Cargando…
FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients
BACKGROUND: The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. METH...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206684/ https://www.ncbi.nlm.nih.gov/pubmed/32384935 http://dx.doi.org/10.1186/s12931-020-01379-z |
_version_ | 1783530459130494976 |
---|---|
author | Chen, Liang Han, Xiudi Li, Yan Li Zhang, Chunxiao Xing, Xiqian |
author_facet | Chen, Liang Han, Xiudi Li, Yan Li Zhang, Chunxiao Xing, Xiqian |
author_sort | Chen, Liang |
collection | PubMed |
description | BACKGROUND: The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. METHODS: A total of 693 laboratory-confirmed FluA-p patients diagnosed between Jan 2013 and Dec 2018 and recruited from five teaching hospitals in China were included in the study. The sample included 494 patients in the derivation cohort and 199 patients in the validation cohort. The prediction rule was established based on independent risk factors for 30-day mortality in FluA-p patients from the derivation cohort. RESULTS: The 30-day mortality of FluA-p patients was 19.6% (136/693). The FluA-p score was based on a multivariate logistic regression model designed to predict mortality. Results indicated the following significant predictors (regression statistics and point contributions toward total score in parentheses): blood urea nitrogen > 7 mmol/L (OR 1.604, 95% CI 1.150–4.492, p = 0.040; 1 points), pO(2)/F(i)O(2) ≤ 250 mmHg (OR 2.649, 95% CI 1.103–5.142, p = 0.022; 2 points), cardiovascular disease (OR 3.967, 95% CI 1.269–7.322, p < 0.001; 3 points), arterial PH < 7.35 (OR 3.959, 95% CI 1.393–7.332, p < 0.001; 3 points), smoking history (OR 5.176, 95% CI 2.604–11.838, p = 0.001; 4 points), lymphocytes < 0.8 × 10(9)/L (OR 8.391, 95% CI 3.271–16.212, p < 0.001; 5 points), and early neurominidase inhibitor therapy (OR 0.567, 95% CI 0.202–0.833, p = 0.005; − 2 points). Seven points was used as the cut-off value for mortality risk stratification. The model showed a sensitivity of 0.941, a specificity of 0.762, and overall better predictive performance than the PSI risk class (AUROC = 0.908 vs 0.560, p < 0.001) and the CURB-65 score (AUROC = 0.908 vs 0.777, p < 0.001). CONCLUSIONS: Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions. |
format | Online Article Text |
id | pubmed-7206684 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72066842020-05-14 FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients Chen, Liang Han, Xiudi Li, Yan Li Zhang, Chunxiao Xing, Xiqian Respir Res Research BACKGROUND: The pneumonia severity index (PSI) and the CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) score have been shown to predict mortality in community-acquired pneumonia. Their ability to predict influenza-related pneumonia, however, is less well-established. METHODS: A total of 693 laboratory-confirmed FluA-p patients diagnosed between Jan 2013 and Dec 2018 and recruited from five teaching hospitals in China were included in the study. The sample included 494 patients in the derivation cohort and 199 patients in the validation cohort. The prediction rule was established based on independent risk factors for 30-day mortality in FluA-p patients from the derivation cohort. RESULTS: The 30-day mortality of FluA-p patients was 19.6% (136/693). The FluA-p score was based on a multivariate logistic regression model designed to predict mortality. Results indicated the following significant predictors (regression statistics and point contributions toward total score in parentheses): blood urea nitrogen > 7 mmol/L (OR 1.604, 95% CI 1.150–4.492, p = 0.040; 1 points), pO(2)/F(i)O(2) ≤ 250 mmHg (OR 2.649, 95% CI 1.103–5.142, p = 0.022; 2 points), cardiovascular disease (OR 3.967, 95% CI 1.269–7.322, p < 0.001; 3 points), arterial PH < 7.35 (OR 3.959, 95% CI 1.393–7.332, p < 0.001; 3 points), smoking history (OR 5.176, 95% CI 2.604–11.838, p = 0.001; 4 points), lymphocytes < 0.8 × 10(9)/L (OR 8.391, 95% CI 3.271–16.212, p < 0.001; 5 points), and early neurominidase inhibitor therapy (OR 0.567, 95% CI 0.202–0.833, p = 0.005; − 2 points). Seven points was used as the cut-off value for mortality risk stratification. The model showed a sensitivity of 0.941, a specificity of 0.762, and overall better predictive performance than the PSI risk class (AUROC = 0.908 vs 0.560, p < 0.001) and the CURB-65 score (AUROC = 0.908 vs 0.777, p < 0.001). CONCLUSIONS: Our results showed that a FluA-p score was easy to derive and that it served as a reliable prediction rule for 30-day mortality in FluA-p patients. The score could also effectively stratify FluA-p patients into relevant risk categories and thereby help treatment providers to make more rational clinical decisions. BioMed Central 2020-05-08 2020 /pmc/articles/PMC7206684/ /pubmed/32384935 http://dx.doi.org/10.1186/s12931-020-01379-z Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://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 Chen, Liang Han, Xiudi Li, Yan Li Zhang, Chunxiao Xing, Xiqian FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients |
title | FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients |
title_full | FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients |
title_fullStr | FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients |
title_full_unstemmed | FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients |
title_short | FluA-p score: a novel prediction rule for mortality in influenza A-related pneumonia patients |
title_sort | flua-p score: a novel prediction rule for mortality in influenza a-related pneumonia patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206684/ https://www.ncbi.nlm.nih.gov/pubmed/32384935 http://dx.doi.org/10.1186/s12931-020-01379-z |
work_keys_str_mv | AT chenliang fluapscoreanovelpredictionruleformortalityininfluenzaarelatedpneumoniapatients AT hanxiudi fluapscoreanovelpredictionruleformortalityininfluenzaarelatedpneumoniapatients AT liyanli fluapscoreanovelpredictionruleformortalityininfluenzaarelatedpneumoniapatients AT zhangchunxiao fluapscoreanovelpredictionruleformortalityininfluenzaarelatedpneumoniapatients AT xingxiqian fluapscoreanovelpredictionruleformortalityininfluenzaarelatedpneumoniapatients |