m+Medelevator.RU
← Поиск публикаций
Archives of osteoporosis · 2023

Network analysis of osteoporosis provides a global view of associated comorbidities and their temporal relationships.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Lee Hyun Il, Yoon Siyeong, Kim Jin Hwan, Ahn Wooyeol, Lee Soonchul

Аннотация

UNLABELLED: We performed comorbidity-network analysis to obtain global view of comorbidity related with osteoporosis. We selected 10000-patients with osteoporosis registered in the National-Health-Insurance Service cohort-database. We found 45-significant disease-clusters. Of these, 14-disease-clusters were related to fra, while 10 were related to musculoskeletal diseases. Our findings will serve as basic data for further studies.

PURPOSE: Osteoporosis causes devastating fractures; however, its exact etiology remains unknown. Elucidating associated comorbidities and their temporal relationships could provide better insights into its pathogenesis. Comorbidity-network analysis was performed to obtain global view of these associations.

METHODS: We randomly selected 10000-patients with osteoporosis registered in the National-Health-Insurance Service cohort-database. These patients were identified using ICD-10 codes M81-M82, which represent osteoporosis without pathological fractures. Control group was created through propensity score matching. The comorbidities in each group were grouped into similar classifications to form "disease cluster"; 126 such clusters were identified. To create a comorbidity network, we selected disease clusters with high associations (i.e., odds ratios and relative risks ranked in the upper 50th percentile). To identify the temporal relationships between these clusters and osteoporosis, trajectories of directions were identified.

RESULTS: Finally, we found 45 significant disease clusters. Of these, 14 disease clusters were related to fractures or injuries, while 10 were related to musculoskeletal diseases. Temporal analysis revealed that 15 disease clusters preceded osteoporosis; these included the following three with the strongest associations: "other fracture", "disorders of bone density and structure (M83-M85)", and "sequelae of injuries of neck and trunk (T91)". Thirty disease clusters followed osteoporosis; these included the following three with the strongest associations: "spine fracture," "spondylopathies (M45-M49)", and "pelvic region and thigh fracture,".

CONCLUSION: We obtained a global view of the osteoporosis comorbidity network, which is otherwise difficult to achieve through study of individual diseases. Our findings will serve as the basic data for further studies.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты