Development and validation of a modified SOFA score for mortality prediction in candidemia patients
Abstract Candidemia is a life-threatening bloodstream infection associated with high mortality rates, particularly in critically ill patients. Accurate risk stratification is crucial for timely intervention and could improve patient outcomes. This study aimed to enhance the predictive performance of...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-04786-8 |
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| author | Xiaofei Liu Ranran Ding Guangming Yang Yuling Qiao Zhen Ma Yaping Feng Feng Qu Qiang Meng |
| author_facet | Xiaofei Liu Ranran Ding Guangming Yang Yuling Qiao Zhen Ma Yaping Feng Feng Qu Qiang Meng |
| author_sort | Xiaofei Liu |
| collection | DOAJ |
| description | Abstract Candidemia is a life-threatening bloodstream infection associated with high mortality rates, particularly in critically ill patients. Accurate risk stratification is crucial for timely intervention and could improve patient outcomes. This study aimed to enhance the predictive performance of the sequential organ failure assessment (SOFA) score by developing a modified SOFA (mSOFA) score, which is specifically designed for candidemia patients. Using data from MIMIC-III, MIMIC-IV, and ICU-JN databases, we identified key prognostic variables through LASSO regression and integrated into the mSOFA_3 model. The model incorporated respiratory_SOFA, coagulation_SOFA, and circulatory_SOFA along with clinical biomarkers, including lactate, albumin, and blood urea nitrogen. The mSOFA_3 model demonstrated superior predictive performance across multiple machine learning algorithms, with the logistic regression-based model achieving the highest AUC of 0.826 in the internal validation cohort and 0.813 in the test cohort. Kaplan-Meier survival analysis further validated the model’s utility in stratifying patients into high-risk and low-risk groups with distinct survival outcomes. These findings highlight the mSOFA_3 as a robust and clinically relevant tool for early risk stratification, offering potential for improved decision-making and therapeutic management in critically ill patients with candidemia. |
| format | Article |
| id | doaj-art-98bcd4acb17f4eeb87ef3d686bbb8588 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-98bcd4acb17f4eeb87ef3d686bbb85882025-08-20T03:03:32ZengNature PortfolioScientific Reports2045-23222025-07-0115111110.1038/s41598-025-04786-8Development and validation of a modified SOFA score for mortality prediction in candidemia patientsXiaofei Liu0Ranran Ding1Guangming Yang2Yuling Qiao3Zhen Ma4Yaping Feng5Feng Qu6Qiang Meng7Department of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalDepartment of Intensive Care Unit, Jining NO. 1 People’s HospitalAbstract Candidemia is a life-threatening bloodstream infection associated with high mortality rates, particularly in critically ill patients. Accurate risk stratification is crucial for timely intervention and could improve patient outcomes. This study aimed to enhance the predictive performance of the sequential organ failure assessment (SOFA) score by developing a modified SOFA (mSOFA) score, which is specifically designed for candidemia patients. Using data from MIMIC-III, MIMIC-IV, and ICU-JN databases, we identified key prognostic variables through LASSO regression and integrated into the mSOFA_3 model. The model incorporated respiratory_SOFA, coagulation_SOFA, and circulatory_SOFA along with clinical biomarkers, including lactate, albumin, and blood urea nitrogen. The mSOFA_3 model demonstrated superior predictive performance across multiple machine learning algorithms, with the logistic regression-based model achieving the highest AUC of 0.826 in the internal validation cohort and 0.813 in the test cohort. Kaplan-Meier survival analysis further validated the model’s utility in stratifying patients into high-risk and low-risk groups with distinct survival outcomes. These findings highlight the mSOFA_3 as a robust and clinically relevant tool for early risk stratification, offering potential for improved decision-making and therapeutic management in critically ill patients with candidemia.https://doi.org/10.1038/s41598-025-04786-8CandidemiaSequential organ failure assessmentLactateBUNAlbumin |
| spellingShingle | Xiaofei Liu Ranran Ding Guangming Yang Yuling Qiao Zhen Ma Yaping Feng Feng Qu Qiang Meng Development and validation of a modified SOFA score for mortality prediction in candidemia patients Scientific Reports Candidemia Sequential organ failure assessment Lactate BUN Albumin |
| title | Development and validation of a modified SOFA score for mortality prediction in candidemia patients |
| title_full | Development and validation of a modified SOFA score for mortality prediction in candidemia patients |
| title_fullStr | Development and validation of a modified SOFA score for mortality prediction in candidemia patients |
| title_full_unstemmed | Development and validation of a modified SOFA score for mortality prediction in candidemia patients |
| title_short | Development and validation of a modified SOFA score for mortality prediction in candidemia patients |
| title_sort | development and validation of a modified sofa score for mortality prediction in candidemia patients |
| topic | Candidemia Sequential organ failure assessment Lactate BUN Albumin |
| url | https://doi.org/10.1038/s41598-025-04786-8 |
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