Restless legs syndrome （RLS） is a common neurological sensory-motor disorder， and the diagnosis of RLS mainly rely on the subjective clinical symptoms described by the patient， with a lack of specific auxiliary examinations or biomarkers. The diagnosis of this disease is still challenging for atypical cases. Various other diseases may have similar clinical symptoms as RLS， such as leg discomfort， leg pain and abnormal leg movement. This article summarizes the RLS mimics that might be confused with RLS symptoms， including the neurogenic， vascular， and musculoskeletal factors that might cause leg discomfort and pain， as well as the differential diagnosis of sleep-related movement disorders with symptoms overlapped with RLS， so as to help clinicians recognize RLS phenotype and provide a reference for the diagnosis of diseases that might be confused with RLS.

Cerebral small vessel disease （CSVD） is a spectrum of pathological conditions affecting intracranial small blood vessels and is associated with a variety of clinical manifestations， including cognitive impairment， gait abnormalities， and sleep disorders. In recent years， the association between CSVD and sleep disorders has attracted increasing attention. This article reviews the association of CSVD with various sleep disorders such as obstructive/central sleep apnea hypoventilation syndrome， restless legs syndrome， and insomnia， analyzes the mechanisms by which sleep disorders cause CSVD， and proposes potential directions for future research.

Phantom limb pain (PLP) is a form of neuropathic pain occurring after limb amputation, and its underlying mechanisms remain unclear, posing significant challenges for clinical management. Spinal cord stimulation (SCS), a neuromodulation technique, has shown potential in relieving chronic pain, though its long-term efficacy and safety in treating PLP require further validation. This report presents a case of a 42-year-old male experiencing persistent radiating, lightning-like pain [Visual Analog Scale (VAS) score 8-9], following right upper limb amputation. Preoperative imaging revealed signal loss in the right nerve roots at C₆-T₁. A percutaneous electrode was implanted surgically to achieve full coverage of the painful region. Five days postoperatively, the VAS score dropped to 2-3, and after 1 year of follow-up, the patient continued to experience significant pain relief (VAS 1-2), with complete resolution of depressive symptoms and cessation of analgesic medication. Existing studies suggest that the long-term outcomes of SCS may fluctuate, and attention should be paid to potential complications such as infection and electrode displacement.
Humans ; Phantom Limb/therapy* ; Male ; Adult ; Spinal Cord Stimulation/methods* ; Electrodes, Implanted ; Amputation, Surgical/adverse effects*

Objective To evaluate the safety and therapeutic efficacy of three-dimensional(3D)-printed personalized cervical correction pillows for treating cervical spondylotic radiculopathy.Methods A finite element model was established to simulate and analyze the biomechanical changes in cervical spine before and after using the pillow.Additionally,20 patients with chronic neck pain were included to analyze changes in visual analogue scale(VAS)scores,neck disability index(NDI),pressure pain threshold(PPT),Borden value,cervical lordosis,T1 slope,cervical slope,and thoracic inlet angle before and after using the pillow.Results Finite element analysis indicated that the maximum stress on vertebral bodies increased by 64.35％and the maximum stress on cartilage tissues by 5.09％after using the pillow.The Borden value improved by 45.75％.Clinical studies showed a significant reduction in VAS scores,NDI,and PPT after treatment(P＜0.05),while PPT,Borden value,cervical lordosis,T1 slope,and thoracic inlet angle significantly increased(P＜0.05).Conclusions The 3D-printed personalized cervical correction pillow is safe and effective in alleviating neck pain and improving cervical curvature,and it provides a new and effective non-surgical treatment option for cervical spondylotic radiculopathy,with significant clinical implications.

