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Predicting population level hip fracture risk: a novel hierarchical model incorporating probabilistic approaches and factor of risk principles

机译:预测人口水平髋关节骨折风险:一种掺入概率方法和风险原则因素的新型等级模型

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摘要

Fall-related hip fractures are a major public health issue. While individual-level risk assessment tools exist, population-level predictive models could catalyze innovation in large-scale interventions. This study presents a hierarchical probabilistic model that predicts population-level hip fracture risk based on Factor of Risk (FOR) principles. Model validation demonstrated that FOR output aligned with a published dataset categorized by sex and hip fracture status. The model predicted normalized FOR for 100000 individuals simulating the Canadian older-adult population. Predicted hip fracture risk was higher for females (by an average of 38%), and increased with age (by15% per decade). Potential applications are discussed.
机译:坠入乎/坠落的髋关节骨折是一个主要的公共卫生问题。 虽然存在个性级风险评估工具,但人口级预测模型可以促进大规模干预的创新。 本研究提出了一种分层概率模型,其基于风险(适用于)原则的因素预测人口级髋关节骨折风险。 模型验证表明,对于输出与性别和髋关节骨折状态分类的发布数据集对齐。 模型预测为100000人模拟加拿大老年人的人口。 雌性的预测髋关节骨折风险较高(平均为38%),随着年龄的增长而增加(每十年15%)。 讨论了潜在的应用。

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