OBJECTIVE: To explore the feasibility of using biomechanical indicators as supplementary evaluation to the Musculoskeletal Tumor Society Scoring System (MSTS) for amputee patients. METHODS: Twenty-four patients who underwent hemipelvectomy between September 2018 and January 2025 were enrolled. There were 15 males and 9 females with an average age of 61.4 years (range, 45-76 years). Participants performed gait tests at self-selected speeds using three assistive devices (prosthesis, single crutch, and double crutches). Motion data were analyzed using a customized OpenSim model. Biomechanical indicators of the intact limb exhibiting common characteristics were screened through correlation and sensitivity analyses. Test-retest reliability [interclass correlation coefficient (ICC)] of selected parameters was assessed to evaluate their potential as MSTS score supplements. RESULTS: All biomechanical indicators showed significant positive correlations with MSTS scores across assistive devices ( P<0.05). Seven indicators demonstrated |Pearson correlation coefficients|>0.8, including walking speed, maximum hip angle, maximum hip moment, peak hip flexion moment, peak hip extension moment, hip flexion impulse, and hip extension impulse. Among these, maximum hip moment, hip flexion impulse, and hip extension impulse exhibited significant between-group differences in adjacent MSTS levels ( P<0.05), indicating high sensitivity, along with excellent test-retest reliability (ICC>0.74, P<0.01). CONCLUSION Biomechanical indicators statistically qualify as potential supplements to MSTS scoring. Maximum hip moment, hip flexion impulse, and hip extension impulse demonstrate particularly high sensitivity to MSTS score variations.
Humans ; Male ; Middle Aged ; Female ; Aged ; Biomechanical Phenomena ; Amputees/rehabilitation* ; Feasibility Studies ; Artificial Limbs ; Reproducibility of Results ; Amputation, Surgical ; Crutches ; Gait

OBJECTIVE: To investigate the load distribution on the more painful and less painful limbs in patients with mild-to-moderate and severe bilateral knee osteoarthritis (KOA) and explore the compensatory mechanisms in both limbs among bilateral KOA patients with different severity levels. METHODS: A total of 113 participants were enrolled between July 2022 and September 2023. This cohort comprised 43 patients with mild-to-moderate bilateral KOA (Kellgren-Lawrence grade 2-3), 43 patients with severe bilateral KOA (Kellgren-Lawrence grade 4), and 27 healthy volunteers (healthy control group). The visual analogue scale (VAS) score for pain, the Hospital for Special Surgery (HSS) score, passive knee range of motion (ROM), and hip-knee-ankle angle (HKA) were used to assess walking pain intensity, joint function, and lower limb alignment in KOA patients, respectively. Motion trajectories of reflective markers and ground reaction force data during walking were captured using a gait analysis system. Musculoskeletal modeling was then employed to calculate biomechanical parameters, including the peak knee adduction moment (KAM), KAM impulse, peak joint contact force (JCF), and peak medial/lateral contact forces (MCF/LCF). Statistical analyses were performed to compare differences in clinical and gait parameters between bilateral limbs. Additionally, one-dimensional statistical parametric mapping was utilized to analyze temporal gait data. RESULTS: Mild-to-moderate KOA patients showed the significantly higher HSS score (67.7±7.9) than severe KOA patients (51.9±8.9; t=8.747, P<0.001). The more painful limb in all KOA patients exhibited significantly greater HKA and higher VAS scores compared to the less painful limb ( P<0.05). While bilateral knee ROM did not differ significantly in mild-to-moderate KOA patients ( P>0.05), the severe KOA patients had significantly reduced ROM in the more painful limb versus the less painful limb ( P<0.05). Healthy controls showed no significant bilateral difference in any biomechanical parameters ( P>0.05). All KOA patients demonstrated longer stance time on the less painful limb ( P<0.05). Critically, severe KOA patients exhibited significantly higher peak KAM, KAM impulse, and peak MCF in the more painful limb ( P<0.05), while mild-to-moderate KOA patients showed the opposite pattern with lower peak KAM and KAM impulse in the more painful limb ( P<0.05) and a similar trend for peak MCF. CONCLUSION Patients with mild-to-moderate KOA effectively reduce load on the more painful limb through compensatory mechanisms in the less painful limb. Conversely, severe bilateral varus deformities in advanced KOA patients nullify compensatory capacity in the less painful limb, paradoxically increasing load on the more painful limb. This dichotomy necessitates personalized management strategies tailored to disease severity.
