Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Objective To develop a static progressive ankle stretcher for the treatment of functional disorders caused by scar contracture of the Achilles tendon after burn,and to evaluate its application effect.Methods The static progressive ankle stretcher was composed of a plantar support section and a calf support section,which was mainly made of a 3.2 mm-thick medical low-temperature thermoplastic plate,a commercially available 1 mm-diameter steel wire rope,grooved wheels,ice fishing reels with a diameter of about 50 mm,curved folding hinges and a locking threader with a hole diameter of about 1.5 mm.Totally 49 patients with scar contracture after deep Ⅱ to Ⅲ-degree burns of the Achilles tendon admitted to some hospital from March 2021 to January 2023 were prospectively selected and divided into a conventional rehabilitation group(25 cases)and a combined rehabilitation group(24 cases)using a randomized numerical table method.The patients in the conventional rehabilitation group underwent routine scar care such as anti-scarring medication application at home,scar massage,resistance training,joint loosening training in the hospital and compression therapy with the customized compression stockings/pants at the rest of the time,the patients in the combined rehabilitation group were treated with the static progressive ankle stretcher besides the measures taken for the conventional group.The two groups were compared in terms of scarring,ankle function and active dorsiflexion mobility of the ankle joint before and 12 weeks after the treatment,balance and walking ability 4 weeks and 12 weeks after the treatment,adverse events during the treatment and patient satisfaction 12 weeks after the treatment.SPSS 23.0 statistical software was used for data analysis.Results In terms of scarring condition,ankle function and active dorsiflexion mobility of the ankle joint all the patients were improved 12 weeks after the treatment,and the ones in the combined rehabilitation group behaved better than the ones in the conventional group,with the differences being statistically significant(P<0.05).The balance and walking ability 12 weeks after the treatment was better than that 4 weeks after the treatment in the two groups,and the combined rehabilitation group gained advantages over the conventional group in balance and walking ability,with the difference being statistically significant(P<0.05).During the treatment no adverse events due to the static progressive ankle stretcher were found,such as muscle tissue strain,scarred skin rupture,instrument friction and pressure injury.The combined rehabilitation group had higher patient satisfaction than the conventional group 12 weeks after the treatment,with the differences being statistically significant(P<0.05).Conclusion The static progressive ankle stretcher combined with the conventional rehabilitation treatment contributes to improving contracture scar conditions and joint mobility at the Achilles tendon area of the post-burn patients,which helps accelerate the recovery of ankle function after burns and enhance the balance and walking ability of the patients.[Chinese Medical Equipment Journal,2025,46(10):54-59]

INTRODUCTION: In December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus emerged and caused a worldwide pandemic, leading to measures being imposed by many countries to reduce its transmission. Singapore implemented the 'circuit breaker', which restricted all movements except for access to necessities and healthcare services. We aimed to investigate the impact of lockdown measures on the pattern of trauma and its effects. METHODS: An observational, retrospective, single-centre descriptive study was conducted using the trauma registry in Singapore General Hospital. It included patients above 18 years old who presented to the emergency department with trauma and were subsequently admitted. Patients admitted from 1 February 2020 to 31 July 2020 and those admitted during the same timeframe in 2019 were studied. Subgroup analyses were performed for patients aged ≥65 years and those <65 years. RESULTS: A total of 1,037 patients were included for analysis. A 17.6% increase in trauma presentations was seen from 2019 to 2020. Patients aged ≥65 years accounted for the rise in admissions. The predominant mechanism of injury was falls at home for older patients and vehicular accidents in patients <65 years. There were no significant differences in injury severity score, intensive care/high-dependency unit admission rates, length of stay, mortality rate, and subsequent need for inpatient rehabilitation. CONCLUSION Our study provided information on differences in trauma presentations before and during the COVID-19 pandemic. Further studies are required to better inform on additional precautionary measures needed to reduce trauma and improve safety during future lockdowns and pandemics.
Humans ; COVID-19/prevention & control* ; Aged ; Retrospective Studies ; Singapore/epidemiology* ; Male ; Female ; Wounds and Injuries/epidemiology* ; Aged, 80 and over ; Middle Aged ; SARS-CoV-2 ; Hospitalization/statistics & numerical data* ; Adult ; Emergency Service, Hospital/statistics & numerical data* ; Registries ; Accidental Falls/statistics & numerical data* ; Pandemics ; Patient Admission/statistics & numerical data* ; Length of Stay ; Accidents, Traffic/statistics & numerical data*

To address issues such as loss of detailed information, blurred target boundaries, and unclear structural hierarchy in medical image fusion, this paper proposes an adaptive feature medical image fusion network based on a full-scale diffusion model. First, a region-level feature map is generated using a kernel-based saliency map to enhance local features and boundary details. Then, a full-scale diffusion feature extraction network is employed for global feature extraction, alongside a multi-scale denoising U-shaped network designed to fully capture cross-layer information. A multi-scale feature integration module is introduced to reinforce texture details and structural information extracted by the encoder. Finally, an adaptive fusion scheme is applied to progressively fuse region-level features, global features, and source images layer by layer, enhancing the preservation of detail information. To validate the effectiveness of the proposed method, this paper validates the proposed model on the publicly available Harvard dataset and an abdominal dataset. By comparing with nine other representative image fusion methods, the proposed approach achieved improvements across seven evaluation metrics. The results demonstrate that the proposed method effectively extracts both global and local features of medical images, enhances texture details and target boundary clarity, and generates fusion image with high contrast and rich information, providing more reliable support for subsequent clinical diagnosis.
Humans ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Diagnostic Imaging/methods* ; Image Interpretation, Computer-Assisted/methods*

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.