Objective: This study aims to evaluate the clinical benefits of the integrated optical and magnetic surgical navigation system in assisting transforaminal endoscopic lumbar discectomy (TELD) for the treatment of lumbar disc herniation (LDH). Methods: A retrospective analysis was conducted on patients who underwent TELD for LDH at Beijing Chaoyang Hospital, Capital Medical University from November 2022 to December 2023. Patients treated with the integrated optical and magnetic surgical navigation system were defined as the navigation-guided TELD (Ng-TELD) group (30 cases), while those treated with the conventional x-ray fluoroscopy method were defined as the control group (31 cases). Record and compare baseline characteristics, surgical parameters, efficacy indicators, and adverse events between the 2 patient groups. Results: The average follow-up duration for the 61 patients was 11.8 months. Postoperatively, both groups exhibited significant relief from back and leg pain, which continued to improve over time. At the final follow-up, patients’ lumbar function and quality of life had significantly improved compared to preoperative levels (p < 0.05). The Ng-TELD group had significantly shorter total operation time (58.43 ± 12.37 minutes vs. 83.23 ± 25.90 minutes), catheter placement time (5.83 ± 1.09 minutes vs. 15.94 ± 3.00 minutes), decompression time (47.17 ± 11.98 minutes vs. 67.29 ± 24.23 minutes), and fewer intraoperative fluoroscopies (3.20 ± 1.45 vs. 16.58 ± 4.25) compared to the control group (p < 0.05). There were no significant differences between the groups in terms of efficacy evaluation indicators and hospital stay. At the final follow-up, the excellent and good rate of surgical outcomes assessed by the MacNab criteria was 98.4%, and the overall adverse event rate was 8.2%, with no statistically significant differences between the groups (p > 0.05). Conclusion This study demonstrates that the integrated optical and magnetic surgical navigation system can reduce the complexity of TELD, shorten operation time, and minimize radiation exposure for the surgeon, highlighting its promising clinical potential.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: This study aims to evaluate the clinical benefits of the integrated optical and magnetic surgical navigation system in assisting transforaminal endoscopic lumbar discectomy (TELD) for the treatment of lumbar disc herniation (LDH). Methods: A retrospective analysis was conducted on patients who underwent TELD for LDH at Beijing Chaoyang Hospital, Capital Medical University from November 2022 to December 2023. Patients treated with the integrated optical and magnetic surgical navigation system were defined as the navigation-guided TELD (Ng-TELD) group (30 cases), while those treated with the conventional x-ray fluoroscopy method were defined as the control group (31 cases). Record and compare baseline characteristics, surgical parameters, efficacy indicators, and adverse events between the 2 patient groups. Results: The average follow-up duration for the 61 patients was 11.8 months. Postoperatively, both groups exhibited significant relief from back and leg pain, which continued to improve over time. At the final follow-up, patients’ lumbar function and quality of life had significantly improved compared to preoperative levels (p < 0.05). The Ng-TELD group had significantly shorter total operation time (58.43 ± 12.37 minutes vs. 83.23 ± 25.90 minutes), catheter placement time (5.83 ± 1.09 minutes vs. 15.94 ± 3.00 minutes), decompression time (47.17 ± 11.98 minutes vs. 67.29 ± 24.23 minutes), and fewer intraoperative fluoroscopies (3.20 ± 1.45 vs. 16.58 ± 4.25) compared to the control group (p < 0.05). There were no significant differences between the groups in terms of efficacy evaluation indicators and hospital stay. At the final follow-up, the excellent and good rate of surgical outcomes assessed by the MacNab criteria was 98.4%, and the overall adverse event rate was 8.2%, with no statistically significant differences between the groups (p > 0.05). Conclusion This study demonstrates that the integrated optical and magnetic surgical navigation system can reduce the complexity of TELD, shorten operation time, and minimize radiation exposure for the surgeon, highlighting its promising clinical potential.

