Risk factors analysis and risk prediction model for failed back surgery syndrome: a prospective cohort study

Risk factors analysis and risk prediction model for failed back surgery syndrome: a prospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Risk factors analysis and risk prediction model for failed back surgery syndrome: a prospective cohort study Parisa Hajilo, behzad Imani, Shirdel Zandi, Ali mehrafshan, salman khazaei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4960039/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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 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. Health sciences/Anatomy Health sciences/Medical research Risk factors Prediction model Surgery Back Syndrome Failed Figures Figure 1 Figure 2 1. Introduction Degenerative lumbar disease (DLD) are recognized as the most common cause of low back pain, with prevalence increasing with age ( 1 ). The first line of treatment for these patients includes many non-surgical options such as lifestyle modifications, medications, and physiotherapy. However, surgical intervention is recommended if symptoms persist. Over the past two decades, the number of patients eligible for spinal surgery has significantly increased ( 2 ). Although initial structural defects are corrected after surgery, persistent pain or limb numbness sometimes continues. Some patients continue to suffer from chronic pain in the lower back and legs, along with ongoing functional limitations ( 3 ). Therefore, most patients who do not improve after surgery are classified under the heterogeneous disorder known as Failed Back Surgery Syndrome (FBSS). FBSS is defined as "a diverse and complex set of symptoms including persistent or recurrent chronic pain after one or more spinal surgeries" ( 4 ). This term is currently used to describe a heterogeneous group of patients whose surgical outcomes do not meet the pre-surgical expectations of the patient and the surgeon ( 5 ). Although the understanding of anatomical structures has increased and minimally invasive techniques have expanded, the prevalence of FBSS is rising due to the complexity of this issue with varied underlying causes ( 6 ). Multiple factors (biological, psychological, and social) are involved in the development of the pain process, necessitating an interdisciplinary approach to clarify its causes further. Researchers believe that age, lifestyle (smoking, obesity, inactivity), the presence of specific comorbidities, the severity of preoperative pain, and psychosocial factors are potential characteristics associated with the incidence of FBSS ( 7 ). Additionally, reports indicate that incorrect surgical techniques, surgical complications, instability, recurrent disc herniation, and neuropathic pain have a significant impact on the occurrence of FBSS ( 8 ). Modern medical research has identified multiple complex factors involved in the FBSS process. However, pain management requires a multidimensional approach, making it challenging to determine the exact causes of FBSS ( 9 ). Therefore, early screening and effective prevention of FBSS have become critical issues for healthcare professionals. In modern medicine, accurately predicting the occurrence and prognosis of diseases has gained increasing importance, as treatments should be individualized to achieve optimal outcomes. Expectations for outcomes should vary based on the type of structural problem, the number of previous surgeries, and the patient's mental health. Surgeons must convey realistic expectations to patients to align the expectations of both the patient and the surgeon ( 10 ). Numerous researchers have demonstrated that developing risk prediction models has effectively reduced disease incidence ( 11 , 12 ). Despite significant advances in diagnosing and treating FBSS, the lack of baseline epidemiological data and a scientific prediction system hinders the successful evaluation of FBSS prevention and prognosis. Therefore, this study aims to identify the most critical risk factors and develop a robust risk prediction model for FBSS. The primary goal is to assist physicians and patients in enhancing prevention and treatment strategies for FBSS. 2. Materials and Methods 2.1 Study Design This study was conducted as a prospective cohort in Iran (Valiasr Hospital, Qom) in 2023 with a one-year follow-up. The research population included all patients who visited Valiasr Hospital for surgery due to degenerative lumbar disease (DLD) from January 2022 to April 2023. The researcher enrolled all patients. The surgeries were performed by a single surgeon at a single center. The article's writing followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. 2.2. Inclusion and Exclusion criteria Inclusion Criteria Age between 20–60 years Patients with DLD Patients who can undergo magnetic resonance imaging (MRI) and computed tomography (CT) scans Exclusion Criteria Patients diagnosed with specific diseases such as malignant tumors, vertebral fractures, spinal infections, inflammatory spondylitis Patients with progressive neurological deficits or severe concomitant neurological symptoms Patients with pain originating from non-spinal causes and/or soft tissue problems 2.3. Instruments and Data collection 2.3.1 Pre-Operative Demographic and clinical information forms for the patients were recorded through a questionnaire and an interview before surgery by the researcher. A detailed history was taken regarding the onset of pain, pain characteristics, pain location, pain pattern, and pain source. Preoperative anxiety was assessed using the Barton et al. (2019) Surgical Anxiety Questionnaire. This questionnaire contains 27 items that measure preoperative anxiety across six dimensions. This questionnaire's minimum and maximum possible scores range from 19 to 95. A score below 38 indicates low surgical anxiety, a score between 39 and 76 indicates moderate anxiety and a score above 77 indicates high anxiety ( 13 ). 2.3.2 During Operative Surgical Technique Surgery was performed on all patients under general anesthesia in the prone position. A midline incision measuring 5–15 cm (depending on the type of surgery) was made. After muscle dissection, bilateral decompression (laminectomy, medial facetectomy, flavectomy, discectomy) was performed. Following decompression, for the Fixation and Fixation + PLIF groups, pedicle screws were placed unilateral or bilateral (depending on the individual condition), and the pedicle screw anchoring process was completed. Then, in the Fixation + PLIF group, after preparing the endplates, an intervertebral cage was placed and fixed ( 14 ). The amount of blood loss (Blood gases + bottle suction), the time of surgery (from skin incision to the last suture), the type of degenerative lumbar disease (Degenerative disc disease, Spinal stenosis, Spinal instability, Spondylolisthesis, Spondylolysis), the type of surgical procedure (with fixation (unilateral, bilateral), without fixation, with and without interbody fusion), the number of surgical levels, and sacrum fixation were recorded by the researcher. 2.3.3 Postoperative Postoperative psychological disorders, quality of life, and sleep quality of the patients were assessed using validated questionnaires. The psychological disorders questionnaire (SCL-25) by Najarian and Davoudi (2001) contains 25 questions that measure anxiety, depression, phobic anxiety, paranoid ideation, psychosis, obsessive-compulsive disorder, and somatic complaints. The minimum and maximum scores in this questionnaire range from 25 to 125. Scores between 25–50 indicate low psychological disorders, 50–75 indicate moderate psychological disorders, and scores above 75 indicate high psychological disorders ( 15 ). Patients' quality of life was assessed using the Short Form Health Survey (SF-36). This questionnaire evaluates eight health domains (physical function, role function-physical, bodily pain, general health, vitality, social function, role function-emotional, mental health) in two dimensions: physical and mental health. The minimum and maximum scores range from 0 to 100, indicating the lowest and highest quality of life, respectively ( 16 ). The Pittsburgh Sleep Quality Index (PSQI) contains 19 items that assess sleep quality across seven scales (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency) sleep disturbances, use of sleeping medication, daytime dysfunction). The total score of these seven scales forms a global score ranging from 0 to 21. A global score of 6 or higher indicates poor sleep quality ( 17 ). After 12 months of follow-up, the patients were divided into two groups. The first group (non-FBSS) consisted of patients who were satisfied with their surgery and completely recovered. The second group (FBSS) included patients who fell into the Failed Back Surgery Syndrome category. Similar studies have provided various definitions of FBSS patients, as outlined below. In FBSS patients, despite successful spinal surgery, chronic radicular pain in the same area recurred or persisted ( 4 ). The outcome of lumbar spinal surgery did not meet the preoperative expectations of the patient and the surgeon ( 1 ). Patients with chronic neuropathic pain for three months, with a score higher than five on the Visual Analog Scale (VAS) in the lumbar area, with or without radiation to the limbs ( 5 ). Patients experienced chronic back or leg pain after successful lumbar surgery without specific reasons, such as compressive lesions or infection ( 8 ). Therefore, for the precise diagnosis of patients, considering the above definitions, a quantitative and systematic definition of FBSS was provided as follows: intractable pain or sensory deficit in the back and/or limbs after surgery that is resistant to conservative treatment (for more than three months), leading to dissatisfaction with the surgical outcome. 2.4. Statistical Analysis Data were analyzed using SPSS version 16. Initially, the equality of variances and the assumption of normality of the data were assessed using Levene's and the Shapiro-Wilk tests. Continuous data were analyzed using the independent t-test and presented as mean (SD). Categorical data were analyzed using the chi-square test and presented as numbers (%). The Omnibus test was used to assess the explanatory and predictive power of the logistic regression model. A binary logistic regression analysis was conducted to build the FBSS risk prediction model, with FBSS occurrence as the dependent variable. The ROC curve (AUC) was used to assess the diagnostic and classification power of the logistic regression model. 3. Results 3.1. Baseline Characteristics A total of 512 patients meeting the criteria were enrolled. Initially, 37 patients were excluded due to hospital transfer, diagnosis of fractures, and malignancy. Subsequently, 475 patients underwent lumbar spine surgery. Another 27 patients were excluded due to undergoing surgery in two stages: pregnancy and lack of follow-up interest.... In the end, 302 patients were in the non-FBSS group, and 146 patients were in the FBSS group, with an incidence rate of 32.5% (Fig. 1). In this study, 30 independent variables potentially influencing the occurrence of FBSS were examined. Based on the principle that the required sample size for multivariate analysis should be 5 to 10 times the number of independent variables ( 18 ), the size of the sample needed for this study was 150 to 300. Four hundred forty-eight patients were analyzed, exceeding the minimum sample size and meeting the statistical requirements. Demographic data analysis showed that the mean age in the FBSS group was significantly higher compared to the healthy group (non-FBSS) (65.68 (8.66) vs. 62.62 (9.03), P < 0.05). Smoking was more prevalent in the FBSS group as a potential risk factor (61.6% vs. 49.7%, P 0.05) (Table 1 ). Table 1 Evaluation of demographic information FBSS (N = 146) Non-FBSS (N = 302) P-value ‡ Age † (yr) , mean (SD) 64.68 ( 8.66) 62.62 (9.03) 0.022 Gender *, NO(%) Male Female 76 (52.1%) 70 (47.9%) 151 (50.0%) 151(50.0%) 0.683 Height † (cm) , mean ± SD) 176.74 ± 8.74 175.02 ± 9.81 0.062 Weight † (kg) , (mean ± SD) 88.25 ± 10.2 87.26 ± 8.99 0.298 BMI(Kg/m 2 ) , (mean ± SD) Employment status *, NO(%) Unemployed Employed 37 (25.3%) 109 (74.7%) 55 (18.2%) 247 (81.8%) 0.08 Smoking *, NO(%) Yes No 90 (61.6%) 56 (38.4%) 150 (49.7%) 152 (50.3%) 0.017 Opioid *, NO(%) Yes No 12 (8.2%) 134 (91.8%) 28 (9.3%) 274 (90.7%) 0.714 Marital status *, NO(%) Single Married 28 (19.2%) 118 (80.8%) 54 (17.9%) 248 (82.1%) 0.739 Level of education *, NO(%) \(\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\le\:\text{D}\text{i}\text{p}\text{l}\text{o}\text{m}\text{a}\) Callegiate 97 (66.4%) 49 (33.6%) 221 (73.2%) 81 (26.8%) 0.141 BMD † (T-score) , mean(SD) -1.83 (0.44) -1.85 (0.65) 0.779 *:Chi-Square, †:t-test, ‡ : Statistical significant as p < 0.05. failed back surgery syndrome (FBSS). BMI: body mass index (BMI), bone mineral density (BMD). 