Objective A Cobb angle prediction model for adolescent idiopathic scoliosis(AIS)based on three-point mechanical data from three-dimensional(3D)-printed orthotics and various machine learning algorithms was developed,so as to provide an innovative,radiation-free method for early clinical screening and monitoring of AIS.Methods Clinical data from AIS patients and mechanical data from 3D-printed orthotics were collected to construct a comprehensive dataset with features such as gender,age,disease type,weight,and Risser score.Six algorithms,namely,random forest,support vector regression,gradient boosting regressor,extreme gradient boosting,lightgbm,and catboost,were used to construct and evaluate the performance of Cobb angle prediction models.Results The gradient boosting regressor model had the best performance on several evaluation metrics,achieving a precision rate of 0.937,recall rate of 0.818,F1-score of 0.949,and an area under curve(AUC)value of 0.843.In the validation set,the model's predictions reached an accuracy rate of 0.942,fitting well with the actual Cobb values.Conclusions The Cobb angle prediction model based on mechanical data and machine learning effectively avoids the radiation risks associated with traditional full-spine X-ray examinations in early clinical screening.It provides a non-invasive assessment for AIS patients,enhancing the safety and efficiency of screening and monitoring,and offering a powerful decision-making tool for clinicians,with a great clinical significance.

Objective A Cobb angle prediction model for adolescent idiopathic scoliosis(AIS)based on three-point mechanical data from three-dimensional(3D)-printed orthotics and various machine learning algorithms was developed,so as to provide an innovative,radiation-free method for early clinical screening and monitoring of AIS.Methods Clinical data from AIS patients and mechanical data from 3D-printed orthotics were collected to construct a comprehensive dataset with features such as gender,age,disease type,weight,and Risser score.Six algorithms,namely,random forest,support vector regression,gradient boosting regressor,extreme gradient boosting,lightgbm,and catboost,were used to construct and evaluate the performance of Cobb angle prediction models.Results The gradient boosting regressor model had the best performance on several evaluation metrics,achieving a precision rate of 0.937,recall rate of 0.818,F1-score of 0.949,and an area under curve(AUC)value of 0.843.In the validation set,the model's predictions reached an accuracy rate of 0.942,fitting well with the actual Cobb values.Conclusions The Cobb angle prediction model based on mechanical data and machine learning effectively avoids the radiation risks associated with traditional full-spine X-ray examinations in early clinical screening.It provides a non-invasive assessment for AIS patients,enhancing the safety and efficiency of screening and monitoring,and offering a powerful decision-making tool for clinicians,with a great clinical significance.

Objective To evaluate the safety and therapeutic efficacy of three-dimensional(3D)-printed personalized cervical correction pillows for treating cervical spondylotic radiculopathy.Methods A finite element model was established to simulate and analyze the biomechanical changes in cervical spine before and after using the pillow.Additionally,20 patients with chronic neck pain were included to analyze changes in visual analogue scale(VAS)scores,neck disability index(NDI),pressure pain threshold(PPT),Borden value,cervical lordosis,T1 slope,cervical slope,and thoracic inlet angle before and after using the pillow.Results Finite element analysis indicated that the maximum stress on vertebral bodies increased by 64.35％and the maximum stress on cartilage tissues by 5.09％after using the pillow.The Borden value improved by 45.75％.Clinical studies showed a significant reduction in VAS scores,NDI,and PPT after treatment(P＜0.05),while PPT,Borden value,cervical lordosis,T1 slope,and thoracic inlet angle significantly increased(P＜0.05).Conclusions The 3D-printed personalized cervical correction pillow is safe and effective in alleviating neck pain and improving cervical curvature,and it provides a new and effective non-surgical treatment option for cervical spondylotic radiculopathy,with significant clinical implications.

Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.

Severe acute pancreatitis(SAP)is a critical condition in general surgery settings,characterized by high mortality and poor prognosis.On February 28,2024,the Department of Hepatobiliary Surgery at the First Affiliated Hospital of Harbin Medical University admitted a 36-year-old male patient.The patient presented with"upper abdominal pain accompanied by fever for three months and jaundice of the skin and sclera for one week."Physical examination revealed 11 puncture tubes,and a palpable mass measuring 3 cm × 5 cm in the upper abdomen.Enhanced CT and magnetic resonance cholangiopancreatography indicated acute pancreatitis.The patient was diagnosed with"SAP,infectious pancreatic necrosis,and biliary stenosis."He had severe abdominal infection and complex postoperative complications,making treatment challenging.Consequently,a multidisciplinary team(MDT)consultation was initiated.After three rounds of MDT consulfation and freating,the patient ultimately recovered successfully and was discharged.This article reviews the MDT treatment process for this patient and summarizes the characteristics of this condition based on relevant literature to provide insights and experience for clinical practice.

Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.