Purpose To investigate the feasibility of a deep learning framework to automatically analyze echocardiographic color Doppler videos in detecting valvular regurgitation.Materials and Methods This study retrospectively collected echocardiographic images of 1 109 patients with valvular regurgitation in the Fourth Medical Center of PLA General Hospital,from June 2015 to September 2019 as the training and validation sets.A prospective continuous collection of 1 562 echocardiography images was used as the test set in the Fourth Medical Center of PLA General Hospital from May 13 to June 13,2023,including 378 cases of mitral regurgitation and 223 cases of aortic regurgitation.This study developed deep learning networks to establish view classification model and valvular regurgitation recognition model,including the efficiency of section classification of deep learning models.Results The deep learning view classification model in this study could automatically identify two views for diagnosing mitral regurgitation and aortic regurgitation.The recognition accuracy for the parasternal long axis color Doppler view and the apical four chamber mitral color Doppler view was 1.00 and 0.93,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model for diagnosing mitral regurgitation were 0.847,0.852,0.849 and 0.930,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model in diagnosing aortic regurgitation were 0.857,0.861,0.859 and 0.940,respectively.Conclusion Deep learning algorithms can automatically identify valvular regurgitation and have the potential to become a screening tool for valvular heart disease.

Objective To compare the effect between unilateral and bilateral upper limb training on motor function of severely hemi-plegic upper limbs in subacute stroke patients after priming robot-assisted training.Methods From September,2023 to December,2024,60 inpatients with hemiplegia after stroke were recruited from Guangdong Work Injury Rehabilitation Hospital,and randomly divided into control group(n=30)and experi-mental group(n=30).Both groups first received 30 minutes of upper limb robot-assisted training.Subsequently,the control group received movement-based unilateral upper limb training for 30 minutes,while the experimental group received activity-based bilateral upper limb training for 30 minutes,for three weeks.They were assessed with Fugl-Meyer Assessment-Upper Extremities(FMA-UE),Hong Kong version of the Functional Test for the Hemiplegic Upper Extremity(FTHUE-HK)and modified Barthel Index(MBI)before and after treatment.Results The scores of FMA-UE,FTHUE-HK and MBI improved in both groups after treatment(t>4.020,P<0.01),and all the scores were better in the experimental group than in the control group(t>2.456,P<0.05).Conclusion Activity-based bilateral upper limb training after priming robot-assisted training is more effective on motor function of severely hemiplegic upper limbs in stroke patients.

Objective To compare the effect between unilateral and bilateral upper limb training on motor function of severely hemi-plegic upper limbs in subacute stroke patients after priming robot-assisted training.Methods From September,2023 to December,2024,60 inpatients with hemiplegia after stroke were recruited from Guangdong Work Injury Rehabilitation Hospital,and randomly divided into control group(n=30)and experi-mental group(n=30).Both groups first received 30 minutes of upper limb robot-assisted training.Subsequently,the control group received movement-based unilateral upper limb training for 30 minutes,while the experimental group received activity-based bilateral upper limb training for 30 minutes,for three weeks.They were assessed with Fugl-Meyer Assessment-Upper Extremities(FMA-UE),Hong Kong version of the Functional Test for the Hemiplegic Upper Extremity(FTHUE-HK)and modified Barthel Index(MBI)before and after treatment.Results The scores of FMA-UE,FTHUE-HK and MBI improved in both groups after treatment(t>4.020,P<0.01),and all the scores were better in the experimental group than in the control group(t>2.456,P<0.05).Conclusion Activity-based bilateral upper limb training after priming robot-assisted training is more effective on motor function of severely hemiplegic upper limbs in stroke patients.

