Due to the irregularity of cervical inferior endplate morphology among individuals and segments, a bone-implant interface (BII) gap is usually unavoidable between the prosthesis and endplate after cervical disc replacement (CDR). This study aimed to investigate the clinical and biomechanical effects of the BII gap after CDR. We retrospectively reviewed the clinical and radiological data of 180 patients who underwent 1-level or 2-level CDR. Cervical sagittal parameters, implant subsidence and migration, heterotopic ossification (HO) were evaluated through lateral radiographs. Endplate morphology was classified into three types according to the position of concavity apex: (I) posterior, (II) central, and (III) anterior. CDR finite element models with and without BII gap were developed based on type II endplate to analyze predictions of relative stress distributions, micromotions and associated risks for subsidence at BII. No statistical differences in clinical outcomes and the incidence of implant subsidence or migration between two groups were noted. The proportion of BII gaps after CDR was significantly larger in segments with type I endplate morphology (68.0

ABSTRACT Objectives The prevertebral fascia (PVF), which constitutes part of the deep layer of the deep cervical fascia, is routinely incised during anterior cervical discectomy and fusion (ACDF) surgery. Suturing the PVF could serve as an optimal barrier between the surface of the fusion device and the posterior esophagus and may alleviate postoperative dysphagia. Thus, this retrospective study was aimed to (1) evaluate the impact of prevertebral fascia (PVF) suturing and (2) perform a multivariate analysis of relevant risk factors for postoperative dysphagia following anterior cervical discectomy and fusion (ACDF). Methods A total of 197 patients who underwent ACDF and had at least 1 year of follow‐up between June 2020 and February 2024 were retrospectively reviewed. To compare baseline data and incidence of dysphagia, the patients were divided into two groups on the basis of whether they had undergone PVF suturing during the operation (suture group, N = 83; nonsuture group, N = 114). The incidence and severity of dysphagia were evaluated using the Bazaz grading system. The patients were further categorized into a dysphagia group (N = 56) and a nondysphagia group (N = 141) to conduct a multivariate analysis of dysphagia. Results Compared with the nonsuture group, the suture group presented a significantly lower incidence and severity of dysphagia at 1 week, 1 month, and 3 months postoperatively (p < 0.05). A binary logistic regression analysis revealed that advanced age (odds ratio [OR], 1.034; 95% confidence interval [95% CI, 1.006–1.063]), greater ΔC2‐7A (OR, 1.141; 95% CI, 1.056–1.232), minor ΔTS‐CL (OR, 0.890; 95% CI, 0.842–0.941), and nonsutured PVF (OR, 0.329; 95% CI, 0.146–0.740) were significantly associated with higher rates of dysphagia (p < 0.05). Conclusion Suturing of the PVF during ACDF can significantly decrease the incidence and severity of transient postoperative dysphagia in patients. The incidence of postoperative dysphagia is also significantly associated with advanced age, greater ΔC2‐7A, and minor ΔTS‐CL.

OBJECTIVE:This study aimed to retrospectively evaluate the long-term clinical and radiological outcomes following cervical disc arthroplasty (CDA). METHODS:This study included 74 patients who underwent single- or two-level CDA between November 2004 and December 2013, with a minimum 10-year follow-up (22 in the Bryan disc group and 52 in the Prestige LP disc group). Patient-reported outcomes and radiological parameters were collected for comparisons. Additionally, the incidences of heterotopic ossification (HO), adjacent segment degeneration (ASD), prosthesis subsidence, and segmental kyphosis at the final follow-up were evaluated and analyzed. A 95% confidence interval (CI) for a mean difference or odds ratio (OR) was used for all general statistical calculations. RESULTS:After 10 years of follow-up, patients with CDA continued to show significant improvement from baseline in patient-reported outcomes (p < 0.001), with no significant differences between the two groups. However, the Bryan disc group had significantly higher global range of motion (ROM; 95% CI 4.8°-19.2°, p = 0.001) and segmental ROM (95% CI 1.3°-5.9°, p = 0.003) compared to the Prestige LP disc group. At 10 years postoperatively, the incidence of HO was 69.2%, including 29.7% ROM-limiting HO. The incidence of ASD was 55.4%. Segmental kyphosis was observed in 10 patients, with a 20.8% incidence in the Bryan disc group and an 8.1% incidence in the Prestige LP disc group (p = 0.072). In the univariate subgroup analysis, the age of the ASD group was significantly higher (95% CI 0.3-6.8, p = 0.034). However, no statistically significant parameters were identified between the HO and non-HO groups. CONCLUSIONS:Through at least 10 years of follow-up, CDA can achieve satisfactory clinical outcomes while effectively preserving segmental mobility.

