European Spine Journal最新文献

Purpose: Cervical disc replacement aims to preserve cervical spine motion and reduce the risk of adjacent segment disease. The Rhine cervical disc is a non-articulating, viscoelastic implant designed to replicate the natural biomechanics of the cervical spine. To date, no explant analyses of this device have been published. This study presents the explant analysis of two Rhine cervical discs retrieved from a 41-year-old female patient who had undergone two-level cervical total disc replacement, C4-C5 and C6-C7, for myeloradiculopathy.

Methods: The implants were removed approximately one year after the surgery due to increasing neck discomfort, recurrent neurological symptoms, and radiographic evidence of osteolysis. Explant analysis was performed on both implants to assess their physical condition and any associated tissue reactions.

Results: Both explants were intact, however, notable findings included plastic deformation of the viscoelastic cores, particularly in the upper disc. The direction of shear deformation differed between the explants, anterior in the upper disc and posterior in the lower disc, suggesting asymmetric loading conditions. In addition, osteolysis was observed predominantly at the posterior aspect of the lower disc one year after implantation.

Conclusion: These observations highlight deformation of the viscoelastic core in Rhine cervical discs. Whether this finding relates to surgical factors such as implant sizing and positioning, or to implant design itself, improper sizing and malpositioning may contribute to excessive shear forces, core deformation, and poor clinical outcomes. These factors are all important in implant survival and should be carefully considered. The deformation observed in the cores of the explants is consistent with viscoelastic polymer limitations reported in the literature for other viscoelastic cervical discs.

Purpose: Compared to linear models, segmented models allow for the identification of threshold effects in severe spinal deformities, beyond which patients' health-related quality of life (QoL) declines significantly. However, no study has established threshold values for cosmetic parameters in adolescent idiopathic scoliosis (AIS). This study aims to determine the threshold values of cosmetic parameters in spinal deformity severity measurements.

Methods: A total of 278 female adolescents with idiopathic scoliosis (age: 14.7 ± 2.0; maximum Cobb angle: 49.4° ± 15.9°) completed the SRS-22r questionnaire. The Cobb angle and cosmetic parameters were measured using X-rays and Image-Pro Plus 6.0 software. Segmented and linear regression models were used to evaluate the correlation and explanatory power (R²) between SRS-22r domains and spinal deformity indicators, and to identify the thresholds of cosmetic parameters that significantly impact SRS-22r scores.

Results: Lateral shoulder tilt (LST) predicted significantly more variance in all SRS-22r domains using segmented (R²: 0.01-0.08) than linear models (R²: 0.00-0.03). Segmented models with a threshold estimated at 5.2° of LST explained 1-6% more variance than the corresponding linear models using the same variables. Cobb angle did not strongly associate with SRS-22r total score variables with linear and segmented models, explaining less than 4% of the variance.

Conclusion: This study shows that QoL stays relatively stable until LST exceeds a threshold of 5.2°, after which it drops markedly. Although the link between QoL and cosmetic parameters is weak, segmented models provide a better explanation than linear models.

Background: The optimal surgical strategy for Lenke 1 C adolescent idiopathic scoliosis (AIS) remains debated. Selective thoracic fusion (STF) preserves lumbar mobility by limiting fusion to the thoracic curve, while non-selective thoracic fusion (NSTF) extends distally to address the thoracolumbar/lumbar (TL/L) curve. The comparative long-term impact of these strategies on health-related quality of life (HRQoL) remains uncertain.

Methods: A systematic search was performed in PubMed, Scopus, Cochrane Library, and Google Scholar till September 2025. Five studies met the inclusion criteria. Key outcomes included perioperative outcomes (operative time and blood loss), radiographic parameters (state them with abbreviations), and HRQoL assessed with SRS-22r or SRS-30, pooled using a random-effects model.

Results: STF was associated with significantly shorter operative time (MD - 76.21 min, p < 0.001) and reduced blood loss (MD - 27.30 mL, p = 0.02). No difference was observed in MT Cobb angle correction at 2 years (p = 0.17). NSTF achieved superior TL/L outcomes, with a smaller residual Cobb angle (MD 5.14°, p = 0.04) and a higher correction rate (MD - 23.65%, p < 0.001). HRQoL analysis showed no significant differences between groups in any domain, including function/activity, pain, self-image/appearance, mental health, satisfaction with management, or in total score (all p > 0.05).