3.2. Pre-Surgery Outcome Analysis of pre-surgery factors indicated that repeated surgeries reduced the success rate of the surgery, and the likelihood of FBSS increased with the number of surgeries (54.8% vs. 35.5%, P < 0.04). As shown in Table 2 , the spread of symptoms to the lower limbs may be associated with FBSS. Therefore, patients without leg pain and numbness in the lower limbs had a lower likelihood of developing FBSS (50.7% vs. 19.9%, P < 0.05) (Table 2 ). Table 2 Evaluation of pre-surgery factors and underlying diseases FBSS (N = 146) Non-FBSS (N = 302) P-value ‡ Anxiety before surgery † , mean (SD) 62.23 ± 12.4 63.60 ± 13.9 0.348 Arthrose *, No(%) Yes No 37 (25.3%) 109 (74.7%) 56 (18.5%) 246 (81.5%) 0.096 Rheumatoid Arthritis *, No(%) Yes No 35 (24.0%) (76.0%)111 (17.9%)54 248 (82.1%) 0.130 Diabetes *, No(%) Yes No 35 (23.97%) (76.02%)111 (23.2%)70 231 (76.5%) 0.774 Hypertension *, No(%) Yes No 41 (28.1%) 105 (71.9%) 73 (24.2%) 229 (75.8%) 0.373 Re-surgery *, No(%) First time Recurrent 66 (45.2%) 80 (54.8%) 195 (64.6%) 107 (35.5%) 0.0001 Symptom location *, No(%) Low back pain without limb symptoms Unilateral limb symptom Bilateral limb symptom 72 (49.3%) 21 (14.4%) 53 (36.3%) 242 (80.1%) 28 (9.3%) 32 (10.6%) 0.0001 Symptom duration (Month) † , mean (SD) 11.3 (3.27) 11.8 (3.09) 0.178 Claudication *, No(%) Yes No 21 (14.4%) 125 (85.6%) 54 (17.9%) 248 (82.1%) 0.353 *:Chi-Square, †:t-test, ‡ : Statistical significant as p < 0.05. failed back surgery syndrome (FBSS) 3.3. During Surgery Outcome Analysis of intraoperative factors showed that the incidence of FBSS significantly varied among different surgical techniques. Therefore, the highest incidence of FBSS was observed in patients who underwent fixation with intervertebral fusion (46.6% vs. 13.9%, P < 0.05) (Table 3 ). Table 3 Evaluation of factors during surgery FBSS (N = 146) Non-FBSS (N = 302) P-value ‡ Time of surgery † , mean (SD) 120.8 (17.3) 117.5 (22.9) 0.076 Type of complication *, No(%) Laminectomy Spinal stenosis Spinal instability Spondylolisthesis Spondylolysis Multiple complications 15 (10.2%) 19 (13.0%) 25 (17.1%) 23 (15.7%) 36 (24.6%) 28 (19.1%) 27 (8.10%) 63 (20.9%) 53 (17.5%) 58 (19.2%) 46 (15.2%) 55 (18.2%) 0.110 Side Fixation *, No(%) Unilateral Bilateral 52 (35.6%) 94 (64.4%) 118 (39.07%) 184 (60.9%) 0.480 Levels of surgery* , No(%) Single level Multilevel 70 (47.9%) 76 (52.1%) 129 (42.7%) 173 (57.3%) 0.296 Type of Surgery *, No(%) Decompressio Fixation alone Fixation + PLIF 25 (17.1%) 53 (36.3%) 68 (46.6%) 164 (54.3%) 96 (31.8%) 42 (13.9%) 0.0001 Sacrum fixation *, No(%) Yes No 36 (24.7%) 110 (75.3%) 95 (31.5%) 207 (68.5%) 0.138 *:Chi-Square, †:t-test, ‡ : Statistical significant as p < 0.05. failed back surgery syndrome (FBSS) 3.4. Post-Surgery Outcome As shown in Table 4 , individuals with poor mental health post-surgery are at a higher risk of developing FBSS (70.03(12.6) vs. 40.8(12.1), P < 0.05). Additionally, data from this study indicate that the highest incidence of FBSS is found in individuals with poor quality of life (31.03(11.1) vs. 64.3 (16.4), P 0.05) (Table 4 ). Table 4 Evaluation of factors post-surgery FBSS (N = 146) Non-FBSS (N = 302) P-value ‡ Rest time(day) † , mean (SD) 42.8 (12.6) 44.6 (11.6) 0.143 Rehabilitation *, No(%) Yes No 49 (33.6%) 97 (66.4%) 90 (29.8%) 212 (70.2%) 0.420 Mental health † , mean (SD) 70.03 (12.6) 63.5 (12.2) 0.0001 Quality of Life † , mean (SD) 31.03 (11.1) 64.3 (16.4) 0.0001 Sleep quality † , mean (SD) 5.87 (1.71) 5.69 (2.15) 0.346 *:Chi-Square, †:t-test, ‡ : Statistical significant as p < 0.05. failed back surgery syndrome (FBSS) Table 5 was used to explain the strength and efficiency of the logistic regression model in distinguishing and classifying individuals with FBSS and non-FBSS. Overall, the classification accuracy of individuals by the fitted logistic regression model was 78.8% (Table 5 ). Table 5 Classification Table Predicted Percentage Correct Non-FBSS FBSS Observed Non-FBSS 267 35 88.4 FBSS 60 86 58.9 Overall Percentage 78.8 failed back surgery syndrome (FBSS) In Table 6 , the coding of qualitative variables has been carried out. For each variable, one group was designated as the reference category to compare the odds of developing FBSS in other groups relative to the reference category (Table 6 ). As shown in Table 7 , based on the odds ratio (OR), the selected surgical technique is the strongest factor in the occurrence of FBSS. Therefore, the likelihood of developing FBSS in individuals who underwent Fixation + PLIF surgery is 10.52 times greater than those who underwent decompression surgery. Additionally, patients who underwent Fixation + PLIF surgery are 2.83 times more likely to develop FBSS compared to those who underwent Fixation surgery. In our regression model, the second most influential factor in the occurrence of FBSS was radicular pain in the lower limbs. The likelihood of developing FBSS in individuals who had radicular pain in both lower limbs before surgery is 7.24 times higher than in those who only suffered from back pain. The likelihood of developing FBSS in individuals whose back pain radiated to both legs before surgery is 2.92 times higher than in those whose back pain radiated to only one leg. Smoking was identified as the third most influential factor in the occurrence of FBSS, with smokers having a 2.55 times higher likelihood of developing FBSS compared to non-smokers. Based on the odds ratio (OR), the likelihood of developing FBSS in revision surgery is 2.50 times higher than in those undergoing surgery for the first time. The odds ratio for the variables of age and psychological disorders is reported to be 1.046 and 1.031, respectively. Thus, an increase in age and a higher score of psychological disorders significantly increase the likelihood of developing FBSS. The odds ratio for the quality of life variable is 0.967, indicating that an increase in the quality of life score significantly reduces the likelihood of developing FBSS (Table 7 ). Table 6 Categorical Variables Codings Frequency Parameter coding (1) (2) Type surgery Decompration 189 1.000 0.000 Fixation 149 0.000 1.000 Fixation + PLIF 110 0.000 0.0001 Symptom location Back-pain 314 1.000 0.0001 Uni-limb 49 0.000 1.000 Bi-limb 85 0.000 0.000 Re-surgery First time 261 1.000 Recurrent 187 0.000 Smoking No 208 1.000 Yes 240 0.000 Table 7 Multivariate logistic prediction model of FBSS Variables Beta S.E Wald Df OR 95% Confidence Interval for OR P-value ‡ Lower Upper Type surgery 51.600 2 0.0001 Type surgery (1) -2.352 0.327 51.595 1 0.095 0.050 0.181 0.0001 Type surgery (2) -1.041 0.299 12.115 1 0.353 0.197 0.635 0.001 Symptom location 39.854 2 0.0001 Symptom location (1) -1.981 0.318 38.847 1 0.138 0.074 0.257 0.0001 Symptom location (2) -1.072 0.451 5.648 1 0.342 0.141 0.829 0.017 Smoking (1) -0.936 0.270 11.995 1 0.392 0.231 0.666 0.001 Re-surgery (1) -0.918 0.254 13.063 1 0.399 0.243 0.657 0.0001 Age 0.045 0.011 15.903 1 1.046 1.023 1.069 0.0001 Psychopathy 0.031 0.008 13.586 1 1.031 1.014 1.048 0.0001 Quality life -0.033 0.009 14.880 1 0.967 0.951 0.984 0.0001 Coefficient value (Beta), Standard error (S.E), Chi-square value (Wald), Degrees of freedom (Df), Odds ratio (OR). ‡ : Statistical significant as p < 0.05. Finally, the logistic regression model was obtained as follows: This model calculates the probability that an individual will develop FBSS. According to the results in Table 8 , the AUC (Area Under the ROC Curve) index is reported to be 0.852, indicating that the proposed logistic regression model has a high performance in correctly identifying and classifying individuals with FBSS and non-FBSS. The sensitivity of the prediction model is 58.9%, and the specificity is 88.4% (Table. 8) (F.I.G.2). Table 8 Area Under the ROC Curve Predicted probability Area S.E 95% Confidence Interval for Area P-value Lower Upper 0.852 0.018 0.816 .887 0.0001 F.I.G. 2. The area under the rock curve shows the performance of the logistic regression model in identifying and classifying people with FBSS or Non-FBSS. The x-axis is the sensitivity, which represents the possibility of predicting positive samples but actually negative samples. The y axis is 1-specific, which represents the possibility of predicting positive samples but actually positive samples. The blue real line is the ROC curve of the model, and the red line represents the ROC curve of random gues. Application example of risk prediction model Case Study Consider a non-smoking, 57-year-old married female patient with a BMI of 30.2 kg/m². Six years ago, she underwent fixation surgery at the L3-L4 lumbar spine level. She presented with severe back pain and radicular pain in both lower limbs. Magnetic resonance imaging showed ASD at the L2-L3 vertebrae level. Additionally, flexion and extension radiographs revealed grade 3 spondylolisthesis at the L5-S1 vertebrae level. Thus, she underwent fixation surgery from the L2 to S1 vertebrae levels. Her surgery lasted 3 hours and 45 minutes. Her quality of life and psychological disorder scores were 33 and 73, respectively. Now, we input these values into the logistic regression model. The predicted probability that this patient will develop FBSS is approximately 0.85 or 85%. Since this probability is more significant than 0.5, according to the logistic regression model, this case is classified as an individual with FBSS. 4. Discussion The present study aimed to analyze the risk factors and develop a risk prediction model for Failed Back Surgery Syndrome (FBSS). A risk prediction model was adopted in this study, which predicts the logistic regression outcomes based on clinical and medical data. This model integrates and compares various determining factors to predict the likelihood of an individual developing this condition. Data analysis revealed that the selected surgical technique is the strongest factor influencing the occurrence of FBSS. Therefore, the highest incidence of FBSS was observed first in the Fixation + PLIF group and then in the Fixation group. Recent reports indicate that pedicle screw fixation techniques, bilateral muscle dissection, removal of posterior elements, and loss of bony structure lead to spinal instability and pain of unknown origin ( 19 , 20 ). Souslian & Patel (2024) stated that after PLIF surgery, the potential for load distribution among spinal structures increases, resulting in axial pain ( 21 ). Cicek et al. (2017) reported similar findings ( 22 ). In patients undergoing PLIF + Fixation surgery, the entire bilateral facet joints are removed, the disc is completely evacuated, and a relatively small intervertebral cage acts as a focal