Background:Anterior bone loss (ABL) is a common phenomenon after cervical disc replacement (CDR), which can also be observed after anterior cervical discectomy and fusion (ACDF). This study aimed to investigate the incidence and severity of ABL in single-level CDR and ACDF and explore the association of cervical sagittal alignment with ABL. Methods:This is a single-center retrospective cohort study. A total of 113 patients treated with CDR and 99 patients treated with ACDF were retrospectively reviewed from January 2014 to December 2018 in West China Hospital. Radiological data were collected at pre-operation, 1 week, 3 months postoperatively, and the last follow-up. The incidence and severity of ABL after both CDR and ACDF were evaluated. Cervical sagittal alignment parameters, including C0-C2 angle, cervical lordosis (CL), C2-C7 sagittal vertical axis (cSVA), T1 slope, functional spinal unit angle, disc angle, and surgical level slope, were evaluated. Results:ABL was identified in 75 (66.4%) patients in the CDR group and 57 (57.6%) patients in the ACDF group. There were no significant differences in the incidence, severity, and location of ABL between the ACDF and CDR groups. For patients who underwent ACDF, the proportion of females was significantly higher in the ABL group (64.9% vs. 33.3%, P=0.002), whereas the body mass index (BMI) was significantly lower in the ABL group compared to the non-ABL group (22.72±3.09 vs. 24.60±3.04, P=0.002). No effect of ABL on the short-term clinical outcomes of ACDF and CDR was observed. In the ACDF group, patients with ABL had significantly smaller postoperative CL (11.83°±8.24° vs. 15.25°±8.32°, P=0.04) and cSVA (17.77±10.08 vs. 23.35±9.86 mm, P=0.007). In the CDR group, no significant differences were found in the cervical sagittal parameters between patients with and without ABL (CL: 12.58±8.70 vs. 15.46±8.50, P=0.10; cSVA: 20.95±8.54 vs. 19.40±9.43, P=0.38). Conclusions:ABL is common after both CDR and ACDF with comparable incidence and severity. Cervical sagittal alignment was closely related to ABL after ACDF yet had less influence on ABL after CDR.

STUDY DESIGN:Prospective, randomized, parallel-controlled trial. OBJECTIVE:The primary aim of this study was to determine whether thrombin-gelatin matrix (TGM) combined with an absorbable gelatin sponge (AGS) could more greatly reduce intraoperative blood loss (IBL) in unilateral open-door laminoplasty than the sole use of an AGS could. The secondary aims were to evaluate the hemostatic efficiency, amount of postoperative bleeding, and safety of the application of TGM combined with an AGS. SUMMARY OF BACKGROUND DATA:IBL during cervical laminoplasty is substantial and is a proper indication for the application of hemostatic agents. However, we are unaware of any clinical trials on the application of TGM and an AGS in posterior cervical spine surgery. METHODS:A total of 80 consecutive patients who underwent unilateral open-door laminoplasty were enrolled from September 2020 to March 2022. Patients were randomized into 2 groups, the TGM-AGS group and the AGS group, with 40 patients in each group. The primary outcome was IBL. Other outcomes included the duration of operation, duration of hemostasis, duration of drainage, maximum decrease in hemoglobin (Hb), length of hospital stay, volume of drainage, number of drainage days, occurrence of adverse events, coagulation indicators, and patient-reported outcome measures (PROMs). RESULTS:The mean IBL for patients in the TGM-AGS group (75.22 ± 21.83 mL) was significantly lower than that in the AGS group (252.43 ± 57.39 mL) (mean difference = 177.21 mL, 95% confidence interval [CI], 157.88-196.53 mL, t=18.25, P <0.001); the duration of hemostasis, volume of drainage, days of drainage in the TGM group, and maximum decrease in Hb were also significantly less than those in the AGS group ( P <0.01). CONCLUSION:The hemostatic efficacy of TGM-AGS is better than that of an AGS alone in IBL. TGM-AGS is also superior to an AGS alone in the evaluation of hemostatic efficiency and postoperative bleeding.

