Objective Inflammatory myofibroblastic tumor (IMT) is a rare condition. This report summarizes the characteristics of IMT in order to strengthen clinicians' understanding of this disease. Case Presentation A 59-year-old female patient presented with intermittent right flank and abdominal pain with fever for 1 month, and a right renal mass detected 3 weeks ago. The highest body temperature during the course of the illness was 39℃. She received symptomatic antiinfective treatment at another hospital for 2 weeks, and the symptoms were alleviated. Enhanced CT of the lower abdomen strongly suggested a right renal carcinoma, with multiple small lymph nodes in the peritoneal cavity and retroperitoneum. MRI indicated a neoplastic lesion in the right kidney, with suspicion of chromophobe cell carcinoma. Laparoscopic partial right nephrectomy was performed under general anesthesia, and the procedure was successful. Postoperative pathology showed that there was significant localized infiltration of lymphocytes and formation of lymphoid follicles, and the lymph nodes showed chronic inflammation. The final diagnosis was IMT. In the follow-up of 3 months, no tumor recurrence was observed. Conclusion IMT has a high misdiagnosis rate. When imaging findings are atypical for renal cell carcinoma, IMT should be suspected. The preferred treatment is laparoscopic partial nephrectomy.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

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: 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 elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

A retrospective analysis was made on clinical data of a child with osteopathia striata with cranial sclerosis (OS-CS) diagnosed in the Department of Neonatology, Children′s Hospital Affiliated to Shandong University in January 2024.The proband was admitted to hospital due to premature delivery at 30 + 2 weeks, shortness of breath and poor response for 13 days after resuscitation.After birth, the child had no spontaneous breathing with floppy limbs.Tracheal intubation was required for positive pressure ventilation.Cranial ultrasound showed right subventricular hemorrhage with bilateral intraventricular hemorrhage and bilateral parieto-occipital subdural hemorrhage; cardiac ultrasound showed patent ductus arteriosus and tricuspid regurgitation; scrotal ultrasound showed bilateral inguinal cryptorchidism with right testicular hydrocele; gastrointestinal ultrasound showed that the lumen of the transverse colon was filled with many fecal matters with strong echoes.Whole exome sequencing(WES) indicated that the proband carried a hemizygous variant of c. 1489C>T(p.Arg497 *) in the AMER1 gene, which was inherited from his mother, as verified by Sanger sequencing.The hemizygous variant of c. 1489C>T(p.Arg497 *) in the AMER1 gene was rated as likely pathogenic (PVS1+ PM2-Supporting) according to the American College of Medical Genetics and Genomics(ACMG) guidelines, which was not included in the Human Gene Mutation Database(HGMD) database.High-throughput sequencing identified the hemizygous variant of c. 1489C>T(p.Arg497 *) in the AMER1 gene as the genetic etiology of the proband.This was the first report of AMER1 gene variant leading to OS-CS in China.The study enriches the variation spectrum and clinical phenotype spectrum of the AMER1 gene, providing a valuable foundation for clinical diagnosis, treatment, and subsequent research of the disease.

Objective To propose a preventive maintenance strategy of the heating,ventilation and air-conditioning(HVAC)system in pharmacy intravenous admixture services(PIVAS)based on the reliability centered maintenance(RCM)method so as to provide references for PIVAS equipment maintenance.Methods Firstly,a HVAC system RCM review team was formed,and the failure modes and impacts of important functional components of the equipment were analyzed to clarify the consequences of the failure of each functional component under the premise of ensuring the safety and integrity of the equipment and with the goal of minimizing the loss of maintenance downtime and the consumption of maintenance resources.Secondly,with a standardized logical decision-making procedure the preventive maintenance strategy was determined and implemented based on the consequences of functional failure.Finally,statistical analyses were carried out on such equipment indicators as performance parameter qualification rate,failure rate and maintenance cost before and after the RCM method-based strategy was executed,in order to evaluate the efficacy of the strategy.Results The RCM method-based preventive maintenance strategy had the performance qualification rate increased from 97.47%to 99.06%(χ2=24.139,P<0.01),the failure rate decreased from 0.24%to 0.03%(χ2=13.519,P<0.01)and the maintenance cost reduced by 11.5%,from RMB 134,200 to 118,700.Conclusion The RCM method-based preventive maintenance strategy provides reliable equipment for PIVAS and lowers the maintenance cost effectively,and references are given for the development of automated and intelligent equipment maintenance strategies for PIVAS.[Chinese Medical Equipment Journal,2025,46(10):78-83]