Humans ; Osteoarthritis, Knee/physiopathology* ; Range of Motion, Articular ; Male ; Female ; Middle Aged ; Biomechanical Phenomena ; Knee Joint/physiopathology* ; Pain Measurement ; Severity of Illness Index ; Aged ; Gait/physiology* ; Walking/physiology* ; Case-Control Studies ; Adult ; Weight-Bearing

OBJECTIVE: To explore, identify, and develop novel blood-based indicators using machine learning algorithms for accurate preoperative assessment and effective prediction of postoperative complication risks in patients with rheumatoid arthritis (RA) undergoing total knee arthroplasty (TKA). METHODS: A retrospective cohort study was conducted including RA patients who underwent unilateral TKA between January 2019 and December 2024. Inpatient and 30-day postoperative outpatient follow-up data were collected. Six machine learning algorithms, including decision tree, random forest, logistic regression, support vector machine, extreme gradient boosting, and light gradient boosting machine, were used to construct predictive models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F1-score, accuracy, precision, and recall. SHapley Additive exPlanations (SHAP) values were employed to interpret and rank the importance of individual variables. RESULTS: According to the inclusion criteria, a total of 1 548 patients were enrolled. Ultimately, 18 preoperative indicators were identified as effective predictive features, and 8 postoperative complications were defined as prediction labels for inclusion in the study. Within 30 days after surgery, 453 patients (29.2%) developed one or more complications. Considering overall accuracy, precision, recall, and F1-score, the random forest model [AUC=0.930, 95% CI (0.910, 0.950)] and the extreme gradient boosting model [AUC=0.909, 95% CI (0.880, 0.938)] demonstrated the best predictive performance. SHAP analysis revealed that anti-cyclic citrullinated peptide antibody, C-reactive protein, rheumatoid factor, interleukin-6, body mass index, age, and smoking status made significant contributions to the overall prediction of postoperative complications. CONCLUSION Machine learning-based models enable accurate prediction of postoperative complication risks among RA patients undergoing TKA. Inflammatory and immune-related blood biomarkers, such as anti-cyclic citrullinated peptide antibody, C-reactive protein, and rheumatoid factor, interleukin-6, play key predictive roles, highlighting their potential value in perioperative risk stratification and individualized management.
Humans ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthritis, Rheumatoid/blood* ; Machine Learning ; Postoperative Complications/blood* ; Female ; Male ; Retrospective Studies ; Middle Aged ; Aged ; Risk Factors ; Preoperative Period ; C-Reactive Protein/analysis* ; Risk Assessment

OBJECTIVE: To compare the short-term clinical efficacy and safety of closed reduction with Kirschner wire fixation versus open reduction with plate fixation for treating osteoporotic Colles' fractures in middle-aged and elderly patients. METHODS: Between January 2018 and January 2023, 119 patients with Colles fractures were retrospectively analyzed, including 39 males and 80 females, aged from 48 to 74 years old with an average of(60.58±6.71) years old. The time from injury to operation ranged 1 to 13 days with an average of (5.29±2.52) days. According to the surgical method, they were divided into Kirschner wire fixation group (Kirschner wire group) and plate internal fixation group (plate group). In Kirschner wire group, there were a total of 68 patients, comprising 21 males and 47 females. The average age was (61.15±6.24) years old, ranged from 49 to 74 years old. Among them, 41 cases involved the left side while 27 cases involved the right side. In the plate group, there were a total of 51 patients, including 18 males and 33 females. The average age was (59.78±5.71) years old ranged from 48 to 72 years old. Among them, there were 31 cases on the left side and 20 cases on the right side. The following parameters were recorded before and after the operation:operation time, intraoperative blood loss, hospitalization days, hospitalization expenses, postoperative complications, and radiographic parameters of distal radius (distal radius height, ulnar deviation angle, palmar tilt angle). The clinical efficacy was evaluated at 3 and 12 months after the operation using Gartland-Werley and disabilites of the arm shoulder and hand (DASH) scores. RESULTS: The patients in both groups were followed up for a duration from 12 to 19 months with an average of(13.32±2.02) months. The