Objectives: To develop and validate an MRI radiomics-based decision support tool for the automated grading of cervical disc degeneration.Methods: The retrospective study included 2,610 cervical disc samples of 435 patients from two hospitals. The cervical magnetic resonance imaging (MRI) analysis of patients confirmed cervical disc degeneration grades using the Pfirrmann grading system. A training set (1,830 samples of 305 patients) and an independent test set (780 samples of 130 patients) were divided for the construction and validation of the machine learning model, respectively. We provided a fine-tuned MedSAM model for automated cervical disc segmentation. Then, we extracted 924 radiomic features from each segmented disc in T1 and T2 MRI modalities. All features were processed and selected using minimum redundancy maximum relevance (mRMR) and multiple machine learning algorithms. Meanwhile, the radiomics models of various machine learning algorithms and MRI images were constructed and compared. Finally, the combined radiomics model was constructed in the training set and validated in the test set. Radiomic feature mapping was provided for auxiliary diagnosis.Results: Of the 2,610 cervical disc samples, 794 (30.4%) were classified as low grade and 1,816 (69.6%) were classified as high grade. The fine-tuned MedSAM model achieved good segmentation performance, with the mean Dice coefficient of 0.93. Higher-order texture features contributed to the dominant force in the diagnostic task (80%). Among various machine learning models, random forest performed better than the other algorithms (p < 0.01), and the T2 MRI radiomics model showed better results than T1 MRI in the diagnostic performance (p < 0.05). The final combined radiomics model had an area under the receiver operating characteristic curve (AUC) of 0.95, an accuracy of 89.51%, a precision of 87.07%, a recall of 98.83%, and an F1 score of 0.93 in the test set, which were all better than those of other models (p < 0.05).Conclusion: The radiomics-based decision support tool using T1 and T2 MRI modalities can be used for cervical disc degeneration grading, facilitating individualized management.

In this paper, we focus on the automated diagnosis of physiological curvature in the cervical spine, with an emphasis on feature point localization. Cervical spine deformity is prevalent, and the Cobb angle is widely recognized as the gold standard for diagnosing and treating it. However, manual measurement is time-consuming, labor-intensive, and heavily reliant on clinical experience. Therefore, there is an urgent need for a high-precision automatically detecting algorithm to meet the clinical requirements of orthopedic surgeons. Traditional methods are constrained by complex steps and limited data, which pose challenges. Therefore, we propose an efficient framework that formulates an automatic diagnosis of cervical spine physiological curvature based on a novel deep neural network. By leveraging the excellent properties of neural memory Ordinary Differential Equation (nmODE) in long-term memory retention and nonlinear representation capabilities, we effectively improve the network’s performance in keypoint detection branching tasks. Additionally, we integrate a novel hybrid transformer based on residual structures and a multi-stage dilated dynamic convolution to alleviate false detections caused by X-ray obstruction and shadows, and the integration also captures the relationship between vertebrae and landmarks to compensate for the lack of detailed information. We constructed a dataset named CSL-947X, comprising 947 cervical spine lateral X-ray images of patients to train and evaluate our proposed model. Extensive experiments on CSL-947X demonstrate that our framework achieves higher accuracy and outperforms most state-of-the-art methods. These results highlight the effectiveness of the proposed architecture and its potential feasibility as a clinical decision-making tool for healthcare professionals.