Objective: This study aims to evaluate the clinical benefits of the integrated optical and magnetic surgical navigation system in assisting transforaminal endoscopic lumbar discectomy (TELD) for the treatment of lumbar disc herniation (LDH). Methods: A retrospective analysis was conducted on patients who underwent TELD for LDH at Beijing Chaoyang Hospital, Capital Medical University from November 2022 to December 2023. Patients treated with the integrated optical and magnetic surgical navigation system were defined as the navigation-guided TELD (Ng-TELD) group (30 cases), while those treated with the conventional x-ray fluoroscopy method were defined as the control group (31 cases). Record and compare baseline characteristics, surgical parameters, efficacy indicators, and adverse events between the 2 patient groups. Results: The average follow-up duration for the 61 patients was 11.8 months. Postoperatively, both groups exhibited significant relief from back and leg pain, which continued to improve over time. At the final follow-up, patients’ lumbar function and quality of life had significantly improved compared to preoperative levels (p < 0.05). The Ng-TELD group had significantly shorter total operation time (58.43 ± 12.37 minutes vs. 83.23 ± 25.90 minutes), catheter placement time (5.83 ± 1.09 minutes vs. 15.94 ± 3.00 minutes), decompression time (47.17 ± 11.98 minutes vs. 67.29 ± 24.23 minutes), and fewer intraoperative fluoroscopies (3.20 ± 1.45 vs. 16.58 ± 4.25) compared to the control group (p < 0.05). There were no significant differences between the groups in terms of efficacy evaluation indicators and hospital stay. At the final follow-up, the excellent and good rate of surgical outcomes assessed by the MacNab criteria was 98.4%, and the overall adverse event rate was 8.2%, with no statistically significant differences between the groups (p > 0.05). Conclusion This study demonstrates that the integrated optical and magnetic surgical navigation system can reduce the complexity of TELD, shorten operation time, and minimize radiation exposure for the surgeon, highlighting its promising clinical potential.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Nutritional support therapy is one of the extremely important treatment methods for patients in the intensive care unit. Timely and effective nutritional support regimens can improve patients' immune function, reduce complications, and optimize clinical outcomes. Energy expenditure is influenced by multiple factors, including patients' baseline characteristics (such as physical condition, gender, age) and dynamic changes in indicators (such as body temperature, nutritional support regimens, and therapeutic interventions). The currently recognized "gold standard" for accurately assessing energy metabolism in clinical practice is the indirect calorimetry system, also known as the metabolic cart. This device monitors carbon dioxide production and oxygen consumption in real time and uses specific algorithms to estimate the metabolic proportions of the three major nutrients (carbohydrates, fats, and proteins) in energy expenditure. An appropriate nutrient ratio helps maintain the balance between supply and demand in the body's nutritional metabolism. In the management of critically ill patients, the application of the metabolic cart enables personalized nutritional therapy, avoiding over- or under-supply of energy and optimizing the use of medical resources. Furthermore, with real-time, quantitative data support from the energy metabolism monitoring system, clinicians can develop more precise nutritional intervention strategies, thereby improving patient prognosis. This article provides a systematic review of the technical features of the metabolic cart and its application value in various critical care scenarios, aiming to offer a reference for indirect calorimetry in clinical practice.
Humans ; Critical Illness/therapy* ; Nutritional Support ; Energy Metabolism ; Calorimetry, Indirect

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

ObjectiveTo observe the clinical efficacy and safety of Tangning Tongluo tablets in the treatment of nonproliferative diabetic retinopathy （DR）. MethodsFourteen research centers participated in this study， which spanned a time interval from September 2021 to May 2023. A total of 240 patients with nonproliferative DR were included and randomly assigned into an observation group （120 cases） and a control group （120 cases）. The observation group was treated with Tangning Tongluo tablets， and the control group with calcium dobesilate capsules. Both groups were treated for 24 consecutive weeks. The vision， DR progression rate， retinal microhemangioma， hemorrhage area， exudation area， glycosylated hemoglobin （HbA1c） level， and TCM syndrome score were assessed before and after treatment， and the safety was observed. ResultsThe vision changed in both groups after treatment （P<0.05）， and the observation group showed higher best corrected visual acuity （BCVA） than the control group （P<0.05）. The DR progression was slow with similar rates in the two groups. The fundus hemorrhage area and exudation area did not change significantly after treatment in both groups， while the observation group outperformed the control group in reducing the fundus hemorrhage area and exudation area. There was no significant difference in the number of microhemangiomas between the two groups before treatment. After treatment， the number of microhemangiomas decreased in both the observation group （Z=-1.437， P<0.05） and the control group （Z=-2.238， P<0.05）， and it showed no significant difference between the two groups. As the treatment time prolonged， the number of microhemangiomas gradually decreased in both groups. There was no significant difference in the HbA1c level between the two groups before treatment. After treatment， the decline in the HbA1c level showed no significant difference between the two groups. The TCM syndrome score did not have a statistically significant difference between the two groups before treatment. After treatment， neither the TCM syndrome score nor the response rate had significant difference between the two groups. With the extension of the treatment time， both groups showed amelioration of TCM syndrome compared with the baseline. ConclusionTangning Tongluo tablets are safe and effective in the treatment of nonproliferative DR， being capable of improving vision and reducing hemorrhage and exudation in the fundus.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny