Comparative clinical efficacy of percutaneous coaxial large-channel endoscopic lumbar interbody fusion and transforaminal lumbar interbody fusion for degenerative lumbar spinal stenosis: a retrospective study.

This study aimed to evaluate the clinical efficacy of percutaneous coaxial large-channel endoscopic lumbar interbody fusion (PCLE-LIF) and transforaminal lumbar interbody fusion (TLIF) in the treatment of degenerative lumbar spinal stenosis. The clinical data of patients with degenerative lumbar spinal stenosis who underwent PCLE-LIF (experimental group) and TLIF (control group) surgery from September 2019 to September 2021 were retrospectively analyzed. We collected clinical data and compared the two groups in terms of perioperative parameters, treatment response rate, inflammatory response markers, postoperative complications, postoperative pain, and functional recovery. The results showed that the treatment outcomes in the experimental group were significantly better than those in the control group. Specifically, perioperative parameters and inflammatory response markers in the experimental group were significantly better than those in the control group, with statistically significant differences (P < 0.05). The overall treatment response rate in the experimental group was significantly higher than that in the control group (P < 0.05). Meanwhile, the incidence of postoperative complications in the experimental group was lower than that in the control group, postoperative VAS pain scores and ODI functional scores were lower, and postoperative JOA functional scores were higher than those in the control group, with statistically significant differences (P < 0.05). In conclusion, PCLE-LIF appears to be a promising technique with better clinical outcomes in the treatment of degenerative lumbar spinal stenosis.

The Impact of Medical Resources and Oral Antiviral Drugs on SARS-CoV-2 Mortality - Hong Kong SAR, China, 2022.

Introduction: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrates increased transmissibility compared to earlier strains, contributing to a significant number of fatalities in Hong Kong Special Administrative Region (HKSAR), China. Adequate medical resources and medications are essential in mitigating these deaths. This study evaluates the effects of supplementary resources from the Chinese mainland during the fifth wave of the pandemic in HKSAR. Methods: Vector autoregression (VAR) was employed to analyze data from the Oxford coronavirus disease 2019 (COVID-19) Government Response Tracker to assess the effectiveness of control measures during five waves of the pandemic in HKSAR. Additionally, a transmission dynamics model was created to investigate the influence of supplementary medical resources from the Chinese mainland and oral medications on mortality. Results: In the initial four waves, workplace closures, restrictions on public events, international travel bans, and shielding the elderly significantly influenced pandemic management. Contrarily, during the fifth wave, these measures showed no notable effects. When comparing a situation without extra medical resources or COVID-19 oral medication, there was a 17.7% decrease in COVID-19 fatalities with mainland medical resources and an additional 10.2% reduction with oral medications. Together, they contributed to a 26.6% decline in fatalities. Discussion: With the rapid spread of the virus, regional reallocation of medical resources may reduce mortality even when the local healthcare system is overstretched.

Adaptive Fourier Decomposition of the First Three SARS-CoV-2 Infection Waves with Epidemic Intervention - London, UK, 2020-2022.

Background: This study provides a detailed analysis of the daily fluctuations in coronavirus disease 2019 (COVID-19) case numbers in London from January 31, 2020 to February 24, 2022. The primary objective was to enhance understanding of the interactions among government pandemic responses, viral mutations, and the subsequent changes in COVID-19 case incidences. Methods: We employed the adaptive Fourier decomposition (AFD) method to analyze diurnal changes and further segmented the AFD into novel multi-component groups consisting of one to three elements. These restructured components were rigorously evaluated using Pearson correlation, and their effectiveness was compared with other signal analysis techniques. This study introduced a novel approach to differentiate individual components across various time-frequency scales using basis decomposition methods. Results: Analysis of London's daily COVID-19 data using AFD revealed a strong correlation between the "stay at home" directive and high-frequency components during the first epidemic wave. This indicates the need for sustained implementation of vaccination policies to maintain their effectiveness. Discussion: The AFD component method provides a comprehensive analysis of the immediate and prolonged impact of governmental policies on the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This robust tool has proven invaluable for analyzing COVID-19 pandemic data, offering critical insights that guide the formulation of future preventive and public health strategies.

Comparison of the efficacy of low-molecular-weight heparin and fondaparinux sodium after total knee arthroplasty: a retrospective cohort study.

