Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors
ObjectiveNew-onset atrial fibrillation (NOAF) is a common complication and one of the primary causes of increased mortality in critically ill adults. Since early assessment of the risk of developing NOAF is difficult, it is critical to establish predictive tools to identify the risk of NOAF.MethodsW...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2022.968615/full |
| _version_ | 1811283537719984128 |
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| author | Zhuanyun Li Ming Pang Yongkai Li Yaling Yu Tianfeng Peng Zhenghao Hu Ruijie Niu Jiming Li Xiaorong Wang |
| author_facet | Zhuanyun Li Ming Pang Yongkai Li Yaling Yu Tianfeng Peng Zhenghao Hu Ruijie Niu Jiming Li Xiaorong Wang |
| author_sort | Zhuanyun Li |
| collection | DOAJ |
| description | ObjectiveNew-onset atrial fibrillation (NOAF) is a common complication and one of the primary causes of increased mortality in critically ill adults. Since early assessment of the risk of developing NOAF is difficult, it is critical to establish predictive tools to identify the risk of NOAF.MethodsWe retrospectively enrolled 1,568 septic patients treated at Wuhan Union Hospital (Wuhan, China) as a training cohort. For external validation of the model, 924 patients with sepsis were recruited as a validation cohort at the First Affiliated Hospital of Xinjiang Medical University (Urumqi, China). Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analyses were used to screen predictors. The area under the ROC curve (AUC), calibration curve, and decision curve were used to assess the value of the predictive model in NOAF.ResultsA total of 2,492 patients with sepsis (1,592 (63.88%) male; mean [SD] age, 59.47 [16.42] years) were enrolled in this study. Age (OR: 1.022, 1.009–1.035), international normalized ratio (OR: 1.837, 1.270–2.656), fibrinogen (OR: 1.535, 1.232–1.914), C-reaction protein (OR: 1.011, 1.008–1.014), sequential organ failure assessment score (OR: 1.306, 1.247–1.368), congestive heart failure (OR: 1.714, 1.126–2.608), and dopamine use (OR: 1.876, 1.227–2.874) were used as risk variables to develop the nomogram model. The AUCs of the nomogram model were 0.861 (95% CI, 0.830–0.892) and 0.845 (95% CI, 0.804–0.886) in the internal and external validation, respectively. The clinical prediction model showed excellent calibration and higher net clinical benefit. Moreover, the predictive performance of the model correlated with the severity of sepsis, with higher predictive performance for patients in septic shock than for other patients.ConclusionThe nomogram model can be used as a reliable and simple predictive tool for the early identification of NOAF in patients with sepsis, which will provide practical information for individualized treatment decisions. |
| first_indexed | 2024-04-13T02:13:19Z |
| format | Article |
| id | doaj.art-0aded3c3541d46828d52092332c87e09 |
| institution | Directory Open Access Journal |
| issn | 2297-055X |
| language | English |
| last_indexed | 2024-04-13T02:13:19Z |
| publishDate | 2022-08-01 |
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| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj.art-0aded3c3541d46828d52092332c87e092022-12-22T03:07:13ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2022-08-01910.3389/fcvm.2022.968615968615Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factorsZhuanyun Li0Ming Pang1Yongkai Li2Yaling Yu3Tianfeng Peng4Zhenghao Hu5Ruijie Niu6Jiming Li7Xiaorong Wang8Department of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Neurophysiology, Cangzhou Hospital of Integrated Traditional Chinese Medicine and Western Medicine, Cangzhou, ChinaDepartment of Emergency Medicine, The First Affiliated Hospital, Xinjiang Medical University, Ürümqi, ChinaDepartment of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Emergency Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Emergency Medicine, The First Affiliated Hospital, Xinjiang Medical University, Ürümqi, ChinaDepartment of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaObjectiveNew-onset atrial fibrillation (NOAF) is a common complication and one of the primary causes of increased mortality in critically ill adults. Since early assessment of the risk of developing NOAF is difficult, it is critical to establish predictive tools to identify the risk of NOAF.MethodsWe retrospectively enrolled 1,568 septic patients treated at Wuhan Union Hospital (Wuhan, China) as a training cohort. For external validation of the model, 924 patients with sepsis were recruited as a validation cohort at the First Affiliated Hospital of Xinjiang Medical University (Urumqi, China). Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analyses were used to screen predictors. The area under the ROC curve (AUC), calibration curve, and decision curve were used to assess the value of the predictive model in NOAF.ResultsA total of 2,492 patients with sepsis (1,592 (63.88%) male; mean [SD] age, 59.47 [16.42] years) were enrolled in this study. Age (OR: 1.022, 1.009–1.035), international normalized ratio (OR: 1.837, 1.270–2.656), fibrinogen (OR: 1.535, 1.232–1.914), C-reaction protein (OR: 1.011, 1.008–1.014), sequential organ failure assessment score (OR: 1.306, 1.247–1.368), congestive heart failure (OR: 1.714, 1.126–2.608), and dopamine use (OR: 1.876, 1.227–2.874) were used as risk variables to develop the nomogram model. The AUCs of the nomogram model were 0.861 (95% CI, 0.830–0.892) and 0.845 (95% CI, 0.804–0.886) in the internal and external validation, respectively. The clinical prediction model showed excellent calibration and higher net clinical benefit. Moreover, the predictive performance of the model correlated with the severity of sepsis, with higher predictive performance for patients in septic shock than for other patients.ConclusionThe nomogram model can be used as a reliable and simple predictive tool for the early identification of NOAF in patients with sepsis, which will provide practical information for individualized treatment decisions.https://www.frontiersin.org/articles/10.3389/fcvm.2022.968615/fullnew-onset atrial fibrillationnomogrampredictive modelsepsisSOFA score |
| spellingShingle | Zhuanyun Li Ming Pang Yongkai Li Yaling Yu Tianfeng Peng Zhenghao Hu Ruijie Niu Jiming Li Xiaorong Wang Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors Frontiers in Cardiovascular Medicine new-onset atrial fibrillation nomogram predictive model sepsis SOFA score |
| title | Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors |
| title_full | Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors |
| title_fullStr | Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors |
| title_full_unstemmed | Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors |
| title_short | Development and validation of a predictive model for new-onset atrial fibrillation in sepsis based on clinical risk factors |
| title_sort | development and validation of a predictive model for new onset atrial fibrillation in sepsis based on clinical risk factors |
| topic | new-onset atrial fibrillation nomogram predictive model sepsis SOFA score |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2022.968615/full |
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