Atta Taseh, Evan Sirls, George Casey, Sarah Hearns, Job N Doornberg, Santiago A Lozano-Calderon, Mitchel B Harris, Soheil Ashkani-Esfahani
{"title":"预测跌倒所致髋部骨折的改良 FRAX 评分;跌倒能量、次数和社会脆弱性指数的附加值","authors":"Atta Taseh, Evan Sirls, George Casey, Sarah Hearns, Job N Doornberg, Santiago A Lozano-Calderon, Mitchel B Harris, Soheil Ashkani-Esfahani","doi":"10.1101/2024.01.27.24301867","DOIUrl":null,"url":null,"abstract":"Background: The Fracture Risk Assessment Tool (FRAX), widely used for predicting the 10-year likelihood of hip fractures, does not incorporate factors like prior falls and sociodemographic characteristics, notably the Social Vulnerability Index (SVI). Recognizing these limitations, we aim to evaluate the predictive accuracy of FRAX by integrating fall frequency, fall energy, and SVI into the model for assessing the risk of fall-induced hip fractures.\nMethods: A retrospective case-control study was conducted, and patients aged ≥ 40 years with a documented diagnosis of a fall-induced hip fracture were age-matched with controls with a history of falls without an associated hip fracture. Basic demographic data, along with information about the number of prior falls and the energy of the current falls, were collected. The FRAX and SVI were calculated accordingly. Logistic regression analysis was employed to identify significant predictors. The performance of the models was evaluated and reported using appropriate metrics. Baseline characteristics of the dataset were presented as medians with interquartile ranges (IQR) or as percentages, where applicable. The significance of the identified variables was quantified using Odds Ratio (OR) along with their 95% Confidence Interval (CI). A p-value threshold of 0.05 was set for statistical significance.\nResults: A total of 261 patients per group were included with a median age of 74 (IQR 67-80) and 72 (IQR 62-83) years. The FRAX score was significantly associated with the likelihood of experiencing a fall-induced hip fracture, as indicated by an OR of 1.06 (CI: 1.03-1.09). Participants with a one-time history of falls had an OR of 1.58 (CI: 1.02-2.37), compared to 1.84 (CI: 1.09-3.1) for those with multiple falls. The white race, along with the Housing Type and Transportation domain of the SVI, also demonstrated to play a role (OR= 2.85 (CI: 1.56-5.2) and OR= 0.3 (CI: 0.12-0.8), respectively).\nConclusion: This study underscored the significance of factors such as fall frequency, SVI, and race in predicting fall-induced hip fractures. It also highlighted the need for further refinement of the FRAX tool. We recommend that future research should be focused on validating the impact of these sociodemographic and fall characteristics on a broader scale, along with exploring the implications of clinical surrogates related to falls. Keywords: FRAX; Fall; Hip Fracture","PeriodicalId":501263,"journal":{"name":"medRxiv - Orthopedics","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modified FRAX Score for Prediction of Fall-induced Hip Fractures; The Added Value of Fall Energy, Number, and Social Vulnerability Index\",\"authors\":\"Atta Taseh, Evan Sirls, George Casey, Sarah Hearns, Job N Doornberg, Santiago A Lozano-Calderon, Mitchel B Harris, Soheil Ashkani-Esfahani\",\"doi\":\"10.1101/2024.01.27.24301867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: The Fracture Risk Assessment Tool (FRAX), widely used for predicting the 10-year likelihood of hip fractures, does not incorporate factors like prior falls and sociodemographic characteristics, notably the Social Vulnerability Index (SVI). Recognizing these limitations, we aim to evaluate the predictive accuracy of FRAX by integrating fall frequency, fall energy, and SVI into the model for assessing the risk of fall-induced hip fractures.\\nMethods: A retrospective case-control study was conducted, and patients aged ≥ 40 years with a documented diagnosis of a fall-induced hip fracture were age-matched with controls with a history of falls without an associated hip fracture. Basic demographic data, along with information about the number of prior falls and the energy of the current falls, were collected. The FRAX and SVI were calculated accordingly. Logistic regression analysis was employed to identify significant predictors. The performance of the models was evaluated and reported using appropriate metrics. Baseline characteristics of the dataset were presented as medians with interquartile ranges (IQR) or as percentages, where applicable. The significance of the identified variables was quantified using Odds Ratio (OR) along with their 95% Confidence Interval (CI). A p-value threshold of 0.05 was set for statistical significance.