Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD
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 inc...
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Canadian Respiratory Journal |
| Online Access: | http://dx.doi.org/10.1155/2024/2639080 |
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| author | Nafeisa Dilixiati Mengyu Lian Ziliang Hou Jie Song Jingjing Yang Ruiyan Lin Jinxiang Wang |
| author_facet | Nafeisa Dilixiati Mengyu Lian Ziliang Hou Jie Song Jingjing Yang Ruiyan Lin Jinxiang Wang |
| author_sort | Nafeisa Dilixiati |
| collection | DOAJ |
| description | 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 × 109 cells/l), hypoalbuminemia, pulmonary encephalopathy, respiratory failure, diabetes, and respiratory intensive care unit (RICU) admissions were risk factors for predicting high hospitalization costs in pAECOPD patients. The AUC value was 0.756 (95% CI: 0.699–0.812) in the training set and 0.792 (95% CI: 0.718–0.867) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. Furthermore, decreased total protein, pulmonary encephalopathy, reflux esophagitis, and RICU admissions were risk factors for predicting prolonged stays in pAECOPD patients. The AUC value was 0.629 (95% CI: 0.575–0.682) in the training set and 0.620 (95% CI: 0.539–0.701) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. We developed and validated two nomograms for predicting high hospitalization costs and prolonged stay, respectively, among hospitalized patients with pAECOPD. This trial is registered with ChiCTR2000039959. |
| format | Article |
| id | doaj-art-cd22874c44df4d61a2f799e3abe6a0a6 |
| institution | Kabale University |
| issn | 1916-7245 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Canadian Respiratory Journal |
| spelling | doaj-art-cd22874c44df4d61a2f799e3abe6a0a62025-02-02T23:05:38ZengWileyCanadian Respiratory Journal1916-72452024-01-01202410.1155/2024/2639080Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPDNafeisa Dilixiati0Mengyu Lian1Ziliang Hou2Jie Song3Jingjing Yang4Ruiyan Lin5Jinxiang Wang6Department of Pulmonary and Critical Care MedicineDepartment of Pulmonary and Critical Care MedicineDepartment of Pulmonary and Critical Care MedicineDepartment of Pulmonary and Critical Care MedicineDepartment of Pulmonary and Critical Care MedicineDepartment of Pulmonary and Critical Care MedicineDepartment of Pulmonary and Critical Care MedicineThis 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 × 109 cells/l), hypoalbuminemia, pulmonary encephalopathy, respiratory failure, diabetes, and respiratory intensive care unit (RICU) admissions were risk factors for predicting high hospitalization costs in pAECOPD patients. The AUC value was 0.756 (95% CI: 0.699–0.812) in the training set and 0.792 (95% CI: 0.718–0.867) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. Furthermore, decreased total protein, pulmonary encephalopathy, reflux esophagitis, and RICU admissions were risk factors for predicting prolonged stays in pAECOPD patients. The AUC value was 0.629 (95% CI: 0.575–0.682) in the training set and 0.620 (95% CI: 0.539–0.701) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. We developed and validated two nomograms for predicting high hospitalization costs and prolonged stay, respectively, among hospitalized patients with pAECOPD. This trial is registered with ChiCTR2000039959.http://dx.doi.org/10.1155/2024/2639080 |
| spellingShingle | Nafeisa Dilixiati Mengyu Lian Ziliang Hou Jie Song Jingjing Yang Ruiyan Lin Jinxiang Wang Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD Canadian Respiratory Journal |
| title | Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD |
| title_full | Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD |
| title_fullStr | Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD |
| title_full_unstemmed | Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD |
| title_short | Nomograms for Predicting High Hospitalization Costs and Prolonged Stay among Hospitalized Patients with pAECOPD |
| title_sort | nomograms for predicting high hospitalization costs and prolonged stay among hospitalized patients with paecopd |
| url | http://dx.doi.org/10.1155/2024/2639080 |
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