Racial/Ethnic Differences in Risk Factors Associated With Severe COVID-19 Among Older Adults With ADRD.
Racial/Ethnic Differences in Risk Factors Associated With Severe COVID-19 Among Older Adults With ADRD.
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ADRD老年人中与严重的Covid-19相关的风险因素的种族/种族差异。
DOI：
10.1016/j.jamda.2023.02.111
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发表时间：
2023-06
影响因子：
7.6
通讯作者：
Cai, Shubing
中科院分区：
文献类型：
--
作者：
Qin, Qiuyuan;Veazie, Peter;Temkin-Greener, Helena;Makineni, Rajesh;Cai, Shubing
旨在检查患有阿尔茨海默病和相关痴呆症 (ADRD) 的老年人中危险因素的种族/民族差异及其与 COVID-19 相关结果的关联。观察性研究。本研究将2020年4月1日至2020年12月31日期间的国家医疗保险索赔数据和最低数据集3.0关联起来。我们纳入了患有 ADRD 且在 2020 年 4 月 1 日至 2020 年 12 月 1 日期间诊断出患有 COVID-19 的社区居住按服务收费医疗保险受益人 (N = 138,533)。定义了两个结果变量：COVID-19 诊断后 14 天内住院和 30 天内死亡。我们根据医疗保险索赔和最低数据集获得了有关个人社会人口特征、慢性病和先前医疗保健利用情况的信息。机器学习方法，包括套索回归和判别模式挖掘，被用来识别种族/族裔亚组（即白人、黑人和西班牙裔）的风险因素。使用逻辑回归评估已确定的风险因素和结果之间的关联，并使用系数比较方法在种族/民族亚组之间进行比较。我们发现黑人和西班牙裔人患 COVID-19 相关结果的风险较高。已确定危险因素的模型的曲线下面积在不同种族/族裔亚组中的死亡率为 0.65 至 0.68，住院率为 0.61 至 0.62。尽管一些确定的与COVID-19相关的风险因素（例如年龄、性别）在所有种族/民族亚组中都很常见，但其他风险因素（例如高血压、肥胖）因种族/民族亚组而异。此外，一些常见风险因素与 COVID-19 相关结果之间的关联也因种族/民族而异。西班牙裔、白人和黑人的死亡几率分别增加 138.2% (95% CI: 1.996–2.841)、64.7% (95% CI: 1.546–1.755) 和 37.1% (95% CI: 1.192–1.578)。此外，已确定的风险因素无法完全解释 COVID-19 相关结果中的种族/民族差异。在发生 COVID-19 相关结果的可能性、特定风险因素以及特定风险因素与 COVID-19 相关结果之间的关系方面检测到了种族/民族差异。需要未来的研究来阐明这些差异的原因。
To examine racial/ethnic differences in risk factors, and their associations with COVID-19–related outcomes among older adults with Alzheimer’s disease and related dementias (ADRD). Observational study. National Medicare claims data and the Minimum Data Set 3.0 from April 1, 2020, to December 31, 2020, were linked in this study. We included community-dwelling fee-for-service Medicare beneficiaries with ADRD, diagnosed with COVID-19 between April 1, 2020, and December 1, 2020 (N = 138,533). Two outcome variables were defined: hospitalization within 14 days and death within 30 days of COVID-19 diagnosis. We obtained information on individual sociodemographic characteristics, chronic conditions, and prior health care utilization based on the Medicare claims and the Minimum Dataset. Machine learning methods, including lasso regression and discriminative pattern mining, were used to identify risk factors in racial/ethnic subgroups (ie, White, Black, and Hispanic individuals). The associations between identified risk factors and outcomes were evaluated using logistic regression and compared across racial/ethnic subgroups using the coefficient comparison approach. We found higher risks of COVID-19–related outcomes among Black and Hispanic individuals. The areas under the curve of the models with identified risk factors were 0.65 to 0.68 for mortality and 0.61 to 0.62 for hospitalization across racial/ethnic subgroups. Although some identified risk factors (eg, age, gender) for COVID-19–related outcomes were common among all racial/ethnic subgroups, other risk factors (eg, hypertension, obesity) varied by racial/ethnic subgroups. Furthermore, the associations between some common risk factors and COVID-19–related outcomes also varied by race/ethnicity. Being male was related to 138.2% (95% CI: 1.996–2.841), 64.7% (95% CI: 1.546–1.755), and 37.1% (95% CI: 1.192–1.578) increased odds of death among Hispanic, White, and Black individuals, respectively. In addition, the racial/ethnic disparity in COVID-19–related outcomes could not be completely explained by the identified risk factors. Racial/ethnic differences were detected in the likelihood of having COVID-19–related outcomes, specific risk factors, and relationships between specific risk factors and COVID-19–related outcomes. Future research is needed to elucidate the reasons for these differences.
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影响因子：
3.8
作者：
Heras E;Garibaldi P;Boix M;Valero O;Castillo J;Curbelo Y;Gonzalez E;Mendoza O;Anglada M;Miralles JC;Llull P;Llovera R;Piqué JM
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2.9
作者：
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作者：
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