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Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia

(1) Background: Biomarker and model development can help physicians adjust the management of patients with community-acquired pneumonia (CAP) by screening for inpatients with a low probability of cure early in their admission; (2) Methods: We conducted a 30-day cohort study of newly admitted adult C...

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Autores principales: Zhang, Teng, Zeng, Yifeng, Lin, Runpei, Xue, Mingshan, Liu, Mingtao, Li, Yusi, Zhen, Yingjie, Li, Ning, Cao, Wenhan, Wu, Sixiao, Zhu, Huiqing, Zhao, Qi, Sun, Baoqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605170/
https://www.ncbi.nlm.nih.gov/pubmed/36294336
http://dx.doi.org/10.3390/jcm11206015
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author Zhang, Teng
Zeng, Yifeng
Lin, Runpei
Xue, Mingshan
Liu, Mingtao
Li, Yusi
Zhen, Yingjie
Li, Ning
Cao, Wenhan
Wu, Sixiao
Zhu, Huiqing
Zhao, Qi
Sun, Baoqing
author_facet Zhang, Teng
Zeng, Yifeng
Lin, Runpei
Xue, Mingshan
Liu, Mingtao
Li, Yusi
Zhen, Yingjie
Li, Ning
Cao, Wenhan
Wu, Sixiao
Zhu, Huiqing
Zhao, Qi
Sun, Baoqing
author_sort Zhang, Teng
collection PubMed
description (1) Background: Biomarker and model development can help physicians adjust the management of patients with community-acquired pneumonia (CAP) by screening for inpatients with a low probability of cure early in their admission; (2) Methods: We conducted a 30-day cohort study of newly admitted adult CAP patients over 20 years of age. Prognosis models to predict the short-term prognosis were developed using random survival forest (RSF) method; (3) Results: A total of 247 adult CAP patients were studied and 208 (84.21%) of them reached clinical stability within 30 days. The soluble form of suppression of tumorigenicity-2 (sST2) was an independent predictor of clinical stability and the addition of sST2 to the prognosis model could improve the performance of the prognosis model. The C-index of the RSF model for predicting clinical stability was 0.8342 (95% CI, 0.8086–0.8598), which is higher than 0.7181 (95% CI, 0.6933–0.7429) of CURB 65 score, 0.8025 (95% CI, 0.7776–8274) of PSI score, and 0.8214 (95% CI, 0.8080–0.8348) of cox regression. In addition, the RSF model was associated with adverse clinical events during hospitalization, ICU admissions, and short-term mortality; (4) Conclusions: The RSF model by incorporating sST2 was more accurate than traditional methods in assessing the short-term prognosis of CAP patients.
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spelling pubmed-96051702022-10-27 Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia Zhang, Teng Zeng, Yifeng Lin, Runpei Xue, Mingshan Liu, Mingtao Li, Yusi Zhen, Yingjie Li, Ning Cao, Wenhan Wu, Sixiao Zhu, Huiqing Zhao, Qi Sun, Baoqing J Clin Med Article (1) Background: Biomarker and model development can help physicians adjust the management of patients with community-acquired pneumonia (CAP) by screening for inpatients with a low probability of cure early in their admission; (2) Methods: We conducted a 30-day cohort study of newly admitted adult CAP patients over 20 years of age. Prognosis models to predict the short-term prognosis were developed using random survival forest (RSF) method; (3) Results: A total of 247 adult CAP patients were studied and 208 (84.21%) of them reached clinical stability within 30 days. The soluble form of suppression of tumorigenicity-2 (sST2) was an independent predictor of clinical stability and the addition of sST2 to the prognosis model could improve the performance of the prognosis model. The C-index of the RSF model for predicting clinical stability was 0.8342 (95% CI, 0.8086–0.8598), which is higher than 0.7181 (95% CI, 0.6933–0.7429) of CURB 65 score, 0.8025 (95% CI, 0.7776–8274) of PSI score, and 0.8214 (95% CI, 0.8080–0.8348) of cox regression. In addition, the RSF model was associated with adverse clinical events during hospitalization, ICU admissions, and short-term mortality; (4) Conclusions: The RSF model by incorporating sST2 was more accurate than traditional methods in assessing the short-term prognosis of CAP patients. MDPI 2022-10-12 /pmc/articles/PMC9605170/ /pubmed/36294336 http://dx.doi.org/10.3390/jcm11206015 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Teng
Zeng, Yifeng
Lin, Runpei
Xue, Mingshan
Liu, Mingtao
Li, Yusi
Zhen, Yingjie
Li, Ning
Cao, Wenhan
Wu, Sixiao
Zhu, Huiqing
Zhao, Qi
Sun, Baoqing
Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
title Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
title_full Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
title_fullStr Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
title_full_unstemmed Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
title_short Incorporation of Suppression of Tumorigenicity 2 into Random Survival Forests for Enhancing Prediction of Short-Term Prognosis in Community-ACQUIRED Pneumonia
title_sort incorporation of suppression of tumorigenicity 2 into random survival forests for enhancing prediction of short-term prognosis in community-acquired pneumonia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9605170/
https://www.ncbi.nlm.nih.gov/pubmed/36294336
http://dx.doi.org/10.3390/jcm11206015
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