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CT-based pathological lung volume and adverse outcomes of patients with Coronavirus Disease 2019 (COVID-19).

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Title: CT-based pathological lung volume and adverse outcomes of patients with Coronavirus Disease 2019 (COVID-19).
Alternate Title: Correlación de volumetría por TC de lesiones pulmonares y resultados adversos en pacientes coronavirus COVID-19.
Authors: Morales-Jaramillo, Leonardo M.1, Timaran-Montenegro, David1, Mateo-Camacho, Yohana1, Torres-Ramírez, Christian1, Fuentes-Badillo, Karla1, Morales-Domínguez, Valeria1, Punzo-Alcaraz, Gerardo1, Tapia-Rangel, Edgar1, Feria-Arroyo, Gustavo1, Parra-Guerrero, Lina1, Sáenz-Castillo, Pedro1, Hernández-Rojas, Ana1, Falla-Trujillo, Manuel1, Obando-Bravo, Daniel1, Contla-Trejo, Giovanni1, Jácome-Portilla, Katherine1, Chávez-Sastré, Alberto1, Govea-Palma, Jovani1, Carrillo-Álvarez, Santiago1, Orozco-Vázquez, Julita1
Source: Anales de Radiologia, Mexico. ene-mar2023, Vol. 22 Issue 1, p1-12. 12p.
Subjects: COVID-19, COMPUTED tomography, LUNG diseases, ARTIFICIAL respiration, INTENSIVE care units
Abstract (English): Objective: To assess the association between CT-based percentage of pathological lung opacities volume (%PLOV) and the occurrence of adverse outcomes of patients with COVID-19. Methods: An observational, longitudinal, single-center study was performed including patients with COVID-19. CT-based lung segmentation was performed to calculate %PLOV. The primary endpoint was the occurrence of adverse lung event (ALE), defined as ICU admission, the use of mechanical ventilation, or death. Mann-Whitney U test was performed for univariate analysis. Logistic regression analysis was performed to determine independent predictors of critical illness. Results: 138 patients (84 men [61%]) with a mean age of 47.3 years were enrolled. Median %PLOV was 28.64% (interquartile range [IQR], 6.33-47.22%). ALE occurred in 52 patients (38%) with an overall mortality rate of 21% (29 patients). Multivariate analysis demonstrated that %PLOV was an independent predictor of ALE with an Odds ratio of 1.049 (95% confidence interval [CI], 1.014-1.085) (p < 0.01). Furthermore, a %PLOV of 64% demonstrated a 25.5-fold increased risk of ALE with a sensitivity and specificity higher than 75% (p < 0.01). Conclusion: The quantitative evaluation of chest CT impacts the determination of severity of COVID-19 pneumonia on admission. %PLOV was the strongest predictor for the development of ALE in hospitalized patients. [ABSTRACT FROM AUTHOR]
Abstract (Spanish): Objetivo: Evaluar asociación entre el porcentaje del volumen de opacidades pulmonares patológicas basado en la TC (% PLOV) y resultados adversos en pacientes con COVID-19. Métodos: Estudio observacional, longitudinal, unicéntrico. Se realizó TC de tórax basal y % PLOV mediante segmentación. Se obtuvieron biomarcadores de inflamación y recuento leucocitario. Resultado adverso (RA) se definió por ingreso en UCI, ventilación mecánica o muerte. Se realizó la prueba U de Mann-Whitney y regresión logística. Resultados: 138 pacientes (84 hombres [61%]) con edad media de 47,3 años. La mediana del% PLOV fue del 28,64% (rango intercuartílico [IQR], 6,33-47,22%). RA se presentó en 52 (38%) tasa de mortalidad global 21% (29 pacientes). Los pacientes con RA tenían niveles séricos más altos de biomarcadores inflamatorios con mediana de% PLOV del 52% frente al 12% de los pacientes sin RA. El análisis multivariado mostró que el% PLOV es predictor independiente de RA con una razón de probabilidades de 1.049 (intervalo de confianza [IC] del 95%, 1.014-1.085) (p < 0.01). Además, un% PLOV del 64% demostró un riesgo 25,5 veces mayor de RA con una sensibilidad y especificidad superiores al 75% (p < 0,01). Conclusión: PLOV fue el predictor más fuerte para el desarrollo de RA en pacientes hospitalizados. [ABSTRACT FROM AUTHOR]
Copyright of Anales de Radiologia, Mexico is the property of Sociedad Mexicana de Radiologia e Imagen A.C. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: CT-based pathological lung volume and adverse outcomes of patients with Coronavirus Disease 2019 (COVID-19).