Introduction: Anterior cervical discectomy and fusion (ACDF) is widely accepted as the gold standard surgical procedure for treating cervical radiculopathy and myelopathy. However, there is concern about the low fusion rate in the early period after ACDF surgery using the Zero-P fusion cage. We creatively designed an assembled uncoupled joint fusion device to improve the fusion rate and solve the implantation difficulties. This study aimed to assess the biomechanical performance of the assembled uncovertebral joint fusion cage in single-level ACDF and compare it with the Zero-P device. Methods: A three-dimensional finite element (FE) of a healthy cervical spine (C2−C7) was constructed and validated. In the one-level surgery model, either an assembled uncovertebral joint fusion cage or a zero-profile device was implanted at the C5–C6 segment of the model. A pure moment of 1.0 Nm combined with a follower load of 75 N was imposed at C2 to determine flexion, extension, lateral bending, and axial rotation. The segmental range of motion (ROM), facet contact force (FCF), maximum intradiscal pressure (IDP), and screw−bone stress were determined and compared with those of the zero-profile device. Results: The results showed that the ROMs of the fused levels in both models were nearly zero, while the motions of the unfused segments were unevenly increased. The FCF at adjacent segments in the assembled uncovertebral joint fusion cage group was less than that that of the Zero-P group. The IDP at the adjacent segments and screw–bone stress were slightly higher in the assembled uncovertebral joint fusion cage group than in those of the Zero-P group. Stress on the cage was mainly concentrated on both sides of the wings, reaching 13.4–20.4 Mpa in the assembled uncovertebral joint fusion cage group. Conclusion: The assembled uncovertebral joint fusion cage provided strong immobilization, similar to the Zero-P device. When compared with the Zero-P group, the assembled uncovertebral joint fusion cage achieved similar resultant values regarding FCF, IDP, and screw–bone stress. Moreover, the assembled uncovertebral joint fusion cage effectively achieved early bone formation and fusion, probably due to proper stress distributions in the wings of both sides.

Background Ceruminous glands are modified apocrine glands of the external auditory canal (EAC). Malignant tumours within the ceruminous glands are extremely rare, and the most common histological type is adenoid cystic carcinoma (ADCC), which has high recurrence and metastasis risks. Although a few cases of metastatic ADCC from other head and neck glands have been reported, metastatic ADCC originating from the ceruminous gland are extremely rare. Case presentation We present an unusual case of spinal metastases of ADCC from ceruminous glands. A 61-year-old woman complaining of low back pain and both lower limbs pain was referred to our department. The primary ceruminous tumour was resected 26 years ago and recurred 6 years later, which was treated by radiotherapy. Three years ago, she presented with low back pain and was diagnosed as multiple lungs and bone metastases. The patient underwent tumour excision, decompression and fusion. The biopsy revealed metastatic ADCC. The symptoms were alleviated after surgery. Conclusions ADCC of EAC is a pernicious malignant tumour that is characterized by slow-growing patterns and a high predisposition to recurrence and metastasis. Differential diagnoses of ADCC and benign tumours in the EAC are challenging, particularly at early stages. We report a rare case of ceruminous ADCC with a prolonged clinical history as well as spinal metastasis and highlight the significance of regular follow-ups for patients undergoing tumour excision in the EAC.