Objective To elucidate the impact of chronic kidney disease(CKD)on the clinical outcomes of patients with left main coronary artery disease(LMCAD)undergoing intravascular ultrasound(IVUS)-guided percutaneous coronary intervention(PCI).Methods This retrospective study enrolled consecutive patients with LMCAD who underwent IVUS-guided PCI at Wuhan Asia Heart Hospital between January 2017 and December 2020.Patients were stratified into CKD and non-CKD groups according to the presence of CKD.Clinical data were systematically retrieved from the electronic health record system.Demographic,clinical,and angiographic characteristics were compared between groups.The primary endpoint was major adverse cardiovascular events(MACE),defined as a composite of all-cause mortality,myocardial infarction,and ischemic stroke.Results A total of 325 LMCAD patients[mean age(62.56±9.86)years;73.54％male]were included,with 31 patients(9.54％)in the CKD group.During a median follow-up of 5 years,CKD patients exhibited significantly older age[(70.13±9.77)years vs.(61.77±9.54)years,P＜0.001],higher prevalence of three-vessel disease(64.52％vs.38.10％;P=0.040)and left main bifurcation lesion(45.16％vs.37.76％,P=0.011),greater IVUS-detected calcification burden(P=0.029),and higher median SYNTAXⅡ scores[(34.10(30.30,39.25)vs.26.75(22.42,31.58),P＜0.001)].The cumulative incidence of MACE was significantly higher in the CKD group compared to the non-CKD group(32.26％vs.9.18％,P＜0.001).Univariate Cox regression analysis and Kaplan-Meier survival curves confirmed a 5.877-fold increased risk of MACE in CKD patients(95％CI 2.765-12.494).After adjusting for age and cardiac function,CKD remained an independent predictor of MACE(HR 3.611,95％CI 1.634-7.978).Conclusions LMCAD patients with concomitant CKD present with advanced age,impaired cardiac function,more extensive coronary disease,and severe calcification.The presence of CKD is associated with a significantly worse long-term prognosis.

OBJECTIVE: Varied acupoint selections represent a potential cause of the uncertainty surrounding the efficacy of acupuncture for knee osteoarthritis (OA). Skin temperature, a guiding factor for acupoint selection, may help to address this issue. This study explored thermal sensitization of acupoints used for the treatment of knee OA. METHODS: This cross-sectional case-control study enrolled cases aged 45-75 years with symptomatic knee OA and age- and gender-matched non-knee OA controls in a 1:1 ratio. All participants underwent infrared thermographic imaging. The primary outcome was the relative skin temperature of acupoint (STA), and the secondary outcome was the absolute STA of 11 acupoints. The Z test was used to compare the relative and absolute STAs between the groups. Principal component analysis was used to extract the common factors (CFs, acupoint cluster) in the STAs. A general linear model was used to identify factors affecting the STA in the knee OA cases. For the group comparisons of relative STA, P < 0.0045 (adjusted for 11 acupoints through Bonferroni correction) was considered to indicate statistical significance. For other analyses, P < 0.05 was used as the threshold for statistical significance. RESULTS: The analysis included 308 participants, consisting of 151 cases (mean age: [64.58 ± 6.67] years; male: 25.83%; mean body mass index: [25.70 ± 3.16] kg/m²) and 157 controls (mean age: [63.37 ± 5.96] years; male: 26.11%; mean body mass index: [24.47 ± 2.84] kg/m²). The relative STAs of ST34 (P = 0.0001), EX-LE2 (P < 0.0001), EX-LE5 (P = 0.0006), SP10 (P < 0.0001), BL40 (P = 0.0012) and GB39 (P = 0.0037) were higher in the knee OA group. No difference was found in the STAs of ST35, ST36, SP9, GB33 and GB34. Four CFs were identified for relative STA in both groups. The acupoints within each CF were consistent between the groups. The mean values of the relative STAs across each CF were higher in the knee OA group. In the knee OA cases, no factors were observed to affect the relative STA, while age and gender were found to affect the absolute STA. CONCLUSION Among patients with knee OA, thermal sensitization occurs in the acupoints of the lower extremity, exhibiting localized and regional thermal consistencies. The thermally sensitized acupoints that we identified in this study, ST34, SP10, EX-LE2, EX-LE5, GB39 and BL40, may be good choices for the acupuncture treatment of knee OA. Please cite this article as: Tu JF, Wang XZ, Yan SY, Wang YR, Yang JW, Shi GX, Zhang WZ, Jing LN, Yang LS, Liu DH, Wang LQ, Mi BH. Thermal sensitization of acupoints in patients with knee osteoarthritis: A cross-sectional case-control study. J Integr Med. 2025; 23(3): 289-296.
Humans ; Osteoarthritis, Knee/physiopathology* ; Male ; Cross-Sectional Studies ; Middle Aged ; Female ; Acupuncture Points ; Case-Control Studies ; Aged ; Skin Temperature ; Acupuncture Therapy