BACKGROUND: Low-molecular-weight heparin (LMWH) and fondaparinux sodium (FPX) are routinely used to prevent deep vein thrombosis (DVT) after total knee arthroplasty (TKA). In this study, we compared the effects of these agents in preventing post-TKA DVT. METHODS: Clinical data of patients who underwent unilateral TKA for unicompartmental knee osteoarthritis at the Ningxia Medical University General Hospital between September 2021 and June 2022 were retrospectively analyzed. Based on the anticoagulation agent used, the patients were divided into LMWH and FPX groups (34 and 37 patients, respectively). Changes in perioperative coagulation-related indicators, d-dimer and platelet count, perioperative complete blood count, amount of blood loss, lower-limb DVT, pulmonary embolism, and allogeneic blood transfusion were determined. RESULTS: Intergroup differences in d-dimer or fibrinogen (FBG) levels before and 1 or 3 days after surgery were not significant (all p > 0.05); within-group pairwise comparisons indicated significant differences (all, p < 0.05). Intergroup differences in preoperative prothrombin time (PT), thrombin time, activated partial PT, and international normalized ratio were not significant (all p > 0.05), whereas significant differences were detected on postoperative days 1 and 3 (all p < 0.05). Intergroup differences in platelet counts before and 1 or 3 days after surgery were not significantly different (all p > 0.05). Pairwise comparisons of hemoglobin and hematocrit levels between patients in the same group before and 1 or 3 days after surgery revealed significant differences in both groups (all p < 0.05); however, intergroup differences were not significant (all p > 0.05). Although intergroup differences in visual analog scale (VAS) scores before and 1 or 3 days after surgery were not significant (p > 0.05), we detected significant intragroup differences in VAS scores before and 1 or 3 days after surgery (p < 0.05). The treatment cost ratio was significantly lower in the LMWH group than in the FPX group (p < 0.05). CONCLUSION: Both LMWH and FPX can effectively prevent DVT after TKA. There are some suggestive signals that FPX may have more beneficial pharmacological effects and clinical significance, while LMWH is cheaper and therefore more economical.

Survival nomogram for osteosarcoma patients: SEER data retrospective analysis with external validation.

This study aimed to develop a nomogram based on the clinicopathological factors affecting the prognosis of osteosarcoma patients to help clinicians predict the overall survival of osteosarcoma patients. A total of 1362 patients diagnosed with osteosarcoma were enrolled in this study, among which, 1081 cases were enrolled from the SEER (Surveillance, Epidemiology, and End Results) database as training group, while 281 patients from two Clinical Medicine Center database were used in validation group. Univariate and multivariate Cox analyses were performed to identify the independent prognostic factors for overall survival. Nomogram predicting the 3- and 5-year overall survival probability was constructed and validated. Multiple validation methods, including calibration plots, consistency indices (C-index), and area under the receiver operating characteristic curve (AUC) were used to validate the accuracy and the reliability of the prediction models. Decision curve analysis (DCA) was conducted to validate the clinical application of the prediction model. Furthermore, all patients were divided into low- and high-risk groups based on their nomogram scores. Kaplan-Meier (KM) curves were applied to compare the difference in survival between the two groups. Predictors in the prediction model included age, sex, tumor size, primary site, grade, M stage, and surgery. Our results showed that the model displayed good prediction ability, and the calibration plots demonstrated great power both in the training and the validation groups. In the training group, C-index was 0.80, and the 3- and 5-year AUCs of the nomogram were 0.82 and 0.81, respectively. In the validation group, C-index was 0.79, and the 3- and 5-year AUCs of the nomogram were 0.85 and 0.83, respectively. Furthermore, DCA data indicated the potential clinical application of this model. Therefore, our prediction model could help clinicians evaluate prognoses, identify high-risk individuals, and provide individualized treatment recommendation for patients with osteosarcoma.

Daily fluctuations in COVID-19 infection rates under Tokyo's epidemic prevention measures - new evidence from adaptive Fourier decomposition.

Background: The COVID-19 pandemic has witnessed widespread infections and variants. Particularly, Tokyo faced the challenge of seven waves of COVID-19, during which government interventions played a pivotal role. Therefore, gaining a comprehensive understanding of government control measures is of paramount importance, which is beneficial for health authorities in the policy development process. Method: Our study analysis the daily change data of the daily COVID-19 infection count in Tokyo from January 16, 2020 to September 30, 2022. We utilized adaptive Fourier decomposition (AFD) for analyzing the temporal trends within COVID-19 data. It extends the conventional AFD approach by constructing new components base on multiple individual components at various time-frequency scales. Furthermore, we conducted Pearson correlation assessments of the first to third-order synthesis results, along with comparative analyses against other signal analysis techniques. Ultimately, these new components are integrated with policy data spanning different time periods for a comprehensive analysis. Result: The analysis of daily COVID-19 data in Tokyo using AFD reveals how various government policies impacted infection rates across seven distinct fluctuation periods. In the decomposition results, the reduction of business hours policy correlated with high-frequency components in the first four waves, while the low-frequency components for the sixth wave suggested a decline in its relevance. The vaccination policy initially displayed a mid-frequency correlation with the fifth wave and continued with a low-frequency correlation in the last wave. Moreover, our statistical analysis (value of p < 0.05) demonstrated that 75% of the third-order AFD components exhibited significant positive correlations with the original infections, while the correlation coefficients of most components in EMD and VMD did not attain significance. Conclusion: In the time-frequency domain, AFD demonstrates superior performance compared to EMD and VMD in capturing crucial data related to epidemic control measures. The variations in daily COVID-19 infection counts during these seven periods under various policies are evident in distinct third-order AFD components. These findings guide the formulation of future public health policies and social measures.