In recent years, cervical spondylosis has become one of the most common chronic diseases and has received much attention from the public. Magnetic resonance imaging (MRI) is the most widely used imaging modality for the diagnosis of degenerative cervical spondylosis. The manual identification and segmentation of the cervical spine on MRI makes it a laborious, time-consuming, and error-prone process. In this work, we collected a new dataset of 300 patients with a total of 600 cervical spine images in the MRI T2-weighted (T2W) modality for the first time, which included the cervical spine, intervertebral discs, spinal cord, and spinal canal information. A new instance segmentation approach called SeUneter was proposed for cervical spine segmentation. SeUneter expanded the depth of the network structure based on the original U-Net and added a channel attention module to the double convolution of the feature extraction. SeUneter could enhance the semantic information of the segmentation and weaken the characteristic information of non-segmentation to the screen for important feature channels in double convolution. In the meantime, to alleviate the over-fitting of the model under insufficient samples, the Cutout was used to crop the pixel information in the original image at random positions of a fixed size, and the number of training samples in the original data was increased. Prior knowledge of the data was used to optimize the segmentation results by a post-process to improve the segmentation performance. The mean of Intersection Over Union (mIOU) was calculated for the different categories, while the mean of the Dice similarity coefficient (mDSC) and mIOU were calculated to compare the segmentation results of different deep learning models for all categories. Compared with multiple models under the same experimental settings, our proposed SeUneter’s performance was superior to U-Net, AttU-Net, UNet++, DeepLab-v3+, TransUNet, and Swin-Unet on the spinal cord with mIOU of 86.34% and the spinal canal with mIOU of 73.44%. The SeUneter matched or exceeded the performance of the aforementioned segmentation models when segmenting vertebral bodies or intervertebral discs. Among all models, SeUneter achieved the highest mIOU and mDSC of 82.73% and 90.66%, respectively, for the whole cervical spine.

BackgroundMore than 70 percent of the world's population is tortured with neck pain more than once in their vast life, of which 50–85% recur within 1–5 years of the initial episode. With medical resources affected by the epidemic, more and more people seek health-related knowledge via YouTube. This article aims to assess the quality and reliability of the medical information shared on YouTube regarding neck pain.MethodsWe searched on YouTube using the keyword “neck pain” to include the top 50 videos by relevance, then divided them into five and seven categories based on their content and source. Each video was quantitatively assessed using the Journal of American Medical Association (JAMA), DISCERN, Global Quality Score (GQS), Neck Pain-Specific Score (NPSS), and video power index (VPI). Spearman correlation analysis was used to evaluate the correlation between JAMA, GQS, DISCERN, NPSS and VPI. A multiple linear regression analysis was applied to identify video features affecting JAMA, GQS, DISCERN, and NPSS.ResultsThe videos had a mean JAMA score of 2.56 (SD = 0.43), DISCERN of 2.55 (SD = 0.44), GQS of 2.86 (SD = 0.72), and NPSS of 2.90 (SD = 2.23). Classification by video upload source, non-physician videos had the greatest share at 38%, and sorted by video content, exercise training comprised 40% of the videos. Significant differences between the uploading sources were observed for VPI (P = 0.012), JAMA (P < 0.001), DISCERN (P < 0.001), GQS (P = 0.001), and NPSS (P = 0.007). Spearman correlation analysis showed that JAMA, DISCERN, GQS, and NPSS significantly correlated with each other (JAMA vs. DISCERN, p < 0.001, JAMA vs. GQS, p < 0.001, JAMA vs. NPSS, p < 0.001, DISCERN vs. GQS, p < 0.001, DISCERN vs. NPSS, p < 0.001, GQS vs. NPSS, p < 0.001). Multiple linear regression analysis suggested that a higher JAMA score, DISCERN, or GQS score were closely related to a higher probability of an academic, physician, non-physician or medical upload source (P < 0.005), and a higher NPSS score was associated with a higher probability of an academic source (P = 0.001) than of an individual upload source.ConclusionsYouTube videos pertaining to neck pain contain low quality, low reliability, and incomplete information. Patients may be put at risk for health complications due to inaccurate, and incomplete information, particularly during the COVID-19 crisis. Academic groups should be committed to high-quality video production and promotion to YouTube users.

