Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA.
Faculty of Nursing, Jordan University of Science and Technology, Irbid, Jordan.
Crit Care Med. 2024 Sep 1;52(9):1380-1390. doi: 10.1097/CCM.0000000000006338. Epub 2024 May 23.
To assess the impact of different methods of calculating Sequential Organ Failure Assessment (SOFA) scores using electronic health record data on the incidence, outcomes, agreement, and predictive validity of Sepsis-3 criteria.
Retrospective observational study.
Five Massachusetts hospitals.
Hospitalized adults, 2015 to 2022.
None.
We defined sepsis as a suspected infection (culture obtained and antibiotic administered) with a concurrent increase in SOFA score by greater than or equal to 2 points (Sepsis-3 criteria). Our reference SOFA implementation strategy imputed normal values for missing data, used Pa o2 /F io2 ratios for respiratory scores, and assumed normal baseline SOFA scores for community-onset sepsis. We then implemented SOFA scores using different missing data imputation strategies (averaging worst values from preceding and following days vs. carrying forward nonmissing values), imputing respiratory scores using Sp o2 /F io2 ratios, and incorporating comorbidities and prehospital laboratory data into baseline SOFA scores. Among 1,064,459 hospitalizations, 297,512 (27.9%) had suspected infection and 141,052 (13.3%) had sepsis with an in-hospital mortality rate of 10.3% using the reference SOFA method. The percentage of patients missing SOFA components for at least 1 day in the infection window was highest for Pa o2 /F io2 ratios (98.6%), followed by Sp o2 /F io2 ratios (73.5%), bilirubin (68.5%), and Glasgow Coma Scale scores (57.2%). Different missing data imputation strategies yielded near-perfect agreement in identifying sepsis (kappa 0.99). However, using Sp o2 /F io2 imputations yielded higher sepsis incidence (18.3%), lower mortality (8.1%), and slightly lower predictive validity for mortality (area under the receiver operating curves [AUROC] 0.76 vs. 0.78). For community-onset sepsis, incorporating comorbidities and historical laboratory data into baseline SOFA score estimates yielded lower sepsis incidence (6.9% vs. 11.6%), higher mortality (13.4% vs. 9.6%), and higher predictive validity (AUROC 0.79 vs. 0.75) relative to the reference SOFA implementation.
Common variations in calculating respiratory and baseline SOFA scores, but not in handling missing data, lead to substantial differences in observed incidence, mortality, agreement, and predictive validity of Sepsis-3 criteria.
评估使用电子健康记录数据计算序贯器官衰竭评估（SOFA）评分的不同方法对 Sepsis-3 标准的发生率、结局、一致性和预测准确性的影响。
回顾性观察性研究。
马萨诸塞州的 5 家医院。
2015 年至 2022 年住院的成年人。
无。
我们将败血症定义为疑似感染（获得培养物并给予抗生素），SOFA 评分增加大于或等于 2 分（Sepsis-3 标准）。我们的参考 SOFA 实施策略对缺失数据进行了正常值推断，使用 Pa o2 /F io2 比值计算呼吸评分，并假设社区发病败血症的基线 SOFA 评分正常。然后，我们使用不同的缺失数据推断策略（从前一天和后一天的最差值中取平均值与向前推断非缺失值）来计算 SOFA 评分，使用 Sp o2 /F io2 比值推断呼吸评分，并将合并症和院前实验室数据纳入基线 SOFA 评分。在 1064459 例住院患者中，297512 例（27.9%）有疑似感染，141052 例（13.3%）有败血症，院内死亡率为 10.3%，采用参考 SOFA 方法。在感染窗口中至少有 1 天缺失 SOFA 成分的患者百分比最高的是 Pa o2 /F io2 比值（98.6%），其次是 Sp o2 /F io2 比值（73.5%）、胆红素（68.5%）和格拉斯哥昏迷量表评分（57.2%）。不同的缺失数据推断策略在识别败血症方面具有近乎完美的一致性（kappa 值 0.99）。然而，使用 Sp o2 /F io2 推断会导致败血症发生率升高（18.3%）、死亡率降低（8.1%）和死亡率预测准确性略有降低（接受者操作特征曲线下面积 [AUROC] 0.76 与 0.78）。对于社区发病败血症，将合并症和历史实验室数据纳入基线 SOFA 评分估计会降低败血症的发生率（6.9%与 11.6%）、死亡率（13.4%与 9.6%）和预测准确性（AUROC 0.79 与 0.75），与参考 SOFA 实施相比。
计算呼吸和基线 SOFA 评分的常见差异，但不包括处理缺失数据，会导致 Sepsis-3 标准的观察发生率、死亡率、一致性和预测准确性存在显著差异。