pivot point. Thus, despite pedicle screw fixation, the structure may inherently be unstable ( 23 ). Contrary to the above results, some studies have shown no significant difference between spinal fixation techniques with and without intervertebral fusion ( 24 ). The discrepancy in results may be due to variations in postoperative follow-up duration, levels of spinal fixation, and different surgical techniques. Data analysis showed that radicular pain in the lower limbs before surgery is the second most influential factor in FBSS. Supporting these findings, Wenbo et al. (2022) believe that preoperative radicular pain in the lower limbs is a significant factor in FBSS development and should be investigated as a marker for identifying at-risk populations ( 25 ). Evandro et al. (2020) reported similar results ( 2 ). Contrary to these findings, some reports suggest that surgical outcomes are not significantly related to the type and severity of preoperative pain ( 1 ). The discrepancy in results may be influenced by the duration of symptoms before surgery and the patient inclusion criteria. The optimal timing for decompression surgery remains unclear. Historically, early surgical intervention for symptomatic spinal stenosis has been recommended based on the view that the condition is always progressive. Unlike peripheral nerves, nerve roots lack a blood-nerve barrier, and prolonged compressive lesions lead to intraneural edema. Over time, this edema causes nerve fibrosis, a process that is irreversible even with surgical intervention ( 26 ). Additionally, research has shown that long-term symptomatic radiculopathy is affected by multiple damaging factors and is more complex than simple neural dysfunction caused by physical pressure ( 27 ). Data analysis indicates that smoking is one of the significant risk factors for the development of FBSS. In this context, a study by Mekhail et al. (2020) with a one-year follow-up showed that the incidence of FBSS was significantly higher in current smokers compared to non-smokers or those who had quit smoking ( 28 ). Robson et al. (2019) reported similar findings ( 23 ). A meta-analysis study found that individuals who quit smoking three months before surgery were less likely to develop FBSS compared to smokers ( 29 ). Contrary to these results, some studies did not find a significant difference in the incidence of FBSS between smokers and non-smokers ( 30 ). The discrepancy in results may be due to the type of intervention, the extent of iatrogenic tissue damage, and the sample size of the studies. In general, nicotine destroys vascular endothelium, playing a crucial role in vasoconstriction, blood flow disruption, synthesis and secretion of biologically active factors, neovascularization, and immune responses. After spinal surgery, the circulatory system plays a key role in tissue healing and postoperative recovery. Therefore, when the vascular endothelium is damaged, the post-surgical healing process is disrupted and inefficient in smokers. The more extensive the iatrogenic soft tissue damage during surgery, the more significantly postoperative complications increase. These findings are supported by several studies reporting increased inflammatory markers in smokers ( 31 , 32 ). Findings from the study indicate that revision surgery is a potential risk factor for developing FBSS. Therefore, patients with previous lumbar surgery were at higher risk. Researchers believe that the number of previous spinal surgeries is a significant predictor of surgical outcomes ( 33 ). Montenegro et al. (2021) found that the average functional status score of 46% of patients significantly decreased six months after revision surgery ( 34 ). Moaven et al. (2020) stated in their study that revision surgery is much more complicated than primary surgery due to unclear anatomical levels and scars around the nerves, requiring a high skill level ( 33 ). In revision surgeries, the absence of spinous processes, bony structures, and fibrous tissue growth in the surgical area leads to significant anatomical changes. Adhesions in the surgical area increase the risk of nerve element damage and dural tears. Therefore, there is concern that the success rate of the second surgery is lower than that of the first surgery. Researchers have noted that the incidence of FBSS increases from 8% in primary surgeries to 48% in revision surgeries. However, the degree of difference may vary depending on surgical techniques and the type of condition ( 35 ). Data analysis showed that age is one of the risk factors for patients undergoing spinal surgery. Early studies have identified age as an important underlying factor in the occurrence of FBSS and believe that it needs special consideration when selecting treatment options ( 35 ). Wenbo et al. (2022) argue that older patients have a significant increase in postoperative complications and often require revision surgery ( 25 ). Other studies in this field have reported similar findings ( 3 , 36 ). Changes in pain perception with aging affect the pain experience in various ways, some of which are still unknown. The assumptions are based on the anatomical changes in older individuals, such as spinal canal and foramina narrowing, increased pressure on neural elements, and microcirculation disruption, which exponentially decrease the success rate after surgery. Researchers have found that the loss of lumbar lordosis, increased thoracic kyphosis, and stiffening of the ligamentum flavum are common changes that contribute to spinal degeneration and are frequent sources of back pain after surgery in older individuals ( 37 ). Data from the study indicate that specific psychological factors, including significant levels of depression, anxiety, phobic anxiety, paranoid ideation, psychosis, obsessive-compulsive disorder, and somatic complaints, lead to an increased incidence of FBSS. Recent reports suggest that these psychological factors affect individual changes in pain sensitivity, thereby influencing pain perception ( 13 , 38 ). The study by Sebaaly et al. (2018) showed a bidirectional relationship between pain and depression ( 39 ). Elsamadicy et al. (2018) believe that mental health is a much stronger predictor of disability from back pain than structural abnormalities ( 3 ). A recent study identified depression as a risk factor for postoperative pain in specific areas, including the head, neck/shoulder, and back ( 7 ). Contrary to these findings, other studies showed no significant difference between psychological disorders and postoperative pain with a one-year follow-up ( 40 ). The discrepancy in results may be due to the type of tools used to measure mental health and the duration of follow-up after surgery. In short-term follow-up, it may be difficult to differentiate between nonspecific pain sources (skin incision, iatrogenic tissue damage, reactive spasms, and nerve root inflammation) and pain originating from the central nervous system. In this context, the results of a study by Graham et al. with a five-year follow-up reported similar findings, illustrating this issue well ( 20 ). The existing literature indicates that psychological disorders can result from stressors and disrupt behavioral patterns. In other words, individuals who experience pain due to their spinal condition avoid normal work and recreational activities, significantly reducing their quality of life ( 41 ). As noted in the present study, poor quality of life predicts FBSS occurrence. Inoue et al. (2017) found that increased FBSS incidence is associated with low quality of life and high levels of functional disability ( 40 ). Therefore, psychological disorders can directly or indirectly increase the prevalence of FBSS. However, it is important to note that awareness of these factors should not prevent patients from undergoing spinal surgery when significant pathology and surgical indications are present. Instead, these risk factors necessitate careful consideration and optimization of surgical timing. Patients with higher surgical risk in spinal surgery may achieve better outcomes with prompt intervention. This is because prolonged pain and discomfort in this population can exacerbate existing psychosocial stressors and reduce the success rate of surgery. It is logical that "the most effective treatment for FBSS is to avoid or prevent FBSS itself," as aging and the exacerbation of psychological, physical, and mechanical effects experienced by patients transform it into a multifactorial, complex, and painful syndrome. The detrimental effects of FBSS are well known, and current strategies and treatment methods are only available after the onset of the disease. Furthermore, most patients with FBSS experience varying degrees of disability, which brings significant anxiety and economic burden to them and their families. Therefore, early screening for this condition is of particular importance. The prediction model presented in the current study demonstrated good performance and is easy to apply in clinical practice, providing the necessary individual diagnostic and treatment requirements. This model may be useful for preventing and treating FBSS and identifying at-risk populations in clinical practice. Limitations There are several limitations to this study. First, a relatively short follow-up period may obscure changes in outcome indicators resulting from other degenerations. Additionally, the patient's risk factors examined in this study were self-reported, which introduces potential recall bias and subjective interpretations. Future research should examine a broader set of clinical variables to enhance the comprehensiveness and completeness of the information obtained by the prediction model. Moreover, using a multicenter approach for sample collection would increase the model's validity and generalizability. 5. Conclusion Based on the results of multivariate logistic regression analysis, this study demonstrated that the selected surgical technique, preoperative pain symptoms, smoking, revision surgery, age, mental health, and quality of life are risk factors for FBSS. Increased awareness in this area can serve as a tool for physicians to identify at-risk populations and provide more effective management to reduce discrepancies between patient and physician expectations. Relying on these factors, an initial FBSS risk prediction model was developed. Additionally, the ROC curve indicated that the logistic regression model performs well in accurately identifying and classifying individuals. Declarations Consent to participate All patients provided written informed consent to participate in the study, publication of radiological images and for their data to be published. The principles of the Helsinki Declaration were adhered to in this study. Competing interests The authors have no potential or real conflict of interests CRediT authorship contribution statement BI: conceptualization, investigation, Writing-review & esiting,. AM: validation, funding acquisition, resources, methodology. SZ: data curation, investiration, Writing-original draft. PH: project administration, visualization. SK: software, formal analysis, validation. Funding The study was funded by Vice-chancellor for Research and Technology, Hamadan University of Medical Sciences (140208237083). Author Contribution BI: conceptualization, investigation, Writing-review & esiting,. AM: validation, funding acquisition, resources, methodology. SZ: data curation, investiration, Writing-original draft. PH: project administration, visualization. SK: software, formal analysis, validation. Acknowledgements This study has been adapted from an MSc thesis project at Hamadan University of Medical Sciences. Data Availability Data associated with the study has not been deposited into a publicly available repository. Data are available from the corresponding author on reasonable request. Ethics approval This study was reviewed and approved by Ethics Committee of Hamedan University of Medical Sciences with the approval number: IR.UMSHA.REC.1402.553. 