Suppr超能文献

老年人 ICD-10-CM 编码数据中 Summary Elixhauser 合并症评分的制定与验证。

Development and Validation of the Summary Elixhauser Comorbidity Score for Use With ICD-10-CM-Coded Data Among Older Adults.

机构信息

Center for Drug Safety & Effectiveness and Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (H.B.M., H.A.).

Sealy Center on Aging, Department of Internal Medicine, The University of Texas Medical Branch at Galveston, Galveston, Texas (S.L., J.S.G.).

出版信息

Ann Intern Med. 2022 Oct;175(10):1423-1430. doi: 10.7326/M21-4204. Epub 2022 Sep 13.

Abstract

BACKGROUND

Older adults have many comorbidities contributing to mortality.

OBJECTIVE

To develop a summary Elixhauser (S-Elixhauser) comorbidity score to predict 30-day, in-hospital, and 1-year mortality in older adults using the 38 comorbidities operationalized by the Agency for Healthcare Research and Quality (AHRQ).

DESIGN

Retrospective cohort study.

SETTING

Medicare beneficiaries from 2017 to 2019.

PATIENTS

Persons hospitalized in 2018 ( 899 844) and 3 disease-specific hospitalized cohorts.

MEASUREMENTS

Weights were derived for 38 comorbidities to predict 30-day, in-hospital, and 1-year mortality. The S-Elixhauser score was internally validated and calibrated. Individual Elixhauser comorbidity indicators (38 comorbidities), the modified application of the AHRQ-derived Elixhauser summary score, the Charlson comorbidity indicators (17 comorbidities), and the Charlson summary score were externally validated. The c-statistic was used to evaluate discrimination of a comorbidity score model.

RESULTS

The S-Elixhauser score was well calibrated and internally validated, with a c-statistic of 0.705 (95% CI, 0.703 to 0.707) in predicting 30-day mortality, 0.654 (CI, 0.651 to 0.657) for in-hospital mortality, and 0.743 (CI, 0.741 to 0.744) for 1-year mortality. In external validation of other comorbidity indices for 30-day mortality, the c-statistic was 0.711 (CI, 0.709 to 0.713) for the individual Elixhauser comorbidity indicators, 0.688 (CI, 0.686 to 0.690) for the AHRQ Elixhauser score, 0.696 (CI, 0.694 to 0.698) for the Charlson comorbidity indicators, and 0.690 (CI, 0.688 to 0.693) for the Charlson summary score. In 3 disease-specific populations, the discrimination of the S-Elixhauser score in predicting 30-day mortality ranged from 0.657 to 0.732.

LIMITATION

Validation of the S-Elixhauser comorbidity score and head-to-head comparison with other comorbidity scores in an external population are needed to evaluate comparative performance.

CONCLUSION

The S-Elixhauser comorbidity score is well calibrated and internally validated but its advantage over the AHRQ Elixhauser and Charlson summary scores is unclear.

PRIMARY FUNDING SOURCE

National Institute on Aging.

摘要

背景

老年人有许多合并症会导致死亡。

目的

利用医疗保健研究与质量局(AHRQ)定义的 38 种合并症,开发一种简化的 Elixhauser(S-Elixhauser)合并症评分,以预测老年人 30 天、住院和 1 年的死亡率。

设计

回顾性队列研究。

地点

2017 年至 2019 年的医疗保险受益人群。

患者

2018 年住院患者(899844 人)和 3 个特定疾病住院患者队列。

测量

为 38 种合并症赋予权重,以预测 30 天、住院和 1 年的死亡率。对 S-Elixhauser 评分进行内部验证和校准。对个体 Elixhauser 合并症指标(38 种合并症)、AHRQ 衍生的 Elixhauser 综合评分的修改应用、Charlson 合并症指标(17 种合并症)和 Charlson 综合评分进行外部验证。使用 C 统计量评估合并症评分模型的判别能力。

结果

S-Elixhauser 评分校准良好且内部验证有效,预测 30 天死亡率的 C 统计量为 0.705(95%CI,0.703 至 0.707),预测住院期间死亡率的 C 统计量为 0.654(CI,0.651 至 0.657),预测 1 年死亡率的 C 统计量为 0.743(CI,0.741 至 0.744)。在对其他合并症指标进行 30 天死亡率的外部验证中,个体 Elixhauser 合并症指标的 C 统计量为 0.711(CI,0.709 至 0.713),AHRQ Elixhauser 评分的 C 统计量为 0.688(CI,0.686 至 0.690),Charlson 合并症指标的 C 统计量为 0.696(CI,0.694 至 0.698),Charlson 综合评分的 C 统计量为 0.690(CI,0.688 至 0.693)。在 3 个特定疾病人群中,S-Elixhauser 评分预测 30 天死亡率的判别能力范围为 0.657 至 0.732。

