Objective To evaluate the efficacy and safety of CT-guided percutaneous radiofrequency ablation (RFA) as an alternative for video-assisted thoracoscopic surgery (VATS) in treating multiple pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of 113 patients with multiple pulmonary nodules admitted to Jiangsu Provincial Hospital of Traditional Chinese Medicine from October 2020 to October 2022. The patients were divided into the RFA group (n＝50) and the VATS group (n＝63) based on the treatment method. Perioperative indicators (operation time, intraoperative blood loss, postoperative length of hospital stay), oncological outcomes (recurrence-free survival [RFS], overall survival [OS]), and postoperative complication rates were compared between the two groups. Univariate and multivariate Cox regression analysis was performed to identify independent prognostic factors. Results The operation time in the RFA group was significantly shorter than that in the VATS group ([75.2±20.1] min vs [102.3±28.7]) min, P＜0.001). No statistically significant differences were observed in intraoperative blood loss and postoperative length of hospital stay. After follow-up of 24 (12, 30) months, no statistically significant differences were found in RFS (HR＝1.25, P＝0.445) or OS (HR＝1.42, P＝0.402) between the two groups. Mixed ground-glass nodules with high solid component and solid nodule were identified as independent risk factors for RFS (HR＝2.44, P＝0.023; HR＝2.97, P＝0.007) and OS (HR＝2.87, P＝0.022; HR＝3.43, P＝0.005) in patients with multiple pulmonary nodules. The total complication rate in the RFA group was lower than that in the VATS group (12.0% vs 34.9%, P＝0.009). Conclusions The efficacy of CT-guided RFA in treating multiple pulmonary nodules is comparable to that of VATS, with good safety, and it shows promise as an alternative to surgical treatment for multiple pulmonary nodules.

BACKGROUND:The sports medicine community has widely called for the use of machine learning technology to efficiently process the huge and complicated sports data resources,and construct intelligent sports injury prediction models,enabling accurate early warning of sports injuries.It is of great significance to comprehensively summarize and review such research results so as to grasp the direction of early warning model improvement and to guide the construction of sports injury prediction models in China. OBJECTIVE:To systematically review and analyze relevant research on sports injury prediction models based on machine learning technology,thereby providing references for the development of sports injury prediction models in China. METHODS:Literature search was conducted on CNKI,Web of Science and EBSCO databases,which mainly searched for literature related to machine learning techniques and sports injuries.Finally,61 articles related to sports injury prediction models were included for analysis. RESULTS AND CONCLUSION:(1)In terms of external risk feature indicators,there is a lack of competition scenario indicators,and the inclusion of related feature indicators needs to be further improved to further enrich the dimensions of the dataset for model training.In addition,the inclusion feature weighting methods of the sports injury prediction model are mainly based on filtering methods and the use of embedding and wrapping weighting methods needs to be strengthened in order to enhance the analysis of the interaction effects of multiple risk factors.(2)In terms of model body training,supervised learning algorithms become the mainstream choice.Such algorithms have higher requirements for the completeness of sample labeling information,and the application scenarios are easily limited.Therefore,the application of unsupervised and semi-supervised algorithms can be increased in the later stage.(3)In terms of model performance evaluation and optimization,the current studies mainly adopt two verification methods:HoldOut crossover and k-crossover.The range of AUC values is(0.76±0.12),the range of sensitivity is(75.92±11.03)%,the range of specificity is(0.03±4.54)%,the range of F1 score is(80.60±10.63)%,the range of accuracy is(69.96±13.10)%,and the range of precision is(70±14.71)%.Data augmentation and feature optimization are the most common model optimization operations.The accuracy and precision of the current sports injury prediction model are about 70%,and the early warning effect is good.However,the model optimization operation is relatively single,and data augmentation methods are often used to improve model performance.Further adjustments to the model algorithm and hyperparameters are needed to further improve model performance.(4)In terms of model feature extraction,most of the internal risk profile indicators included are mainly based on anthropometrics,training load,years of training,and injury history,but there is a lack of sports recovery and physical function indicators.