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Neurosurg. 38 (1), 61–67. https://doi.org/10.1080/02688697.2021.1881041 (2024). Cicek, E., Koçak, M. M., Koçak, S., Sağlam, B. C. & Türker, S. A. Postoperative pain intensity after using different instrumentation techniques: a randomized clinical study. J. Appl. Oral Sci. 25 , 20–26. https://doi.org/10.1590/1678-77572016-0138 (2017). Robson, E. K. et al. Healthy Lifestyle Program (HeLP) for low back pain: protocol for a randomised controlled trial. BMJ open. 9 (9), e029290. https://doi.org/10.1136/bmjopen-2019-029290 (2019). Keorochana, G. et al. Comparative outcomes of cortical screw trajectory fixation and pedicle screw fixation in lumbar spinal fusion: systematic review and meta-analysis. World Neurosurg. 102 , 340–349. https://doi.org/10.1016/j.wneu.2017.03.010 (2017). Xu, W., Ran, B., Zhao, J., Luo, W. & Gu, R. Risk factors for failed back surgery syndrome following open posterior lumbar surgery for degenerative lumbar disease. BMC Musculoskelet. Disord. 23 (1), 1141. https://doi.org/10.1186/s12891-022-06066-2 (2022). Sheaths, C. T. 5 Nerve Anatomy and Physiology, Compression Neuropathies, and Nerve Injuries. Review of Hand Surgery. E-Book . 85. http://dx.doi.org/10.1016/j.jassh.2004.06.007 (2021). Urits, I. et al. Low back pain, a comprehensive review: pathophysiology, diagnosis, and treatment. Curr. Pain Headache Rep. 23 , 1–10. https://doi.org/10.1007/s11916-019-0757-1 (2019). Mekhail, N. et al. The impact of tobacco smoking on spinal cord stimulation effectiveness in complex regional pain syndrome patients. Neuromodulation: Technol. Neural Interface . 23 (1), 133–139. https://doi.org/10.1111/ner.13058 (2020). Mills, E. et al. Smoking Cessation Reduces Postoperative Complications: A Systematic Review and Meta-analysis. Am. J. Med. 124 (2), 144. https://doi.org/10.1016/j.amjmed.2010.09.013 (2011). 54.e8 Alan, N. et al. Smoking and postoperative outcomes in elective cranial surgery. J. Neurosurg. 120 (4), 811–819. https://doi.org/10.3171/2014.1.JNS131852 (2014). Yılmaz, M. & Kayançiçek, H. A new inflammatory marker: elevated monocyte to HDL cholesterol ratio associated with smoking. J. Clin. Med. 7 (4), 76. https://doi.org/10.3390%2Fjcm7040076 (2018). Elisia, I. et al. The effect of smoking on chronic inflammation, immune function and blood cell composition. Sci. Rep. 10 (1), 19480. https://doi.org/10.1038/s41598-020-76556-7 (2020). Moaven, M., Ilkhechi, R. B., Zeinali, M., Hesam, S. & Jamali, K. Study of Re-Operational Risk Factors in Lumbar Herniated Disk Patients Referring to Golestan Hospital, Ahvaz From 2011 to 2015. Jundishapur J. Health Sci. 12 (1). http://dx.doi.org/10.5812/jjhs.99748 (2020). Montenegro, T. S. et al. Clinical outcomes in revision lumbar spine fusions: an observational cohort study. J. Neurosurgery: Spine . 35 (4), 437–445. https://doi.org/10.3171/2020.12.spine201908 (2021). Puvanesarajah, V. et al. Risk factors for revision surgery following primary adult spinal deformity surgery in patients 65 years and older. J. Neurosurgery: Spine . 25 (4), 486–493. https://doi.org/10.3171/2016.2.spine151345 (2016). Vasdev, N. Multicentric validation of nomograms based on BC-116 and BC-106 urine peptide biomarker panels for bladder cancer diagnostics and monitoring in two prospective cohorts of patients. Br. J. Cancer . 128 (6), 929. https://doi.org/10.1038/s41416-023-02142-z (2023). Cloyd, J. M., Acosta, F. L. Jr & Ames, C. P. Complications and outcomes of lumbar spine surgery in elderly people: a review of the literature. J. Am. Geriatr. Soc. 56 (7), 1318–1327. https://doi.org/10.1111/j.1532-5415.2008.01771.x (2008). Bener, A. et al. Psychological factors: anxiety, depression, and somatization symptoms in low back pain patients. J. pain Res. 95–101. https://doi.org/10.2147/jpr.s40740 (2013). Sebaaly, A., Lahoud, M-J., Rizkallah, M., Kreichati, G. & Kharrat, K. Etiology, evaluation, and treatment of failed back surgery syndrome. Asian spine J. 12 (3), 574. https://doi.org/10.4184/asj.2018.12.3.574 (2018). Inoue, S. et al. Prevalence, characteristics, and burden of failed back surgery syndrome: the influence of various residual symptoms on patient satisfaction and quality of life as assessed by a nationwide Internet survey in Japan. J. Pain Res. 811–823. https://doi.org/10.2147/jpr.s129295 (2017). Imani, B., Hajilo, P., Zandi, S. & Mehrafshan, A. Comparing the intraoperative and postoperative complications of the scalpel and electrocautery techniques for severing the inner layers of the lumbar disc during discectomy surgery. Front. Surg. 10 , 1264519. https://doi.org/10.3389/fsurg.2023.1264519 (2023). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4960039","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":361350144,"identity":"36b80e18-326d-419d-b164-ae87300bd4f5","order_by":0,"name":"Parisa Hajilo","email":"","orcid":"","institution":"Hamedan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Parisa","middleName":"","lastName":"Hajilo","suffix":""},{"id":361350145,"identity":"2399b06e-e696-4db5-9d77-f59758ae4f34","order_by":1,"name":"behzad Imani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYBACAwYeIMkmAeYY/6kAkszMDcRrKeA5A9LCSJQWCOcDbxuIIqDFnL338IcfZRbR/LMbGDdIzquN5m8HavlRsQ2nFsuecwmGPeckcmfcOcBsYLjteO6Mw4wNjD1nbuN22I0cgwTeNonchhsJbAaJ247lNgC1MDO24dFy/43Bwb9ALfNvJLD/ODjnWO58glpu8Bg2g2zZcCOBwbCxoSZ3AyEtlj05xswyQL9svJHYYMxw7EDuRqCWg/j8Ys5+xvjjm7K63Hk3kg8YM9QAGecPH3zwowK3FiQAjo7DYOYBYtTDQB0pikfBKBgFo2CEAADlbl6lmtZWoQAAAABJRU5ErkJggg==","orcid":"","institution":"Hamedan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"behzad","middleName":"","lastName":"Imani","suffix":""},{"id":361350146,"identity":"48cef442-6b01-4dc5-87bb-3e9a18e73929","order_by":2,"name":"Shirdel Zandi","email":"","orcid":"","institution":"Hamedan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Shirdel","middleName":"","lastName":"Zandi","suffix":""},{"id":361350147,"identity":"d0cf13f1-c97e-446c-b4e9-5e77d273d745","order_by":3,"name":"Ali mehrafshan","email":"","orcid":"","institution":"Qom University of Medical Science and Health Services","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"mehrafshan","suffix":""},{"id":361350148,"identity":"bfe3c0ab-0fef-4cd5-8ef2-94525085fcff","order_by":4,"name":"salman khazaei","email":"","orcid":"","institution":"Hamedan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"salman","middleName":"","lastName":"khazaei","suffix":""}],"badges":[],"createdAt":"2024-08-22 19:37:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4960039/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4960039/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66949099,"identity":"f18cf977-fb68-4782-b0aa-af0a5765ac45","added_by":"auto","created_at":"2024-10-18 10:00:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34564,"visible":true,"origin":"","legend":"\u003cp\u003eSTORBE\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4960039/v1/dde2924466e4c527330d6b25.png"},{"id":66949100,"identity":"667c17f1-0241-433e-8f00-d6575959df07","added_by":"auto","created_at":"2024-10-18 10:00:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38844,"visible":true,"origin":"","legend":"\u003cp\u003eThe area under the rock curve shows the performance of the logistic regression model in identifying and classifying people with FBSS or Non-FBSS.The x-axis is the sensitivity, which represents the possibility of predicting positive samples but actually negative samples. The y axis is 1-specific, which represents the possibility of predicting positive samples but actually positive samples. The blue real line is the ROC curve of the model, and the red line represents the ROC curve of random gues.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4960039/v1/e4f2df3b2f8a6bec3105a01b.png"},{"id":67192621,"identity":"300725a0-4c22-4fd5-82d2-4143966da1db","added_by":"auto","created_at":"2024-10-22 08:39:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1111363,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4960039/v1/dcbc8388-fc62-413c-9eef-3967a5a46fe8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk factors analysis and risk prediction model for failed back surgery syndrome: a prospective cohort study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDegenerative lumbar disease (DLD) are recognized as the most common cause of low back pain, with prevalence increasing with age (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The first line of treatment for these patients includes many non-surgical options such as lifestyle modifications, medications, and physiotherapy. However, surgical intervention is recommended if symptoms persist. Over the past two decades, the number of patients eligible for spinal surgery has significantly increased (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Although initial structural defects are corrected after surgery, persistent pain or limb numbness sometimes continues. Some patients continue to suffer from chronic pain in the lower back and legs, along with ongoing functional limitations (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Therefore, most patients who do not improve after surgery are classified under the heterogeneous disorder known as Failed Back Surgery Syndrome (FBSS). FBSS is defined as \"a diverse and complex set of symptoms including persistent or recurrent chronic pain after one or more spinal surgeries\" (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This term is currently used to describe a heterogeneous group of patients whose surgical outcomes do not meet the pre-surgical expectations of the patient and the surgeon (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Although the understanding of anatomical structures has increased and minimally invasive techniques have expanded, the prevalence of FBSS is rising due to the complexity of this issue with varied underlying causes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMultiple factors (biological, psychological, and social) are involved in the development of the pain process, necessitating an interdisciplinary approach to clarify its causes further. Researchers believe that age, lifestyle (smoking, obesity, inactivity), the presence of specific comorbidities, the severity of preoperative pain, and psychosocial factors are potential characteristics associated with the incidence of FBSS (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Additionally, reports indicate that incorrect surgical techniques, surgical complications, instability, recurrent disc herniation, and neuropathic pain have a significant impact on the occurrence of FBSS (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eModern medical research has identified multiple complex factors involved in the FBSS process. However, pain management requires a multidimensional approach, making it challenging to determine the exact causes of FBSS (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Therefore, early screening and effective prevention of FBSS have become critical issues for healthcare professionals. In modern medicine, accurately predicting the occurrence and prognosis of diseases has gained increasing importance, as treatments should be individualized to achieve optimal outcomes. Expectations for outcomes should vary based on the type of structural problem, the number of previous surgeries, and the patient's mental health. Surgeons must convey realistic expectations to patients to align the expectations of both the patient and the surgeon (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Numerous researchers have demonstrated that developing risk prediction models has effectively reduced disease incidence (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Despite significant advances in diagnosing and treating FBSS, the lack of baseline epidemiological data and a scientific prediction system hinders the successful evaluation of FBSS prevention and prognosis. Therefore, this study aims to identify the most critical risk factors and develop a robust risk prediction model for FBSS. The primary goal is to assist physicians and patients in enhancing prevention and treatment strategies for FBSS.