To systematically quantify the diagnostic accuracy and identify potential covariates affecting the performance of artificial intelligence (AI) in diagnosing orthopedic fractures. PubMed, Embase, Web of Science, and Cochrane Library were systematically searched for studies on AI applications in diagnosing orthopedic fractures from inception to September 29, 2021. Pooled sensitivity and specificity and the area under the receiver operating characteristic curves (AUC) were obtained. This study was registered in the PROSPERO database prior to initiation (CRD 42021254618). Thirty-nine were eligible for quantitative analysis. The overall pooled AUC, sensitivity, and specificity were 0.96 (95% CI 0.94–0.98), 90% (95% CI 87–92%), and 92% (95% CI 90–94%), respectively. In subgroup analyses, multicenter designed studies yielded higher sensitivity (92% vs. 88%) and specificity (94% vs. 91%) than single-center studies. AI demonstrated higher sensitivity with transfer learning (with vs. without: 92% vs. 87%) or data augmentation (with vs. without: 92% vs. 87%), compared to those without. Utilizing plain X-rays as input images for AI achieved results comparable to CT (AUC 0.96 vs. 0.96). Moreover, AI achieved comparable results to humans (AUC 0.97 vs. 0.97) and better results than non-expert human readers (AUC 0.98 vs. 0.96; sensitivity 95% vs. 88%). AI demonstrated high accuracy in diagnosing orthopedic fractures from medical images. Larger-scale studies with higher design quality are needed to validate our findings. • Multicenter study design, application of transfer learning, and data augmentation are closely related to improving the performance of artificial intelligence models in diagnosing orthopedic fractures. • Utilizing plain X-rays as input images for AI to diagnose fractures achieved results comparable to CT (AUC 0.96 vs. 0.96). • AI achieved comparable results to humans (AUC 0.97 vs. 0.97) but was superior to non-expert human readers (AUC 0.98 vs. 0.96, sensitivity 95% vs. 88%) in diagnosing fractures.

The increasing prevalence of neck pain poses a huge socioeconomic burden. Physiotherapy exercise plays a vital role in the management of neck pain; consequently, the current COVID-19 pandemic accompanying the lockdown has resulted in a shortage of physiotherapy care. YouTube, in particular, is a leading source due to its easy access to information and visual advantages for internet users. However, the nature of these videos is often unscientific, misleading, and even harmful. The study aimed to investigate the quality and reliability of neck pain physiotherapy exercise videos shared on YouTube and identified factors associated with the overall video quality and reliability. On 15 April 2022, a YouTube search was performed using the keywords “neck pain relief exercises”, “neck pain physiotherapy” and “neck pain rehabilitation”. Videos were categorized by 3 doctors based on whether the video content provided useful or misleading information. Furthermore, the reliability and quality of the videos were assessed using the Journal of the American Medical Association (JAMA) benchmark criteria, the 5-point DISCERN tool, and the 5-point global quality score criteria (GQS). Spearman correlation analysis was applied to assess the correlation between JAMA, GQS, DISCERN, and video power index (VPI). A multiple linear regression analysis was performed to identify video characteristics affecting the JAMA, GQS, DISCERN, and VPI. Out of the 89 videos selected for the study, 38 (42.7%) were classified as useful, whereas 51 (57.3%) provided misleading information. A total of 36.0% of videos (32/89) were generated by nonphysicians compared to 12.4% of videos (11/89) contributed by academic sources. In the useful information group, the videos had a higher JAMA (P<.001), DISCERN (P=.004), and GQS scores (P<.001). The VPI was higher for the misleading information group (888.00 vs 575.67) but did not reach a level of statistical significance (P=.507). The uploading sources of the videos were mainly academic, physician, nonphysician, medical, commercial and individual. Statistical differences were found between the uploading source groups in terms of the JAMA, DISCERN, and GQS (P<.001). JAMA, DISCERN, and GQS scores significantly correlated with each other (JAMA score vs GQS, p<.001; JAMA score vs DISCERN, p<.001; DISCERN vs GQS, p<.001). A higher video quality or reliability score was associated with a higher probability of academic and physician (P<.001) uploading sources compared with individual sources. VPI was not significantly correlated with quality or reliability (P>.05). Even though the academic and physician group provide the highest percentage of useful information (7/11), a statistical difference was not noted between the useful and misleading video groups regarding the uploading sources (P=.144). YouTube videos on neck pain physiotherapy exercises have low quality and reliability. Our findings suggest that academic and physician groups should provide and promote high-quality video content to YouTube users and patients. This study did not require a trial registration since it is not a clinical trial and only publicly available data were used.

