Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD.
Humans
Nomograms
Male
Female
Aged
Length of Stay
/ statistics & numerical data
Pulmonary Disease, Chronic Obstructive
/ economics
Community-Acquired Infections
/ economics
Hospitalization
/ economics
Middle Aged
Pneumonia
/ economics
Hospital Costs
/ statistics & numerical data
ROC Curve
Risk Factors
Aged, 80 and over
Logistic Models
Leukocyte Count
Journal
Canadian respiratory journal
ISSN: 1916-7245
Titre abrégé: Can Respir J
Pays: Egypt
ID NLM: 9433332
Informations de publication
Date de publication:
2024
2024
Historique:
received:
30
03
2024
revised:
24
06
2024
accepted:
17
08
2024
medline:
17
9
2024
pubmed:
17
9
2024
entrez:
16
9
2024
Statut:
epublish
Résumé
This study aimed to develop nomograms to predict high hospitalization costs and prolonged stays in hospitalized acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients with community-acquired pneumonia (CAP), also known as pAECOPD. A total of 635 patients with pAECOPD were included in this observational study and divided into training and testing sets. Variables were initially screened using univariate analysis, and then further selected using a backward stepwise regression. Multivariable logistic regression was performed to establish nomograms. The predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve, and decision curve analysis (DCA) in both the training and testing sets. Finally, the logistic regression analysis showed that elevated white blood cell count (WBC>10 × 10
Identifiants
pubmed: 39280690
doi: 10.1155/2024/2639080
pmc: PMC11398965
doi:
Types de publication
Journal Article
Observational Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
2639080Informations de copyright
Copyright © 2024 Nafeisa Dilixiati et al.
Déclaration de conflit d'intérêts
The authors declare that they have no conflicts of interest.