Objective To systematically evaluate qualitative studies on the experience of inhalation therapy for patients with chronic obstructive pulmonary disease(COPD),in order to provide a basis for healthcare professionals to optimize the care strategies.Methods A systematic search was conducted for qualitative studies on the experience of inhalation therapy for patients with COPD included in domestic and international databases,with a timeframe from the establishment of the database to September 2024.Literature quality was evaluated using the Australian JBI Centre for Evidence-Based Health Care Literature Quality Assessment Criteria for Qualitative Research,and the results were integrated by a pooled integration approach.Results A total of 12 articles were included,and 84 original findings were extracted and summarized into 10 new categories to form 4 integrated results,including low level of drug literacy,differences in perceived efficacy,multiple medication burdens,and multi-dimensional support for inhalation therapy.Conclusion COPD patients have multiple experiences during inhalation therapy.Medical staff should strengthen drug education,enhance patients'cognition and medication skills,foster a positive treatment attitude,and integrate multiple resources to improve patients'inhalation therapy experience.

Objective:To systematically evaluate the factors influencing the physical activity levels of patients with chronic obstructive pulmonary disease (COPD) .Methods:Computer retrieval of literature related to the influencing factors of physical activity in patients with COPD in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang, VIP Database, and China Biology Medicine disc, and the search period was from the establishment of the databases to March 2024. Two researchers independently screened the literature and conducted quality assessment according to inclusion and exclusion criteria. Meta-analysis was conducted using RevMan 5.4 software.Results:A total of 14 studies were included. The results of the Meta-analysis showed that gender [ OR=1.54, 95% CI (1.21, 1.96) ], degree of dyspnea [ OR=1.74, 95% CI (1.37, 2.21) ], fatigue [ OR=2.06, 95% CI (1.48, 2.87) ], and depression [ OR=1.63, 95% CI (1.30, 2.04) ] were influencing factors of physical activity levels in COPD patients ( P<0.05) . Conclusions:The physical activity levels of COPD patients are influenced by gender, degree of dyspnea, fatigue, and depression. Healthcare providers should develop personalized intervention goals and plans to improve patients' participation in and adherence to physical activity.

Baihuasheshecao(Hedyotis diffusa) is a commonly used traditional Chinese medicine derived from the whole herb of H. diffusa and has been widely utilized in folk medicine. It possesses anti-tumor, antibacterial, and anti-inflammatory properties, making it one of the frequently used herbs in TCM clinical practice. However, Shuixiancao(H. corymbosa) and Xianhuaercao(H. tenelliflora), species of the same genus, are often used as substitutes for Baihuasheshecao. To substantiate the medicinal basis of Baihuasheshecao, this study systematically reviewed classical herbal texts and modern literature, examining its nomenclature, botanical origin, harvesting, processing, properties, meridian tropism, pharmacological effects, and clinical applications. The results indicate that Baihuasheshecao was initially recorded as "Shuixiancao" in Preface to the Indexes to the Great Chinese Botany(Zhi Wu Ming Shi Tu Kao). Based on its morphological characteristics and habitat description, it was identified as H. diffusa in the Rubiaceae family. Subsequent records predominantly refer to it as Baihuasheshecao as its official name. In most regions, Baihuasheshecao is recognized as the authentic medicinal material, distinct from Shuixiancao and Xianhuaercao. Baihuasheshecao is harvested in late summer and early autumn, and the dried whole plant, including its roots, is used medicinally. The standard processing method involves cutting. It is known for its effects in clearing heat, removing toxins, reducing swelling and pain, and promoting diuresis to resolve abscesses. Initially, it was mainly used for treating appendicitis, intestinal abscesses, and venomous snake bites, and later, it became a treatment for cancer. The excavation of its clinical value followed a process in which overseas Chinese introduced the herb from Chinese folk medicine to other countries. After its unique anti-cancer effects were recognized abroad, it was reintroduced to China and gradually became a crucial TCM for cancer treatment. The findings of this study help clarify the historical and contemporary uses of Baihuasheshecao, providing literature support and a scientific basis for its rational development and precise clinical application.
Humans ; China ; Drugs, Chinese Herbal/chemistry* ; Hedyotis/classification* ; Medicine, Chinese Traditional/history*

Objective To systematically evaluate qualitative studies on the experience of inhalation therapy for patients with chronic obstructive pulmonary disease(COPD),in order to provide a basis for healthcare professionals to optimize the care strategies.Methods A systematic search was conducted for qualitative studies on the experience of inhalation therapy for patients with COPD included in domestic and international databases,with a timeframe from the establishment of the database to September 2024.Literature quality was evaluated using the Australian JBI Centre for Evidence-Based Health Care Literature Quality Assessment Criteria for Qualitative Research,and the results were integrated by a pooled integration approach.Results A total of 12 articles were included,and 84 original findings were extracted and summarized into 10 new categories to form 4 integrated results,including low level of drug literacy,differences in perceived efficacy,multiple medication burdens,and multi-dimensional support for inhalation therapy.Conclusion COPD patients have multiple experiences during inhalation therapy.Medical staff should strengthen drug education,enhance patients'cognition and medication skills,foster a positive treatment attitude,and integrate multiple resources to improve patients'inhalation therapy experience.