The menopausal age is one of the important menopausal factors, and women of different menopausal ages have different risks of diabetes. This study reviewed the evidence from prospective studies on the association between the age at natural menopause and diabetes risk, both domestically and internationally, and presented its research design and main findings. Advanced menopause, especially premature and early menopause, will increase the risk of diabetes in postmenopausal women. The research on the influence of delayed menopause on the incidence of diabetes is still insufficient. Many factors may modify the association between menopausal age and the risk of diabetes.

The menopausal age is one of the important menopausal factors, and women of different menopausal ages have different risks of diabetes. This study reviewed the evidence from prospective studies on the association between the age at natural menopause and diabetes risk, both domestically and internationally, and presented its research design and main findings. Advanced menopause, especially premature and early menopause, will increase the risk of diabetes in postmenopausal women. The research on the influence of delayed menopause on the incidence of diabetes is still insufficient. Many factors may modify the association between menopausal age and the risk of diabetes.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Puerariae Lobatae Radix, as a traditional Chinese medicine(TCM) with both medicinal and edible properties, possesses effects such as relieving muscle tension and fever, generating fluids and quenching thirst, and unblocking the meridians and collaterals. Modern fermentation technology, combined with microecology and modern bioengineering, can regulate the fermentation process and efficiently produce fermentation products. In recent years, modern fermentation technology has been widely applied in TCM, enhancing or altering efficacy, reducing toxicity, and expanding the scope of clinical applications. This paper reviewed the current research on Puerariae Lobatae Radix fermentation, including fermentation methods, strain selection, fermentation processes, and pharmacological effects, with the aim of providing a reference for further in-depth research, development, and utilization of Puerariae Lobatae Radix fermentation.
Pueraria/chemistry* ; Fermentation ; Drugs, Chinese Herbal/chemistry* ; Humans ; Animals

Objective: To investigate the correlation between magnetic resonance imaging-based vertebral bone quality (VBQ) score and screw loosening after dynamic pedicle screw fixation with polyetheretherketone (PEEK) rods, and evaluate its predictive value. Methods: A retrospective analysis was conducted on the patients who underwent dynamic pedicle screw fixation with PEEK rods from March 2017 to June 2022. Data on age, sex, body mass index, hypertension, diabetes, hyperlipidemia history, long-term smoking, alcohol consumption, VBQ score, L1–4 average Hounsfield unit (HU) value, surgical fixation length, and the lowest instrumented vertebra were collected. Logistic regression analysis was employed to assess the relationship between VBQ score and pedicle screw loosening (PSL). Results: A total of 24 patients experienced PSL after surgery (20.5%). PSL group and non-PSL group showed statistical differences in age, number of fixed segments, fixation to the sacrum, L1–4 average HU value, and VBQ score (p < 0.05). The VBQ score in the PSL group was higher than that in the non-PSL group (3.56 ± 0.45 vs. 2.77 ± 0.31, p < 0.001). In logistic regression analysis, VBQ score (odds ratio, 3.425; 95% confidence interval, 1.552–8.279) were identified as independent risk factors for screw loosening. The area under the receiver operating characteristic curve for VBQ score predicting PSL was 0.819 (p < 0.05), with the optimal threshold of 3.15 (sensitivity, 83.1%; specificity, 80.5%). Conclusion The VBQ score can independently predict postoperative screw loosening in patients undergoing lumbar dynamic pedicle screw fixation with PEEK rods, and its predictive value is comparable to HU value.