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design\u003c/h2\u003e \u003cp\u003eThis study was conducted as a prospective cohort in Iran (Valiasr Hospital, Qom) in 2023 with a one-year follow-up. The research population included all patients who visited Valiasr Hospital for surgery due to degenerative lumbar disease (DLD) from January 2022 to April 2023. The researcher enrolled all patients. The surgeries were performed by a single surgeon at a single center. The article's writing followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Inclusion and Exclusion criteria\u003c/h2\u003e \u003cp\u003e \u003cb\u003eInclusion Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAge between 20\u0026ndash;60 years\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients with DLD\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients who can undergo magnetic resonance imaging (MRI) and computed tomography (CT) scans\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eExclusion Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePatients diagnosed with specific diseases such as malignant tumors, vertebral fractures, spinal infections, inflammatory spondylitis\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients with progressive neurological deficits or severe concomitant neurological symptoms\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatients with pain originating from non-spinal causes and/or soft tissue problems\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Instruments and Data collection\u003c/h2\u003e \u003ch2\u003e2.3.1 Pre-Operative\u003c/h2\u003e \u003cp\u003eDemographic and clinical information forms for the patients were recorded through a questionnaire and an interview before surgery by the researcher. A detailed history was taken regarding the onset of pain, pain characteristics, pain location, pain pattern, and pain source.\u003c/p\u003e \u003cp\u003ePreoperative anxiety was assessed using the Barton et al. (2019) Surgical Anxiety Questionnaire. This questionnaire contains 27 items that measure preoperative anxiety across six dimensions. This questionnaire's minimum and maximum possible scores range from 19 to 95. A score below 38 indicates low surgical anxiety, a score between 39 and 76 indicates moderate anxiety and a score above 77 indicates high anxiety (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003ch2\u003e2.3.2 During Operative\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSurgical Technique\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSurgery was performed on all patients under general anesthesia in the prone position. A midline incision measuring 5\u0026ndash;15 cm (depending on the type of surgery) was made. After muscle dissection, bilateral decompression (laminectomy, medial facetectomy, flavectomy, discectomy) was performed. Following decompression, for the Fixation and Fixation\u0026thinsp;+\u0026thinsp;PLIF groups, pedicle screws were placed unilateral or bilateral (depending on the individual condition), and the pedicle screw anchoring process was completed. Then, in the Fixation\u0026thinsp;+\u0026thinsp;PLIF group, after preparing the endplates, an intervertebral cage was placed and fixed (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe amount of blood loss (Blood gases\u0026thinsp;+\u0026thinsp;bottle suction), the time of surgery (from skin incision to the last suture), the type of degenerative lumbar disease (Degenerative disc disease, Spinal stenosis, Spinal instability, Spondylolisthesis, Spondylolysis), the type of surgical procedure (with fixation (unilateral, bilateral), without fixation, with and without interbody fusion), the number of surgical levels, and sacrum fixation were recorded by the researcher.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Postoperative\u003c/h2\u003e \u003cp\u003ePostoperative psychological disorders, quality of life, and sleep quality of the patients were assessed using validated questionnaires. The psychological disorders questionnaire (SCL-25) by Najarian and Davoudi (2001) contains 25 questions that measure anxiety, depression, phobic anxiety, paranoid ideation, psychosis, obsessive-compulsive disorder, and somatic complaints. The minimum and maximum scores in this questionnaire range from 25 to 125. Scores between 25\u0026ndash;50 indicate low psychological disorders, 50\u0026ndash;75 indicate moderate psychological disorders, and scores above 75 indicate high psychological disorders (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePatients' quality of life was assessed using the Short Form Health Survey (SF-36). This questionnaire evaluates eight health domains (physical function, role function-physical, bodily pain, general health, vitality, social function, role function-emotional, mental health) in two dimensions: physical and mental health. The minimum and maximum scores range from 0 to 100, indicating the lowest and highest quality of life, respectively (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Pittsburgh Sleep Quality Index (PSQI) contains 19 items that assess sleep quality across seven scales (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency) sleep disturbances, use of sleeping medication, daytime dysfunction). The total score of these seven scales forms a global score ranging from 0 to 21. A global score of 6 or higher indicates poor sleep quality (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter 12 months of follow-up, the patients were divided into two groups. The first group (non-FBSS) consisted of patients who were satisfied with their surgery and completely recovered. The second group (FBSS) included patients who fell into the Failed Back Surgery Syndrome category. Similar studies have provided various definitions of FBSS patients, as outlined below. In FBSS patients, despite successful spinal surgery, chronic radicular pain in the same area recurred or persisted (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The outcome of lumbar spinal surgery did not meet the preoperative expectations of the patient and the surgeon (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Patients with chronic neuropathic pain for three months, with a score higher than five on the Visual Analog Scale (VAS) in the lumbar area, with or without radiation to the limbs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Patients experienced chronic back or leg pain after successful lumbar surgery without specific reasons, such as compressive lesions or infection (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Therefore, for the precise diagnosis of patients, considering the above definitions, a quantitative and systematic definition of FBSS was provided as follows: intractable pain or sensory deficit in the back and/or limbs after surgery that is resistant to conservative treatment (for more than three months), leading to dissatisfaction with the surgical outcome.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS version 16. Initially, the equality of variances and the assumption of normality of the data were assessed using Levene's and the Shapiro-Wilk tests. Continuous data were analyzed using the independent t-test and presented as mean (SD). Categorical data were analyzed using the chi-square test and presented as numbers (%). The Omnibus test was used to assess the explanatory and predictive power of the logistic regression model. A binary logistic regression analysis was conducted to build the FBSS risk prediction model, with FBSS occurrence as the dependent variable. The ROC curve (AUC) was used to assess the diagnostic and classification power of the logistic regression model.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Baseline Characteristics\u003c/h2\u003e \u003cp\u003eA total of 512 patients meeting the criteria were enrolled. Initially, 37 patients were excluded due to hospital transfer, diagnosis of fractures, and malignancy. Subsequently, 475 patients underwent lumbar spine surgery. Another 27 patients were excluded due to undergoing surgery in two stages: pregnancy and lack of follow-up interest.... In the end, 302 patients were in the non-FBSS group, and 146 patients were in the FBSS group, with an incidence rate of 32.5% (Fig.\u0026nbsp;1). In this study, 30 independent variables potentially influencing the occurrence of FBSS were examined. Based on the principle that the required sample size for multivariate analysis should be 5 to 10 times the number of independent variables (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), the size of the sample needed for this study was 150 to 300. Four hundred forty-eight patients were analyzed, exceeding the minimum sample size and meeting the statistical requirements.\u003c/p\u003e \u003cp\u003eDemographic data analysis showed that the mean age in the FBSS group was significantly higher compared to the healthy group (non-FBSS) (65.68 (8.66) vs. 62.62 (9.03), P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Smoking was more prevalent in the FBSS group as a potential risk factor (61.6% vs. 49.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No significant differences were observed between the two groups for other variables (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation of demographic information\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-FBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;302)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(yr)\u003c/b\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.68 ( 8.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.62 (9.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e*, NO(%)\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (52.1%)\u003c/p\u003e \u003cp\u003e70 (47.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151 (50.0%)\u003c/p\u003e \u003cp\u003e151(50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.683\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeight\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(cm)\u003c/b\u003e, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176.74\u0026thinsp;\u0026plusmn;\u0026thinsp;8.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175.02\u0026thinsp;\u0026plusmn;\u0026thinsp;9.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(kg)\u003c/b\u003e, (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88.25\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87.26\u0026thinsp;\u0026plusmn;\u0026thinsp;8.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI(Kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e, (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e*, NO(%)\u003c/p\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (25.3%)\u003c/p\u003e \u003cp\u003e109 (74.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (18.2%)\u003c/p\u003e \u003cp\u003e247 (81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e*, NO(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (61.6%)\u003c/p\u003e \u003cp\u003e56 (38.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 (49.7%)\u003c/p\u003e \u003cp\u003e152 (50.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOpioid\u003c/b\u003e*, NO(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (8.2%)\u003c/p\u003e \u003cp\u003e134 (91.