Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery
Background: Weaning patients from mechanical ventilation is a critical clinical challenge post cardiac surgery. The effective liberation of patients from the ventilator significantly improves their recovery and survival rates. This study aimed to develop and validate a clinical prediction model to e...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024041720 |
| _version_ | 1797246784569868288 |
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| author | Rong-Cheng Xie Yu-Ting Wang Xue-Feng Lin Xiao-Ming Lin Xiang-Yu Hong Hong-Jun Zheng Lian-Fang Zhang Ting Huang Jie-Fei Ma |
| author_facet | Rong-Cheng Xie Yu-Ting Wang Xue-Feng Lin Xiao-Ming Lin Xiang-Yu Hong Hong-Jun Zheng Lian-Fang Zhang Ting Huang Jie-Fei Ma |
| author_sort | Rong-Cheng Xie |
| collection | DOAJ |
| description | Background: Weaning patients from mechanical ventilation is a critical clinical challenge post cardiac surgery. The effective liberation of patients from the ventilator significantly improves their recovery and survival rates. This study aimed to develop and validate a clinical prediction model to evaluate the likelihood of successful extubation in post-cardiac surgery patients. Method: A predictive nomogram was constructed for extubation success in individual patients, and receiver operating characteristic (ROC) and calibration curves were generated to assess its predictive capability. The superior performance of the model was confirmed using Delong's test in the ROC analysis. A decision curve analysis (DCA) was conducted to evaluate the clinical utility of the nomogram. Results: Among 270 adults included in our study, 107 (28.84%) experienced delayed extubation. A predictive nomogram system was derived based on five identified risk factors, including the proportion of male patients, EuroSCORE II, operation time, pump time, bleeding during operation, and brain natriuretic peptide (BNP) level. Based on the predictive system, five independent predictors were used to construct a full nomogram. The area under the curve values of the nomogram were 0.880 and 0.753 for the training and validation cohorts, respectively. The DCA and clinical impact curves showed good clinical utility of this model. Conclusion: Delayed extubation and weaning failure, common and potentially hazardous complications following cardiac surgery, vary in timing based on factors such as sex, EuroSCORE II, pump duration, bleeding, and postoperative BNP reduction. The nomogram developed and validated in this study can accurately predict when extubation should occur in these patients. This tool is vital for assessing risks on an individual basis and making well-informed clinical decisions. |
| first_indexed | 2024-04-24T19:48:18Z |
| format | Article |
| id | doaj.art-354ae981e680405d95825e28af9bd9f4 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T19:48:18Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-354ae981e680405d95825e28af9bd9f42024-03-25T04:17:55ZengElsevierHeliyon2405-84402024-04-01107e28141Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgeryRong-Cheng Xie0Yu-Ting Wang1Xue-Feng Lin2Xiao-Ming Lin3Xiang-Yu Hong4Hong-Jun Zheng5Lian-Fang Zhang6Ting Huang7Jie-Fei Ma8Department of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR ChinaDepartment of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR ChinaDepartment of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR ChinaDepartment of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR ChinaDepartment of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR ChinaDepartment of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR ChinaDepartment of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR China; Corresponding author.Department of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR China; Corresponding author.Department of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR China; Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 310000, PR China; Corresponding author. Department of Critical Care Medicine, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, Fujian province, PR China.Background: Weaning patients from mechanical ventilation is a critical clinical challenge post cardiac surgery. The effective liberation of patients from the ventilator significantly improves their recovery and survival rates. This study aimed to develop and validate a clinical prediction model to evaluate the likelihood of successful extubation in post-cardiac surgery patients. Method: A predictive nomogram was constructed for extubation success in individual patients, and receiver operating characteristic (ROC) and calibration curves were generated to assess its predictive capability. The superior performance of the model was confirmed using Delong's test in the ROC analysis. A decision curve analysis (DCA) was conducted to evaluate the clinical utility of the nomogram. Results: Among 270 adults included in our study, 107 (28.84%) experienced delayed extubation. A predictive nomogram system was derived based on five identified risk factors, including the proportion of male patients, EuroSCORE II, operation time, pump time, bleeding during operation, and brain natriuretic peptide (BNP) level. Based on the predictive system, five independent predictors were used to construct a full nomogram. The area under the curve values of the nomogram were 0.880 and 0.753 for the training and validation cohorts, respectively. The DCA and clinical impact curves showed good clinical utility of this model. Conclusion: Delayed extubation and weaning failure, common and potentially hazardous complications following cardiac surgery, vary in timing based on factors such as sex, EuroSCORE II, pump duration, bleeding, and postoperative BNP reduction. The nomogram developed and validated in this study can accurately predict when extubation should occur in these patients. This tool is vital for assessing risks on an individual basis and making well-informed clinical decisions.http://www.sciencedirect.com/science/article/pii/S2405844024041720Weaning post-cardiac surgery nomogram prediction validation |
| spellingShingle | Rong-Cheng Xie Yu-Ting Wang Xue-Feng Lin Xiao-Ming Lin Xiang-Yu Hong Hong-Jun Zheng Lian-Fang Zhang Ting Huang Jie-Fei Ma Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery Heliyon Weaning post-cardiac surgery nomogram prediction validation |
| title | Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery |
| title_full | Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery |
| title_fullStr | Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery |
| title_full_unstemmed | Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery |
| title_short | Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery |
| title_sort | development and validation of a clinical prediction model for early ventilator weaning in post cardiac surgery |
| topic | Weaning post-cardiac surgery nomogram prediction validation |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024041720 |
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