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Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia

BACKGROUND: No multivariable model incorporating erector spinae muscle (ESM) has been developed to predict clinical outcomes in older patients with severe community-acquired pneumonia (SCAP). This study aimed to construct a nomogram based on ESM to predict in-hospital mortality in patients with SCAP...

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Autores principales: Shang, Na, Li, Qiujing, Liu, Huizhen, Li, Junyu, Guo, Shubin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500910/
https://www.ncbi.nlm.nih.gov/pubmed/37710218
http://dx.doi.org/10.1186/s12890-023-02640-z
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author Shang, Na
Li, Qiujing
Liu, Huizhen
Li, Junyu
Guo, Shubin
author_facet Shang, Na
Li, Qiujing
Liu, Huizhen
Li, Junyu
Guo, Shubin
author_sort Shang, Na
collection PubMed
description BACKGROUND: No multivariable model incorporating erector spinae muscle (ESM) has been developed to predict clinical outcomes in older patients with severe community-acquired pneumonia (SCAP). This study aimed to construct a nomogram based on ESM to predict in-hospital mortality in patients with SCAP. METHODS: Patients aged ≥ 65 years with SCAP were enrolled in this prospective observational study. Least absolute selection and shrinkage operator and multivariable logistic regression analyses were used to identify risk factors for in-hospital mortality. A nomogram prediction model was constructed. The predictive performance was evaluated using the concordance index (C-index), calibration curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis. RESULTS: A total of 490 patients were included, and the in-hospital mortality rate was 36.1%. The nomogram included the following independent risk factors: mean arterial pressure, peripheral capillary oxygen saturation, Glasgow Coma Scale score (GCS), lactate, lactate dehydrogenase, blood urea nitrogen levels, and ESM cross-sectional area. Incorporating ESM into the base model with other risk factors significantly improved the C-index from 0.803 (95% confidence interval [CI], 0.761–0.845) to 0.836 (95% CI, 0.798–0.873), and these improvements were confirmed by category-free NRI and IDI. The ESM-based nomogram demonstrated a high level of discrimination, good calibration, and overall net benefits for predicting in-hospital mortality compared with the combination of confusion, urea, respiratory rate, blood pressure, and age ≥ 65 years (CURB-65), Pneumonia Severity Index (PSI), Acute Physiology and Chronic Health Evaluation II (APACHEII), and Sequential Organ Failure Assessment (SOFA). CONCLUSIONS: The proposed ESM-based nomogram for predicting in-hospital mortality among older patients with SCAP may help physicians to promptly identify patients prone to adverse outcomes. TRIAL REGISTRATION: This study was registered at www.chictr.org.cn (registration number Chi CTR-2300070377). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02640-z.
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spelling pubmed-105009102023-09-15 Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia Shang, Na Li, Qiujing Liu, Huizhen Li, Junyu Guo, Shubin BMC Pulm Med Research BACKGROUND: No multivariable model incorporating erector spinae muscle (ESM) has been developed to predict clinical outcomes in older patients with severe community-acquired pneumonia (SCAP). This study aimed to construct a nomogram based on ESM to predict in-hospital mortality in patients with SCAP. METHODS: Patients aged ≥ 65 years with SCAP were enrolled in this prospective observational study. Least absolute selection and shrinkage operator and multivariable logistic regression analyses were used to identify risk factors for in-hospital mortality. A nomogram prediction model was constructed. The predictive performance was evaluated using the concordance index (C-index), calibration curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis. RESULTS: A total of 490 patients were included, and the in-hospital mortality rate was 36.1%. The nomogram included the following independent risk factors: mean arterial pressure, peripheral capillary oxygen saturation, Glasgow Coma Scale score (GCS), lactate, lactate dehydrogenase, blood urea nitrogen levels, and ESM cross-sectional area. Incorporating ESM into the base model with other risk factors significantly improved the C-index from 0.803 (95% confidence interval [CI], 0.761–0.845) to 0.836 (95% CI, 0.798–0.873), and these improvements were confirmed by category-free NRI and IDI. The ESM-based nomogram demonstrated a high level of discrimination, good calibration, and overall net benefits for predicting in-hospital mortality compared with the combination of confusion, urea, respiratory rate, blood pressure, and age ≥ 65 years (CURB-65), Pneumonia Severity Index (PSI), Acute Physiology and Chronic Health Evaluation II (APACHEII), and Sequential Organ Failure Assessment (SOFA). CONCLUSIONS: The proposed ESM-based nomogram for predicting in-hospital mortality among older patients with SCAP may help physicians to promptly identify patients prone to adverse outcomes. TRIAL REGISTRATION: This study was registered at www.chictr.org.cn (registration number Chi CTR-2300070377). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02640-z. BioMed Central 2023-09-14 /pmc/articles/PMC10500910/ /pubmed/37710218 http://dx.doi.org/10.1186/s12890-023-02640-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Shang, Na
Li, Qiujing
Liu, Huizhen
Li, Junyu
Guo, Shubin
Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
title Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
title_full Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
title_fullStr Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
title_full_unstemmed Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
title_short Erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
title_sort erector spinae muscle-based nomogram for predicting in-hospital mortality among older patients with severe community-acquired pneumonia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500910/
https://www.ncbi.nlm.nih.gov/pubmed/37710218
http://dx.doi.org/10.1186/s12890-023-02640-z
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