Thoracic spinal stenosis (TSS) is one of the most challenging conditions in the field of spinal surgery. With the global trend of population aging, the incidence of TSS is increasing annually. For instance, Korea scholars Moon et al. (1) evaluated MRI findings in 2,134 patients (with back pain or low back pain) and reported an ossification of ligamentum flavum (OLF) prevalence of 16.9% (OLF being the most common cause of TSS), which increased with age. Similarly, Japanese scholars Mori et al. (2) analyzed CT scans of 3,010 patients (screened for pulmonary diseases) and found an OLF prevalence of 36%. In a comparable study, Chinese researchers Lang et al. (3) standardized prevalence rates according to age demographics, revealing a remarkably high adjusted OLF prevalence of 63.9%. This progressive rise has established TSS as a major health issue affecting the quality of life in middle-aged and elderly patients. Notably, clinical studies have shown that approximately 52.1% of TSS patients also present with degenerative changes at other spinal levels, making diagnosis and treatment significantly more complex (4). Although traditional open surgery can effectively decompress the spinal cord, its large surgical trauma and high complication rate limit its clinical application. Several studies have reported complication rates of up to 25% following conventional posterior laminectomy and decompression procedures (5, 6). Recently, the rapid development of minimally invasive spinal techniques has introduced unilateral biportal endoscopy (UBE) as a promising alternative for TSS treatment. Compared with traditional open surgery, UBE offers significant minimally invasive advantages, including better visualization of the surgical field and reduced paraspinal muscle dissection (7). Clinical research indicates that patients undergoing UBE experience an average reduction in intraoperative blood loss by 62%, a 3.5-day shorter postoperative hospital stays, and faster early functional recovery (8, 9). Particularly in elderly patients or those with multiple comorbidities, UBE provides a safer surgical option, with the 30-day postoperative complication rate being approximately 40% lower than that of open procedures (10).

However, despite the overall lower complication rate of UBE compared to open surgery, specific complications such as epidural hematoma and cerebrospinal fluid (CSF) leakage remain non-negligible (11). More importantly, most existing predictive models are based on data from open surgeries and are not fully applicable to the UBE technique. For example, UBE’s restricted working corridor increases the risk of dural tears and neural injury due to instrument crowding. Meanwhile, its fluid-mediated visualization system may predispose to unique complications like epidural hematoma from sustained irrigation pressure. As a result, risk assessment in current UBE procedures largely depends on the surgeon’s experience, with a lack of systematic predictive tools. A multicenter survey revealed that a majority of spinal surgeons believe that current risk assessment methods are inadequate for UBE surgery (12). This gap between clinical demand and technological capability highlights the importance and urgency of developing UBE-specific complication prediction models.

This study aims to innovatively construct the first nomogram model for predicting postoperative complications in TSS patients undergoing UBE. Through systematic integration of multidimensional clinical data encompassing baseline characteristics, radiographic parameters, and intraoperative variables, the model offers a comprehensive visualization of each risk factor’s predictive contribution. This quantitative tool enables precise preoperative risk stratification, helping surgeons to identify high-risk patients and optimize perioperative management strategies. Ultimately, the proposed model has the potential to significantly reduce the incidence of complications following UBE and to fill the current gap in risk assessment within the context of minimally invasive spinal surgery. Moreover, it offers valuable support for the standardized and precise development of UBE techniques in clinical practice.

Surgical treatment of TSS remains a significant challenge in spinal surgery, with the core focus on achieving effective decompression while minimizing the risk of perioperative complications. Recently, UBE has emerged as a minimally invasive option for TSS due to its advantages of enhanced visualization and flexible manipulation. However, given the complex anatomical structure of the thoracic spine and the low tolerance of the spinal cord to surgical stress, systematic analysis of postoperative complications after UBE is still limited. Identifying high-risk factors and establishing a risk warning model are crucial for clinical practice. In this retrospective study of 375 patients who underwent UBE for TSS, we developed a nomogram for predicting postoperative complications for the first time. The results demonstrated that diabetes, SC/ECA ≥ 55%, and intramedullary high signal were markedly associated with poor outcomes. The model showed good discrimination in both the training and validation cohorts, providing an important tool for preoperative risk assessment, patient stratification, and individualized treatment planning.

