Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients
Hip fracture patients have a high risk of mortality after surgery, with 30-day postoperative rates as high as 10%. This study aimed to explore the predictive ability of preoperative characteristics in traumatic hip fracture patients as they relate to 30-day postoperative mortality using readily avai...
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| Format: | Article |
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MDPI AG
2021-04-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/11/5/353 |
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| author | Yang Cao Maximilian Peter Forssten Ahmad Mohammad Ismail Tomas Borg Ioannis Ioannidis Scott Montgomery Shahin Mohseni |
| author_facet | Yang Cao Maximilian Peter Forssten Ahmad Mohammad Ismail Tomas Borg Ioannis Ioannidis Scott Montgomery Shahin Mohseni |
| author_sort | Yang Cao |
| collection | DOAJ |
| description | Hip fracture patients have a high risk of mortality after surgery, with 30-day postoperative rates as high as 10%. This study aimed to explore the predictive ability of preoperative characteristics in traumatic hip fracture patients as they relate to 30-day postoperative mortality using readily available variables in clinical practice. All adult patients who underwent primary emergency hip fracture surgery in Sweden between 2008 and 2017 were included in the analysis. Associations between the possible predictors and 30-day mortality was performed using a multivariate logistic regression (LR) model; the bidirectional stepwise method was used for variable selection. An LR model and convolutional neural network (CNN) were then fitted for prediction. The relative importance of individual predictors was evaluated using the permutation importance and Gini importance. A total of 134,915 traumatic hip fracture patients were included in the study. The CNN and LR models displayed an acceptable predictive ability for predicting 30-day postoperative mortality using a test dataset, displaying an area under the ROC curve (AUC) of as high as 0.76. The variables with the highest importance in prediction were age, sex, hypertension, dementia, American Society of Anesthesiologists (ASA) classification, and the Revised Cardiac Risk Index (RCRI). Both the CNN and LR models achieved an acceptable performance in identifying patients at risk of mortality 30 days after hip fracture surgery. The most important variables for prediction, based on the variables used in the current study are age, hypertension, dementia, sex, ASA classification, and RCRI. |
| first_indexed | 2024-03-10T11:51:54Z |
| format | Article |
| id | doaj.art-3761986551e74527b7d8bb27ec3d5955 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-10T11:51:54Z |
| publishDate | 2021-04-01 |
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| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-3761986551e74527b7d8bb27ec3d59552023-11-21T17:34:47ZengMDPI AGJournal of Personalized Medicine2075-44262021-04-0111535310.3390/jpm11050353Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture PatientsYang Cao0Maximilian Peter Forssten1Ahmad Mohammad Ismail2Tomas Borg3Ioannis Ioannidis4Scott Montgomery5Shahin Mohseni6Clinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, 70182 Örebro, SwedenDepartment of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, SwedenDepartment of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, SwedenDepartment of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, SwedenDepartment of Orthopedic Surgery, Orebro University Hospital, 70185 Orebro, SwedenClinical Epidemiology and Biostatistics, School of Medical Sciences, Örebro University, 70182 Örebro, SwedenSchool of Medical Sciences, Orebro University, 70182 Orebro, SwedenHip fracture patients have a high risk of mortality after surgery, with 30-day postoperative rates as high as 10%. This study aimed to explore the predictive ability of preoperative characteristics in traumatic hip fracture patients as they relate to 30-day postoperative mortality using readily available variables in clinical practice. All adult patients who underwent primary emergency hip fracture surgery in Sweden between 2008 and 2017 were included in the analysis. Associations between the possible predictors and 30-day mortality was performed using a multivariate logistic regression (LR) model; the bidirectional stepwise method was used for variable selection. An LR model and convolutional neural network (CNN) were then fitted for prediction. The relative importance of individual predictors was evaluated using the permutation importance and Gini importance. A total of 134,915 traumatic hip fracture patients were included in the study. The CNN and LR models displayed an acceptable predictive ability for predicting 30-day postoperative mortality using a test dataset, displaying an area under the ROC curve (AUC) of as high as 0.76. The variables with the highest importance in prediction were age, sex, hypertension, dementia, American Society of Anesthesiologists (ASA) classification, and the Revised Cardiac Risk Index (RCRI). Both the CNN and LR models achieved an acceptable performance in identifying patients at risk of mortality 30 days after hip fracture surgery. The most important variables for prediction, based on the variables used in the current study are age, hypertension, dementia, sex, ASA classification, and RCRI.https://www.mdpi.com/2075-4426/11/5/353hip fracturepostoperative mortalitypredictionvariable importancemachine learningneural network |
| spellingShingle | Yang Cao Maximilian Peter Forssten Ahmad Mohammad Ismail Tomas Borg Ioannis Ioannidis Scott Montgomery Shahin Mohseni Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients Journal of Personalized Medicine hip fracture postoperative mortality prediction variable importance machine learning neural network |
| title | Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients |
| title_full | Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients |
| title_fullStr | Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients |
| title_full_unstemmed | Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients |
| title_short | Predictive Values of Preoperative Characteristics for 30-Day Mortality in Traumatic Hip Fracture Patients |
| title_sort | predictive values of preoperative characteristics for 30 day mortality in traumatic hip fracture patients |
| topic | hip fracture postoperative mortality prediction variable importance machine learning neural network |
| url | https://www.mdpi.com/2075-4426/11/5/353 |
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