Osteoporosis (OP) is a chronic metabolic bone disease characterized by the decrease of bone tissue per unit volume under the combined action of genetic and environmental factors, which leads to the decrease of bone strength, makes the bone brittle, and raises the possibility of bone fracture. However, the exact mechanism that determines the progression of OP remains to be underlined. There are hundreds of trillions of symbiotic bacteria living in the human gut, which have a mutually beneficial symbiotic relationship with the human body that helps to maintain human health. With the development of modern high-throughput sequencing (HTS) platforms, there has been growing evidence that the gut microbiome may play an important role in the programming of bone metabolism. In the present review, we discuss the potential mechanisms of the gut microbiome in the development of OP, such as alterations of bone metabolism, bone mineral absorption, and immune regulation. The potential of gut microbiome-targeted strategies in the prevention and treatment of OP was also evaluated.Cite this article: Bone Joint Res 2020;9(8):524–530.

Purpose: We aimed to explore the relationship between bone mineral density (BMD), bone metabolism markers, and blood lipid-related indicators, body mass index (BMI) in elderly individuals. Methods: A retrospective analysis was conducted on 710 patients. Patients’ gender, age, height, weight, bone density values, T-scores, bone metabolism markers (including serum N-terminal propeptide of type I collagen (s-PINP), serum C-terminal telopeptide of type I collagen (s-CTX) and 1,25-dihydroxyvitamin D₃ (1,25(OH)₂D₃) and lipid-related indicators (including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and Castelli index 1 (TC/HDL-C index) and Castelli index 2 (LDL-C/HDL-C index) were recorded. Correlations between variables were analyzed, and patients were grouped according to gender and T-score for intergroup comparisons. Results: HDL-C negatively correlates with BMD and s-CTX. TG, Castelli index, and BMI positively correlate with BMD. BMI negatively correlates with s-PINP. 1,25(OH)₂D₃ negatively correlates with TC, LDL-C, and Castelli index. LDL-C positively correlates with BMD in males, and TC negatively correlates with s-PINP. In females, HDL-C negatively correlates with BMD, and s-CTX positively correlates with Castelli index. 1,25(OH)₂D₃ negatively correlates with TC, LDL-C, and Castelli index. TG and Castelli index were higher in normal bone mass group, while HDL-C is higher in the osteoporosis group. TG and BMI positively predicted bone mass density, while HDL-C negatively predicted bone mass density. Conclusions: HDL-C may have a predictive role in osteoporosis, particularly in women. The likelihood of osteoporosis is lower in individuals with high BMI or hyperlipidemia. Some lipid metabolism markers can be used to predict osteoporosis, and further research is needed.

Leveraging its ability to handle large and complex datasets, artificial intelligence can uncover subtle patterns and correlations that human observation may overlook. This is particularly valuable for understanding the intricate dynamics of spinal surgery and its multifaceted impacts on patient prognosis. This review aims to delineate the role of artificial intelligence in spinal surgery. A search of the PubMed database from 1992 to 2023 was conducted using relevant English publications related to the application of artificial intelligence in spinal surgery. The search strategy involved a combination of the following keywords: "Artificial neural network," "deep learning," "artificial intelligence," "spinal," "musculoskeletal," "lumbar," "vertebra," "disc," "cervical," "cord," "stenosis," "procedure," "operation," "surgery," "preoperative," "postoperative," and "operative." A total of 1,182 articles were retrieved. After a careful evaluation of abstracts, 90 articles were found to meet the inclusion criteria for this review. Our review highlights various applications of artificial neural networks in spinal disease management, including (1) assessing surgical indications, (2) assisting in surgical procedures, (3) preoperatively predicting surgical outcomes, and (4) estimating the occurrence of various surgical complications and adverse events. By utilizing these technologies, surgical outcomes can be improved, ultimately enhancing the quality of life for patients.