Kirschner wire group exhibited significantly shorter operation time compared to the plate group 27.91(13.00, 42.00) min vs 67.52(29.72, 105.32) min, Z=-8.74, P=0.00. Intraoperative blood loss was also significantly lower in the Kirschner wire group than in the plate group 3.24(1.08, 5.40) ml vs 21.91(17.38, 26.44) ml, Z=-9.31, P=0.00. Furthermore, patients in the Kirschner wire group had a shorter length of hospital stay compared to those in the plate group (8.38±2.63) days vs (11.40±2.78) days, t=-3.12, P=0.00. Additionally, hospitalization cost was significantly lower in the Kirschner wire group than in the plate group 10 111.29(6 738.98, 13 483.60) yuan vs 15 871.11(11 690.40, 20 051.82) yuan, Z=-5.62, P=0.00. The incidence of complications was 2 cases in the Kirschner wire group and 1 case in the plate group, with no statistically significant difference(P>0.05). At 3 months postoprative, the radial height of the Kirschner wire group was found to be significantly smaller than that of the plate group, with measurements of (11.45±1.69) mm and (12.11±1.78) mm respectively (t=-2.06, P=0.04). However, there were no statistically significant differences observed in ulnar deviation angle and palmar tilt angle between the two groups (P>0.05). The DASH score and Gartland-Werley score in the Kirschner group were significantly higher than those in the plate group at 3 months post-operation (19.10±9.89) vs (13.47±3.51), t=4.34, P=0.00;(11.15±3.61) vs (6.41±2.75), t=8.13, P=0.00). However, there was no significant difference between the two groups at 12 months post-operation (P>0.05). CONCLUSION Compared to plate internal fixation, closed reduction with Kirschner wire support fixation yields a slightly inferior recovery of radial height;however, there is no significant disparity in the functional score of the affected limb at 12 months post-operation. Nonetheless, this technique offers advantages such as shorter operation time, reduced intraoperative blood loss, decreased hospitalization duration, and lower cost.
Humans ; Female ; Male ; Middle Aged ; Aged ; Fracture Fixation, Internal/instrumentation* ; Bone Wires ; Bone Plates ; Retrospective Studies ; Colles' Fracture/surgery* ; Minimally Invasive Surgical Procedures/methods* ; Open Fracture Reduction/methods* ; Osteoporotic Fractures/surgery*

OBJECTIVE: To investigate the effects of bone density, plate bending degree and proximal screw type on the stress fracture of clavicle hook. METHODS: Three sows weighing between 45 and 50 kg were selected, from which a total of 40 rivs were collected. The 15 ribs of sows were divided into 3 groups according to bone density and bone hardness with 5 rivs in each group. And then the 3 groups were fixed with 6-hole collarbone hook plates and 3 locking screws. Measure the maximum torsion force when the ribs were fractured by force. The same size 15 rids were divided into 3 groups, named forward bending group, 0° group(the angle between the plate surface and the rib surface) and reverse bending group. All fixed with 6-hole collarbone hook plates and locking screws to measure the maximum torsion force of rib stress fracture. Then the same size 10 rids were divided into 2 groups, the normal screw group and the locking screw group with 5 ribs in each group. Both groups were fixed with 6-hole collarbone hook plates and screws. The normal screw group was a normal screw, fixed in proximal end, and two locking screws. The locking screw group was fixed by locking screws. Measure the maximum torsion force of the two groups when the ribs fracture by force. RESULTS: In the bone density experiment, the torque force of hard bone group (104.51±6.27) N was greater than the normal bone group (75.04±3.81) N(t=8.979, P<0.05). The force of normal bone group was greater than the osteoporosis group (49.99±2.12) N(t=12.832, P<0.05). In the bending collarbone hook experiment, the order of the torque force generated by each group as follow:the forward bending group (343.59±6.18) N greater than the 0° group (106.01±5.29) N(t=65.279, P<0.05) greater than the reverse bending group (95.82±4.12) N(t=3.398, P<0.05). The force of the normal screw group (98.68±0.70) N was greater than the locking screw group (50.20±0.95) N(t=91.484, P<0.05). The data comparisons of each group were statistically significant. CONCLUSION Bone density, plate bending degree and proximal screw type had an impact on stress fracture of clavicle hook plate. Higher bone density, forward bending of the steel plate, and ordinary screws in proximal end can reduce the rates of stress fractures of clavicle hooks.