Containment of SARS-CoV-2 Delta strain in Guangzhou, China by quarantine and social distancing: a modelling study.

China detected the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with Delta variant in May 2021. We assessed control strategies against this variant of concern. We constructed a robust transmission model to assess the effectiveness of interventions against the Delta variant in Guangzhou with initial quarantine/isolation, followed by social distancing. We also assessed the effectiveness of alternative strategies and that against potentially more infectious variants. The effective reproduction number (Rt) fell below 1 when the average daily number of close contacts was reduced to ≤ 7 and quarantine/isolation was implemented on average at the same day of symptom onset in Guangzhou. Simulations showed that the outbreak could still be contained when quarantine is implemented on average 1 day after symptom onset while the average daily number of close contacts was reduced to ≤ 9 per person one week after the outbreak's beginning. Early quarantine and reduction of close contacts were found to be important for containment of the outbreaks. Early implementation of quarantine/isolation along with social distancing measures could effectively suppress spread of the Delta and more infectious variants.

Development of a nomogram to predict medication nonadherence risk in patients with rheumatoid arthritis.

OBJECTIVES: Poor adherence among patients with chronic diseases including inflammatory rheumatic diseases (IRDs) is a complex and serious global health care problem. This study aimed to develop an intelligent nomogram using retrospectively collected patient clinical data for predicting nonadherence to biologic treatment in rheumatoid arthritis (RA) patients. METHODS: The clinical characteristics of 102 RA patients were collected from outpatients and inpatients at the Orthopedic Departments of Ningxia General Hospital of Ningxia Medical University and Ningxia Hui Autonomous Region People's Hospital from October 2020 to September 2021. Adherence was evaluated using the proportion of treatment days covered within 6 months as the outcome event. A least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify risk predictors, and then multivariate logistic regression analysis was applied to construct the risk prediction model. Furthermore, the nomogram was plotted by multivariable logistic regression. RESULTS: Among the 102 patients analyzed, 43 patients did not adhere to biologic therapy for various reasons. LASSO regression analysis identified age, sex, education level, disease activity, monthly income, medical insurance, and adverse drug reactions as the significant risk predictors. By incorporating these factors, the nomogram was plotted which showed good discrimination, calibration, and clinical value. The C-index was 0.759 (95% CI: 0.665-0.853), and the area under the receiver operating characteristic (ROC) curve was 0.7416 with a good calibration ability. Decision curve analysis showed that the prediction effect of this model could benefit about 75% of the patients without compromising the interests of other patients. CONCLUSIONS: This nomogram could help medical staff identify patients with higher risk of nonadherence early, so that intervention measures can be taken in time.

Tetrandrine Inhibits Titanium Particle-Induced Inflammatory Osteolysis through the Nuclear Factor-κB Pathway.

Peri-implant osteolysis (PIO) and the subsequent aseptic loosening are the main reasons for artificial joint implant failure. Existing methods for treating aseptic loosening are far from satisfactory, necessitating advanced drug exploration. This study is aimed at investigating the effect and underlying mechanism of tetrandrine (Tet) on inflammatory osteolysis. We established a Ti particle-induced inflammatory osteolysis mouse model and administered Tet or an equal volume of phosphate-buffered saline (PBS). Two weeks later, specimens were collected. Histological staining showed that Tet administration inhibited Ti-stimulated osteolysis. Tartrate-resistant acid phosphate (TRAP) staining and transmission electron microscopy (TEM) demonstrated that osteoclast formation was remarkably inhibited in the groups treated with Tet in a dose-dependent manner. In addition, relevant inflammatory cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6) were also significantly reduced in the calvaria of the Tet-treated groups. Exposure of receptor activator for nuclear factor-κB ligand- (RANKL-) induced bone marrow-derived macrophages (BMMs) and RAW264.7 cells to Tet significantly reduced osteoclast formation, F-actin ring formation, bone resorption, and the expression of relevant genes (matrix metallopeptidase 9 (MMP-9), TRAP, and nuclear factor of activated T-cells, cytoplasmic 1 (NFATc1)) during osteoclastogenesis in vitro. Mechanistic studies using Western blotting demonstrated that Tet inhibited the nuclear factor (NF)-κB signaling pathway by decreasing the phosphorylation of inhibitor of NF-κB α (IκBα) and p65, which play important roles in osteoclast formation. Collectively, our data indicate that Tet suppressed Ti-induced inflammatory osteolysis and osteoclast formation in mice, suggesting that Tet has the potential to be developed to treat and prevent wear particle-induced inflammatory osteolysis.