Your browser doesn't support javascript.
Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: a cross-sectional study based on machine learning.
Wang, Xingrui; Che, Qinglin; Ji, Xiaoxiao; Meng, Xinyi; Zhang, Lang; Jia, Rongrong; Lyu, Hairong; Bai, Weixian; Tan, Lingjie; Gao, Yanjun.
  • Wang X; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Che Q; Xi'an Key Laboratory of Cardiovascular and Cerebrovascular Diseases, Xi'an No.3 Hospital, the Affiliated Hospital of Northwest University, Northwest University, Xi'an, 710018, Shaanxi Province, China.
  • Ji X; Department of Radiology, Jingmen No.1 People's Hospital, Jingmen, 448000, Hubei Province, China.
  • Meng X; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Zhang L; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Jia R; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Lyu H; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Bai W; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Tan L; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
  • Gao Y; Department of Radiology, Xi'an No.3 Hospital, The Affiliated Hospital of Northwest University, Shaanxi Province, 710018, Xi'an, China.
BMC Infect Dis ; 21(1): 192, 2021 Feb 18.
Artículo en Inglés | MEDLINE | ID: covidwho-1090689
ABSTRACT

BACKGROUND:

Coronavirus 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.

METHODS:

Chest 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.

RESULTS:

No 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%.

CONCLUSIONS:

Lung 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.
Asunto(s)
Palabras clave

Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Aprendizaje Automático / COVID-19 / Pulmón Tipo de estudio: Estudios diagnósticos / Estudio observacional / Estudio pronóstico / Ensayo controlado aleatorizado Límite: Adulto / Femenino / Humanos / Masculino / Middle aged Idioma: Inglés Revista: BMC Infect Dis Asunto de la revista: Enfermedades Transmisibles Año: 2021 Tipo del documento: Artículo País de afiliación: S12879-021-05839-9

Similares

MEDLINE

...
LILACS

LIS


Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Aprendizaje Automático / COVID-19 / Pulmón Tipo de estudio: Estudios diagnósticos / Estudio observacional / Estudio pronóstico / Ensayo controlado aleatorizado Límite: Adulto / Femenino / Humanos / Masculino / Middle aged Idioma: Inglés Revista: BMC Infect Dis Asunto de la revista: Enfermedades Transmisibles Año: 2021 Tipo del documento: Artículo País de afiliación: S12879-021-05839-9