Animals ; Bone Plates ; Clavicle/surgery* ; Swine ; Fractures, Stress/etiology* ; Female ; Risk Factors ; Fracture Fixation, Internal/instrumentation* ; Bone Screws ; Biomechanical Phenomena ; Bone Density

BACKGROUND: It is inaccurate to reflect the level of dust exposure through working years. Furthermore, identifying a predictive indicator for lung function decline is significant for coal miners. The study aimed to explored whether club cell secretory protein (CC16) levels can reflect early lung function changes. METHODS: The cumulative respiratory dust exposure (CDE) levels of 1,461 coal miners were retrospectively assessed by constructed a job-exposure matrix to replace working years. Important factors affecting lung function and CC16 were selected by establishing random forest models. Subsequently, the potential of CC16 to reflect lung injury was explored from multiple perspectives. First, restricted cubic spline (RCS) models were used to compare the trends of changes in lung function indicators and plasma CC16 levels after dust exposure. Then mediating analysis was performed to investigate the role of CC16 in the association between dust exposure and lung function decline. Finally, the association between baseline CC16 levels and follow-up lung function was explored. RESULTS: The median CDE were 35.13 mg/m³-years. RCS models revealed a rapid decline in forced vital capacity (FVC), forced expiratory volume in the first second (FEV₁), and their percentages of predicted values when CDE exceeded 25 mg/m³-years. The dust exposure level (<5 mg/m³-years) causing significant changes in CC16 was much lower than the level (25 mg/m³-years) that caused changes in lung function indicators. CC16 mediated 11.1% to 26.0% of dust-related lung function decline. Additionally, workers with low baseline CC16 levels experienced greater reductions in lung function in the future. CONCLUSIONS CC16 levels are more sensitive than lung indicators in reflecting early lung function injury and plays mediating role in lung function decline induced by dust exposure. Low baseline CC16 levels predict poor future lung function.
Uteroglobin/blood* ; Humans ; Dust/analysis* ; Occupational Exposure/analysis* ; Male ; Middle Aged ; Adult ; Retrospective Studies ; Lung Injury/chemically induced* ; Coal Mining ; Biomarkers/blood* ; China/epidemiology* ; Air Pollutants, Occupational ; Female

OBJECTIVES: To assess the efficacy and safety of Tiaozhou Ziyin (TZZY) recipe for treatment of premature ovarian insufficiency (POI) and explore the possible mechanisms. METHODS: We used bioinformatics analyses and network pharmacology to identify the main active ingredients in TZZY recipe and their core targets, which were verified by Western blotting. We tested the efficacy and safety of the recipe in 60 POI patients, who were randomized into control group (n=30) with Femoston treatment and TZZY group (n=30) with additional TZZY recipe treatment for 3 menstrual cycles. RESULTS: The core active ingredients of TZZY recipe included kaempferol, β-sitosterol, luteolin, and quercetin. The core targets included SRC, TP53, STAT3, PIK3CA, and MAPK3, which were involved in positive regulation of cell movement and protein phosphorylation, the cancer pathways and the PI3K-Akt signaling pathway. Molecular docking showed that the core active ingredients had good binding ability with the core targets. In female rat models of POI, TZZY recipe treatment significantly up-regulated ovarian expressions of p-PI3K and p-Akt proteins. In the clinical trial, treatment with Femoston and Femoston plus TZZY recipe both significantly increased E₂ levels and reduced FSH and LH levels and Kupperman scores of the patients, and the combined treatment produced significantly stronger effects. Both treatments increased the number of antral follicles of the patients, but the combined treatment also significantly increased the levels of AMH. CONCLUSIONS The therapeutic mechanism of TZZY recipe for POI involves multiple active ingredients, multiple therapeutic targets and multiple pathways, and activating the PI3K /Akt pathway is one of its main mechanisms of action, to improve ovarian reserve function, alleviate clinical symptoms, and enhance clinical efficacy in POI patients.