Conclusions: STF reduces surgical burden and preserve lumbar motion, while NSTF achieves superior TL/L correction. Yet, these differences did not translate into significant HRQoL variation, suggesting that in borderline Lenke 1 C patients, surgical decision-making should not rely on radiographic outcomes alone but also integrate patient-centered and subjective considerations.

Purpose: This study aimed to evaluate the utility of L1-L4 average Hounsfield Unit (HU) values from lumbar spine computed tomography (CT) in predicting osteoporosis using multiple machine learning (ML) models.

Methods: We retrospectively analyzed 172 patients (≥ 50 years) who underwent lumbar spine surgery and received preoperative CT and dual-energy X-ray absorptiometry (DXA) within 3 months. Osteoporosis was defined as a T-score < - 2.5 at either the lumbar spine or femoral neck. The L1-L4 average HU value was used as the sole input variable to develop seven supervised ML models. Model performance was compared using accuracy, precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC), and HU-based thresholds for osteoporosis screening were explored.

Results: Of 172 patients, 59 (34.3%) were classified as having osteoporosis. The osteoporosis group showed significantly lower L1-L4 HU values than the non-osteoporosis group (105.1 ± 47.5 vs. 140.1 ± 61.3, p < 0.01). Among the models, K-nearest neighbors (KNN) achieved the most balanced diagnostic performance (accuracy: 0.714 ± 0.048; F1 score: 0.466 ± 0.073). Logistic Regression and Naive Bayes showed the highest AUCs (0.785 ± 0.096 and 0.777 ± 0.098, respectively) but limited recall, whereas Support Vector Machine demonstrated moderate performance. Tree-based models yielded comparatively lower discriminatory ability. Optimal HU ranges for identifying high osteoporosis risk generally converged around 90-130 HU.

Conclusions: ML models using L1-L4 HU values can aid in osteoporosis screening. KNN provided the most robust and balanced diagnostic performance, while Logistic Regression and SVM offered stable threshold-based classification. These findings support the utility of CT-based ML approaches in preoperative spinal surgery settings, particularly where DXA is unavailable or limited.

Study design: Prospective single-center observational cohort study.

Objectives: To assess whether prior arthroscopic experience is associated with a shorter learning curve in uniportal interlaminar endoscopic lumbar discectomy (IELD), primarily in terms of operative efficiency, and to descriptively evaluate perioperative complications and patient-reported outcomes.

Methods: In accordance with STROBE guidelines, 240 consecutive patients with single-level lumbar disc herniation (MSU A/B, non-calcified, symptom duration ≤ 3 months) underwent IELD between 2021 and 2023 at a single academic orthopedic center. Procedures were performed by three spine surgeons without prior endoscopic experience; one surgeon had performed more than 300 shoulder arthroscopies. Operative time was analyzed using cumulative sum (CUSUM) methodology and linear regression. Missing outcome data were handled using last observation carried forward. Complications were recorded descriptively and stratified by learning phase and surgeon. Oswestry Disability Index (ODI) and Visual Analog Scale (VAS) scores for back and leg pain were assessed preoperatively and at 3 and 12 months.

Results: All surgeons demonstrated a three-phase learning curve consisting of learning, improvement, and stabilization phases. Operative efficiency stabilized after approximately 50 cases across surgeons. The surgeon with prior arthroscopic experience reached the CUSUM inflection point earlier (case 12) compared with the other surgeons (cases 24-26). The overall major complication rate was 9.2% and was highest during the initial learning phase. ODI and VAS scores improved significantly at 3 and 12 months (all p < 0.001), with no statistically significant between-surgeon differences at final follow-up.

Conclusions: Prior arthroscopic experience was associated with earlier adaptation during the initial learning phase of IELD, as measured by operative time. Following procedural stabilization, no statistically significant differences were detected in operative efficiency, major complication rates, or patient-reported outcomes between surgeons. These findings suggest that arthroscopic experience may facilitate early adaptation to endoscopic visualization and workflow but does not independently determine long-term clinical outcomes.

Level of evidence: III.