Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study
Introduction: With the growing number of posterior open surgery, the incidence of failed back surgery syndrome (FBSS) increases gradually. Currently, there is a lack of predictive systems and scientific evaluation in clinical practice. This study aimed to risk factors analysis of FBSS and develop a...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024166388 |
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| author | Parisa Hajilo Behzad Imani Shirdel Zandi Ali Mehrafshan Salman khazaei |
| author_facet | Parisa Hajilo Behzad Imani Shirdel Zandi Ali Mehrafshan Salman khazaei |
| author_sort | Parisa Hajilo |
| collection | DOAJ |
| description | Introduction: With the growing number of posterior open surgery, the incidence of failed back surgery syndrome (FBSS) increases gradually. Currently, there is a lack of predictive systems and scientific evaluation in clinical practice. This study aimed to risk factors analysis of FBSS and develop a risk prediction model. Materials and methods: Baseline data were collected from 512 patients. Patients were followed up for one year. Ultimately, 146 patients were classified in the FBSS group, with an incidence rate of 32.5 %. Logistic regression was used to screen for independent risk factors influencing the occurrence of FBSS. The diagnostic power of model was evaluated using the receiver operating characteristic (ROC) curve. Findings: Age, smoking, type of pain, revision surgery, surgical technique, quality of life, and psychological status were significantly associated with the incidence of FBSS. The strongest factor in this model was the selected surgical technique, with an odds ratio of 0.095. The area under the ROC curve for the model's diagnostic and classification power was 0.852. Conclusion: The causes of FBSS can stem from underlying factors, lifestyle, surgical causes, and patients' psychological factors. Therefore, prevention and treatment for each individual should be based on their specific cause to achieve optimal results. |
| format | Article |
| id | doaj-art-5e55f16ca8314314a08fd78480d018ff |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-5e55f16ca8314314a08fd78480d018ff2025-01-17T04:49:41ZengElsevierHeliyon2405-84402025-01-01111e40607Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort studyParisa Hajilo0Behzad Imani1Shirdel Zandi2Ali Mehrafshan3Salman khazaei4Student Operating Room (MSc), Student Research Committee, Hamadan University of Medical Sciences, Hamadan, IranDepartment of Operating Room, School of Paramedicine, Hamadan University of Medical Sciences, Hamadan, Iran; Corresponding author.Department of Operating Room, School of Paramedicine, Hamadan University of Medical Sciences, Hamadan, IranDepartment of Neurosurgery, Nekuii Forghani Hospital University of Medical Sciense Qom, Qom, IranHamadan University of Medical Sciences, Hamadan, IranIntroduction: With the growing number of posterior open surgery, the incidence of failed back surgery syndrome (FBSS) increases gradually. Currently, there is a lack of predictive systems and scientific evaluation in clinical practice. This study aimed to risk factors analysis of FBSS and develop a risk prediction model. Materials and methods: Baseline data were collected from 512 patients. Patients were followed up for one year. Ultimately, 146 patients were classified in the FBSS group, with an incidence rate of 32.5 %. Logistic regression was used to screen for independent risk factors influencing the occurrence of FBSS. The diagnostic power of model was evaluated using the receiver operating characteristic (ROC) curve. Findings: Age, smoking, type of pain, revision surgery, surgical technique, quality of life, and psychological status were significantly associated with the incidence of FBSS. The strongest factor in this model was the selected surgical technique, with an odds ratio of 0.095. The area under the ROC curve for the model's diagnostic and classification power was 0.852. Conclusion: The causes of FBSS can stem from underlying factors, lifestyle, surgical causes, and patients' psychological factors. Therefore, prevention and treatment for each individual should be based on their specific cause to achieve optimal results.http://www.sciencedirect.com/science/article/pii/S2405844024166388Risk factorsPrediction modelSurgeryBackSyndromeFailed |
| spellingShingle | Parisa Hajilo Behzad Imani Shirdel Zandi Ali Mehrafshan Salman khazaei Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study Heliyon Risk factors Prediction model Surgery Back Syndrome Failed |
| title | Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study |
| title_full | Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study |
| title_fullStr | Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study |
| title_full_unstemmed | Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study |
| title_short | Risk factors analysis and risk prediction model for failed back surgery syndrome: A prospective cohort study |
| title_sort | risk factors analysis and risk prediction model for failed back surgery syndrome a prospective cohort study |
| topic | Risk factors Prediction model Surgery Back Syndrome Failed |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024166388 |
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