Department of Anesthesiology, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA.
Icahn School of Medicine At Mt. Sinai, New York, NY, USA.
World J Surg. 2019 Oct;43(10):2357-2364. doi: 10.1007/s00268-019-05078-9.
Critical illness disproportionately affects people in low-income countries (LICs). Efforts to improve critical care in LICs must account for differences in demographics and infrastructure compared to high-income settings. Part of this effort includes the development and validation of intensive care unit (ICU) risk stratification models feasible for use in LICs. The purpose of this study was to validate and compare the performance of ICU mortality models developed for use in sub-Saharan Africa.
This was a prospective, observational cohort study of ICU patients in a referral hospital in Malawi. Models were selected for comparison based on a Medline search for studies which developed ICU mortality models based on cohorts in sub-Saharan Africa. Model discrimination was evaluated using the area under the curve with 95% confidence intervals (CI).
During the study, 499 patients were admitted to the study ICU, and after exclusions, there were 319 patients. The cohort was 62% female, with the mean age 31 years (IQR: 23-41), and 74% had surgery preceding ICU admission. Discrimination for hospital mortality ranged from 0.54 (95% CI 0.48, 0.60) for the Universal Vital Assessment (UVA) to 0.72 (95% CI 0.66, 0.78) for the Malawi Intensive care Mortality Evaluation (MIME). After tenfold cross-validation, these results were unchanged.
The MIME outperformed other models in this prospective study. Most ICU models developed for LICs had poor to modest discrimination for hospital mortality. Future research may contribute to a better risk stratification model for LICs by refining and enhancing the MIME.
危重病在低收入国家(LICs)的发病率不成比例。要改善 LICs 的重症监护,必须考虑到与高收入环境相比,人口统计学和基础设施方面的差异。这项工作的一部分包括开发和验证适用于 LICs 的重症监护病房(ICU)风险分层模型。本研究的目的是验证和比较为撒哈拉以南非洲开发的 ICU 死亡率模型的性能。
这是马拉维一家转诊医院 ICU 患者的前瞻性观察队列研究。根据在撒哈拉以南非洲队列中开发 ICU 死亡率模型的研究进行了 Medline 搜索,选择了模型进行比较。使用曲线下面积(95%置信区间(CI)来评估模型的判别能力。
在研究期间,有 499 名患者入住研究 ICU,排除后有 319 名患者。该队列中 62%为女性,平均年龄为 31 岁(IQR:23-41),74%在 ICU 入院前接受过手术。医院死亡率的判别范围从通用生命评估(UVA)的 0.54(95%CI 0.48, 0.60)到马拉维重症监护死亡率评估(MIME)的 0.72(95%CI 0.66, 0.78)。经过十倍交叉验证,结果保持不变。
在这项前瞻性研究中,MIME 优于其他模型。为 LICs 开发的大多数 ICU 模型对医院死亡率的判别能力较差或中等。未来的研究可能通过改进和增强 MIME,为 LICs 提供更好的风险分层模型。