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Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation

BACKGROUND: Patients with acute respiratory failure secondary to tuberculous destroyed lung (TDL) have a poor prognosis. The aim of the present retrospective study was to develop a mortality prediction model for TDL patients who require mechanical ventilation. METHODS: Data from consecutive TDL pati...

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Autores principales: Kim, Won-Young, Kim, Mi-Hyun, Jo, Eun-Jung, Eom, Jung Seop, Mok, Jeongha, Kim, Ki Uk, Park, Hye-Kyung, Lee, Min Ki, Lee, Kwangha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Tuberculosis and Respiratory Diseases 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030661/
https://www.ncbi.nlm.nih.gov/pubmed/29926549
http://dx.doi.org/10.4046/trd.2017.0126
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author Kim, Won-Young
Kim, Mi-Hyun
Jo, Eun-Jung
Eom, Jung Seop
Mok, Jeongha
Kim, Ki Uk
Park, Hye-Kyung
Lee, Min Ki
Lee, Kwangha
author_facet Kim, Won-Young
Kim, Mi-Hyun
Jo, Eun-Jung
Eom, Jung Seop
Mok, Jeongha
Kim, Ki Uk
Park, Hye-Kyung
Lee, Min Ki
Lee, Kwangha
author_sort Kim, Won-Young
collection PubMed
description BACKGROUND: Patients with acute respiratory failure secondary to tuberculous destroyed lung (TDL) have a poor prognosis. The aim of the present retrospective study was to develop a mortality prediction model for TDL patients who require mechanical ventilation. METHODS: Data from consecutive TDL patients who had received mechanical ventilation at a single university-affiliated tertiary care hospital in Korea were reviewed. Binary logistic regression was used to identify factors predicting intensive care unit (ICU) mortality. A TDL on mechanical Ventilation (TDL-Vent) score was calculated by assigning points to variables according to β coefficient values. RESULTS: Data from 125 patients were reviewed. A total of 36 patients (29%) died during ICU admission. On the basis of multivariate analysis, the following factors were included in the TDL-Vent score: age ≥65 years, vasopressor use, and arterial partial pressure of oxygen/fraction of inspired oxygen ratio <180. In a second regression model, a modified score was then calculated by adding brain natriuretic peptide. For TDL-Vent scores 0 to 3, the 60-day mortality rates were 11%, 27%, 30%, and 77%, respectively (p<0.001). For modified TDL-Vent scores 0 to ≥3, the 60-day mortality rates were 0%, 21%, 33%, and 57%, respectively (p=0.001). For both the TDL-Vent score and the modified TDL-Vent score, the areas under the receiver operating characteristic curve were larger than that of other illness severity scores. CONCLUSION: The TDL-Vent model identifies TDL patients on mechanical ventilation with a high risk of mortality. Prospective validation studies in larger cohorts are now warranted.
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spelling pubmed-60306612018-07-06 Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation Kim, Won-Young Kim, Mi-Hyun Jo, Eun-Jung Eom, Jung Seop Mok, Jeongha Kim, Ki Uk Park, Hye-Kyung Lee, Min Ki Lee, Kwangha Tuberc Respir Dis (Seoul) Original Article BACKGROUND: Patients with acute respiratory failure secondary to tuberculous destroyed lung (TDL) have a poor prognosis. The aim of the present retrospective study was to develop a mortality prediction model for TDL patients who require mechanical ventilation. METHODS: Data from consecutive TDL patients who had received mechanical ventilation at a single university-affiliated tertiary care hospital in Korea were reviewed. Binary logistic regression was used to identify factors predicting intensive care unit (ICU) mortality. A TDL on mechanical Ventilation (TDL-Vent) score was calculated by assigning points to variables according to β coefficient values. RESULTS: Data from 125 patients were reviewed. A total of 36 patients (29%) died during ICU admission. On the basis of multivariate analysis, the following factors were included in the TDL-Vent score: age ≥65 years, vasopressor use, and arterial partial pressure of oxygen/fraction of inspired oxygen ratio <180. In a second regression model, a modified score was then calculated by adding brain natriuretic peptide. For TDL-Vent scores 0 to 3, the 60-day mortality rates were 11%, 27%, 30%, and 77%, respectively (p<0.001). For modified TDL-Vent scores 0 to ≥3, the 60-day mortality rates were 0%, 21%, 33%, and 57%, respectively (p=0.001). For both the TDL-Vent score and the modified TDL-Vent score, the areas under the receiver operating characteristic curve were larger than that of other illness severity scores. CONCLUSION: The TDL-Vent model identifies TDL patients on mechanical ventilation with a high risk of mortality. Prospective validation studies in larger cohorts are now warranted. The Korean Academy of Tuberculosis and Respiratory Diseases 2018-07 2018-06-19 /pmc/articles/PMC6030661/ /pubmed/29926549 http://dx.doi.org/10.4046/trd.2017.0126 Text en Copyright©2018. The Korean Academy of Tuberculosis and Respiratory Diseases http://creativecommons.org/licenses/by-nc/4.0/ It is identical to the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle Original Article
Kim, Won-Young
Kim, Mi-Hyun
Jo, Eun-Jung
Eom, Jung Seop
Mok, Jeongha
Kim, Ki Uk
Park, Hye-Kyung
Lee, Min Ki
Lee, Kwangha
Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation
title Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation
title_full Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation
title_fullStr Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation
title_full_unstemmed Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation
title_short Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation
title_sort predicting mortality in patients with tuberculous destroyed lung receiving mechanical ventilation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030661/
https://www.ncbi.nlm.nih.gov/pubmed/29926549
http://dx.doi.org/10.4046/trd.2017.0126
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