Treat Systems ApS, Aalborg, Denmark.
Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
Eur J Clin Microbiol Infect Dis. 2019 Aug;38(8):1515-1522. doi: 10.1007/s10096-019-03581-4. Epub 2019 May 11.
Selecting high-risk patients may improve the cost-effectiveness of rapid diagnostics. Our objective was to assess whether model-based selection or clinical selection is better for selecting high-risk patients with a high rate of bacteremia and/or DNAemia. This study involved a model-based, retrospective selection of patients from a cohort from which clinicians selected high-risk patients for rapid direct-from-blood diagnostic testing. Patients were included if they were suspected of sepsis and had blood cultures ordered at the emergency department. Patients were selected by the model by adding those with the highest probability of bacteremia until the number of high-risk patients selected by clinicians was reached. The primary outcome was bacteremia rate. Secondary outcomes were DNAemia rate, and 30-day mortality. Data were collected for 1395 blood cultures. Following exclusion, 1142 patients were included in the analysis. In each high-risk group, 220/1142 were selected, where 55 were selected both by clinicians and the model. For the remaining 165 in each group, the model selected for a higher bacteremia rate (74/165, 44.8% vs. 45/165, 27.3%, p = 0.001), and a higher 30-day mortality (49/165, 29.7% vs. 19/165, 11.5%, p = 0.00004) than the clinically selected group. The model outperformed clinicians in selecting patients with a high rate of bacteremia. Using such a model for risk stratification may contribute towards closing the gap in cost between rapid and culture-based diagnostics.
选择高危患者可能会提高快速诊断的成本效益。我们的目的是评估基于模型的选择还是临床选择更适合选择菌血症和/或 DNA 血症发生率较高的高危患者。本研究涉及对来自队列的患者进行基于模型的回顾性选择,其中临床医生为快速直接从血液中进行诊断检测选择高危患者。如果患者怀疑患有败血症并且在急诊科开了血培养,则将其纳入研究。通过添加菌血症可能性最高的患者,模型选择患者,直到达到临床医生选择的高危患者数量。主要结局是菌血症发生率。次要结局是 DNA 血症发生率和 30 天死亡率。共收集了 1395 份血培养数据。排除后,1142 名患者纳入分析。在每个高危组中,选择了 1142 名中的 220 名,其中 55 名是由临床医生和模型共同选择的。对于每组中的其余 165 名患者,模型选择的菌血症发生率更高(74/165,44.8%比 45/165,27.3%,p=0.001),30 天死亡率更高(49/165,29.7%比 19/165,11.5%,p=0.00004)。与临床选择组相比,模型在选择菌血症发生率较高的患者方面表现优于临床医生。使用这种模型进行风险分层可能有助于缩小快速和基于培养的诊断之间的成本差距。