Study Design: Retrospective cohort study. Objectives: This study aimed to explore the effect of preoperative cervical spondylosis on the heterotopic ossification (HO) formation in different locations after cervical disc replacement (CDR). Methods: The degree of preoperative cervical spondylosis was evaluated radiologically, including the intervertebral disc, uncovertebral joints, facet joints and ligaments. The effects of cervical spondylosis on the HO formation after CDR were analyzed according to the location of HO. Multivariate logistic regression was performed to identify the independent factors. Results: 149 patients with a total of 196 arthroplasty segments were involved in this study. HO, anterior HO (AHO), and posterior HO (PHO) developed in 59.69%, 22.96%, and 41.84% levels, respectively. The significant factors in univariate analysis for PHO after CDR included the disc height loss, anterior osteophytes, preoperative uncovertebral joint osteophytes and facet joint degeneration. The incidence of adjacent segment degeneration (ASD) was significantly higher in the PHO group compared to that without PHO at the last follow-up (P = .003). The disc height loss in high-grade HO was significantly more than that in low-grade group (P = .039). Multivariate analysis identified disc height loss was the only independent factor for PHO (P = .009). No significant degenerative factors related to the formation of AHO were found. Conclusions: Preoperative cervical spondylosis predominantly affected the HO formation in the posterior disc space after CDR. The disc height loss was an independent risk factor for PHO formation. Rigorous criteria for the extent of preoperative disc height loss should be used when selecting appropriate candidates for CDR.

Study Design: Retrospective cohort study. Objective: To explore the association between craniocervical sagittal balance and clinical and radiological outcomes of cervical disc replacement (CDR). Methods: Patients who underwent 1-level and 2-level CDR were retrospectively analyzed. Clinical outcomes were evaluated using scores on the Japanese Orthopaedic Association (JOA), Visual Analogue Scale (VAS), and Neck Disability Index (NDI). The craniocervical sagittal alignment parameters, including the C0-C2 Cobb angle, C2-C7 Cobb angle, C2 slope, T1 slope, C2-C7 sagittal vertical axis (SVA), C1-C7 SVA, the center of gravity of the head (CGH)-C7 SVA, and range of motion (ROM) at the surgical segments were measured. Results: A total of 169 patients were involved. Significantly lower pre- and postoperative C2 slope and CGH-C7 SVA were found in arthroplasty levels with better ROMs. Patients with a higher preoperative C2 slope and CGH-C7 SVA had lower cervical lordosis and ROM after surgery. There were no significant differences in the clinical outcomes between patients with different sagittal balance statuses. C2-C7 SVA and CGH-C7 SVA were significantly associated with radiographic adjacent segment pathology (rASP). Conclusion: Craniocervical sagittal balance is associated with cervical lordosis and ROM at the index level after CDR. A higher preoperative SVA is related to the presence and progression of rASP. A relationship between sagittal alignment and clinical outcomes was not observed.

Objective: To conduct a high-level meta-analysis of the RCTs to evaluate perioperative steroids use in the management of fusion rate, dysphagia, and VAS following anterior cervical spine surgery for up to 1 year. Methods: We searched the database PubMed, EMBASE, Web of Science, Cochrane Library, Google Scholar, Ovid, and ClinicalTrials.gov without time restriction to identify RCTs that evaluate the effectiveness of perioperative steroids after anterior cervical spine surgery. A subgroup analysis was undertaken to investigate the effects of intravenous and local steroids. This study was registered in the PROSPERO database prior to initiation (CRD42022313444). Results: A total of 14 RCTs were eligible for final inclusion. This meta-analysis showed that steroids could achieve lower dysphagia rate ( p < 0.001), severe dysphagia rate within 1 year ( p < 0.001), lower VAS scores at both 1 day ( p = 0.005), 2 weeks ( p < 0.001) and shorter hospital stay ( p = 0.014). However, there was no significant difference between the two groups regarding operation time ( p = 0.670), fusion rates ( p = 0.678), VAS scores at 6 months ( p = 0.104) and 1 year ( p = 0.062). There was no significant difference between intravenous and local steroid administration regarding dysphagia rates ( p = 0.82), fusion rate ( p = 1.00), and operative time ( p = 0.10). Conclusion: Steroids intravenously or locally following anterior cervical spine surgery can reduce incidence and severity of dysphagia within 1 year, VAS score within 2 weeks, and shorten the length of hospital stay without affecting fusion rates, increasing the operating time, VAS score at 6 months and 1 year.

