The use of Chinese medicine (CM) for the management of: menopausal syndrome is considered effective both at home and abroad, and more and more clinical studies are confirming its efficacy. However, many problems still exit in current studies, such as the standard of CM syndrome differentiation, the design methodology and criteria to assess the quality of clinical trials and the efficacy of interventions. In this paper, the authors present the CM research and treatment strategies for menopausal syndrome with concepts explaining the CM understanding of the mechanism of the disorder. It is concluded that CM is effective for menopausal syndrome, but improvement in both study methodology and treatment strategy is needed. In detail, it is firstly necessary to conduct clinical studies to evaluate the difference of various CM treatments for menopausal syndrome manifesting different symptoms, so as to establish a comprehensive treatment protocol of CM. Secondly, an acknowledged evaluation system needs to be founded, which embodies the characteristics of CM, and covers appropriate endpoint indices and parameters to objectively evaluate the effect and study quality of CM. Finally, an epidemiological survey with large sample size should be implemented with robust statistical design and CM expertise to collect data for establishing diagnostic criteria for menopause in different stages and with different symptoms.
Biomedical Research ; Drugs, Chinese Herbal ; pharmacology ; Female ; Humans ; Medicine, Chinese Traditional ; trends ; Menopause ; drug effects ; Syndrome

Animals ; Calcium ; metabolism ; Diaphragm ; physiology ; ultrastructure ; Male ; Muscle Contraction ; Rats ; Rats, Sprague-Dawley ; Respiration, Artificial ; Sarcoplasmic Reticulum ; metabolism

Seventy percentage of perimenopausal and early postmenopausal women will experience menopause symptoms. Primary menopause symptoms in Western countries included hot flashes, insomnia, somatic pain, depression, and fatigue. Hot flashes were most commonly treated. Menopausal hormone replacement therapy (HRT) continues to have a clinical role in the management of vasomotor symptoms, but since 2002 there has been a marked global decline in its use due to concerns about the risks and benefits of HRT; consequently many women with menopause symptoms are now seeking alternatives including acupuncture. Acupuncture has a long tradition of use for the treatment of different menopause symptoms. Its effectiveness has been studied for natural menopause or chemical and surgery induced menopause. Here we provide an update on recent advances in the field for clinicians. The recent systematic reviews on acupuncture in menopausal symptoms suggest that acupuncture is an effective and valuable option for women suffering from menopause. However, the science of acupuncture therapies is still inadequate to sufficiently support the benefits of acupuncture therapies. Finally, we discuss our points of view on clinical trials of acupuncture for menopause symptoms.
Acupuncture Therapy ; methods ; Biomedical Research ; Female ; Humans ; Menopause ; physiology ; Randomized Controlled Trials as Topic

Objective To evaluate the feasibility,reliability,validity and responsiveness of a Chinese Menopause Rating Scale (CMRS).Methods Cross-sectional survey and convenience sampling were adopted. Participants:women with menopause syndrome and those in menopause but without menopause syndrome were recruited.All participants were asked to complete the CMRS,Kupperman Index,WHOQOL-BREF and MENQOL.The Self-control observation design was adopted when the responsiveness was evaluated.Patients were treated with TCM for weeks.MRSTCM was evaluated before and after the treatment.Results (1) Feasibility:3343 participants including 2320 patients and 1023 menopause women,were surveyed in 8 different settings.The recovery rate of CMRS was 100%,with a response rate as 99.7%.The completion of the CMRS took 10.30 minutes on average.(2)Reliability:Cronbach's alpha of CMRS,soma dimension,psychology dimension and community dimension of CMRS were 0.93,0.87,0.89 and 0.73 respectively,with the correlation coefficient of split half of the CMRS.Soma dimension,psychology dimension and community dimension were 0.92,0.89,0.86 and 0.73 respectively and the test-retest correlation coefficient of MRSTCM,the soma dimension,psychology dimension and community dimension were as 0.88,0.91,0.85 and 0.77 respectively.(3) Validity:CMRS was established on the basis of connotation of menopause syndrome,and a series of steps were adopted to modify the scale.CMRS was applicable for patients with menopause syndrome.CMRS seemed to have had good content-related validity.The result of exploratory factor analysis was accorded with the theory frame of CMRS by and large.The correlations between CMRS and KI,CMRS and WHOQOLBREF,CMRS and MENQOL seemed good.The CMRS was able to discriminate between groups of people with or without menopausal syndrome and bad good discriminative validity.(4) Responsibility:The CMRS was measured based on 174 patients with menopausal syndrome before and after the TCM therapy.Our result showed that the CMRS having the ability to measure the clinically important differences.Conclusion CMRS was suitable for outcome assessment of menopausal syndrome.This primary research proved that the CMRS had good feasibility,reliability,validity as well as responsiveness.

Objective To select the items from the Chinese menopause rating scale(CMRS)through pre-tcsting those people with menopausal syndromes.Methods 293 people were surveyed in Guangzhou in 2005.among which 196 people with menopausal syndromes and others without.Psychometrics methods were employed to develop the scale.The item pools were all round.Methods used would include:focus group discussion and interviews,subjective evaluation method and Delphi method,to preliminarily screen the items.Data on scales measured from 196 cases with and 97 subjects without menopausal syndromes during the menopausal period,were collected.Again,seven statistical methods were employed to select the items.Results The 40-items scale for menopausal syndrome was formed to include:a)three domains:somatic(18-items),psychological(14-items)and social(5-items);b)one general appraisaIitem:c)two lie-test iterns.Conclusion The Chinese menopausal syndrome scale we used seemed to possess good content validity.feasibility and intra-class reliability.

BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images. METHODS: Taking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR-), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists. RESULTS: The accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87-0.91, 0.89-0.92, 0.87-0.91, and 0.86-0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%). CONCLUSIONS: The CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists. TRIAL REGISTRATION Chictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.
Area Under Curve ; Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; China ; Deep Learning ; Humans ; ROC Curve ; Sensitivity and Specificity