Background: To date, few reports have evaluated the long-term outcome of percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures (OVCFs) and the factors influencing the long-term outcome of this procedure are uncertain.Methods: A total of 91 patients underwent PKP for thoracolumbar OVCFs from June 2012 to December 2012. Pain Visual Analogue Scores (VAS) and Oswestry Disability Index (ODI) were recorded preoperatively and after 10-year follow-up. Factors that may affect surgical outcome, such as gender, age, height, weight, hypertension, diabetes, cause of injury, fracture segment, length of hospitalization, history of previous spinal surgery, preoperative bone mineral density (BMD), preoperative VAS and ODI scores, length of surgery, bone cement dosage, postoperative standardized anti-osteoporosis treatment, and other new vertebral fractures, were analyzed by multiple linear regression with VAS and ODI scores at the last follow-up. The correlation factors affecting the efficacy were analyzed.Results: The preoperative and final follow-up pain VAS was 7.9 ± 1.1 and 2.2 ± 1.1. ODI scores were 30.4 ± 4.2 and 10.7 ± 2.6. The difference was statistically significant (P < 0.05). Most of the patients were females aged 65–75 years who suffered low-energy injuries, with most of the fracture segments in the thoracolumbar region (T11-L2). At the final follow-up visit, 12 cases (13.19%) developed other new vertebral fractures, and 33 cases (36.26%) continued to adhere to anti-osteoporosis treatment after discharge. Multiple linear regression analysis showed that there was a statistical difference between gender and VAS score at the last follow-up (P < 0.05), and between age, cause of injury and postoperative standardized anti-osteoporosis treatment and ODI at the last follow-up (P < 0.05). There were no statistically significant differences between the other factors and the final follow-up VAS and ODI scores (P > 0.05).Conclusion: The long-term outcome after PKP is satisfactory. Age, gender, cause of injury, and standardized postoperative anti-osteoporosis treatment may be factors affecting the long-term outcome.

Objectives: This study aimed to evaluate the clinical efficacy and safety of percutaneous endoscopic interlaminar discectomy (PEID) for treating highly downward-migrated disc herniation. Methods: We conducted a retrospective study on 39 patients with highly downward-migrated disc herniation who underwent PEID treatment between January 2015 and October 2020. The clinical outcomes, including the preoperative and postoperative visual analogue scale (VAS) for the back and leg, Oswestry Disability Index (ODI), and MacNab criteria for surgical success, were evaluated and compared to thirty-seven patients treated with posterior lumbar interbody fusion (PLIF). Results: The mean operation time of PEID was 93.00(77.00,110.00) min, while that of PLIF was 169.00(157.00,183.00) min. Continued improvement in both PEID and PLIF was observed in the VAS and ODI scores immediately after the surgery to the last follow‐up. The VAS and ODI scores of PEID one week after surgery were significantly different from those of PLIF. One patient with recurrent lumbar disc herniation in the same segment improved after undergoing repeat PEID, two patients had dura tears, and conservative treatment helped relieve the symptoms. The overall percentage of patients with good to excellent results of PELD according to the modified MacNab criteria was 97.43%, while that of PLIF was 94.60%. Conclusions: PEID has reliable efficacy and safety for treating highly downward-migrated disc herniation. And the long-term efficacy of PEID is comparable to PLIF. No severe complications occurred after surgery, and most patients’ symptoms were relieved.

Background: This study aims to explore the correlation between bone metabolism indices and osteoporotic thoracolumbar vertebrae fracture (OTVF) in postmenopausal women. Methods: A total of 447 female patients with postmenopause and underwent OTVF in our hospital were selected as group A. Three hundred eighty-seven out-patients without fractures were selected as group B. Bone metabolism index including the serum levels of total Serum procollagen type N-terminal propeptide (tPINP), the age-related type I cross linked C-telopeptide (beta-CTX) and 25hydroxyvitamin D (25-OHD) were collected and compared. The relation between bone metabolism indices and OTVF was analyzed. Results: The mean tPINP in group A was 61.72 +/- 28.43, which was notably higher than group B (P < 0.01). Meanwhile, greater beta CTX were higher founded in group A than group B (0.778 +/- 0.316 vs 0.669 +/- 0.303 mu g/l). However, the 25-OHD in group A was significantly lower than that in group B (P < 0.05). Multivariate logistic regression analysis revealed that the serum level of tPINP (OR: 0.008, P = 0.011), the serum level of beta-CTX (OR: 0.805, P = 0.002) and the serum level of 25-OHD (OR: -0.029, P = 0.003) were independently correlated with postmenopausal OTVF. Conclusion: Bone metabolic markers play an important role in predicting OTVF. As a reflection of bone mass and bone strength, BMD is inadequate in predicting OTVF. High expression of bone metabolism indicators beta-CTX, tPINP and relatively low expression of 25-OHD suggest an increased risk of OTVF. Early detection of postmenopausal bone metabolism abnormalities can be used for early intervention to reduce the incidence of OTVF.