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (9.3%)\u003c/p\u003e \u003cp\u003e274 (90.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e*, NO(%)\u003c/p\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (19.2%)\u003c/p\u003e \u003cp\u003e118 (80.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (17.9%)\u003c/p\u003e \u003cp\u003e248 (82.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e*, NO(%)\u003c/p\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\le\\:\\text{D}\\text{i}\\text{p}\\text{l}\\text{o}\\text{m}\\text{a}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eCallegiate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (66.4%)\u003c/p\u003e \u003cp\u003e49 (33.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221 (73.2%)\u003c/p\u003e \u003cp\u003e81 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMD\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(T-score)\u003c/b\u003e, mean(SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.83 (0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.85 (0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*:Chi-Square, \u0026dagger;:t-test, \u003cb\u003e\u0026Dagger;\u003c/b\u003e: Statistical significant as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. failed back surgery syndrome\u003cb\u003e\u003c/b\u003e (FBSS). BMI: body mass index (BMI), bone mineral density (BMD).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Pre-Surgery Outcome\u003c/h2\u003e \u003cp\u003eAnalysis of pre-surgery factors indicated that repeated surgeries reduced the success rate of the surgery, and the likelihood of FBSS increased with the number of surgeries (54.8% vs. 35.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.04). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the spread of symptoms to the lower limbs may be associated with FBSS. Therefore, patients without leg pain and numbness in the lower limbs had a lower likelihood of developing FBSS (50.7% vs. 19.9%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation of pre-surgery factors and underlying diseases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-FBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;302)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnxiety before surgery\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.23\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.60\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eArthrose\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (25.3%)\u003c/p\u003e \u003cp\u003e109 (74.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (18.5%)\u003c/p\u003e \u003cp\u003e246 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRheumatoid Arthritis\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (24.0%)\u003c/p\u003e \u003cp\u003e(76.0%)111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(17.9%)54\u003c/p\u003e \u003cp\u003e248 (82.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (23.97%)\u003c/p\u003e \u003cp\u003e(76.02%)111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(23.2%)70\u003c/p\u003e \u003cp\u003e231 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (28.1%)\u003c/p\u003e \u003cp\u003e105 (71.9%)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (24.2%)\u003c/p\u003e \u003cp\u003e229 (75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRe-surgery\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003e First time\u003c/p\u003e \u003cp\u003eRecurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (45.2%)\u003c/p\u003e \u003cp\u003e80 (54.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e195 (64.6%)\u003c/p\u003e \u003cp\u003e107 (35.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptom location\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eLow back pain without limb symptoms\u003c/p\u003e \u003cp\u003eUnilateral limb symptom\u003c/p\u003e \u003cp\u003eBilateral limb symptom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (49.3%)\u003c/p\u003e \u003cp\u003e21 (14.4%)\u003c/p\u003e \u003cp\u003e53 (36.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242 (80.1%)\u003c/p\u003e \u003cp\u003e28 (9.3%)\u003c/p\u003e \u003cp\u003e32 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptom duration (Month)\u003c/b\u003e \u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.3 (3.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.8 (3.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClaudication\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (14.4%)\u003c/p\u003e \u003cp\u003e125 (85.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (17.9%)\u003c/p\u003e \u003cp\u003e248 (82.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*:Chi-Square, \u0026dagger;:t-test, \u003cb\u003e\u0026Dagger;\u003c/b\u003e: Statistical significant as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. failed back surgery syndrome (FBSS)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. During Surgery Outcome\u003c/h2\u003e \u003cp\u003eAnalysis of intraoperative factors showed that the incidence of FBSS significantly varied among different surgical techniques. Therefore, the highest incidence of FBSS was observed in patients who underwent fixation with intervertebral fusion (46.6% vs. 13.9%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation of factors during surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-FBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;302)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime of surgery\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120.8 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117.5 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of complication\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eLaminectomy\u003c/p\u003e \u003cp\u003eSpinal stenosis\u003c/p\u003e\u003cp\u003eSpinal instability\u003c/p\u003e\u003cp\u003eSpondylolisthesis\u003c/p\u003e\u003cp\u003eSpondylolysis\u003c/p\u003e\u003cp\u003eMultiple complications\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (10.2%)\u003c/p\u003e \u003cp\u003e19 (13.0%)\u003c/p\u003e \u003cp\u003e25 (17.1%)\u003c/p\u003e \u003cp\u003e23 (15.7%)\u003c/p\u003e \u003cp\u003e36 (24.6%)\u003c/p\u003e \u003cp\u003e28 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (8.10%)\u003c/p\u003e \u003cp\u003e63 (20.9%)\u003c/p\u003e \u003cp\u003e53 (17.5%)\u003c/p\u003e \u003cp\u003e58 (19.2%)\u003c/p\u003e \u003cp\u003e46 (15.2%)\u003c/p\u003e \u003cp\u003e55 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSide Fixation\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eUnilateral\u003c/p\u003e \u003cp\u003eBilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (35.6%)\u003c/p\u003e \u003cp\u003e94 (64.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (39.07%)\u003c/p\u003e \u003cp\u003e184 (60.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevels of surgery*\u003c/b\u003e, No(%)\u003c/p\u003e \u003cp\u003eSingle level\u003c/p\u003e \u003cp\u003eMultilevel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (47.9%)\u003c/p\u003e \u003cp\u003e76 (52.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129 (42.7%)\u003c/p\u003e \u003cp\u003e173 (57.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of Surgery\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eDecompressio\u003c/p\u003e \u003cp\u003eFixation alone\u003c/p\u003e \u003cp\u003eFixation\u0026thinsp;+\u0026thinsp;PLIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (17.1%)\u003c/p\u003e \u003cp\u003e53 (36.3%)\u003c/p\u003e \u003cp\u003e68 (46.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164 (54.3%)\u003c/p\u003e \u003cp\u003e96 (31.8%)\u003c/p\u003e \u003cp\u003e42 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSacrum fixation\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (24.7%)\u003c/p\u003e \u003cp\u003e110 (75.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (31.5%)\u003c/p\u003e \u003cp\u003e207 (68.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*:Chi-Square, \u0026dagger;:t-test, \u003cb\u003e\u0026Dagger;\u003c/b\u003e: Statistical significant as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. failed back surgery syndrome (FBSS)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Post-Surgery Outcome\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, individuals with poor mental health post-surgery are at a higher risk of developing FBSS (70.03(12.6) vs. 40.8(12.1), P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, data from this study indicate that the highest incidence of FBSS is found in individuals with poor quality of life (31.03(11.1) vs. 64.3 (16.4), P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No significant differences were observed between the two groups in terms of rest time post-surgery, physiotherapy, and sleep quality (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation of factors post-surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;146)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-FBSS\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;302)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRest time(day)\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.8 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.6 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRehabilitation\u003c/b\u003e*, No(%)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (33.6%)\u003c/p\u003e \u003cp\u003e97 (66.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (29.8%)\u003c/p\u003e \u003cp\u003e212 (70.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMental health\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70.03 (12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.5 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality of Life\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.03 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.3 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSleep quality\u003c/b\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.87 (1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.69 (2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*:Chi-Square, \u0026dagger;:t-test, \u003cb\u003e\u0026Dagger;\u003c/b\u003e: Statistical significant as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. failed back surgery syndrome (FBSS)\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e was used to explain the strength and efficiency of the logistic regression model in distinguishing and classifying individuals with FBSS and non-FBSS. Overall, the classification accuracy of individuals by the fitted logistic regression model was 78.8% (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification Table\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePredicted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePercentage Correct\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-FBSS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFBSS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eObserved\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-FBSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eOverall Percentage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e78.