Female ; Primary Ovarian Insufficiency/drug therapy* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Animals ; Rats ; Molecular Docking Simulation ; Signal Transduction ; Sitosterols/therapeutic use* ; Kaempferols/therapeutic use*

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To analyze and evaluate the early warning efficacy of D-dimer/albumin ratio(DAR)combined with interleukin-6(IL-6)and fibrin degradation products(FDP)in the postoperative treatment of acute Stanford type A aortic dissection(ATAAD).Methods A retrospective cohort study was conducted on 284 ATAAD patients who underwent the Sun's procedure at our hospital from July 2024 to March 2025.Patients were divided into a non-adverse outcome group(n=196)and an adverse outcome group(n=88)based on the occurrence of postop-erative complications within 30 days,including acute renal failure requiring dialysis,secondary thoracotomy for hemostasis,severe neurological complications,multiple organ failure,or all-cause mortality.Preoperative baseline data,perioperative parameters,and laboratory indicators were collected via the electronic medical record system.The Mann-Whitney U test was used to compare the differences between groups for continuous variables that did not conform to the normal distribution,and Chi-square test or Fisher's exact test was selected for statistical difference analysis according to the frequency distribution characteristics of categorical variables.On the basis of univariate analysis,multivariate logistic regression analysis was used to screen independent risk factors.Results Statistically significant differences were observed between the non-adverse and adverse outcome group in age,cardiopulmonary bypass time,lactate dehydrogenase(LDH),IL-6,D-dimer(D-D),FDP,and DAR levels(P<0.05).Multivariate analysis revealed that DAR,IL-6,D-D,FDP,and prolonged cardiopulmonary bypass time were independent risk factors for adverse postoperative outcomes(P<0.05).Combined detection analysis demonstrated that the combination of DAR,IL-6,FDP,and cardiopulmonary bypass time yielded the highest predictive efficacy,with an area under the ROC curve of 0.886(95％CI:0.846～0.927).Conclusion The combination of DAR,IL-6,FDP,and cardio-pulmonary bypass time effectively predicts adverse postoperative outcomes in ATAAD patients.This biomarker panel may serve as a robust predictive tool for postoperative risk stratification.

Background Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with the development of metabolic syndrome (MS). However, the role of amino acids in PAH-induced MS remains unclear. Objective To explore the impact of PAHs exposure on the incidence of MS among coking workers, and to determine potential modifying effect of amino acid on this relationship. Methods Unmatched nested case-control design was adopted and the baseline surveys of coking workers were conducted in two plants in Taiyuan in 2017 and 2019, followed by a 4-year follow-up. The cohort comprised 667 coking workers. A total of 362 participants were included in the study, with 84 newly diagnosed cases of MS identified as the case group and 278 as the control group. Urinary levels of 11 PAH metabolites and plasma levels of 17 amino acids were measured by ultrasensitive performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Logistic regression was used to estimate the association between individual PAH metabolites and MS. Stratified by the median concentration of amino acids, Bayesian kernel machine regression (BKMR) model was employed to assess the mixed effects of PAHs on MS. Due to the skewed data distribution, all PAH metabolites and amino acids in the analysis were converted by natural logarithm ln (expressed as lnv). Results The median age of the 362 participants was 37 years, and 83.2% were male. Compared to the control group, the case group exhibited higher concentrations of urinary 2-hydroxyphenanthrene (2-OHPhe), 9-hydroxyphenanthrene (9-OHPhe), and hydroxyphenanthrene (OHPhe) (P=0.005, P=0.049, and P=0.004, respectively), as well as elevated levels of plasma branched chain amino acid (BCAA) and aromatic amino acid (AAA) (P<0.05). After being adjusted for confounding factors, for every unit increase in lnv_2-OHPhe in urine, the OR (95%CI) of MS was 1.57 (1.11, 2.26), and for every unit increase in lnv_OHPhe, the OR (95%CI) of MS was 1.82 (1.16, 2.90). Tyrosine, leucine, and AAA all presented a significant nonlinear correlation with MS. At low levels, tyrosine, leucine, and AAA did not significantly increase the risk of MS, but at high levels, they increased the risk of MS. In the low amino acid concentration group, as well as in the low BCAA and low AAA concentration groups, it was found that compared to the PAH metabolite levels at the 50th percentile (P₅₀), the log-odds of MS when the PAH metabolite levels was at the 75th percentile (P₇₅) were 0.158 (95%CI: 0.150, 0.166), 0.218 (95%CI: 0.209, 0.227), and 0.262 (95% CI: 0.241, 0.282), respectively, However, no correlation between PAHs and MS was found in the high amino acid concentration group. Conclusion Amino acids modify the effect of PAHs exposure on the incidence of MS. In individuals with low plasma amino acid levels, the risk of developing MS increases with higher concentrations of mixed PAH exposure. This effect is partly due to the low concentrations of BCAA and AAA.