局限性

需要对 S-Elixhauser 合并症评分进行外部人群验证和与其他合并症评分的头对头比较,以评估比较性能。

结论

S-Elixhauser 合并症评分校准良好且内部验证有效,但与 AHRQ Elixhauser 和 Charlson 综合评分相比其优势尚不清楚。

主要资金来源

美国国家老龄化研究所。

相似文献

1
Development and Validation of the Summary Elixhauser Comorbidity Score for Use With ICD-10-CM-Coded Data Among Older Adults.
Ann Intern Med. 2022 Oct;175(10):1423-1430. doi: 10.7326/M21-4204. Epub 2022 Sep 13.
2
Adapting the Elixhauser comorbidity index for cancer patients.
Cancer. 2018 May 1;124(9):2018-2025. doi: 10.1002/cncr.31269. Epub 2018 Feb 1.
3
Development of comorbidity score for patients undergoing major surgery.
Health Serv Res. 2019 Dec;54(6):1223-1232. doi: 10.1111/1475-6773.13209. Epub 2019 Oct 1.
5
The Elixhauser comorbidity method outperforms the Charlson index in predicting inpatient death after orthopaedic surgery.
Clin Orthop Relat Res. 2014 Sep;472(9):2878-86. doi: 10.1007/s11999-014-3686-7. Epub 2014 May 28.

引用本文的文献

1
Outcomes After Transcatheter Aortic Valve Replacement Among Medicare Beneficiaries: The Impact of Frailty and Social Vulnerability.
Struct Heart. 2025 Jun 24;9(8):100685. doi: 10.1016/j.shj.2025.100685. eCollection 2025 Aug.
3
Outcomes of Human Metapneumovirus Infections in Nursing Home Residents: A Matched Cohort Analysis.
J Infect Dis. 2025 Jul 16;232(Supplement_1):S29-S36. doi: 10.1093/infdis/jiaf151.
4
ECMO and impella increase stroke risk in acute myocardial infarction.
Sci Rep. 2025 Jul 14;15(1):25402. doi: 10.1038/s41598-025-10555-4.
5
Retrospective analysis of general surgery outcomes in multicenter cohorts in Saudi Arabia.
J Med Life. 2025 Apr;18(4):299-305. doi: 10.25122/jml-2024-0337.
7
Correlation of the femoral pulse and mesenteric perfusion pressure in acute aortic dissection.
JTCVS Open. 2024 Nov 15;23:34-43. doi: 10.1016/j.xjon.2024.10.028. eCollection 2025 Feb.
8
Approaches to characterising multimorbidity in older people accessing hospital care: a scoping review.
Eur Geriatr Med. 2025 Aug;16(4):1099-1113. doi: 10.1007/s41999-025-01166-3. Epub 2025 Mar 1.
10
Engaging Patients in Discussions About Medication Deprescribing.
J Gen Intern Med. 2025 Jan 29. doi: 10.1007/s11606-024-09346-w.

本文引用的文献

1
Patient Trajectories Among Persons Hospitalized for COVID-19 : A Cohort Study.
Ann Intern Med. 2021 Jan;174(1):33-41. doi: 10.7326/M20-3905. Epub 2020 Sep 22.
2
Validation in prediction research: the waste by data splitting.
J Clin Epidemiol. 2018 Nov;103:131-133. doi: 10.1016/j.jclinepi.2018.07.010. Epub 2018 Jul 29.
3
On the Use of Summary Comorbidity Measures for Prognosis and Survival Treatment Effect Estimation.
Health Serv Outcomes Res Methodol. 2017 Dec;17(3-4):237-255. doi: 10.1007/s10742-017-0171-2. Epub 2017 Jun 21.
5
Regression coefficient-based scoring system should be used to assign weights to the risk index.
J Clin Epidemiol. 2016 Nov;79:22-28. doi: 10.1016/j.jclinepi.2016.03.031. Epub 2016 May 13.
6
Comparison of Comorbidity Scores in Predicting Surgical Outcomes.
Med Care. 2016 Feb;54(2):180-7. doi: 10.1097/MLR.0000000000000465.
7
A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality.
Med Care. 2015 Apr;53(4):374-9. doi: 10.1097/MLR.0000000000000326.
10
Why Summary Comorbidity Measures Such As the Charlson Comorbidity Index and Elixhauser Score Work.
Med Care. 2015 Sep;53(9):e65-72. doi: 10.1097/MLR.0b013e318297429c.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验