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003efailed back surgery syndrome (FBSS)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the coding of qualitative variables has been carried out. For each variable, one group was designated as the reference category to compare the odds of developing FBSS in other groups relative to the reference category (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, based on the odds ratio (OR), the selected surgical technique is the strongest factor in the occurrence of FBSS. Therefore, the likelihood of developing FBSS in individuals who underwent Fixation\u0026thinsp;+\u0026thinsp;PLIF surgery is 10.52 times greater than those who underwent decompression surgery. Additionally, patients who underwent Fixation\u0026thinsp;+\u0026thinsp;PLIF surgery are 2.83 times more likely to develop FBSS compared to those who underwent Fixation surgery. In our regression model, the second most influential factor in the occurrence of FBSS was radicular pain in the lower limbs. The likelihood of developing FBSS in individuals who had radicular pain in both lower limbs before surgery is 7.24 times higher than in those who only suffered from back pain. The likelihood of developing FBSS in individuals whose back pain radiated to both legs before surgery is 2.92 times higher than in those whose back pain radiated to only one leg. Smoking was identified as the third most influential factor in the occurrence of FBSS, with smokers having a 2.55 times higher likelihood of developing FBSS compared to non-smokers.\u003c/p\u003e \u003cp\u003eBased on the odds ratio (OR), the likelihood of developing FBSS in revision surgery is 2.50 times higher than in those undergoing surgery for the first time. The odds ratio for the variables of age and psychological disorders is reported to be 1.046 and 1.031, respectively. Thus, an increase in age and a higher score of psychological disorders significantly increase the likelihood of developing FBSS. The odds ratio for the quality of life variable is 0.967, indicating that an increase in the quality of life score significantly reduces the likelihood of developing FBSS (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCategorical Variables Codings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eParameter coding\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eType surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecompration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFixation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFixation\u0026thinsp;+\u0026thinsp;PLIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSymptom location\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBack-pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUni-limb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBi-limb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eRe-surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFirst time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic prediction model of FBSS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e95% Confidence Interval for OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType surgery (1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType surgery (2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptom location\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptom location (1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptom location (2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking (1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRe-surgery (1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychopathy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality life\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCoefficient value (Beta), Standard error (S.E), Chi-square value (Wald), Degrees of freedom (Df), Odds ratio (OR). \u003cb\u003e\u0026Dagger;\u003c/b\u003e: Statistical significant as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eFinally, the logistic regression model was obtained as follows:\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1727960395.png\"\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eThis model calculates the probability that an individual will develop FBSS.\u003c/p\u003e \u003cp\u003eAccording to the results in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the AUC (Area Under the ROC Curve) index is reported to be 0.852, indicating that the proposed logistic regression model has a high performance in correctly identifying and classifying individuals with FBSS and non-FBSS. The sensitivity of the prediction model is 58.9%, and the specificity is 88.4% (Table. 8) (F.I.G.2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eArea Under the ROC Curve\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePredicted probability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eArea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e95% Confidence Interval for Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.852\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eF.I.G. 2.\u003c/b\u003e The area under the rock curve shows the performance of the logistic regression model in identifying and classifying people with FBSS or Non-FBSS. The x-axis is the sensitivity, which represents the possibility of predicting positive samples but actually negative samples. The y axis is 1-specific, which represents the possibility of predicting positive samples but actually positive samples. The blue real line is the ROC curve of the model, and the red line represents the ROC curve of random gues.\u003c/p\u003e \u003cp\u003e \u003cb\u003eApplication example of risk prediction model\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCase Study\u003c/strong\u003e \u003cp\u003eConsider a non-smoking, 57-year-old married female patient with a BMI of 30.2 kg/m\u0026sup2;. Six years ago, she underwent fixation surgery at the L3-L4 lumbar spine level. She presented with severe back pain and radicular pain in both lower limbs. Magnetic resonance imaging showed ASD at the L2-L3 vertebrae level. Additionally, flexion and extension radiographs revealed grade 3 spondylolisthesis at the L5-S1 vertebrae level. Thus, she underwent fixation surgery from the L2 to S1 vertebrae levels. Her surgery lasted 3 hours and 45 minutes. Her quality of life and psychological disorder scores were 33 and 73, respectively. Now, we input these values into the logistic regression model.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1727960473.png\"\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eThe predicted probability that this patient will develop FBSS is approximately 0.85 or 85%. Since this probability is more significant than 0.5, according to the logistic regression model, this case is classified as an individual with FBSS.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study aimed to analyze the risk factors and develop a risk prediction model for Failed Back Surgery Syndrome (FBSS). A risk prediction model was adopted in this study, which predicts the logistic regression outcomes based on clinical and medical data. This model integrates and compares various determining factors to predict the likelihood of an individual developing this condition. Data analysis revealed that the selected surgical technique is the strongest factor influencing the occurrence of FBSS. Therefore, the highest incidence of FBSS was observed first in the Fixation\u0026thinsp;+\u0026thinsp;PLIF group and then in the Fixation group. Recent reports indicate that pedicle screw fixation techniques, bilateral muscle dissection, removal of posterior elements, and loss of bony structure lead to spinal instability and pain of unknown origin (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Souslian \u0026amp; Patel (2024) stated that after PLIF surgery, the potential for load distribution among spinal structures increases, resulting in axial pain (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Cicek et al. (2017) reported similar findings (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In patients undergoing PLIF\u0026thinsp;+\u0026thinsp;Fixation surgery, the entire bilateral facet joints are removed, the disc is completely evacuated, and a relatively small intervertebral cage acts as a focal pivot point. Thus, despite pedicle screw fixation, the structure may inherently be unstable (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Contrary to the above results, some studies have shown no significant difference between spinal fixation techniques with and without intervertebral fusion (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The discrepancy in results may be due to variations in postoperative follow-up duration, levels of spinal fixation, and different surgical techniques.\u003c/p\u003e \u003cp\u003eData analysis showed that radicular pain in the lower limbs before surgery is the second most influential factor in FBSS. Supporting these findings, Wenbo et al. (2022) believe that preoperative radicular pain in the lower limbs is a significant factor in FBSS development and should be investigated as a marker for identifying at-risk populations (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Evandro et al. (2020) reported similar results (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Contrary to these findings, some reports suggest that surgical outcomes are not significantly related to the type and severity of preoperative pain (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The discrepancy in results may be influenced by the duration of symptoms before surgery and the patient inclusion criteria. The optimal timing for decompression surgery remains unclear. Historically, early surgical intervention for symptomatic spinal stenosis has been recommended based on the view that the condition is always progressive. Unlike peripheral nerves, nerve roots lack a blood-nerve barrier, and prolonged compressive lesions lead to intraneural edema. Over time, this edema causes nerve fibrosis, a process that is irreversible even with surgical intervention (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Additionally, research has shown that long-term symptomatic radiculopathy is affected by multiple damaging factors and is more complex than simple neural dysfunction caused by physical pressure (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData analysis indicates that smoking is one of the significant risk factors for the development of FBSS. In this context, a study by Mekhail et al. (2020) with a one-year follow-up showed that the incidence of FBSS was significantly higher in current smokers compared to non-smokers or those who had quit smoking (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Robson et al. (2019) reported similar findings (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). A meta-analysis study found that individuals who quit smoking three months before surgery were less likely to develop FBSS compared to smokers (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Contrary to these results, some studies did not find a significant difference in the incidence of FBSS between smokers and non-smokers (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The discrepancy in results may be due to the type of intervention, the extent of iatrogenic tissue damage, and the sample size of the studies. In general, nicotine destroys vascular endothelium, playing a crucial role in vasoconstriction, blood flow disruption, synthesis and secretion of biologically active factors, neovascularization, and immune responses. After spinal surgery, the circulatory system plays a key role in tissue healing and postoperative recovery. Therefore, when the vascular endothelium is damaged, the post-surgical healing process is disrupted and inefficient in smokers. The more extensive the iatrogenic soft tissue damage during surgery, the more significantly postoperative complications increase. These findings are supported by several studies reporting increased inflammatory markers in smokers (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFindings from the study indicate that revision surgery is a potential risk factor for developing FBSS. Therefore, patients with previous lumbar surgery were at higher risk. Researchers believe that the number of previous