Objective: To investigate the correlation between magnetic resonance imaging-based vertebral bone quality (VBQ) score and screw loosening after dynamic pedicle screw fixation with polyetheretherketone (PEEK) rods, and evaluate its predictive value. Methods: A retrospective analysis was conducted on the patients who underwent dynamic pedicle screw fixation with PEEK rods from March 2017 to June 2022. Data on age, sex, body mass index, hypertension, diabetes, hyperlipidemia history, long-term smoking, alcohol consumption, VBQ score, L1–4 average Hounsfield unit (HU) value, surgical fixation length, and the lowest instrumented vertebra were collected. Logistic regression analysis was employed to assess the relationship between VBQ score and pedicle screw loosening (PSL). Results: A total of 24 patients experienced PSL after surgery (20.5%). PSL group and non-PSL group showed statistical differences in age, number of fixed segments, fixation to the sacrum, L1–4 average HU value, and VBQ score (p < 0.05). The VBQ score in the PSL group was higher than that in the non-PSL group (3.56 ± 0.45 vs. 2.77 ± 0.31, p < 0.001). In logistic regression analysis, VBQ score (odds ratio, 3.425; 95% confidence interval, 1.552–8.279) were identified as independent risk factors for screw loosening. The area under the receiver operating characteristic curve for VBQ score predicting PSL was 0.819 (p < 0.05), with the optimal threshold of 3.15 (sensitivity, 83.1%; specificity, 80.5%). Conclusion The VBQ score can independently predict postoperative screw loosening in patients undergoing lumbar dynamic pedicle screw fixation with PEEK rods, and its predictive value is comparable to HU value.

Objective: To investigate the correlation between magnetic resonance imaging-based vertebral bone quality (VBQ) score and screw loosening after dynamic pedicle screw fixation with polyetheretherketone (PEEK) rods, and evaluate its predictive value. Methods: A retrospective analysis was conducted on the patients who underwent dynamic pedicle screw fixation with PEEK rods from March 2017 to June 2022. Data on age, sex, body mass index, hypertension, diabetes, hyperlipidemia history, long-term smoking, alcohol consumption, VBQ score, L1–4 average Hounsfield unit (HU) value, surgical fixation length, and the lowest instrumented vertebra were collected. Logistic regression analysis was employed to assess the relationship between VBQ score and pedicle screw loosening (PSL). Results: A total of 24 patients experienced PSL after surgery (20.5%). PSL group and non-PSL group showed statistical differences in age, number of fixed segments, fixation to the sacrum, L1–4 average HU value, and VBQ score (p < 0.05). The VBQ score in the PSL group was higher than that in the non-PSL group (3.56 ± 0.45 vs. 2.77 ± 0.31, p < 0.001). In logistic regression analysis, VBQ score (odds ratio, 3.425; 95% confidence interval, 1.552–8.279) were identified as independent risk factors for screw loosening. The area under the receiver operating characteristic curve for VBQ score predicting PSL was 0.819 (p < 0.05), with the optimal threshold of 3.15 (sensitivity, 83.1%; specificity, 80.5%). Conclusion The VBQ score can independently predict postoperative screw loosening in patients undergoing lumbar dynamic pedicle screw fixation with PEEK rods, and its predictive value is comparable to HU value.

Objective: To investigate the correlation between magnetic resonance imaging-based vertebral bone quality (VBQ) score and screw loosening after dynamic pedicle screw fixation with polyetheretherketone (PEEK) rods, and evaluate its predictive value. Methods: A retrospective analysis was conducted on the patients who underwent dynamic pedicle screw fixation with PEEK rods from March 2017 to June 2022. Data on age, sex, body mass index, hypertension, diabetes, hyperlipidemia history, long-term smoking, alcohol consumption, VBQ score, L1–4 average Hounsfield unit (HU) value, surgical fixation length, and the lowest instrumented vertebra were collected. Logistic regression analysis was employed to assess the relationship between VBQ score and pedicle screw loosening (PSL). Results: A total of 24 patients experienced PSL after surgery (20.5%). PSL group and non-PSL group showed statistical differences in age, number of fixed segments, fixation to the sacrum, L1–4 average HU value, and VBQ score (p < 0.05). The VBQ score in the PSL group was higher than that in the non-PSL group (3.56 ± 0.45 vs. 2.77 ± 0.31, p < 0.001). In logistic regression analysis, VBQ score (odds ratio, 3.425; 95% confidence interval, 1.552–8.279) were identified as independent risk factors for screw loosening. The area under the receiver operating characteristic curve for VBQ score predicting PSL was 0.819 (p < 0.05), with the optimal threshold of 3.15 (sensitivity, 83.1%; specificity, 80.5%). Conclusion The VBQ score can independently predict postoperative screw loosening in patients undergoing lumbar dynamic pedicle screw fixation with PEEK rods, and its predictive value is comparable to HU value.