Introduction: Anterior cervical discectomy and fusion (ACDF) is a widely accepted surgical procedure in the treatment of cervical radiculopathy and myelopathy. A solid interbody fusion is of critical significance in achieving satisfactory outcomes after ACDF. However, the current radiographic techniques to determine the degree of fusion are inaccurate and radiative. Several animal experiments suggested that the mechanical load on the spinal instrumentation could reflect the fusion process and evaluated the stability of implant. This study aims to investigate the biomechanical changes during the fusion process and explore the feasibility of reflecting the fusion status after ACDF through the load changes borne by the interbody fusion cage.Methods: The computed tomography (CT) scans preoperatively, immediately after surgery, at 3 months, and 6 months follow-up of patients who underwent ACDF at C5/6 were used to construct the C2–C7 finite element (FE) models representing different courses of fusion stages. A 75-N follower load with 1.0-Nm moments was applied to the top of C2 vertebra in the models to simulate flexion, extension, lateral bending, and axial rotation with the C7 vertebra fixed. The Von Mises stress at the surfaces of instrumentation and the adjacent intervertebral disc and force at the facet joints were analyzed.Results: The facet contact force at C5/6 suggested a significantly stepwise reduction as the fusion proceeded while the intradiscal pressure and facet contact force of adjacent levels changed slightly. The stress on the surfaces of titanium plate and screws significantly decreased at 3 and 6 months follow-up. A markedly changed stress distribution in extension among three models was noted in different fusion stages. After solid fusion is achieved, the stress was more uniformly distributed interbody fusion in all loading conditions.Conclusions: Through a follow-up study of 6 months, the stress on the surfaces of cervical instrumentation remarkably decreased in all loading conditions. After solid intervertebral fusion formed, the stress distributions on the surfaces of interbody cage and screws were more uniform. The stress distribution in extension altered significantly in different fusion status. Future studies are needed to develop the interbody fusion device with wireless sensors to achieve longitudinal real-time monitoring of the stress distribution during the course of fusion.

目的 提出一种用于辅助诊断的胸腰椎骨折智能分类方法,并分析其临床应用的可行性.方法 收集四川大学华西医院2019年1月-2020年3月共1256张胸腰椎骨折CT影像,通过影像LabelImg系统用统一的标准进行标注.所有CT图像按照AO Spine胸腰椎损伤分类.在ABC型的分类中,共使用1039张CT图像进行训练和验证来优化深度学习系统,其中训练集1004张,验证集35张;其余217张CT图像作为测试集,对比深度学习系统和临床医生诊断结果.在A型亚型的分类中,共使用581张CT图像进行训练和验证来优化深度学习系统,其中训练集556张,验证集25张;其余104张CT图像作为测试集,对比深度学习系统和临床医生诊断结果.结果 深度学习系统骨折ABC分类的正确率为89.4％,Kappa系数为0.849(P＜0.001);A型亚分型的正确率为87.5％,Kappa系数为0.817(P＜0.001).结论 基于深度学习的胸腰椎骨折智能分类正确率高.这种方法可以用来辅助智能诊断胸腰椎骨折CT图像,改善目前人工复杂的诊断流程.

随着人工智能、大数据和5G技术的迅速发展,医学的发展已经步入智能医学时代,骨科的发展也由经典骨科时代进入智能骨科的早期阶段.智能骨科技术的发展挑战与机遇并存,智能骨科时代不仅要求研究生导师学习和掌握相关的智能技术,更对医、理、工高度交叉的学科背景下骨科研究生科研与创新能力的培养提出了新的要求,本文分析了传统骨科研究生培养存在的问题以及智能骨科时代下研究生科研与创新能力培养的意义和经验策略,做如下总结供广大骨科研究生导师参考.