Enhancing Sepsis prognosis: Integrating social determinants and demographic variables into a comprehensive model for critically ill patients

IF 3.2 3区 医学 Q2 CRITICAL CARE MEDICINE Journal of critical care Pub Date : 2024-07-11 DOI:10.1016/j.jcrc.2024.154857
Elie Sarraf , Alireza Vafaei Sadr , Vida Abedi , Anthony S. Bonavia
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Abstract

Background

The Sequential Organ Failure Assessment (SOFA) score monitors organ failure and defines sepsis but may not fully capture factors influencing sepsis mortality. Socioeconomic and demographic impacts on sepsis outcomes have been highlighted recently.

Objective

To evaluate the prognostic value of SOFA scores against demographic and social health determinants for predicting sepsis mortality in critically ill patients, and to assess if a combined model increases predictive accuracy.

Methods

The study utilized retrospective data from the MIMIC-IV database and prospective external validation from the Penn State Health cohort. A Random Forest model incorporating SOFA scores, demographic/social data, and the Charlson Comorbidity Index was trained and validated.

Findings

In the MIMIC-IV dataset of 32,970 sepsis patients, 6,824 (20.7%) died within 30 days. A model including demographic, socioeconomic, and comorbidity data with SOFA scores improved predictive accuracy beyond SOFA scores alone. Day 2 SOFA, age, weight, and comorbidities were significant predictors. External validation showed consistent performance, highlighting the importance of delta SOFA between days 1 and 3.

Conclusion

Adding patient-specific demographic and socioeconomic information to clinical metrics significantly improves sepsis mortality prediction. This suggests a more comprehensive, multidimensional prognostic approach is needed for accurate sepsis outcome predictions.

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加强败血症预后:将社会决定因素和人口统计学变量纳入重症患者综合模型
背景序贯器官衰竭评估(SOFA)评分可监测器官衰竭并定义败血症,但可能无法完全捕捉影响败血症死亡率的因素。方法该研究利用了来自 MIMIC-IV 数据库的回顾性数据和来自宾夕法尼亚州立卫生院队列的前瞻性外部验证。研究结果在MIMIC-IV数据库的32970名脓毒症患者中,有6824人(20.7%)在30天内死亡。一个包含人口统计学、社会经济学和合并症数据以及 SOFA 评分的模型比单独的 SOFA 评分提高了预测准确性。第2天的SOFA、年龄、体重和合并症是重要的预测因素。结论 在临床指标中添加患者特异性人口和社会经济信息可显著提高脓毒症死亡率预测。这表明,要准确预测脓毒症结果,需要一种更全面、多维度的预后方法。
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来源期刊
Journal of critical care
Journal of critical care 医学-危重病医学
CiteScore
8.60
自引率
2.70%
发文量
237
审稿时长
23 days
期刊介绍: The Journal of Critical Care, the official publication of the World Federation of Societies of Intensive and Critical Care Medicine (WFSICCM), is a leading international, peer-reviewed journal providing original research, review articles, tutorials, and invited articles for physicians and allied health professionals involved in treating the critically ill. The Journal aims to improve patient care by furthering understanding of health systems research and its integration into clinical practice. The Journal will include articles which discuss: All aspects of health services research in critical care System based practice in anesthesiology, perioperative and critical care medicine The interface between anesthesiology, critical care medicine and pain Integrating intraoperative management in preparation for postoperative critical care management and recovery Optimizing patient management, i.e., exploring the interface between evidence-based principles or clinical insight into management and care of complex patients The team approach in the OR and ICU System-based research Medical ethics Technology in medicine Seminars discussing current, state of the art, and sometimes controversial topics in anesthesiology, critical care medicine, and professional education Residency Education.
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