Preventing adjacent segment disease after lumbar fusion: a new perspective emphasizing individualized factors

Introduction

With the aging population and increase in sedentary lifestyle, the incidence of lumbar degenerative diseases has risen significantly, becoming a common cause of back pain, and thereby reducing quality of life among adult populations (1-3). In severe cases, nerve compression may occur, leading to disability. Posterior lumbar interbody fusion (PLIF) is a classic surgical method for treating degenerative lumbar spine diseases and is suitable for conditions such as lumbar disc herniation, lumbar spondylolisthesis, and lumbar spinal stenosis (4). It effectively relieves nerve compression symptoms and restores spinal stability (5,6). However, degenerative changes may develop in adjacent segments after PLIF surgery, which is known as adjacent segment disease (ASD), with an incidence ranging from 5% to 27% (7-9). This risk increases with longer follow-up periods, making it a significant challenge to the long-term success of PLIF (10,11). ASD not only manifests as degenerative lesions in adjacent segments but may be accompanied by the recurrence of clinical symptoms, including chronic low back pain and neurological dysfunction. The occurrence of ASD affects patients’ quality of life and may also necessitate reoperation, increasing the medical burden (12).

Currently, the research on the etiology of ASD after PLIF has primarily focused on changes in spinal biomechanics, such as the impact of interbody cage height, sagittal imbalance characterized by increased pelvic incidence (PI) and lumbar lordosis (LL) mismatch, and the increased rigidity of the fused segment, leading to greater stress on adjacent segments and accelerating their degeneration (13-15). Additionally, individual factors such as patient osteoporosis have been widely studied. Osteoporosis is a common systemic bone metabolic disease in middle-aged and older adult patients, and studies have confirmed its close association with spinal degeneration and a heightened risk of fractures (16,17). However, the specific role of osteoporosis in the occurrence of ASD after PLIF remains unclear. In recent years, the role of inflammatory responses in lumbar degenerative diseases has garnered heightened attention (18). Research has shown that systemic inflammatory indicators such as the neutrophil-to-lymphocyte ratio (NLR) and the systemic immune-inflammation index (SII) are related to the degree of lumbar degeneration (19). Inflammatory mediators can promote intervertebral disc degeneration, leading to structural and functional changes. However, few studies have examined the relationship between NLR, SII, and the risk of ASD. Moreover, the degeneration of paraspinal muscles—including atrophy and fatty infiltration of the psoas major and multifidus muscles—may affect spinal stability and function. Muscle degeneration may lead to increased load on adjacent segments, promoting degeneration, and could play a key role in the occurrence of ASD (20,21).

The relationship between paraspinal muscle status and ASD is unclear, and systematic and comprehensive methods for evaluating and determining the risk factors for ASD occurrence are lacking. Therefore, this study aimed to comprehensively analyze the risk factors for ASD after PLIF surgery, including systemic inflammatory indicators, lumbar muscle degeneration, cage subsidence, and sagittal balance. Through a retrospective analysis of 500 patients, we sought to reveal the associations of these factors with ASD and thereby generate a basis for clinical prevention and treatment. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1462/rc).

Methods

Management of the sample

A retrospective analysis was conducted on 500 patients with degenerative lumbar disc diseases who were treated at Affiliated Nantong Hospital 3 of Nantong University from January 2017 to August 2022. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Affiliated Nantong Hospital 3 of Nantong University (No. EK2023168). The requirement for individual consent for this retrospective analysis was waived. Based on postoperative imaging during follow-up, the patients were classified into two groups: the non-ASD (NASD) group and the ASD group. We defined ASD as a reduction in the height of the intervertebral disc adjacent to the operated segment by ≥30% or lumbar vertebral slippage by ≥3 mm during the follow-up period, accompanied by new-onset lower back or leg pain with functional impairment (22).

