and biomarker measurement (troponin I, D-dimer and C-reactive protein) were retrospectively analyzed. Biomarker and tomographic data were compared and associated with death and intensive care unit admission. Results: The number of elevated biomarkers was significantly associated with greater opacification percentages, lower lung volumes and higher death and intensive care unit admission rates. Total lung volume <3.0 l provided further stratification for mortality when combined with biomarker evaluation. Conclusion: Adding automated CT data to a multiple biomarker approach may provide a simple strategy for enhancing risk stratification of patients with COVID-19.

SUBMITTER: Ferreira RM

PROVIDER: S-EPMC8855956 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Biomarker evaluation for prognostic stratification of patients with COVID-19: the added value of quantitative chest CT.

Ferreira Roberto M RM Ferreira Roberto M RM de Oliveira Gabriel Ss GS da Rocha João Rf JR Mc Ribeiro Felipe de F Stern João J JJ S Costa Rangel de R Lemgruber Ricardo N RN Ramalho Júlia Fp JF de Almeida Alexandre Cp AC Sampaio Pedro Pn PP Filho João Mansur JM Lima Ricardo Ac RA

Biomarkers in medicine 20220218 4

<b>Aim:</b> Pulmonary disease burden and biomarkers are possible predictors of outcomes in patients with COVID-19 and provide complementary information. In this study, the prognostic value of adding quantitative chest computed tomography (CT) to a multiple biomarker approach was evaluated among 148 hospitalized patients with confirmed COVID-19. <b>Materials & methods:</b> Patients admitted between March and July 2020 who were submitted to chest CT and biomarker measurement (troponin I, D-dimer a ...[more]

PMID: 35176874

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Project description:ObjectiveThis study aims to explore the prognostic value of quantitatively evaluating muscle mass using chest high resolution computed tomography (HRCT) in patients with active tuberculosis (TB).MethodsThis retrospective cohort study collected data from 309 patients with active TB diagnosed at Ningbo No.2 Hospital from 2020 to 2023. Based on the skeletal muscle index (SMI) at the T12 vertebra (with thresholds of <28.8 cm2/m2 for men and <20.8 cm2/m2 for women), patients were divided into a low muscle mass group and a normal muscle mass group. The study compared baseline characteristics, muscle mass-related indicators, body mass index (BMI), and imaging features between the two groups. The correlation between muscle mass-related indicators, BMI, and TB imaging features and prognosis was analyzed. Receiver operating characteristic (ROC) curve analysis and multivariate logistic regression were used to assess the prognostic value of muscle mass-related indicators and BMI in patients undergoing anti-TB treatment.ResultsA total of 309 patients were included in the study, divided into a normal muscle mass group (n = 229) and a low muscle mass group (n = 80). There was a significant difference in prognosis between the two groups (χ 2 test, p < 0.05). Patients in the low muscle mass group were older, had a higher proportion of males, and had a lower BMI (p < 0.05). Additionally, these patients had a higher likelihood of developing pulmonary cavities (p < 0.05). In terms of imaging features, the two groups showed significant differences in the pre-treatment proportion of pulmonary fibrotic bands, ground-glass opacities, consolidation, lesion percentage, and lesion absorption ratio (all p < 0.05). Univariate analysis indicated that both the T12 skeletal muscle index (T12 SMI) and BMI were correlated with TB imaging characteristics (p < 0.05), with T12 SMI showing a stronger correlation than BMI. Multivariable linear regression analysis revealed that after adjusting for age, gender, and T12 skeletal muscle radiation attenuation (T12 SMRA), T12 SMI remained significantly correlated with the whole-lung lesion proportion (β: - 4.56, 95% CI [-5.45 to -3.67]) and lesion absorption ratio (β:0.036, 95% CI [0.031-0.041]). Multivariable logistic regression analysis demonstrated that after accounting for age, gender, T12 SMRA, T12 SMI was significantly associated with the prognosis of TB patients (OR: 20.10, 95% CI [8.81-51.56], p < 0.05), indicating that low T12 SMI is an independent risk factor associated with poor prognosis. ROC curve analysis indicated that T12 SMI may offer advantages over BMI, with an area under the ROC curve (AUC) of T12 SMI (0.761, 95% CI [0.690-0.832]) higher than the AUC of BMI (0.700, 95% CI [0.619-0.781].ConclusionQuantitative evaluation of muscle mass using chest HRCT, particularly the T12 SMI, may provide valuable prognostic information for tuberculosis patients, potentially offering advantages over BMI in assessing patient outcomes.

Project description:INTRODUCTION:COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients. MATERIALS AND METHODS:From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p?<?0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis. RESULTS:Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66?±?16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63?±?15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55?±?0.26L vs 0.43?±?0.23L, p?=?0.0005) and fibrotic alterations (0.05?±?0.03 L vs 0.04?±?0.03 L, p?<?0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p?<?0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p?<?0.001), respectively. CONCLUSIONS:Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.

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Biomarker evaluation for prognostic stratification of patients with COVID-19: the added value of quantitative chest CT.

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Biomarker evaluation for prognostic stratification of patients with COVID-19: the added value of quantitative chest CT.

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