spinal surgeries is a significant predictor of surgical outcomes (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Montenegro et al. (2021) found that the average functional status score of 46% of patients significantly decreased six months after revision surgery (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Moaven et al. (2020) stated in their study that revision surgery is much more complicated than primary surgery due to unclear anatomical levels and scars around the nerves, requiring a high skill level (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In revision surgeries, the absence of spinous processes, bony structures, and fibrous tissue growth in the surgical area leads to significant anatomical changes. Adhesions in the surgical area increase the risk of nerve element damage and dural tears. Therefore, there is concern that the success rate of the second surgery is lower than that of the first surgery. Researchers have noted that the incidence of FBSS increases from 8% in primary surgeries to 48% in revision surgeries. However, the degree of difference may vary depending on surgical techniques and the type of condition (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData analysis showed that age is one of the risk factors for patients undergoing spinal surgery. Early studies have identified age as an important underlying factor in the occurrence of FBSS and believe that it needs special consideration when selecting treatment options (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Wenbo et al. (2022) argue that older patients have a significant increase in postoperative complications and often require revision surgery (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Other studies in this field have reported similar findings (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Changes in pain perception with aging affect the pain experience in various ways, some of which are still unknown. The assumptions are based on the anatomical changes in older individuals, such as spinal canal and foramina narrowing, increased pressure on neural elements, and microcirculation disruption, which exponentially decrease the success rate after surgery. Researchers have found that the loss of lumbar lordosis, increased thoracic kyphosis, and stiffening of the ligamentum flavum are common changes that contribute to spinal degeneration and are frequent sources of back pain after surgery in older individuals (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData from the study indicate that specific psychological factors, including significant levels of depression, anxiety, phobic anxiety, paranoid ideation, psychosis, obsessive-compulsive disorder, and somatic complaints, lead to an increased incidence of FBSS. Recent reports suggest that these psychological factors affect individual changes in pain sensitivity, thereby influencing pain perception (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The study by Sebaaly et al. (2018) showed a bidirectional relationship between pain and depression (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Elsamadicy et al. (2018) believe that mental health is a much stronger predictor of disability from back pain than structural abnormalities (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A recent study identified depression as a risk factor for postoperative pain in specific areas, including the head, neck/shoulder, and back (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Contrary to these findings, other studies showed no significant difference between psychological disorders and postoperative pain with a one-year follow-up (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). The discrepancy in results may be due to the type of tools used to measure mental health and the duration of follow-up after surgery. In short-term follow-up, it may be difficult to differentiate between nonspecific pain sources (skin incision, iatrogenic tissue damage, reactive spasms, and nerve root inflammation) and pain originating from the central nervous system. In this context, the results of a study by Graham et al. with a five-year follow-up reported similar findings, illustrating this issue well (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe existing literature indicates that psychological disorders can result from stressors and disrupt behavioral patterns. In other words, individuals who experience pain due to their spinal condition avoid normal work and recreational activities, significantly reducing their quality of life (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). As noted in the present study, poor quality of life predicts FBSS occurrence. Inoue et al. (2017) found that increased FBSS incidence is associated with low quality of life and high levels of functional disability (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Therefore, psychological disorders can directly or indirectly increase the prevalence of FBSS. However, it is important to note that awareness of these factors should not prevent patients from undergoing spinal surgery when significant pathology and surgical indications are present. Instead, these risk factors necessitate careful consideration and optimization of surgical timing. Patients with higher surgical risk in spinal surgery may achieve better outcomes with prompt intervention. This is because prolonged pain and discomfort in this population can exacerbate existing psychosocial stressors and reduce the success rate of surgery.\u003c/p\u003e \u003cp\u003eIt is logical that \"the most effective treatment for FBSS is to avoid or prevent FBSS itself,\" as aging and the exacerbation of psychological, physical, and mechanical effects experienced by patients transform it into a multifactorial, complex, and painful syndrome. The detrimental effects of FBSS are well known, and current strategies and treatment methods are only available after the onset of the disease. Furthermore, most patients with FBSS experience varying degrees of disability, which brings significant anxiety and economic burden to them and their families. Therefore, early screening for this condition is of particular importance. The prediction model presented in the current study demonstrated good performance and is easy to apply in clinical practice, providing the necessary individual diagnostic and treatment requirements. This model may be useful for preventing and treating FBSS and identifying at-risk populations in clinical practice.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThere are several limitations to this study. First, a relatively short follow-up period may obscure changes in outcome indicators resulting from other degenerations. Additionally, the patient's risk factors examined in this study were self-reported, which introduces potential recall bias and subjective interpretations. Future research should examine a broader set of clinical variables to enhance the comprehensiveness and completeness of the information obtained by the prediction model. Moreover, using a multicenter approach for sample collection would increase the model's validity and generalizability.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eBased on the results of multivariate logistic regression analysis, this study demonstrated that the selected surgical technique, preoperative pain symptoms, smoking, revision surgery, age, mental health, and quality of life are risk factors for FBSS. Increased awareness in this area can serve as a tool for physicians to identify at-risk populations and provide more effective management to reduce discrepancies between patient and physician expectations. Relying on these factors, an initial FBSS risk prediction model was developed. Additionally, the ROC curve indicated that the logistic regression model performs well in accurately identifying and classifying individuals.\u003c/p\u003e "},{"header":"Declarations","content":" \u003ch2\u003eConsent to participate\u003c/h2\u003e \u003cp\u003eAll patients provided written informed consent to participate in the study, publication of radiological images and for their data to be published. The principles of the Helsinki Declaration were adhered to in this study.\u003c/p\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors have no potential or real conflict of interests\u003c/p\u003e \u003ch2\u003eCRediT authorship contribution statement\u003c/h2\u003e \u003cp\u003eBI: conceptualization, investigation, Writing-review \u0026amp; esiting,. AM: validation, funding acquisition, resources, methodology. SZ: data curation, investiration, Writing-original draft. PH: project administration, visualization. SK: software, formal analysis, validation.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe study was funded by Vice-chancellor for Research and Technology, Hamadan University of Medical Sciences (140208237083).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eBI: conceptualization, investigation, Writing-review \u0026amp; esiting,. AM: validation, funding acquisition, resources, methodology. SZ: data curation, investiration, Writing-original draft. PH: project administration, visualization. SK: software, formal analysis, validation.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis study has been adapted from an MSc thesis project at Hamadan University of Medical Sciences.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData associated with the study has not been deposited into a publicly available repository. Data are available from the corresponding author on reasonable request.\u003c/p\u003e\u003ch2\u003eEthics approval\u003c/h2\u003e This study was reviewed and approved by Ethics Committee of Hamedan University of Medical Sciences with the approval number: IR.UMSHA.REC.1402.553.\u003c/p\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHo, C-N., Liao, J-C. \u0026amp; Chen, W-J. Instrumented Posterolateral fusion versus instrumented Interbody fusion for degenerative lumbar diseases in uremic patients under hemodialysis. \u003cem\u003eBMC Musculoskelet. 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Surg.\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e, 1264519. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fsurg.2023.1264519\u003c/span\u003e\u003cspan address=\"10.3389/fsurg.2023.1264519\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Risk factors, Prediction model, Surgery, Back, Syndrome, Failed","lastPublishedDoi":"10.21203/rs.3.rs-4960039/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4960039/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eWith 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.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eBaseline 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 ROC curve.\u003c/p\u003e\u003ch2\u003eFindings:\u003c/h2\u003e \u003cp\u003eAge, 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.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe 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.\u003c/p\u003e","manuscriptTitle":"Risk factors analysis and risk prediction model for failed back surgery syndrome: a prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-18 10:00:36","doi":"10.21203/rs.3.rs-4960039/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0865355f-972f-4b0e-91fc-8df592ce95a1","owner":[],"postedDate":"October 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38445301,"name":"Health sciences/Anatomy"},{"id":38445302,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2024-10-22T08:39:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-18 10:00:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4960039","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4960039","identity":"rs-4960039","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}