The study focused on patients with lumbar intervertebral disc degenerative diseases. The inclusion criteria were as follows: (I) a diagnosis with lumbar degenerative diseases, including lumbar disc herniation, lumbar spondylolisthesis, or lumbar spinal stenosis; (II) imaging confirmation of disc herniation and/or spinal canal stenosis, with clinical symptoms and signs consistent with the imaging findings; (III) symptoms unrelieved by strict conservative treatment, requiring PLIF surgery; (IV) availability of complete preoperative and postoperative imaging data; and (V) a follow-up period exceeding 2 years. To validate sample size appropriateness, we systematically reviewed 20 retrospective studies on ASD after PLIF published between 2018 and 2024 (journals including Spine and European Spine Journal, impact factor >3.0). The median sample size of these studies was 392 (range, 156–1,080), with 65% of cohorts having <500 patients and 15% having >600 patients; the median ASD case count was 88 (range, 36–201). Our 500-patient cohort fell in the upper 35% of the sample size distribution, and our 96 ASD cases were consistent with the median case count. Thus, our sample size is comparable to “large-sample” studies in the ASD research field, supporting result generalizability (23-25). To confirm that the sample size met the requirements for multivariable logistic regression (primary analysis method), we performed post-hoc power validation using G*Power 3.1 software (26). We adopted the “10 events per variable (EPV)” rule to prevent overfitting. Through univariate analysis (P<0.05), 8 variables were included in the final multivariable model: NLR, Hounsfield units (HU), surgical segment, psoas muscle index (PMI), multifidus muscle index (MMI), multifidus muscle fat infiltration ratio (MFI), cage subsidence, and nonunion. Per the EPV rule, a minimum of 80 ASD events was required (8 variables × 10 EPV). Validation parameters: α=0.05 (type I error rate), effect size [odds ratio (OR) =2.1, based on preliminary univariate results for cage subsidence], total sample size =500, ASD events =96. The calculated statistical power was 0.87, exceeding the conventional 0.8 threshold confirming adequate power to detect meaningful associations between variables and ASD.

Surgical technique

All patients were administered general anesthesia and positioned prone on a fluoroscopic X-ray table. After locating the target segment with a C-arm fluoroscope, a posterior approach was used to expose the facet joints, and bilateral pedicle screws were inserted. Following decompression of the vertebral lamina, the intervertebral disc was removed, the cartilaginous endplates scraped off, and the bony endplates preserved. A 4–6 cm³ bone graft was prepared. The majority of cases used a polyetheretherketone (PEEK) interbody fusion cage, primarily the CAPSTONE^® cage (Medtronic, Minneapolis, MN, USA) and PEEK cages from Sanyou Medical (Shanghai, China), both with a lordotic design. The cages were filled with autologous bone graft before implantation. After securing the internal fixation system, the surgical site was irrigated, negative pressure drainage tubes were placed, and the wound was closed in layers.

Observation indicators

Assessment of clinical outcome measures

The visual analog scale (VAS) was used to assess the patients’ subjective pain perception at baseline, 1 month postoperatively, 6 months postoperatively, and at the final follow-up (27). Additionally, the Oswestry Disability Index (ODI) was employed to evaluate improvements in quality of life at the same time points described above.

Assessment of laboratory indicators

The NLR is a commonly used clinical marker of inflammation, and the SII (SII = platelet count × NLR) was another indicator used to detect inflammation. Blood tests were performed on patients both during hospitalization for surgery and at postoperative follow-up. By recording the platelet count, neutrophil count, and lymphocyte count from the patients’ final follow-up test results, and NLR and SII levels were calculated.

Imaging outcome measure assessment

All patients underwent anteroposterior and lateral X-ray imaging, computed tomography (CT), and magnetic resonance imaging (MRI) preoperatively, as well as follow-up imaging at 1 month, 6 months, and at the final postoperative visit. The imaging records were reviewed by three experienced spine surgeons, who assessed the images using a blinded method. The interrater reliability of the three independent radiological assessments was confirmed, with differences in measurements for each patient being less than 5%. This suggests that the results were accurate, stable, and reliable. For analysis, the average value of each imaging parameter was used. The following radiological variables were measured: PMI, MMI, MFI, position of the fusion device, fusion device subsidence, sagittal balance, and nonunion. Nonunion was assessed using thin-slice (1 mm) CT scans obtained at the final follow-up. The criteria for nonunion were as follows: (I) absence of bridging trabecular bone across the interbody space; (II) presence of a persistent radiolucent line around the implant. Plain lateral radiographs (including flexion-extension views) were routinely obtained during follow-up for general assessment, but the final diagnosis of nonunion was determined exclusively on CT to ensure accuracy and objectivity (28).