Objective:To systematically evaluate the factors influencing the physical activity levels of patients with chronic obstructive pulmonary disease (COPD) .Methods:Computer retrieval of literature related to the influencing factors of physical activity in patients with COPD in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang, VIP Database, and China Biology Medicine disc, and the search period was from the establishment of the databases to March 2024. Two researchers independently screened the literature and conducted quality assessment according to inclusion and exclusion criteria. Meta-analysis was conducted using RevMan 5.4 software.Results:A total of 14 studies were included. The results of the Meta-analysis showed that gender [ OR=1.54, 95% CI (1.21, 1.96) ], degree of dyspnea [ OR=1.74, 95% CI (1.37, 2.21) ], fatigue [ OR=2.06, 95% CI (1.48, 2.87) ], and depression [ OR=1.63, 95% CI (1.30, 2.04) ] were influencing factors of physical activity levels in COPD patients ( P<0.05) . Conclusions:The physical activity levels of COPD patients are influenced by gender, degree of dyspnea, fatigue, and depression. Healthcare providers should develop personalized intervention goals and plans to improve patients' participation in and adherence to physical activity.

Objective To achieve intelligent recognition and segmentation of common craniocerebral inju-ries(hereinafter referred to as"segmentation")by training convolutional neural network DeepLabV3+model based on CT images of blunt craniocerebral injury(BCI),and to explore the value of deep learning in automated diagnosis of BCI in forensic medicine.Methods A total of 5 486 CT images of BCI from living persons were collected as the training set,validation set and test set for model training and performance evaluation.Another 255 CT images of BCI and 156 normal craniocerebral CT images from living persons were collected as the blind test set to evaluate the ability of the model to seg-ment the five types of craniocerebral injuries including scalp hematoma,skull fracture,epidural hema-toma,subdural hematoma,and brain contusion.Another 340 BCI and 120 normal craniocerebral CT images from cadavers were collected as the new blind test set to explore the application value of the model trained by living CT images in the segmentation of BCI in cadavers.The five types CT images of all BCI except the blind test set were manually labeled;then,each dataset was inputted into the model to train the model.The performance of the model was evaluated and optimized based on the loss function and accuracy curves of the training set and validation set,and the generalization ability was evaluated based on the Dice value of the test set.According to the accuracy,precision and F1 value of the blind test set,the segmentation performance of the model for five types of BCI was evaluated.Results After training and optimizing the model,the average Dice values of the final optimal model to scalp hematoma,skull fracture,epidural hematoma,subdural hematoma and brain contusion segmen-tation were 0.766 4,0.812 3,0.938 7,0.782 7 and 0.858 1,respectively,all greater than 0.75,meeting the expected requirements.External validation showed that the F1 values were 93.02%,89.80%,87.80%,92.93%and 86.57%in living CT images,respectively;83.92%,44.90%,76.47%,64.29%and 48.89%in cadaveric CT images,respectively.The above suggested that the model was able to accu-rately segment various types of craniocerebral injury on living CT images,while its segmentation ability was relatively poor on cadaveric CT images,but still able to accurately segment scalp hematoma,epidu-ral hematoma and subdural hematoma.Conclusion Deep learning model trained on CT images can be used for BCI segmentation.However,the direct use of living persons'BCI models for the identifica-tion of cadaveric BCI has some limitations.This study provides a new approach for intelligent segmen-tation of virtual anatomical data for BCI.

As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
Humans ; Angioedemas, Hereditary/drug therapy*

As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
Humans ; Angioedemas, Hereditary/drug therapy*

Objective:To analyze the accuracy of a single-lead electrocardiogram (iECG) algorithm based on intelligent wristwatch in identifying sinus tachycardia and atrial fibrillation (AF) with rapid ventricular rate.Methods:In this non-randomized control trial, 642 patients aged ≥18 years were enrolled in the General Hospital of Chinese PLA between December 15, 2020 and May 30, 2022, with sinus tachycardia or rapid ventricular rate of AF (ranging from 111 to 145 beats/min for sinus tachycardia, from 110 to 150 beats/min for rapid ventricular rate of AF, respectively). The patients wore Huawei Watch GT2 Pro smartwatches on their left wrists, and the physiological signals detected by the smartwatches in a relaxed state were used as the measured data. The iECG algorithm developed by Huawei was used for identification. Simultaneously, 12-lead electrocardiograms (12L-ECG) were performed, and two cardiologists served as the gold standard for interpretation. Three participants who did not meet the inclusion criteria were excluded based on the detection results, and a total of 639 participants were included in the study. The accuracy of the algorithm in identifying sinus tachycardia and rapid ventricular rate AF was evaluated using metrics such as recall rate, precision rate, macro F1 score for multi-class classification.Results:Among 639 subjects, there were 469 males and 170 females. There were 389 cases of sinus tachycardia and 250 cases of rapid ventricular rate AF, with a mean age of (46.53±13.32) years. The recall rate, precision rate, and F1 value of iECG algorithm in identifying sinus tachycardia was 98.7%, 99.2% and 99.0%, respectively, while it was 98.8%, 98.0% and 98.4%, respectively for AF with rapid ventricular rate. The macro F1 of AF with rapid ventricular rate and sinus tachycardia was 98.7%. The iECG based on the intelligent wristwatch showed good consistency with the corresponding 12L-ECG waveforms.Conclusion:The intelligent wristwatch-based iECG algorithm can effectively identify sinus tachycardia and rapid ventricular rate AF, demonstrating good accuracy.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Early diagnosis and effective management are important to reduce atrial fibrillation-related adverse events. Photoplethysmography (PPG) is often used to assist wearables for continuous electrocardiograph monitoring, which shows its unique value. The development of PPG has provided an innovative solution to AF management. Serial studies of mobile health technology for improving screening and optimized integrated care in atrial fibrillation have explored the application of PPG in screening, diagnosing, early warning, and integrated management in patients with AF. This review summarizes the latest progress of PPG analysis based on artificial intelligence technology and mobile health in AF field in recent years, as well as the limitations of current research and the focus of future research.
Humans ; Atrial Fibrillation/therapy* ; Photoplethysmography ; Artificial Intelligence ; Electrocardiography ; Biomedical Technology