Literature DB >> 33691358

Predictors of Worsening Oxygenation in COVID-19.

Jee Youn Oh1.   

Abstract

Entities:  

Year:  2021        PMID: 33691358      PMCID: PMC8273014          DOI: 10.4046/trd.2021.0034

Source DB:  PubMed          Journal:  Tuberc Respir Dis (Seoul)        ISSN: 1738-3536


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The spread of coronavirus disease 2019 (COVID-19) has resulted in a pandemic, leading to a sudden and substantial increase in the use of medical resources worldwide1. Although the key characteristic of COVID-19 is that most patients have a mild clinical course, some patients demonstrate rapid deterioration to respiratory failure2. Thus, it is important to triage and stratify the risk of COVID-19 patients in order to optimize the distribution of medical resources and prevent progression3. Worsening oxygenation is the key finding that forecasts severe cases4, but investigating biomarkers for worsening oxygenation is still an unmet medical need in COVID-19 patients. Hahm et al.5 retrospectively evaluated the factors associated with worsening oxygenation in patients with non-severe COVID-19 pneumonia. Quantitative analysis of computed tomography (CT) using artificial intelligence (AI) tools as well as laboratory findings such as C-reactive protein (CRP), ferritin, lactic dehydrogenase (LDH), and lower lymphocyte counts were predictors of worsening oxygenation. Although this was a retrospective, single-center study involving a small number of patients with non-severe pneumonia, it synthetically analyzed the factors known to be associated with deterioration including comorbidities, pro-inflammatory cytokines, and CT findings using AI tools, and provided an automatic and objective estimation of the disease burden. Previous studies have reported that age and underlying diseases may be risk factors for COVID-19 patients requiring oxygenation, which is a well-known risk factor for other pneumonia6. Particularly for COVID-19, some patients progress to hypoxemia rapidly at approximately 1–2 weeks after onset, likely not due to the cytopathic activity of the virus, but due to the cytokine storm, as evidenced by increased proinflammatory cytokines7. Thus, inflammatory markers such as CRP, procalcitonin levels, neutrophil-lymphocyte ratio, and the rate of change of CRP have been reported to predict the progression of COVID-198. Subsequently, more critical COVID-19 patients release procoagulant autoantibodies and markers associated with cytokine-mediated tissue damage and organ failure, and these are reported markers predicting severe COVID-19 or poor outcomes of COVID-199. Elevated D-dimer levels, LDH, troponin I, and thrombocytopenia in patients with severe COVID-19 have also been reported, suggesting that a hyper-coagulable state may contribute to the severity of illness and mortality10. In non-severe cases, chest CT is pivotal in predicting prognosis11,12. Chest quantitative CT has a promising role in the early diagnosis of COVID-19 and provides new metrics for predicting clinical outcomes13. The binding of coronavirus spike protein to angiotensin-converting enzyme II receptor increases pulmonary capillary permeability and causes diffuse opacities in CT14. CT could reflect the early pathogenesis of COVID-19 inflammation, even though chest radiography could not detect the abnormalities15. In fact, CT severity score is associated with inflammatory levels, and CT severity score on admission is an independent risk factor for early deterioration16. Moreover, the rapid improvement of AI has enabled the automatic quantification of lesions and the prediction of outcomes more precisely. There have been thousands of reports on biomarkers for predicting outcomes of COVID-19 with various parameters, diverse clinical severities, and outcomes. In particular, many studies have dealt with mortality predictors for severe COVID-19 cases4,10,17. However, rather than predicting mortality for initially critical patients, Hahm et al.5 investigated the scoring of non-severe patients on potential rapidly worsening oxygenation, which would be a more useful tool in regions where non-severe cases are more prevalent due to mass surveillance screening18. More accurate, simple, and easily applicable tools for predicting worsening oxygenation in COVID-19 for initial risk stratification and medical resource arrangement are needed.
  17 in total

1.  Is a "Cytokine Storm" Relevant to COVID-19?

Authors:  Pratik Sinha; Michael A Matthay; Carolyn S Calfee
Journal:  JAMA Intern Med       Date:  2020-09-01       Impact factor: 21.873

2.  Responding to Covid-19 - A Once-in-a-Century Pandemic?

Authors:  Bill Gates
Journal:  N Engl J Med       Date:  2020-02-28       Impact factor: 91.245

Review 3.  Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review.

Authors:  W Joost Wiersinga; Andrew Rhodes; Allen C Cheng; Sharon J Peacock; Hallie C Prescott
Journal:  JAMA       Date:  2020-08-25       Impact factor: 56.272

4.  Factors Associated with Worsening Oxygenation in Patients with Non-severe COVID-19 Pneumonia.

Authors:  Cho Rom Hahm; Young Kyung Lee; Dong Hyun Oh; Mi Young Ahn; Jae-Phil Choi; Na Ree Kang; Jungkyun Oh; Hanzo Choi; Suhyun Kim
Journal:  Tuberc Respir Dis (Seoul)       Date:  2021-01-05

5.  Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients.

