Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC; Department of Family Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC; School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC.
J Am Med Dir Assoc. 2018 Jun;19(6):492-496.e1. doi: 10.1016/j.jamda.2018.02.001. Epub 2018 Mar 26.
To determine whether and to what extent simple screening tools might identify nursing home (NH) residents who are at high risk of becoming septic.
Retrospective chart audit of all residents who had been hospitalized and returned to participating NHs during the study period.
A total of 236 NH residents, 59 of whom returned from hospitals with a diagnosis of sepsis and 177 who had nonsepsis discharge diagnoses, from 31 community NHs that are typical of US nursing homes overall.
NH documentation of vital signs, mental status change, and medical provider visits 0-12 and 13-72 hours prior to the hospitalization. The specificity and sensitivity of 5 screening tools were evaluated for their ability to detect residents with incipient sepsis during 0-12 and 13-72 hours prior to hospitalization: The Systemic Inflammatory Response Syndrome criteria, the quick Sequential Organ Failure Assessment (SOFA), the 100-100-100 Early Detection Tool, and temperature thresholds of 99.0°F and 100.2°F. In addition, to validate the hospital diagnosis of sepsis, hospital discharge records in the NHs were audited to calculate SOFA scores.
Documentation of 1 or more vital signs was absent in 26%-34% of cases. Among persons with complete vital sign documentation, during the 12 hours prior to hospitalization, the most sensitive screening tools were the 100-100-100 Criteria (79%) and an oral temperature >99.0°F (51%); and the most specific tools being a temperature >100.2°F (93%), the quick SOFA (88%), the Systemic Inflammatory Response Syndrome criteria (86%), and a temperature >99.0°F (85%). Many SOFA data points were missing from the record; in spite of this, 65% of cases met criteria for sepsis.
NHs need better systems to monitor NH residents whose status is changing, and to present that information to medical providers in real time, either through rapid medical response programs or telemetry.
确定简单的筛查工具是否以及在何种程度上可以识别有发生脓毒症高风险的养老院(NH)居民。
对研究期间住院后返回参与 NH 的所有居民进行回顾性图表审查。
来自 31 家社区 NH 的 236 名 NH 居民,其中 59 名从医院返回时有脓毒症诊断,177 名有非脓毒症出院诊断,这些 NH 是美国 NH 的典型代表。
NH 记录了生命体征、精神状态变化以及住院前 0-12 小时和 13-72 小时内的医疗提供者就诊情况。评估了 5 种筛查工具的特异性和敏感性,以评估它们在住院前 0-12 小时和 13-72 小时内识别有初期脓毒症的居民的能力:全身炎症反应综合征标准、快速序贯器官衰竭评估(SOFA)、100-100-100 早期检测工具以及 99.0°F 和 100.2°F 的体温阈值。此外,为了验证 NH 中脓毒症的医院诊断,对 NH 的医院出院记录进行了审核,以计算 SOFA 评分。
在 26%-34%的病例中,有 1 项或多项生命体征记录缺失。在有完整生命体征记录的人群中,在住院前 12 小时内,最敏感的筛查工具是 100-100-100 标准(79%)和口腔温度>99.0°F(51%);最特异的工具是体温>100.2°F(93%)、快速 SOFA(88%)、全身炎症反应综合征标准(86%)和体温>99.0°F(85%)。记录中缺失了许多 SOFA 数据点;尽管如此,仍有 65%的病例符合脓毒症标准。
NH 需要更好的系统来监测 NH 居民的状态变化,并实时向医疗提供者提供这些信息,无论是通过快速医疗响应计划还是遥测技术。