Carmen Huertas Marín, Trinidad Dierssen-Soto, Yhivian Peñasco, Elena Cuenca-Fito, Reinhard Wallmann, Raquel Ferrero-Franco, Juan Carlos Rodríguez-Borregán, Alejandro González-Castro
{"title":"大流行期间ICU-COVID患者住院费用预测的Logistic回归模型：来自一家三级医院的结果","authors":"Carmen Huertas Marín, Trinidad Dierssen-Soto, Yhivian Peñasco, Elena Cuenca-Fito, Reinhard Wallmann, Raquel Ferrero-Franco, Juan Carlos Rodríguez-Borregán, Alejandro González-Castro","doi":"10.1016/j.medine.2025.502255","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To analyse which variables associated with ICU admission for COVID-19 were linked to higher hospital costs according to the APR-DRG classification.</p><p><strong>Design: </strong>Retrospective, observational, and analytical study.</p><p><strong>Setting: </strong>COVID-19 ICU in a tertiary hospital.</p><p><strong>Patients: </strong>Adults (>18 years) with a confirmed diagnosis of SARS-CoV-2 infection.</p><p><strong>Interventions: </strong>Predictive models using multiple logistic regression.</p><p><strong>Main variables of interest: </strong>Hospital cost, APR-DRG, mechanical ventilation.</p><p><strong>Results: </strong>A total of 799 patients were analyzed and categorized into tertiles based on hospital stay costs, resulting in three groups: 266 patients with lower costs (median €6160 [p25: 3962-p75: 6160]), 314 with intermediate costs (median €16,446 [p25: 10,653-p75: 18,274]), and 219 with higher costs (median €26,085 [p25: 26,085-p75: 51,523]). The best predictive model, with an AIC of 490.09 and an R<sup>2</sup> of 0.32, identified the following factors as significantly associated with higher hospital costs: ICU length of stay (OR: 1.05; 95% CI: 1.03-1.07; p < 0.01), development of VAT/VAP (OR: 4.72; 95% CI: 2.83-7.85; p < 0.01), OXA-48 infection (OR: 2.65; 95% CI: 1.25-5.61; p = 0.01), pulmonary embolism (OR: 6.42; 95% CI: 2.17-19.26; p < 0.01), smoking history (OR: 2.22; 95% CI: 1.49-3.74; p < 0.01), and vasopressor requirement (OR: 1.79; 95% CI: 1.22-2.86; p = 0.01). The area under the curve (AUC) was 0.866 (p < 0.01).</p><p><strong>Conclusions: </strong>Prolonged ICU stay, infectious and thromboembolic complications, smoking history, and vasopressor requirement were significantly associated with higher hospital costs.</p>","PeriodicalId":94139,"journal":{"name":"Medicina intensiva","volume":" ","pages":"502255"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Logistic regression model for predicting higher hospital costs in ICU-COVID patients during the pandemic: Results from a tertiary hospital.\",\"authors\":\"Carmen Huertas Marín, Trinidad Dierssen-Soto, Yhivian Peñasco, Elena Cuenca-Fito, Reinhard Wallmann, Raquel Ferrero-Franco, Juan Carlos Rodríguez-Borregán, Alejandro González-Castro\",\"doi\":\"10.1016/j.medine.2025.502255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To analyse which variables associated with ICU admission for COVID-19 were linked to higher hospital costs according to the APR-DRG classification.</p><p><strong>Design: </strong>Retrospective, observational, and analytical study.</p><p><strong>Setting: </strong>COVID-19 ICU in a tertiary hospital.</p><p><strong>Patients: </strong>Adults (>18 years) with a confirmed diagnosis of SARS-CoV-2 infection.</p><p><strong>Interventions: </strong>Predictive models using multiple logistic regression.</p><p><strong>Main variables of interest: </strong>Hospital cost, APR-DRG, mechanical ventilation.</p><p><strong>Results: </strong>A total of 799 patients were analyzed and categorized into tertiles based on hospital stay costs, resulting in three groups: 266 patients with lower costs (median €6160 [p25: 3962-p75: 6160]), 314 with intermediate costs (median €16,446 [p25: 10,653-p75: 18,274]), and 219 with higher costs (median €26,085 [p25: 26,085-p75: 51,523]). The best predictive model, with an AIC of 490.09 and an R<sup>2</sup> of 0.32, identified the following factors as significantly associated with higher hospital costs: ICU length of stay (OR: 1.05; 95% CI: 1.03-1.07; p < 0.01), development of VAT/VAP (OR: 4.72; 95% CI: 2.83-7.85; p < 0.01), OXA-48 infection (OR: 2.65; 95% CI: 1.25-5.61; p = 0.01), pulmonary embolism (OR: 6.42; 95% CI: 2.17-19.26; p < 0.01), smoking history (OR: 2.22; 95% CI: 1.49-3.74; p < 0.01), and vasopressor requirement (OR: 1.79; 95% CI: 1.22-2.86; p = 0.01). The area under the curve (AUC) was 0.866 (p < 0.01).</p><p><strong>Conclusions: </strong>Prolonged ICU stay, infectious and thromboembolic complications, smoking history, and vasopressor requirement were significantly associated with higher hospital costs.</p>\",\"PeriodicalId\":94139,\"journal\":{\"name\":\"Medicina intensiva\",\"volume\":\" \",\"pages\":\"502255\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medicina intensiva\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.medine.2025.502255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicina intensiva","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.medine.2025.502255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Logistic regression model for predicting higher hospital costs in ICU-COVID patients during the pandemic: Results from a tertiary hospital.
Objective: To analyse which variables associated with ICU admission for COVID-19 were linked to higher hospital costs according to the APR-DRG classification.
Design: Retrospective, observational, and analytical study.
Setting: COVID-19 ICU in a tertiary hospital.
Patients: Adults (>18 years) with a confirmed diagnosis of SARS-CoV-2 infection.
Interventions: Predictive models using multiple logistic regression.
Main variables of interest: Hospital cost, APR-DRG, mechanical ventilation.
Results: A total of 799 patients were analyzed and categorized into tertiles based on hospital stay costs, resulting in three groups: 266 patients with lower costs (median €6160 [p25: 3962-p75: 6160]), 314 with intermediate costs (median €16,446 [p25: 10,653-p75: 18,274]), and 219 with higher costs (median €26,085 [p25: 26,085-p75: 51,523]). The best predictive model, with an AIC of 490.09 and an R2 of 0.32, identified the following factors as significantly associated with higher hospital costs: ICU length of stay (OR: 1.05; 95% CI: 1.03-1.07; p < 0.01), development of VAT/VAP (OR: 4.72; 95% CI: 2.83-7.85; p < 0.01), OXA-48 infection (OR: 2.65; 95% CI: 1.25-5.61; p = 0.01), pulmonary embolism (OR: 6.42; 95% CI: 2.17-19.26; p < 0.01), smoking history (OR: 2.22; 95% CI: 1.49-3.74; p < 0.01), and vasopressor requirement (OR: 1.79; 95% CI: 1.22-2.86; p = 0.01). The area under the curve (AUC) was 0.866 (p < 0.01).
Conclusions: Prolonged ICU stay, infectious and thromboembolic complications, smoking history, and vasopressor requirement were significantly associated with higher hospital costs.
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