Glycemic status affects the severity of coronavirus disease 2019 in patients with diabetes mellitus: an observational study of CT radiological manifestations using an artificial intelligence algorithm

Lu, Xiaoting; Cui, Zhenhai; Pan, Feng; Li, Lingli; Li, Lin; Liang, Bo; Yang, Lian; Zheng, Chuansheng

doi:10.1007/s00592-020-01654-x

Cited by 19 publications

(14 citation statements)

References 29 publications

(42 reference statements)

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“…This could be explained by the significant correlation of those comorbidities with disease burden in COVID-19 patients and accordingly severity of lung affection and CT-severity score. This agrees with the study of Lu et al [21] which stated that older age and increased blood glucose level were correlated with the severity of lung involvement and clinical prognosis in COVID-19 patients. There was a positive correlation between blood glucose level on admission and lung lesions.…”

Section: Discussionsupporting

confidence: 93%

Semi-quantitative CT severity scoring as a predictor of development of post-COVID syndrome

Saad

Khateeb

Ahmed

et al. 2021

Egypt J Radiol Nucl Med

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Background Following COVID-19 pandemic, clinical description focused on the clinical presentation of patients in the acute stage of the disease. More recently, data have emerged that some patients continue to experience symptoms related to COVID-19 after the acute phase of infection has subsided (post-COVID syndrome). Although characteristics of post-COVID syndrome have been well described, less is known about the possible invitations during acute illnesses that can predict such syndrome. Our study is a prospective study aiming at assessment of CT severity scoring in the acute phase of COVID-19 pneumonia as a predictor for development of post-COVID syndrome in recovering patients. Results A total of 192 symptomatic COVID-19 patients between April 2020 and October 2020 were enrolled in this single-center study, and high-resolution chest CT examinations were evaluated for CT severity scoring. Data were matched with the long-term clinical outcome. CT severity score was significantly higher in patients who developed post-COVID symptoms (p < 0.001). A CT score of > 7 was associated with an increased risk and was found to be predictive of condition development with sensitivity (95.9%), specificity (96%), positive predictive value (95.92%), negative predictive value (96%), and accuracy (95.96%). Conclusions CT severity scoring can help in predicting the long-term outcome of COVID-19 patients with cutoff value of CT-SSS > 7 showing highest sensitivity and specificity for predicting development of post-COVID syndrome.

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Section: Discussionsupporting

confidence: 93%

Semi-quantitative CT severity scoring as a predictor of development of post-COVID syndrome

Saad

Khateeb

Ahmed

et al. 2021

Egypt J Radiol Nucl Med

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“…DM is a known risk factor for severe COVID-19[43]. Here we observed increased levels of HbA1c in 184/280 PACS cases, most of whom had no previous diagnosis of DM.…”

Section: Discussionsupporting

confidence: 49%

Post-Acute COVID Syndrome, the Aftermath of Mild to Severe COVID-19 in Brazilian Patients

Barreto

Duarte

Cerqueira‐Silva

et al. 2021

Preprint

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Objective: To describe persistent symptoms after acute COVID-19 in different spectrum of disease severity in a population from an upper/middle income country, and identify the main clinical features impacting the quality of life. Design: Cross-sectional study. Setting: Outpatient clinic from a public post-COVID-19 health center (CPC) at Bahia-Brazil, a state where 80% are black or mixed race. Participants: Patients admitted between August 2020 and February 2021 with symptoms at least one month after the onset of COVID-19. Main outcome measures: PACS and related disorders such as hospitalization one month or later after disease onset, biochemical dysregulation and reduced quality of life (EQ-5D-5L questionnaire). Results: Among 683 individuals assisted at CPC in this period, 602 were recruited. Patients had average of 52 (±14.6) years, 355 (59%) were female, 528 (88%) black/brown. Individuals were classified as mild (39.9%), moderate (27.9%) or severe (32.2%) during acute illness if outpatient, hospitalized non-UCI or UCI, respectively. Most patients reported a polysymptomatic profile, in median eight (IQR=6-9) acute symptoms. The most frequent residual symptoms were dyspnea (66%), fatigue (62%) and chest pain (43%). Women were more affected regardless disease severity at acute stage: presented more residual symptoms [4 (2-6) vs 3 (2-4)] and a higher impact in quality of life. Altered HbA1c [(184/275 (66.9%)], high CRP levels [195/484 (40.3%)] and anemia [143/545 (26.2%)] were the most common abnormalities in laboratory exams. 76 patients presented HbA1c above 6.4% although only 42 referred previous diagnosis of diabetes mellitus. After one month of disease onset, 30 patients required hospitalization, including seven cases with mild acute illness. Hospital admission after acute disease was required on 30 patients, seven (23%) were mild. Quality of life had been affected for 357/404 (88.4%) patients according to EuroQoL (EQ-5D-5L), mainly the domains of anxiety/depression [severe or extreme anxiety for 79/401 (19.7%)] and pain/discomfort [severe or extreme pain for 71/403 (17.6%)]. The median EuroQoL Global Score was 70 [IQR 50-80]. PACS symptoms such as dyspnea, chest pain, and fatigue, was associated with decreased quality of life. Conclusions: PACS, such as dyspnea, chest pain and fatigue, occurred after variable degree of disease severity. Among this majority black/mixed-race patients, woman seemed to be more affected. Other consequences included post-acute hospitalization, and abnormal glucose metabolism and reduced quality of life.

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“…It was demonstrated a positive correlation between blood glucose level, measured also with blood fasting glucose, at admission and pulmonary involvement (higher PLV, PGV and PCV) that, in turn, were predictors of poor clinical outcomes (AUC of 0.796, 0.783, 0.816, respectively) [125]. Another retrospective study quantified pneumonia lesions on CT images through a UNet neural network to assess the influence of comorbidity on COVID-19 patients.…”

Section: Ai In the Stratification And Definition Of Severity And Complications Of Covid-19 Pneumonia At Chest Ctmentioning

confidence: 99%

The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review

et al. 2021

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Diagnostic imaging is regarded as fundamental in the clinical work-up of patients with a suspected or confirmed COVID-19 infection. Recent progress has been made in diagnostic imaging with the integration of artificial intelligence (AI) and machine learning (ML) algorisms leading to an increase in the accuracy of exam interpretation and to the extraction of prognostic information useful in the decision-making process. Considering the ever expanding imaging data generated amid this pandemic, COVID-19 has catalyzed the rapid expansion in the application of AI to combat disease. In this context, many recent studies have explored the role of AI in each of the presumed applications for COVID-19 infection chest imaging, suggesting that implementing AI applications for chest imaging can be a great asset for fast and precise disease screening, identification and characterization. However, various biases should be overcome in the development of further ML-based algorithms to give them sufficient robustness and reproducibility for their integration into clinical practice. As a result, in this literature review, we will focus on the application of AI in chest imaging, in particular, deep learning, radiomics and advanced imaging as quantitative CT.

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Glycemic status affects the severity of coronavirus disease 2019 in patients with diabetes mellitus: an observational study of CT radiological manifestations using an artificial intelligence algorithm

Cited by 19 publications

References 29 publications

Semi-quantitative CT severity scoring as a predictor of development of post-COVID syndrome

Semi-quantitative CT severity scoring as a predictor of development of post-COVID syndrome

Post-Acute COVID Syndrome, the Aftermath of Mild to Severe COVID-19 in Brazilian Patients

The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review

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