Authors:  Nathalie Lassau; Samy Ammari; Emilie Chouzenoux; Hugo Gortais; Paul Herent; Matthieu Devilder; Samer Soliman; Olivier Meyrignac; Marie-Pauline Talabard; Jean-Philippe Lamarque; Remy Dubois; Nicolas Loiseau; Paul Trichelair; Etienne Bendjebbar; Gabriel Garcia; Corinne Balleyguier; Mansouria Merad; Annabelle Stoclin; Simon Jegou; Franck Griscelli; Nicolas Tetelboum; Yingping Li; Sagar Verma; Matthieu Terris; Tasnim Dardouri; Kavya Gupta; Ana Neacsu; Frank Chemouni; Meriem Sefta; Paul Jehanno; Imad Bousaid; Yannick Boursin; Emmanuel Planchet; Mikael Azoulay; Jocelyn Dachary; Fabien Brulport; Adrian Gonzalez; Olivier Dehaene; Jean-Baptiste Schiratti; Kathryn Schutte; Jean-Christophe Pesquet; Hugues Talbot; Elodie Pronier; Gilles Wainrib; Thomas Clozel; Fabrice Barlesi; Marie-France Bellin; Michael G B Blum
Journal:  Nat Commun       Date:  2021-01-27       Impact factor: 14.919

Review 6.  Angiotensin-Converting Enzyme 2: SARS-CoV-2 Receptor and Regulator of the Renin-Angiotensin System: Celebrating the 20th Anniversary of the Discovery of ACE2.

Authors:  Mahmoud Gheblawi; Kaiming Wang; Anissa Viveiros; Quynh Nguyen; Jiu-Chang Zhong; Anthony J Turner; Mohan K Raizada; Maria B Grant; Gavin Y Oudit
Journal:  Circ Res       Date:  2020-04-08       Impact factor: 17.367

7.  Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Authors:  Kang Zhang; Xiaohong Liu; Jun Shen; Zhihuan Li; Ye Sang; Xingwang Wu; Yunfei Zha; Wenhua Liang; Chengdi Wang; Ke Wang; Linsen Ye; Ming Gao; Zhongguo Zhou; Liang Li; Jin Wang; Zehong Yang; Huimin Cai; Jie Xu; Lei Yang; Wenjia Cai; Wenqin Xu; Shaoxu Wu; Wei Zhang; Shanping Jiang; Lianghong Zheng; Xuan Zhang; Li Wang; Liu Lu; Jiaming Li; Haiping Yin; Winston Wang; Oulan Li; Charlotte Zhang; Liang Liang; Tao Wu; Ruiyun Deng; Kang Wei; Yong Zhou; Ting Chen; Johnson Yiu-Nam Lau; Manson Fok; Jianxing He; Tianxin Lin; Weimin Li; Guangyu Wang
Journal:  Cell       Date:  2020-05-04       Impact factor: 41.582

8.  Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions.

Authors:  Arthur Eumann Mesas; Iván Cavero-Redondo; Celia Álvarez-Bueno; Marcos Aparecido Sarriá Cabrera; Selma Maffei de Andrade; Irene Sequí-Dominguez; Vicente Martínez-Vizcaíno
Journal:  PLoS One       Date:  2020-11-03       Impact factor: 3.240

9.  Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics.

Authors:  Zhichao Feng; Qizhi Yu; Shanhu Yao; Lei Luo; Wenming Zhou; Xiaowen Mao; Jennifer Li; Junhong Duan; Zhimin Yan; Min Yang; Hongpei Tan; Mengtian Ma; Ting Li; Dali Yi; Ze Mi; Huafei Zhao; Yi Jiang; Zhenhu He; Huiling Li; Wei Nie; Yin Liu; Jing Zhao; Muqing Luo; Xuanhui Liu; Pengfei Rong; Wei Wang
Journal:  Nat Commun       Date:  2020-10-02       Impact factor: 14.919

10.  Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Authors:  Laure Wynants; Ben Van Calster; Gary S Collins; Richard D Riley; Georg Heinze; Ewoud Schuit; Marc M J Bonten; Darren L Dahly; Johanna A A Damen; Thomas P A Debray; Valentijn M T de Jong; Maarten De Vos; Paul Dhiman; Maria C Haller; Michael O Harhay; Liesbet Henckaerts; Pauline Heus; Michael Kammer; Nina Kreuzberger; Anna Lohmann; Kim Luijken; Jie Ma; Glen P Martin; David J McLernon; Constanza L Andaur Navarro; Johannes B Reitsma; Jamie C Sergeant; Chunhu Shi; Nicole Skoetz; Luc J M Smits; Kym I E Snell; Matthew Sperrin; René Spijker; Ewout W Steyerberg; Toshihiko Takada; Ioanna Tzoulaki; Sander M J van Kuijk; Bas van Bussel; Iwan C C van der Horst; Florien S van Royen; Jan Y Verbakel; Christine Wallisch; Jack Wilkinson; Robert Wolff; Lotty Hooft; Karel G M Moons; Maarten van Smeden
Journal:  BMJ       Date:  2020-04-07
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  1 in total

1.  Predictors of Worsening COVID-19 Illness.

Authors:  Beuy Joob; Viroj Wiwanitkit
Journal:  Tuberc Respir Dis (Seoul)       Date:  2021-04-02
  1 in total

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