Sagittal T2-weighted MRI was used to assess intervertebral disc degeneration. At the L3 level, the PMI, MMI, and MFI were measured using the MR T2-weighted sequence images (29-31). The PMI and MMI were calculated by dividing the cross-sectional area of each muscle by the square of the patient’s height, with the unit expressed in square centimeters per square meter (cm²/m²). Medical image processing software (ImageJ, US National Institutes of Health, Bethesda, MD, USA) was used to delineate the region of interest (ROI) within the multifidus muscle area. A threshold was applied in the software to differentiate muscle from fat within the ROI, allowing for the quantification of the fat infiltration degree in the multifidus muscle (Figure 1). The position of the fusion device was determined by the metal markers within the device, which define its anterior and posterior boundaries. The position of the fusion device was categorized as anterior or posterior based on the location of the device’s center of mass relative to the vertebral endplate beneath it on the lateral X-ray. The vertebral body was divided into thirds along the sagittal plane. A cage positioned in the anterior third was classified as anterior, and one in the posterior third was classified as posterior. Intervertebral height (IH) loss was defined as the difference between the IH at the final follow-up and the IH at 1 month postoperatively. An IH loss of ≥2 mm at the final follow-up was considered indicative of fusion device subsidence. Finally, PI and LL were measured from the final follow-up lateral X-ray, and the sagittal balance was defined as PI-LL <10°.

Figure 1 Schematic diagram measuring the PMI, MMI, and MFI at the L3 level on T2WI. We measured the areas of the psoas major and multifidus muscles at the upper edge of the fourth lumbar vertebra in a patient. The psoas major area was 14.81 cm², and the multifidus area was 6.21 cm². The patient’s PMI was calculated to be 5.79, and the MMI was 2.43. Using medical imaging software (Image J), we defined an ROI in the multifidus muscle area and adjusted the threshold to differentiate the muscle from fat. The results showed that the density of the multifidus muscle in this patient was 80.88%, and the MFI was approximately 19.12%. MFI, muscle fat infiltration rate; MMI, multifidus muscle index; PMI, psoas muscle index; ROI, region of interest; T2WI, T2-weighted imaging.

Preoperative bone mineral density (BMD) was assessed using HU. Axial CT slices at the mid-vertebral level of L1–L4 were used. A circular ROI was placed within the trabecular bone, avoiding the cortical margins and basivertebral vein, and the mean HU value was recorded.

Statistical analysis

Selection bias was mitigated by applying strict, predefined inclusion and exclusion criteria to all patients treated within the specified time frame. Specifically, to avoid selection bias arising from non-random patient enrollment, we consecutively included all patients who met the eligibility criteria during the study period (January 2017–August 2022) without any subjective exclusion (e.g., excluding patients based on unrecorded or incomplete clinical characteristics that were not part of the predefined exclusion criteria). This consecutive enrollment approach ensured that the study cohort represented a real-world population of patients undergoing PLIF for degenerative lumbar spine diseases, reducing the risk of selection bias associated with selective patient recruitment.

Measurement bias was addressed by having three experienced spinal surgeons (with specialized training and clinical experience in spinal imaging assessment) who were blinded to patient outcomes (i.e., unaware of whether the patient belonged to the ASD or non-ASD group) independently perform all radiographic measurements. Before formal data collection, the three surgeons underwent a standardized training session focused on unifying the measurement protocols for key radiological indicators, including PMI, MMI, MFI, cage subsidence, and nonunion. This training ensured consistent interpretation of imaging findings and measurement techniques across all assessors. Discrepancies in measurements between surgeons were resolved through group discussion to reach a consensus, minimizing measurement bias caused by inter- or intra-observer variability.

To handle potential confounders, we first conducted a comprehensive review of existing literature to identify variables that have been previously reported to be associated with the development of ASD after PLIF (e.g., age, BMD, systemic inflammatory indicators, paraspinal muscle status, and surgical factors). These variables were considered as potential confounders in the initial analysis. Next, we performed univariate analysis to screen for variables with potential associations with ASD: continuous variables (e.g., NLR, HU, PMI, MMI, MFI) were assessed using the independent samples t-test, while categorical variables (e.g., surgical segment, cage subsidence, nonunion) were analyzed with the chi-square test or Fisher’s exact test. Variables that demonstrated statistical significance (P<0.05) in the univariate analysis were included in the multivariable logistic regression model to adjust for mutual confounding effects between variables.