\\nResults: A total of 261 patients per group were included with a median age of 74 (IQR 67-80) and 72 (IQR 62-83) years. The FRAX score was significantly associated with the likelihood of experiencing a fall-induced hip fracture, as indicated by an OR of 1.06 (CI: 1.03-1.09). Participants with a one-time history of falls had an OR of 1.58 (CI: 1.02-2.37), compared to 1.84 (CI: 1.09-3.1) for those with multiple falls. The white race, along with the Housing Type and Transportation domain of the SVI, also demonstrated to play a role (OR= 2.85 (CI: 1.56-5.2) and OR= 0.3 (CI: 0.12-0.8), respectively).\\nConclusion: This study underscored the significance of factors such as fall frequency, SVI, and race in predicting fall-induced hip fractures. It also highlighted the need for further refinement of the FRAX tool. We recommend that future research should be focused on validating the impact of these sociodemographic and fall characteristics on a broader scale, along with exploring the implications of clinical surrogates related to falls. Keywords: FRAX; Fall; Hip Fracture\",\"PeriodicalId\":501263,\"journal\":{\"name\":\"medRxiv - Orthopedics\",\"volume\":\"20 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Orthopedics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.01.27.24301867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Orthopedics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.01.27.24301867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
背景:骨折风险评估工具(FRAX骨折风险评估工具(FRAX)被广泛用于预测10年髋部骨折的可能性,但该工具并没有将先前跌倒和社会人口特征等因素纳入其中,特别是社会脆弱性指数(SVI)。认识到这些局限性,我们旨在通过将跌倒频率、跌倒能量和 SVI 纳入模型来评估 FRAX 的预测准确性,从而评估跌倒诱发髋部骨折的风险:方法: 我们进行了一项回顾性病例对照研究,将年龄≥40 岁、确诊为跌倒诱发髋部骨折的患者与有跌倒史但未伴有髋部骨折的对照组进行年龄配对。研究人员收集了基本的人口统计学数据、先前跌倒的次数和当前跌倒的能量等信息。并据此计算出 FRAX 和 SVI。采用逻辑回归分析来确定重要的预测因素。使用适当的指标对模型的性能进行评估和报告。数据集的基线特征以中位数和四分位数间距 (IQR) 或百分比(如适用)表示。已确定变量的显著性使用比值比(OR)及其 95% 置信区间(CI)进行量化。统计显著性的 p 值阈值设定为 0.05:每组共纳入 261 名患者,中位年龄分别为 74 岁(IQR 67-80)和 72 岁(IQR 62-83)。FRAX 评分与跌倒导致髋部骨折的可能性有明显相关性,OR 值为 1.06(CI:1.03-1.09)。有过一次跌倒史的参与者的 OR 值为 1.58(CI:1.02-2.37),而有过多次跌倒史的参与者的 OR 值为 1.84(CI:1.09-3.1)。白种人以及SVI的住房类型和交通领域也显示出了一定的作用(OR= 2.85(CI:1.56-5.2)和OR= 0.3(CI:0.12-0.8)):本研究强调了跌倒频率、SVI 和种族等因素在预测跌倒诱发髋部骨折方面的重要性。研究还强调了进一步完善 FRAX 工具的必要性。我们建议今后的研究应侧重于在更大范围内验证这些社会人口学特征和跌倒特征的影响,同时探索与跌倒相关的临床代用指标的影响。关键词FRAX;跌倒;髋部骨折
Modified FRAX Score for Prediction of Fall-induced Hip Fractures; The Added Value of Fall Energy, Number, and Social Vulnerability Index
Background: The Fracture Risk Assessment Tool (FRAX), widely used for predicting the 10-year likelihood of hip fractures, does not incorporate factors like prior falls and sociodemographic characteristics, notably the Social Vulnerability Index (SVI). Recognizing these limitations, we aim to evaluate the predictive accuracy of FRAX by integrating fall frequency, fall energy, and SVI into the model for assessing the risk of fall-induced hip fractures.
Methods: A retrospective case-control study was conducted, and patients aged ≥ 40 years with a documented diagnosis of a fall-induced hip fracture were age-matched with controls with a history of falls without an associated hip fracture. Basic demographic data, along with information about the number of prior falls and the energy of the current falls, were collected. The FRAX and SVI were calculated accordingly. Logistic regression analysis was employed to identify significant predictors. The performance of the models was evaluated and reported using appropriate metrics. Baseline characteristics of the dataset were presented as medians with interquartile ranges (IQR) or as percentages, where applicable. The significance of the identified variables was quantified using Odds Ratio (OR) along with their 95% Confidence Interval (CI). A p-value threshold of 0.05 was set for statistical significance.
Results: A total of 261 patients per group were included with a median age of 74 (IQR 67-80) and 72 (IQR 62-83) years. The FRAX score was significantly associated with the likelihood of experiencing a fall-induced hip fracture, as indicated by an OR of 1.06 (CI: 1.03-1.09). Participants with a one-time history of falls had an OR of 1.58 (CI: 1.02-2.37), compared to 1.84 (CI: 1.09-3.1) for those with multiple falls. The white race, along with the Housing Type and Transportation domain of the SVI, also demonstrated to play a role (OR= 2.85 (CI: 1.56-5.2) and OR= 0.3 (CI: 0.12-0.8), respectively).
Conclusion: This study underscored the significance of factors such as fall frequency, SVI, and race in predicting fall-induced hip fractures. It also highlighted the need for further refinement of the FRAX tool. We recommend that future research should be focused on validating the impact of these sociodemographic and fall characteristics on a broader scale, along with exploring the implications of clinical surrogates related to falls. Keywords: FRAX; Fall; Hip Fracture