ArticleBMC infectious diseases2021
Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.
Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 25 citations in OpenAlex.
- Evidence of a cognitive bias in the quantification of COVID-19 with CT: an artificial intelligence randomised clinical trial.Scientific reports · 2023Trial
- Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.Scientific reports · 2021Trial
- Classification of the ICU Admission for COVID-19 Patients with Transfer Learning Models Using Chest X-Ray Images.Diagnostics (Basel, Switzerland) · 2025Article
- Two Years after the Beginning of COVID-19: Comparing Families Who Had or Did not Have Patients with COVID-19 on Health Beliefs and Obsessive-Compulsive Symptoms.Iranian journal of psychiatry · 2023Article
- Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review.SN computer science · 2023Article
- After the virus has cleared-Can preclinical models be employed for Long COVID research?PLoS pathogens · 2022Review
- Screening and assessment for post-acute COVID-19 syndrome (PACS), guidance by personal pilots and support with individual digital trainings within intersectoral care: a study protocol of a randomized controlled trial.BMC infectious diseases · 2022Article
- Article
- Machine Learning and Lean Six Sigma to Assess How COVID-19 Has Changed the Patient Management of the Complex Operative Unit of Neurology and Stroke Unit: A Single Center Study.International journal of environmental research and public health · 2022Article
- Medical imaging of pulmonary disease in SARS-CoV-2-exposed non-human primates.Trends in molecular medicine · 2022Review
- A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19.Diagnostics (Basel, Switzerland) · 2021Review
- Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19.Pathogens (Basel, Switzerland) · 2021Review
- The Rise of SARS-CoV-2 Variants and the Role of Convalescent Plasma Therapy for Management of Infections.Life (Basel, Switzerland) · 2021Review
- Longitudinal trajectories of pneumonia lesions and lymphocyte counts associated with disease severity among convalescent COVID-19 patients: a group-based multi-trajectory analysis.BMC pulmonary medicine · 2021Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoronavirus disease 2019 (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in COVID-19 and to analyse its underlying mechanism.
methodsChest high-resolution computer tomography (CT) images and laboratory examination data of 31 patients with COVID-19 were extracted, and the lesion areas in CT images were quantitatively segmented and calculated using a deep learning (DL) system. A cross-sectional study method was carried out to explore the differences among the proportions of lung lobe infection and to correlate the percentage of infection (POI) of the whole lung in all patients with clinical laboratory examination values.
resultsNo significant difference in the proportion of infection was noted among various lung lobes (P > 0.05). The POI of total lung was negatively correlated with the peripheral blood lymphocyte percentage (L%) (r = - 0.633, P < 0.001) and lymphocyte (LY) count (r = - 0.555, P = 0.001) but positively correlated with the neutrophil percentage (N%) (r = 0.565, P = 0.001). Otherwise, the POI was not significantly correlated with the peripheral blood white blood cell (WBC) count, monocyte percentage (M%) or haemoglobin (HGB) content. In some patients, as the infection progressed, the L% and LY count decreased progressively accompanied by a continuous increase in the N%.
conclusionsLung lesions in COVID-19 patients are significantly correlated with the peripheral blood lymphocyte and neutrophil levels, both of which could serve as prognostic indicators that provide warning implications, and contribute to clinical interventions in patients.
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