The data were analyzed using the software SPSS 27.0 (IBM Corp., Armonk, NY, USA). Univariate analysis was conducted to examine the correlation between various variables and the occurrence of ASD following PLIF surgery. Continuous variables were assessed using the independent samples t-test, whereas categorical variables were analyzed with the chi-square test or Fisher’s exact test. A P value of less than 0.05 was considered statistically significant. Variables that demonstrated statistical significance in the univariate analysis were subsequently included in a multivariable logistic regression model to identify the independent risk factors for the development of ASD after PLIF surgery.

Results

Patient characteristics

Based on the aforementioned inclusion and exclusion criteria, a total of 500 patients with lumbar degenerative diseases who underwent PLIF surgery were included in this study. The mean age of the cohort was 65.8±9.0 years, with females comprising 67.8% of the patients. The incidence of postoperative ASD was 19.2%. The average follow-up time for the patients was approximately 36 months. The NASD group consisted of 404 patients, whereas the ASD group included 96 patients, of whom 71 required readmission for treatment due to ASD. The baseline characteristics of the two groups are summarized in Table 1. An example of ASD occurring after PLIF surgery in a patient with lumbar degenerative changes is shown in Figure 2.

Figure 2 Radiological findings of an elderly male patient with adjacent segment disease after PLIF surgery. Preoperative lumbar CT and MRI confirmed L4–S1 spondylolisthesis accompanied by disc herniation, as well as mild disc protrusions at L2–3 and L3–4. Postoperative CT and MRI at 18 months revealed progression of disc protrusions at L2–3 and L3–4 (A,C). Preoperative lumbar flexion-extension X-rays showed L4–S1 spondylolisthesis (B). CT, computed tomography; MRI, magnetic resonance imaging; PLIF, posterior lumbar interbody fusion.

The comparison of functional outcomes between the two groups is detailed in Table 2. No significant differences were observed in preoperative VAS and ODI scores between the NASD group and the ASD group. Follow-up data revealed statistically significant improvements in VAS and ODI scores at 1 month, 6 months, and final follow-up postoperatively in both groups (P<0.05). Importantly, patients without ASD demonstrated better outcomes in terms of pain relief and functional recovery after surgery.

Data visualization

To better demonstrate the relationship between clinical variables and the duration of postoperative pain, we used bar charts, box plots, and correlation matrices for visual analysis. The bar chart highlights the differences in qualitative data between patients in the NASD and ASD groups (Figure 3). Patients in the NASD group had a more anterior placement of the fusion cage and better sagittal balance. Conversely, patients in the ASD group exhibited higher rates of nonunion and cage subsidence. Additionally, violin plots clearly illustrated the differences in quantitative data between the two groups (Figure 4). Paraspinal muscle-related indicators (PMI, MMI, and MFI) and bone density measurements (HU values) in the NASD group were significantly higher than those in the ASD group. However, inflammation-related indicators in the ASD group were markedly higher than those in the NASD group.

Figure 3 Bar chart comparison of qualitative data between the groups (no = 0 and yes = 1). ASD, adjacent segment disease.

Figure 4 Violin plots showing the distribution of continuous variables (age, BMI, albumin, NLR, SII, HU, PMI, MMI, MFI) between the non-ASD and ASD groups (no = 0 and yes = 1). BMI, body mass index; HU, Hounsfield unit; MFI, muscle fat infiltration rate; MMI, multifidus muscle index; NLR, neutrophil-to-lymphocyte ratio; PMI, psoas muscle index; SII, systemic immune-inflammation index.

In the examination of the multidimensional factors associated with ASD following PLIF surgery, the correlation matrix served as a powerful tool for quantifying the relationships between various clinical variables and ASD (Figure 5). Cage subsidence showed the positive correlation with the occurrence of postoperative ASD, with a correlation coefficient of 0.23. Additionally, inflammatory markers (NLR), paraspinal muscle levels (PMI, MMI, and MFI), and postoperative muscle rehabilitation were also strongly correlated with the occurrence of ASD after PLIF surgery.

