OBJECTIVE To provide a reference for pharmaceutical care in patients with ulcerative colitis （UC） and ankylosing spondylitis （AS） who developed pustular psoriasis induced by infliximab. METHODS Clinical pharmacists participated in the pharmaceutical care process of a patient with UC and AS who developed pustular psoriasis after using infliximab. The clinical pharmacists determined， using Naranjo’s Scale， that the correlation between the patient’s pustular psoriasis and infliximab was “likely”. Regarding the patient’s development of pustular psoriasis after using infliximab， the clinical pharmacists recommended discontinuing infliximab and switching to Upadacitinib extended-release tablets. For the patient’s skin allergic reaction after using upadacitinib， the clinical pharmacists advised continuing the use of upadacitinib and closely monitoring any potential adverse reactions during the treatment period. RESULTS The clinicians adopted the clinical pharmacists’ recommendation. Following the treatment， the patient’s symptoms were significantly alleviated， and the patient was discharged with medication. The follow-up after discharge showed that the treatment was effective and well-tolerated. CONCLUSIONS The clinical pharmacists analyzed the causal relationship between infliximab and pustular psoriasis. Through pharmaceutical care measures such as dynamic monitoring of skin lesions， evaluation of treatment responses， and optimization of drug regimens， they assisted the physicians in formulating an individualized medication plan， ensuring the safety and efficacy of the patient’s medication use.

During transfer tasks, the dual-arm nursing-care robot require a human-robot mechanics model to determine the balance region to support the patient safely and stably. Previous studies utilized human-robot two-dimensional static equilibrium models, ignoring the human body volume and muscle torques, which decreased model accuracy and confined the robot ability to adjust the patient's posture in three-dimensional spatial. Therefore, this study proposes a three-dimensional spatial mechanics modeling method based on individualized human musculoskeletal multibody dynamics. Firstly, based on the mechanical features of dual-arm support, this study constructed a foundational three-dimensional human-robot mechanics model including body posture, contact position and body force. With the computed tomography data from subjects, a three-dimensional femur-pelvis-sacrum model was reconstructed, and the individualized musculoskeletal dynamics was analyzed using the ergonomics software, which derived the human joint forces and completed the mechanic model. Then, this study established a dual-arm robot transfer platform to conduct subject transfer experiments, showing that the constructed mechanics model possessed higher accuracy than previous methods. In summary, this study provides a three-dimensional human-robot mechanics model adapting to individual transfers, which has potential application in various scenarios such as nursing-care and rehabilitating robots.
Humans ; Robotics ; Biomechanical Phenomena ; Posture ; Imaging, Three-Dimensional ; Nursing Care

BACKGROUND: The proportion of patients with non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations is relatively high in China. However, these patients currently lack significant benefits from available neoadjuvant treatment options. This study aims to explore the potential application value of neoadjuvant targeted therapy by evaluating its efficacy and safety in patients with EGFR-mutant resectable lung adenocarcinoma. METHODS: A multicenter retrospective study was used to analyze the treatment effect of patients with stage IIA-IIIB EGFR-mutant lung adenocarcinoma who underwent surgical resection after receiving neoadjuvant targeted therapy from July 2019 to October 2024. RESULTS: A total of 24 patients with EGFR-mutant lung adenocarcinoma from three centers were included in this study. All patients successfully underwent surgery and achieved R0 resection of 100.0%. The objective response rate (ORR) was 83.3% (20/24) . The major pathologic response (MPR) rate was 37.5% (9/24), with 2 patients (8.3%) achieving pathological complete response (pCR). During neoadjuvant therapy, 13 out of 24 patients (54.2%) experienced adverse events of grade 1-2, with no occurrences of ≥ grade 3. The most common treatment-related adverse events were rash (n=4, 16.7%), mouth sores (n=2, 8.3%), and diarrhea (n=2, 8.3%). The median follow-up time was 33.0 months, no deaths occurred in all patients, and the overall survival (OS) rate was 100.0%. The 1-year disease-free survival (DFS) rate was 91.1%, and the 2-year DFS rate remained at 86.2%. CONCLUSIONS The application of neoadjuvant targeted therapy in patients with EGFR-mutant resectable lung adenocarcinoma is safe and feasible, and is expected to become a highly promising neoadjuvant treatment option for the patients with EGFR-mutant lung adenocarcinoma.
Humans ; ErbB Receptors/metabolism* ; Male ; Female ; Middle Aged ; Adenocarcinoma of Lung/surgery* ; Neoadjuvant Therapy ; Lung Neoplasms/surgery* ; Aged ; Retrospective Studies ; Mutation ; Adult

