Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit
Abstract Heart failure is a common complication in patients with sepsis, and individuals who experience both sepsis and heart failure are at a heightened risk for adverse outcomes. This study aims to develop an effective nomogram model to predict the 7-day, 15-day, and 30-day survival probabilities...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-85596-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841544796021194752 |
|---|---|
| author | Tong Tong Yikun Guo Qingqing Wang Xiaoning Sun Ziyi Sun Yuhan Yang Xiaoxiao Zhang Kuiwu Yao |
| author_facet | Tong Tong Yikun Guo Qingqing Wang Xiaoning Sun Ziyi Sun Yuhan Yang Xiaoxiao Zhang Kuiwu Yao |
| author_sort | Tong Tong |
| collection | DOAJ |
| description | Abstract Heart failure is a common complication in patients with sepsis, and individuals who experience both sepsis and heart failure are at a heightened risk for adverse outcomes. This study aims to develop an effective nomogram model to predict the 7-day, 15-day, and 30-day survival probabilities of septic patients with heart failure in the intensive care unit (ICU). This study extracted the pertinent clinical data of septic patients with heart failure from the Critical Medical Information Mart for Intensive Care (MIMIC-IV) database. Patients were then randomly allocated into a training set and a test set at a ratio of 7:3. Cox proportional hazards regression analysis was used to determine independent risk factors influencing patient prognosis and to develop a nomogram model. The model’s efficacy and clinical significance were assessed through metrics such as the concordance index (C-index), time-dependent receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA). A total of 5,490 septic patients with heart failure were included in the study. A nomogram model was developed to predict short-term survival probabilities, using 13 variables: age, pneumonia, endotracheal intubation, mechanical ventilation, potassium (K), anion gap (AG), lactate (Lac), activated partial thromboplastin time (APTT), white blood cell count (WBC), red cell distribution width (RDW), hemoglobin-to-red cell distribution width ratio (HRR), Sequential Organ Failure Assessment (SOFA) score, and Charlson Comorbidity Index (CCI). The C-index was 0.730 (95% CI 0.719–0.742) for the training set and 0.761 (95% CI 0.745–0.776) for the test set, indicating strong model accuracy, indicating good model accuracy. Evaluations via the ROC curve, calibration curve, and decision curve analyses further confirmed the model’s reliability and utility. This study effectively developed a straightforward and efficient nomogram model to predict the 7-day, 15-day, and 30-day survival probabilities of septic patients with heart failure in the ICU. The implementation of treatment strategies that address the risk factors identified in the model can enhance patient outcomes and increase survival rates. |
| format | Article |
| id | doaj-art-0e38573fd6ee42e28ffa00771351e1cb |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0e38573fd6ee42e28ffa00771351e1cb2025-01-12T12:15:59ZengNature PortfolioScientific Reports2045-23222025-01-0115111310.1038/s41598-025-85596-wDevelopment and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unitTong Tong0Yikun Guo1Qingqing Wang2Xiaoning Sun3Ziyi Sun4Yuhan Yang5Xiaoxiao Zhang6Kuiwu Yao7Guang’anmen Hospital, China Academy of Chinese Medical SciencesBeijing University of Chinese MedicineGuang’anmen Hospital, China Academy of Chinese Medical SciencesGuang’anmen Hospital, China Academy of Chinese Medical SciencesGuang’anmen Hospital, China Academy of Chinese Medical SciencesGuang’anmen Hospital, China Academy of Chinese Medical SciencesGuang’anmen Hospital, China Academy of Chinese Medical SciencesChina Academy of Chinese Medical SciencesAbstract Heart failure is a common complication in patients with sepsis, and individuals who experience both sepsis and heart failure are at a heightened risk for adverse outcomes. This study aims to develop an effective nomogram model to predict the 7-day, 15-day, and 30-day survival probabilities of septic patients with heart failure in the intensive care unit (ICU). This study extracted the pertinent clinical data of septic patients with heart failure from the Critical Medical Information Mart for Intensive Care (MIMIC-IV) database. Patients were then randomly allocated into a training set and a test set at a ratio of 7:3. Cox proportional hazards regression analysis was used to determine independent risk factors influencing patient prognosis and to develop a nomogram model. The model’s efficacy and clinical significance were assessed through metrics such as the concordance index (C-index), time-dependent receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA). A total of 5,490 septic patients with heart failure were included in the study. A nomogram model was developed to predict short-term survival probabilities, using 13 variables: age, pneumonia, endotracheal intubation, mechanical ventilation, potassium (K), anion gap (AG), lactate (Lac), activated partial thromboplastin time (APTT), white blood cell count (WBC), red cell distribution width (RDW), hemoglobin-to-red cell distribution width ratio (HRR), Sequential Organ Failure Assessment (SOFA) score, and Charlson Comorbidity Index (CCI). The C-index was 0.730 (95% CI 0.719–0.742) for the training set and 0.761 (95% CI 0.745–0.776) for the test set, indicating strong model accuracy, indicating good model accuracy. Evaluations via the ROC curve, calibration curve, and decision curve analyses further confirmed the model’s reliability and utility. This study effectively developed a straightforward and efficient nomogram model to predict the 7-day, 15-day, and 30-day survival probabilities of septic patients with heart failure in the ICU. The implementation of treatment strategies that address the risk factors identified in the model can enhance patient outcomes and increase survival rates.https://doi.org/10.1038/s41598-025-85596-wNomogram modelSepsisHeart failureRetrospective analysisMIMIC-IV database |
| spellingShingle | Tong Tong Yikun Guo Qingqing Wang Xiaoning Sun Ziyi Sun Yuhan Yang Xiaoxiao Zhang Kuiwu Yao Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit Scientific Reports Nomogram model Sepsis Heart failure Retrospective analysis MIMIC-IV database |
| title | Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit |
| title_full | Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit |
| title_fullStr | Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit |
| title_full_unstemmed | Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit |
| title_short | Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit |
| title_sort | development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit |
| topic | Nomogram model Sepsis Heart failure Retrospective analysis MIMIC-IV database |
| url | https://doi.org/10.1038/s41598-025-85596-w |
| work_keys_str_mv | AT tongtong developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT yikunguo developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT qingqingwang developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT xiaoningsun developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT ziyisun developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT yuhanyang developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT xiaoxiaozhang developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit AT kuiwuyao developmentandvalidationofanomogramtopredictsurvivalinsepticpatientswithheartfailureintheintensivecareunit |