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  Data: Correlaci&#243;n de volumetr&#237;a por TC de lesiones pulmonares y resultados adversos en pacientes coronavirus COVID-19.
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  Data: Objective: To assess the association between CT-based percentage of pathological lung opacities volume (%PLOV) and the occurrence of adverse outcomes of patients with COVID-19. Methods: An observational, longitudinal, single-center study was performed including patients with COVID-19. CT-based lung segmentation was performed to calculate %PLOV. The primary endpoint was the occurrence of adverse lung event (ALE), defined as ICU admission, the use of mechanical ventilation, or death. Mann-Whitney U test was performed for univariate analysis. Logistic regression analysis was performed to determine independent predictors of critical illness. Results: 138 patients (84 men [61%]) with a mean age of 47.3 years were enrolled. Median %PLOV was 28.64% (interquartile range [IQR], 6.33-47.22%). ALE occurred in 52 patients (38%) with an overall mortality rate of 21% (29 patients). Multivariate analysis demonstrated that %PLOV was an independent predictor of ALE with an Odds ratio of 1.049 (95% confidence interval [CI], 1.014-1.085) (p &lt; 0.01). Furthermore, a %PLOV of 64% demonstrated a 25.5-fold increased risk of ALE with a sensitivity and specificity higher than 75% (p &lt; 0.01). Conclusion: The quantitative evaluation of chest CT impacts the determination of severity of COVID-19 pneumonia on admission. %PLOV was the strongest predictor for the development of ALE in hospitalized patients. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (Spanish)
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  Data: Objetivo: Evaluar asociaci&#243;n entre el porcentaje del volumen de opacidades pulmonares patol&#243;gicas basado en la TC (% PLOV) y resultados adversos en pacientes con COVID-19. M&#233;todos: Estudio observacional, longitudinal, unic&#233;ntrico. Se realiz&#243; TC de t&#243;rax basal y % PLOV mediante segmentaci&#243;n. Se obtuvieron biomarcadores de inflamaci&#243;n y recuento leucocitario. Resultado adverso (RA) se defini&#243; por ingreso en UCI, ventilaci&#243;n mec&#225;nica o muerte. Se realiz&#243; la prueba U de Mann-Whitney y regresi&#243;n log&#237;stica. Resultados: 138 pacientes (84 hombres [61%]) con edad media de 47,3 a&#241;os. La mediana del% PLOV fue del 28,64% (rango intercuart&#237;lico [IQR], 6,33-47,22%). RA se present&#243; en 52 (38%) tasa de mortalidad global 21% (29 pacientes). Los pacientes con RA ten&#237;an niveles s&#233;ricos m&#225;s altos de biomarcadores inflamatorios con mediana de% PLOV del 52% frente al 12% de los pacientes sin RA. El an&#225;lisis multivariado mostr&#243; que el% PLOV es predictor independiente de RA con una raz&#243;n de probabilidades de 1.049 (intervalo de confianza [IC] del 95%, 1.014-1.085) (p &lt; 0.01). Adem&#225;s, un% PLOV del 64% demostr&#243; un riesgo 25,5 veces mayor de RA con una sensibilidad y especificidad superiores al 75% (p &lt; 0,01). Conclusi&#243;n: PLOV fue el predictor m&#225;s fuerte para el desarrollo de RA en pacientes hospitalizados. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Anales de Radiologia, Mexico is the property of Sociedad Mexicana de Radiologia e Imagen A.C. and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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