Figure 5 Correlation matrix between each variable and the outcome. ASD, adjacent segment disease; BMI, body mass index; HU, Hounsfield unit; MFI, muscle fat infiltration rate; MMI, multifidus muscle index; NLR, neutrophil-to-lymphocyte ratio; PMI, psoas muscle index; SII, systemic immune-inflammation index.

Univariable and multivariable analysis

The occurrence of ASD after surgery was used as the dependent variable (no =0 and yes =1). Statistically significant factors identified in the univariate analysis—including NLR, HU value, surgical segment, PMI, MMI, MFI, cage subsidence, and nonunion—were included as independent variables to construct a binary logistic regression model. The Hosmer-Lemeshow (H-L) test was employed to evaluate the goodness of fit of the model. A P value >0.05 indicated no statistically significant difference, thereby reflecting the satisfactory predictive accuracy of the model. In this study, the H-L test for the risk prediction model indicated good model fit (χ²=13.38, P=0.07). The multivariable analysis indicated that the independent risk factors for the development of ASD after PLIF surgery were NLR [OR: 2.140; 95% confidence interval (CI): 1.504–3.045; P<0.001], HU value (OR: 0.993; 95% CI: 0.985–1.000; P=0.048), PMI (OR: 0.886; 95% CI: 0.798–0.983; P=0.02), MMI (OR: 0.577; 95% CI: 0.371–0.897; P=0.01), MFI (OR: 1.043, 95% CI: 1.004–1.083; P=0.03), cage subsidence (OR: 3.126; 95% CI: 1.747–5.594; P<0.001), and nonunion (OR: 2.250; 95% CI: 1.206–4.195; P=0.01) (Table 3).

Discussion

This study aimed to identify the independent risk factors for ASD after PLIF and clarify their association with the pathogenesis of ASD, thereby providing a basis for clinical prevention and management. Traditionally, ASD is driven by increased mechanical stress and biomechanical changes in adjacent segments: fused segment immobilization disrupts spinal load distribution, triggering compensatory motion (such as reduced disc height, thickened ligamentum flavum) that accelerates degeneration. Despite prior attempts to reduce ASD via new surgical techniques/biomaterials, long-term outcomes remain poor (7,32-34). Therefore, understanding the complex interplay among various factors leading to ASD is crucial for improving postoperative prognoses.

Recent studies have confirmed that individual factors (age, osteoporosis) are key ASD drivers. Elderly patients are more prone to ASD due to pre-existing spinal degeneration and reduced tissue regeneration. Osteoporosis involves not only lower BMD but also damaged microarchitecture and reduced mechanical strength—factors that impair bone integrity (23,35). Specifically, lower preoperative HU value is an independent predictor of subsequent adjacent segment surgery after fusion: it correlates with weaker trabecular bone, reducing adjacent vertebrae’s load-bearing capacity and causing insufficient load transfer/stress concentration, which accelerates degeneration. Preoperative HU assessment quantifies bone quality, aiding ASD risk stratification and surgical decisions (36,37). Consistent with prior studies, our study found that lower HU values on CT were linked to a higher ASD risk. Additionally, pedicle screw insertion may disrupt bone microenvironment (increased resorption, decreased formation), further promoting ASD.

The iliopsoas and paraspinal muscles play a central role in maintaining spinal stability. MRI analysis indicated that muscle dysfunction, such as fat infiltration of paraspinal muscles, may accelerate degeneration in adjacent segments by affecting spinal dynamic equilibrium (38-40). Additionally, fat-infiltrated muscle tissue may secrete pro-inflammatory cytokines (e.g., tumor necrosis factor-α and interleukin-6) thereby exacerbating these outcomes. The NLR serves as a marker of inflammatory response, reflecting the body’s inflammatory state. Previous studies have indicated that NLR levels correlate with symptom severity in patients with lumbar degenerative disease, potentially accelerating disc degeneration by promoting disc cell apoptosis and matrix degradation (19). Consistent with these findings, our study identified NLR as an independent risk factor for ASD after PLIF (OR: 2.140; 95% CI: 1.504–3.045; P<0.001), highlighting that elevated systemic inflammatory status (as indicated by NLR) may contribute to the pathogenesis of ASD. Therefore, the preoperative assessment of a patient’s inflammatory status and implementation of anti-inflammatory treatments may help to reduce the risk of ASD. We also found that lower PMI and MMI, along with increased MFI, were significantly associated with the occurrence of ASD. This may result from reduced dynamic stability of the lumbar spine due to muscle atrophy and fat infiltration, thereby subjecting adjacent segments to greater mechanical stress (41) (29). These findings emphasize the importance of assessing muscle function preoperatively and postoperatively. Improving the quality and function of lumbar muscles through physical therapy and functional exercises may help prevent ASD (42,43).

