Journal of clinical orthopaedics and trauma · 2025
Development of a cost-effective osteoporosis risk scoring system for early detection in low-resource settings: A community-based approach.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
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.
Muzzammil Muhammad, Owais Minhas Muhammad, Jamil Amna
Аннотация
BACKGROUND: Osteoporotic fractures pose a significant public health burden, particularly in resource-constrained settings where diagnostic tools like DXA scans are unavailable. This study aimed to develop and validate a simple, community-based osteoporosis risk scoring system that incorporates demographic, clinical, and radiographic parameters to identify high-risk individuals for early intervention.
METHODS: A cross-sectional study was conducted in Karachi, Pakistan, involving 750 participants aged 40 years and above. Data on demographic characteristics, clinical risk factors, and lifestyle habits were collected using a structured questionnaire. Radiographic assessments identified vertebral compression fractures, generalized osteopenia, and trabecular bone loss. Participants were stratified into four risk categories: low, moderate, high, and very high risk. The predictive validity of the scoring system was evaluated using logistic regression and receiver operating characteristic (ROC) curve analysis.
RESULTS: The developed tool classified participants into low (38 %), moderate (32 %), high (20 %), and very high (10 %) risk groups. Fracture incidence ranged from 11.29 % in the low-risk group to 28.23 % in the very high-risk group. The scoring system demonstrated strong predictive accuracy, with a sensitivity of 83 %, specificity of 75 %, and an area under the curve (AUC) of 0.82. Odds ratios for fractures progressively increased with higher risk categories, confirming the model's validity.
CONCLUSION: This Muzzammil's osteoporosis risk scoring system is a cost-effective and practical tool for early identification of high-risk individuals in low-resource settings. Its implementation could aid in targeted prevention strategies, reducing osteoporotic fracture incidence and improving public health outcomes. Further validation in diverse populations is recommended to optimize its utility.
METHODS: A cross-sectional study was conducted in Karachi, Pakistan, involving 750 participants aged 40 years and above. Data on demographic characteristics, clinical risk factors, and lifestyle habits were collected using a structured questionnaire. Radiographic assessments identified vertebral compression fractures, generalized osteopenia, and trabecular bone loss. Participants were stratified into four risk categories: low, moderate, high, and very high risk. The predictive validity of the scoring system was evaluated using logistic regression and receiver operating characteristic (ROC) curve analysis.
RESULTS: The developed tool classified participants into low (38 %), moderate (32 %), high (20 %), and very high (10 %) risk groups. Fracture incidence ranged from 11.29 % in the low-risk group to 28.23 % in the very high-risk group. The scoring system demonstrated strong predictive accuracy, with a sensitivity of 83 %, specificity of 75 %, and an area under the curve (AUC) of 0.82. Odds ratios for fractures progressively increased with higher risk categories, confirming the model's validity.
CONCLUSION: This Muzzammil's osteoporosis risk scoring system is a cost-effective and practical tool for early identification of high-risk individuals in low-resource settings. Its implementation could aid in targeted prevention strategies, reducing osteoporotic fracture incidence and improving public health outcomes. Further validation in diverse populations is recommended to optimize its utility.