Although UBE has markedly reduced the incidence of postoperative complications in TSS (8–10% in our study vs. up to 25.2% in traditional open surgery), CSF leakage and neurological deterioration remain concerning, especially in high-risk patients with complex anatomy. This highlights that while minimally invasive techniques reduce surgical trauma, they cannot fully overcome the inherent technical challenges of thoracic spine surgery, such as dense adhesions between the dura and ligaments and limited spinal cord buffering space. Therefore, accurate preoperative identification of high-risk patients, optimization of surgical strategies, and enhanced postoperative monitoring are essential to further ensure surgical safety, which underscores the clinical value of this study.

Regarding patient-related baseline factors, diabetes and low preoperative JOA scores were identified as independent risk factors for postoperative complications. Diabetes was associated with a four-fold increased risk of complications, the reason maybe that chronic hyperglycemia promotes the accumulation of advanced glycation end-products, leading to microvascular basement membrane thickening and endothelial dysfunction, which compromise tissue perfusion and oxygen delivery, impairing wound and neural tissue healing (13). Moreover, diabetic patients exhibit impaired neutrophil chemotaxis and macrophage polarization imbalance, substantially increasing the risk of postoperative infection (14). In our study, all six patients with poor wound healing had pre-existing type 2 diabetes. The inverse association between JOA scores and complications (36.4% risk reduction per point increase) reflects the consequence of severe baseline neurological impairment. A low preoperative JOA score, reflecting severe neurological impairment, suggests irreversible changes such as axonal degeneration, demyelination, and neuronal apoptosis due to prolonged spinal cord compression (15). These conditions reduce the spinal cord’s tolerance to mechanical stress during surgery. Furthermore, the thoracic spinal cord’s unique vascular anatomy makes it a watershed region with fewer anastomoses. Chronic compression-induced microcirculatory dysfunction may predispose the tissue to ischemic preconditioning, rendering it vulnerable to reperfusion injury after decompression (16). These findings are consistent with those reported by Hitchon et al. (17) and emphasize the importance of comprehensive preoperative assessment and optimized perioperative management, particularly in patients with diabetes or severe neurological deficits.

In terms of preoperative imaging parameters, SC/ECA ≥ 55%, intramedullary high signal, and TK angle ≥ 45 ° were identified as significant risk factors for postoperative complications. SC/ECA, calculated from axial MRI, provides a precise quantification of spinal canal stenosis. When this ratio exceeds 55%, the spinal cord’s buffering capacity is drastically reduced, often accompanied by epidural fat obliteration and altered CSF dynamics, which increase the risk of iatrogenic injury during surgery. Intramedullary high signal is widely considered a marker of spinal cord damage and is associated with poor neurological recovery (18). These hyperintense regions exhibit increased vulnerability to secondary injury due to edema and inflammation, while underlying microvascular impairment and metabolic abnormalities further hinder postoperative recovery (19). In our study, 5 of 8 patients with postoperative neurological deterioration had preoperative intramedullary high signal. TK angle ≥ 45 ° also warrants attention, as such deformity causes the spinal cord to shift anteriorly and adhere to the posterior vertebral body, reducing the dural sac’s buffering space by 30–40% (20). Moreover, the abnormal stress distribution associated with kyphosis can form dural folds within the decompression zone, creating “blind spots” that increase the risk of instrument-induced injury. Hu (21) et al. stated that a kyphosis angle ≥ 45 ° increases the complication rate of decompression surgery by 1–3.5-fold, which aligns with our clinical observations. These findings underscore the necessity of thorough preoperative evaluation of imaging features and the formulation of individualized surgical strategies to optimize procedural safety.

From a surgical perspective, multisegment lesions were identified as the most potent independent risk factor for complications following UBE. These cases require more extensive decompression, increasing dural exposure and surgical duration (22). Moreover, continuous multilevel decompression can lead to cumulative spinal cord traction, especially in the presence of dural adhesions, which act as anchor points that amplify mechanical stress and exacerbate neurological injury risk (23). The resulting nonlinear risk escalation likely contributes to the elevated OR. However, the wide confidence intervals observed may reflect limitations in statistical power due to the relatively small sample size of the multisegment subgroup and low event rates of complications. Multilevel decompression may also compromise spinal stability, particularly in patients with significant TK. In our cohort, 36% of patients with TK angle > 45 ° and multisegment lesions developed postoperative complications, predominantly neurological deterioration. Dural adhesions obscure normal anatomical planes, making dural separation from ligamentous tissue difficult, thereby increasing the risk of CSF leakage (notably, 53% of CSF leak cases in our study involved dural adhesions) and complicating hemostasis. Importantly, dural adhesions and multisegment lesions had a synergistic effect, increasing the risk of CSF leakage by 7.2-fold when both were present. This finding suggests that for such high-risk patients, modified strategies such as “floating decompression” or staged surgeries should be considered.

Regarding perioperative indicators, prolonged hospitalization was associated with complications through multiple pathways. This may reflect the cumulative effects of surgical trauma, especially in multisegment surgery or cases involving dural adhesions, where increased operative time and tissue injury delay recovery (24). Alternatively, prolonged hospitalization may serve as an early warning sign of impending complications (25). Among patients hospitalized for more than 10 days, 38.5% subsequently developed infections or neurological deterioration. This association was more pronounced in patients with diabetes or TK, indicating a more complex clinical course and highlighting the need for early multidisciplinary intervention and close postoperative monitoring.

This study successfully developed and validated a nomogram integrating multidimensional perioperative risk factors for predicting complications following UBE in TSS patients. Multisegment lesions (25 points) and SC/ECA ≥ 55% (20 points) were identified as the most predictive factors, aligning with the anatomical and surgical challenges discussed earlier. The inclusion of diabetes (10 points) and dural adhesions (10 points) further validated the synergistic effects of systemic metabolic and local pathological changes on complication risk. The model demonstrated excellent predictive performance, with AUCs of 0.964 and 0.846 in the training and validation cohorts, respectively, markedly outperforming existing predictive tools for spinal surgery complications [e.g., AUC 0.782–0.818 for surgical site infection models after lumbar discectomy (26); AUC 0.772–0.792 for deep vein thrombosis models following posterior lumbar fusion (27); AUC 0.722–0.743 for infection models after degenerative lumbar instrumentation (28)]. Calibration curves indicated high concordance between predicted and observed probabilities, while DCA curve analysis confirmed a clear clinical net benefit when the threshold probability exceeded 0.1. A key strength of this model is its ability to transform complex multifactorial interactions into an intuitive point-line system, enabling rapid preoperative risk assessment and providing an evidence-based foundation for personalized surgical planning, thereby optimizing both “decompression precision” and “complication control.”

Nevertheless, several limitations should be acknowledged. Firstly, although external validation was performed, the validation cohort was relatively small (n = 100) and sourced from a single center, which may limit the model’s generalizability to other institutions. Secondly, although the model integrates nine key predictive indicators, it does not encompass all potential influencing factors—particularly operator experience and surgical instrument type, which are important technical variables. Thirdly, due to the limited sample size, we were unable to develop complication-specific models (CSF leakage or neurological deterioration), despite potential differences in their risk profiles. These limitations suggest that future research should aim to improve model performance through multicenter, prospective studies, incorporating more comprehensive predictors and long-term follow-up data to further enhance the clinical utility of this tool.

This study successfully developed and validated the first predictive model for postoperative complications following UBE in TSS patients. The model incorporates multiple key factors, including diabetes, preoperative JOA score, SC/ECA ratio, intramedullary high signal, TK angle, intraoperative blood loss, dural adhesions, number of multisegment lesions, and hospital stays, which were shown to collectively influence complication risk. The model demonstrated high predictive accuracy and strong clinical applicability. It provides a valuable tool for preoperative risk assessment and individualized treatment planning, contributing to the precision and safety of minimally invasive thoracic spine surgery and ultimately improving patient outcomes.