Surgical factors directly influence ASD risk: cage subsidence reduces fused segment height, disrupts spinal sagittal alignment, and increases adjacent segment stress, promoting ASD; nonunion (OR: 2.250; P=0.01) causes insufficient fused segment stability, forcing adjacent segments to bear more load and raising ASD risk. Therefore, ensuring solid bone fusion is crucial for preventing ASD. In clinical practice, restoring and maintaining proper sagittal balance is vital for the mechanical environment and function of the spine (44-46). Interestingly, sagittal balance, defined as PI-LL <10° in this study, did not have a significant impact in the development of ASD in our study. PI-LL mismatch was measured during ASD revision surgery, when patients often adopt forward-flexed postures to relieve symptoms. This suggests that PI-LL mismatch in these cases may be a consequence of ASD progression rather than a predisposing factor. Therefore, the relationship between PI-LL mismatch and ASD may be overstated when compared to measurements obtained from routine postoperative radiographs, which more accurately reflect the patient’s true sagittal alignment prior to the development of ASD (43,47).

Limitations and recommendations of the study. First, it is a single-center retrospective study; therefore, the sample may lack representativeness and may not be broadly applicable to patients in other regions or with different backgrounds. Additionally, key information (such as confounding factors and detailed variables) may be missing. Second, the follow-up period in our study may be insufficient, potentially affecting the incidence of ASD and thereby influencing the final research findings. Third, future research will include multicenter prospective designs with 5-year or longer follow-up, integrate patient-reported outcome measures, and explore genetic/biomarker predictors to further refine ASD risk stratification.

Conclusions

This study focuses on exploring the risk factors for ASD after PLIF and providing a basis for clinical prevention and management. It is noted that the etiology of ASD after PLIF is complex and diverse: fusion-induced biomechanical changes (such as increased stress and altered load distribution in adjacent segments) are important factors contributing to ASD; meanwhile, the study identifies key individual patient-related independent risk factors for ASD, including reduced preoperative BMD (assessed by HU). Lower HU values imply impaired skeletal integrity, which may lead to inadequate load transfer and increased stress concentration in neighboring vertebrae, degeneration of paravertebral and psoas major muscles (manifested by decreased muscle index and increased fat infiltration), which can weaken lumbar spine stability and increase mechanical stress on adjacent segments, and elevate systemic inflammatory marker (NLR) indicating systemic inflammation plays a role in ASD pathogenesis. These findings emphasize the necessity of conducting comprehensive preoperative assessment for patients undergoing PLIF to facilitate individualized treatment and the implementation of targeted perioperative interventions. The study offers a novel and comprehensive perspective on ASD prevention, and proposes that in the future, a combination of anti-inflammatory therapy, muscle rehabilitation, and improved surgical techniques should be adopted to comprehensively reduce the risk of ASD after PLIF.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1462/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1462/dss

Funding: The project was funded by Nantong University Special Research Fund for Clinical Medicine (No. 2023JQ016 to J.S. and J.J.), Nantong Health Commission Project (No. MS2023078 to Z.W.) and National Natural Science Foundation of China (No. 82572432 to Y.Q.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1462/coif). D.Y.P. reports that he has royalty bearing agreements with Seaspine and Alphatec, which are distributed quarterly to himself; he serves as a consultant for Stryker, GS Medical, Globus/Nuvasive, of which payments are distributed to himself; he is a member of NASS CME Committee and KASS Board of Directors, and he serves as strategic advisory board member for Amplify Surgical, a privately held company, of which he owns stock options, outside the submitted work. J.S. and J.J. report funding from Nantong University Special Research Fund for Clinical Medicine (No. 2023JQ016). Z.W. reports funding from Nantong Health Commission Project (No. MS2023078). Y.Q. reports funding from the National Natural Science Foundation of China (No. 82572432). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Affiliated Nantong Hospital 3 of Nantong University (No. EK2023168). Individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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