Purpose To investigate the feasibility of a deep learning framework to automatically analyze echocardiographic color Doppler videos in detecting valvular regurgitation.Materials and Methods This study retrospectively collected echocardiographic images of 1 109 patients with valvular regurgitation in the Fourth Medical Center of PLA General Hospital,from June 2015 to September 2019 as the training and validation sets.A prospective continuous collection of 1 562 echocardiography images was used as the test set in the Fourth Medical Center of PLA General Hospital from May 13 to June 13,2023,including 378 cases of mitral regurgitation and 223 cases of aortic regurgitation.This study developed deep learning networks to establish view classification model and valvular regurgitation recognition model,including the efficiency of section classification of deep learning models.Results The deep learning view classification model in this study could automatically identify two views for diagnosing mitral regurgitation and aortic regurgitation.The recognition accuracy for the parasternal long axis color Doppler view and the apical four chamber mitral color Doppler view was 1.00 and 0.93,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model for diagnosing mitral regurgitation were 0.847,0.852,0.849 and 0.930,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model in diagnosing aortic regurgitation were 0.857,0.861,0.859 and 0.940,respectively.Conclusion Deep learning algorithms can automatically identify valvular regurgitation and have the potential to become a screening tool for valvular heart disease.

Objective To explore the effect of occupational skills relearning programme on hemiplegic arm motor function and ac-tivities of daily living(ADL)in stroke patients. Methods From February,2022 to August,2023,74 stroke patients in Guangdong Work Injury Rehabilitation Hospital were enrolled and randomly divided into control group(n=37)and experimental group(n=37).The control group received conventional rehabilitation training,and the experimental group received additional occupational skills relearning programme,for three weeks.They were assessed with Fugl-Meyer Assessment-Upper Extremi-ties(FMA-UE),Functional Test for the Hemiplegic Upper Extremity-Hong Kong(FTHUE-HK),Motor Activity Log(MAL)-amount of use(AOU)and MAL-quality of movement(QOM),modified Barthel Index(MBI),and Stroke Impact Scale(SIS)-Hand and SIS-ADL before and after treatment. Results The scores in all assessments improved significantly in both groups(|t|>3.597,P<0.05)after treatment,while the scores of FMA-UE,FTHUE-HK,MAL-AOU,MAL-QOM were higher in the experimental group than in the control group(|t|>2.352,P<0.05). Conclusion Occupational skills relearning programme could promote the recovery of hemiplegic arm motor and activity,and facilitate the use of the hemiplegic arm in daily life in stroke patients.

Objective To investigate the progress of two-dimensional echocardiographic parameters in patients with different severity of aortic stenosis.Methods A retrospective analysis was per-formed on 96 patients diagnosed with aortic stenosis with at least 2 times of transthoracic echo-cardiography(interval ≥1 year)in Department of Cardiology,Fourth Medical Center of Chinese PLA General Hospital from March 2017 to December 2023.According to aortic stenosis severity,they were divided into a mild group(72 cases),a moderate group(14 cases)and a severe group(10 cases).Peak pressure gradient(PPG)across aortic valve,Vmax,mean aortic valve pressure gradient(ΔPm),pulmonary artery systolic pressure(PASP)were collected,and the changes and annual progress of these echocardiographic parameters at baseline and before and after follow-up were analyzed.Results The values of IVST,LVPWT,Vmax,aortic valve PPG and ΔPm were sig-nificantly increased in the mild,moderate and severe stenosis groups in turn(P＜0.05,P＜0.01).The values of Vmax,PPG and ΔPm were significantly lower in the mild stenosis group than the moderate and severe stenosis groups,and the LVPWT value was obviously lower in the mild ste-nosis group than the severe stenosis group(P＜0.05).The aortic valve PPG and ΔPm values at follow-up were significantly higher than those before the follow-up in the three stenosis groups(P＜0.05,P＜0.01).After follow-up,the Vmax values in mild and moderate stenosis groups were notably higher than before(P＜0.01).The PASP value at follow-up was significantly higher than before in the severe stenosis group(P＜0.05).The annual progression rate of Vmax,PASP,LVEF were gradually increased in the mild,moderate,and severe stenosis groups(P＞0.05).The annual progression rate of ΔPm was gradually increased in the three groups in turn(2.30±1.77 mm Hg/year vs 2.40±1.18 mm Hg/year vs 6.08±1.70 mm Hg/year,P＜0.05).Conclusion As the severity of baseline aortic stenosis increases,obvious changes are observed in cardiac structure and function.Before and after follow-up,the serious the aortic stenosis severity is,the faster the annual progression rates of Vmax,PPG,LVEF and PASP are.