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

OBJECTIVES: To construct an intelligent analysis model for classifying fetal orientation during intrapartum ultrasound videos based on multi-feature fusion. METHODS: The proposed model consists of the Input, Backbone Network and Classification Head modules. The Input module carries out data augmentation to improve the sample quality and generalization ability of the model. The Backbone Network was responsible for feature extraction based on Yolov8 combined with CBAM, ECA, PSA attention mechanism and AIFI feature interaction module. The Classification Head consists of a convolutional layer and a softmax function to output the final probability value of each class. The images of the key structures (the eyes, face, head, thalamus, and spine) were annotated with frames by physicians for model training to improve the classification accuracy of the anterior occipital, posterior occipital, and transverse occipital orientations. RESULTS: The experimental results showed that the proposed model had excellent performance in the tire orientation classification task with the classification accuracy reaching 0.984, an area under the PR curve (average accuracy) of 0.993, and area under the ROC curve of 0.984, and a kappa consistency test score of 0.974. The prediction results by the deep learning model were highly consistent with the actual classification results. CONCLUSIONS The multi-feature fusion model proposed in this study can efficiently and accurately classify fetal orientation in intrapartum ultrasound videos.
Humans ; Female ; Ultrasonography, Prenatal/methods* ; Pregnancy ; Fetus/diagnostic imaging* ; Neural Networks, Computer ; Video Recording

Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in passenger drivers and its influencing factors. Methods A total of 951 passenger drivers in Guangdong Province were selected as the research subjects using the judgmental sampling method. A Musculoskeletal Injury Questionnaire was employed to assess the prevalence of WMSDs in the past year. Results The prevalence of WMSDs in passenger drivers was 41.11%. The result of multivariable logistic regression analysis showed that married drivers had a higher risk of WMSDs than single drivers (P<0.05). The lower the frequency of physical exercise, the longer the driving time per week, the longer the continuous driving time, the more restricted the driving working space, the poorer the foot comfort during driving, and the more affected the normal meal, the higher the risk of WMSDs (all P<0.05). The risk of WMSDs in drivers with sleep time ≤ 8.0 h/d was higher than that in drivers with sleep time > 8.0 h/d (P<0.01), and the risk of WMSDs in drivers with the same posture for a long time on the shoulder was higher than that in drivers without this poor working posture (P<0.01). Conclusion WMSDs were prevalent among passenger drivers, which was associated with demographic and adverse ergonomic factors. Intervention on lifestyle and adverse ergonomic factors could further reduce the risk of WMSDs of passenger drivers.

Although symptomatic treatment is widely applied in clinical practice， it is often regarded as a relatively low-level therapeutic method. Based on Traditional Chinese Medicine （TCM） state theory， the macroscopic， mesoscopic， and microscopic characterization parameters of TCM symptomatology are horizontally integrated， the full life cycle of states （pre-disease， incipient disease， manifest disease， post-disease） is vertically covered， and the cognitive system of "symptoms" is reconstructed from multiple dimensions. Accordingly， the application approach of symptomatic treatment at different state stages is proposed： implementing preventive intervention in the pre-disease state， strengthening the interception of disease progression in the incipient disease state， regulating dynamic development and treatment in the manifest disease state， and formulating a staged diagnosis and treatment strategy which focuses on functional rehabilitation in the post-disease state.

OBJECTIVE To investigate the independent risk factors for carbapenem-resistant Klebsiella pneumoniae （CRKP） infection， develop a nomogram prediction model and validate it. METHODS Clinical data of hospitalized patients infected with CRKP between April 2020 and May 2023 at Kunming First People’s Hospital were retrospectively collected and matched 1∶1 with patients infected with carbapenem-susceptible Klebsiella pneumoniae （CSKP） during the same period as the modeling group. Using the same criteria， data from patients hospitalized and infected with CRKP and matched CSKP between June 2023 and June 2024 were collected as the validation group. Univariate analysis， LASSO regression and multivariate Logistic regression were conducted to identify independent risk factors for CRKP infection and to develop a nomogram prediction model. Internal validation of the model was performed using Bootstrap resampling， and external validation was carried out using the data of validation group. The predictive performance of the model was evaluated using receiver operating characteristic （ROC） curves and calibration plots. RESULTS A total of 530 patients were enrolled， with 372 in the modeling group and 158 in the validation group. Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to β-lactamase inhibitor compound agents were identified as independent risk factors for CRKP infection （P＜0.05）. The nomogram predicting CRKP infection risk achieved an area under ROC of 0.729 and 0.803 in internal and external validations， respectively. Calibration curves indicated a high degree of consistency between predicted and observed probabilities. CONCLUSIONS Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to β-lactamase inhibitor compound agent are independent risk factors for CRKP infection. The developed nomogram model for predicting CRKP infection risk demonstrates good predictive performance and can aid in the early identification of patients at high risk for CRKP infection.