Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy
ObjectiveThe aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population.MethodsA population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged...
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| Format: | Article |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1173957/full |
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| author | Giovanni Corrao Giovanni Corrao Giovanni Corrao Andrea Stella Bonaugurio Andrea Stella Bonaugurio Yu Xi Chen Yu Xi Chen Matteo Franchi Matteo Franchi Antonio Lora Antonio Lora Olivia Leoni Giovanni Pavesi Guido Bertolaso |
| author_facet | Giovanni Corrao Giovanni Corrao Giovanni Corrao Andrea Stella Bonaugurio Andrea Stella Bonaugurio Yu Xi Chen Yu Xi Chen Matteo Franchi Matteo Franchi Antonio Lora Antonio Lora Olivia Leoni Giovanni Pavesi Guido Bertolaso |
| author_sort | Giovanni Corrao |
| collection | DOAJ |
| description | ObjectiveThe aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population.MethodsA population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged 18 years or older in January 2015. Each individual was classified as exposed or unexposed to 69 candidate predictors measured before baseline, updated to include four mental health disorders. Conditions independently associated with 5-year mortality were selected using the Cox regression model on a random sample including 5.4 million citizens. The predictive performance of the obtained CReSc-2.0 was assessed on the remaining 2.7 million citizens through discrimination and calibration.ResultsA total of 35 conditions significantly contributed to the CReSc-2.0, among which Alzheimer's and Parkinson's diseases, dementia, heart failure, active neoplasm, and kidney dialysis contributed the most to the score. Approximately 36% of citizens suffered from at least one condition. CReSc-2.0 discrimination performance was remarkable, with an area under the receiver operating characteristic curve of 0.83. Trends toward increasing short-term (1-year) and long-term (5-year) rates of mortality, hospital admission, hospital stay, and healthcare costs were observed as CReSc-2.0 increased.ConclusionCReSC-2.0 represents an improved tool for stratifying populations according to healthcare needs. |
| first_indexed | 2024-03-12T11:52:19Z |
| format | Article |
| id | doaj.art-44b9f605f2394e34ab770c90a1bc124c |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-03-12T11:52:19Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-44b9f605f2394e34ab770c90a1bc124c2023-08-31T05:51:54ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-08-011110.3389/fpubh.2023.11739571173957Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of LombardyGiovanni Corrao0Giovanni Corrao1Giovanni Corrao2Andrea Stella Bonaugurio3Andrea Stella Bonaugurio4Yu Xi Chen5Yu Xi Chen6Matteo Franchi7Matteo Franchi8Antonio Lora9Antonio Lora10Olivia Leoni11Giovanni Pavesi12Guido Bertolaso13National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyUnit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyNational Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyNational Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyNational Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyUnit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, ItalyNational Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyLombardy Region DG Welfare, Milan, ItalyObjectiveThe aim of this study was to improve the performance of the Chronic Related Score (CReSc) in predicting mortality and healthcare needs in the general population.MethodsA population-based study was conducted, including all beneficiaries of the Regional Health Service of Lombardy, Italy, aged 18 years or older in January 2015. Each individual was classified as exposed or unexposed to 69 candidate predictors measured before baseline, updated to include four mental health disorders. Conditions independently associated with 5-year mortality were selected using the Cox regression model on a random sample including 5.4 million citizens. The predictive performance of the obtained CReSc-2.0 was assessed on the remaining 2.7 million citizens through discrimination and calibration.ResultsA total of 35 conditions significantly contributed to the CReSc-2.0, among which Alzheimer's and Parkinson's diseases, dementia, heart failure, active neoplasm, and kidney dialysis contributed the most to the score. Approximately 36% of citizens suffered from at least one condition. CReSc-2.0 discrimination performance was remarkable, with an area under the receiver operating characteristic curve of 0.83. Trends toward increasing short-term (1-year) and long-term (5-year) rates of mortality, hospital admission, hospital stay, and healthcare costs were observed as CReSc-2.0 increased.ConclusionCReSC-2.0 represents an improved tool for stratifying populations according to healthcare needs.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1173957/fullscorestratificationcomorbiditieshealthcarerisk profiling |
| spellingShingle | Giovanni Corrao Giovanni Corrao Giovanni Corrao Andrea Stella Bonaugurio Andrea Stella Bonaugurio Yu Xi Chen Yu Xi Chen Matteo Franchi Matteo Franchi Antonio Lora Antonio Lora Olivia Leoni Giovanni Pavesi Guido Bertolaso Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy Frontiers in Public Health score stratification comorbidities healthcare risk profiling |
| title | Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy |
| title_full | Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy |
| title_fullStr | Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy |
| title_full_unstemmed | Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy |
| title_short | Improved prediction of 5-year mortality by updating the chronic related score for risk profiling in the general population: lessons from the italian region of Lombardy |
| title_sort | improved prediction of 5 year mortality by updating the chronic related score for risk profiling in the general population lessons from the italian region of lombardy |
| topic | score stratification comorbidities healthcare risk profiling |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1173957/full |
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