{"title":"前降钙素用于安全减少急诊科不必要的血培养:预测模型的开发与验证。","authors":"","doi":"10.1016/j.jinf.2024.106251","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>Blood cultures (BCs) are commonly ordered in emergency departments (EDs), while a minority yields a relevant pathogen. Diagnostic stewardship is needed to safely reduce unnecessary BCs. We aimed to develop and validate a bacteremia prediction model for ED patients, with specific focus on the benefit of incorporating procalcitonin.</p></div><div><h3>Methods</h3><p>We included adult patients with suspected bacteremia from a Dutch ED for a one-year period. We defined 23 candidate predictors for a “full model”, of which nine were used for an automatable \"basic model”. Variations of both models with C-reactive protein and procalcitonin were constructed using LASSO regression, with bootstrapping for internal validation. External validation was done in an independent cohort of patients with confirmed infection from 71 Spanish EDs. We assessed discriminative performance using the C-statistic and calibration with calibration curves. Clinical usefulness was evaluated by sensitivity, specificity, saved BCs, and Net Benefit.</p></div><div><h3>Results</h3><p>Among 2111 patients in the derivation cohort (mean age 63 years, 46% male), 273 (13%) had bacteremia, versus 896 (20%) in the external cohort (n = 4436). Adding procalcitonin substantially improved performance for all models. The basic model with procalcitonin showed most promise, with a C-statistic of 0.87 (0.86–0.88) upon external validation. At a 5% risk threshold, it showed a sensitivity of 99% and could have saved 29% of BCs while only missing 10 out of 896 (1.1%) bacteremia patients.</p></div><div><h3>Conclusions</h3><p>Procalcitonin-based bacteremia prediction models can safely reduce unnecessary BCs at the ED. Further validation is needed across a broader range of healthcare settings.</p></div>","PeriodicalId":50180,"journal":{"name":"Journal of Infection","volume":null,"pages":null},"PeriodicalIF":14.3000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0163445324001853/pdfft?md5=e49f0fd005e16187df59fc3617f0bf8b&pid=1-s2.0-S0163445324001853-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Procalcitonin for safe reduction of unnecessary blood cultures in the emergency department: Development and validation of a prediction model\",\"authors\":\"\",\"doi\":\"10.1016/j.jinf.2024.106251\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>Blood cultures (BCs) are commonly ordered in emergency departments (EDs), while a minority yields a relevant pathogen. Diagnostic stewardship is needed to safely reduce unnecessary BCs. We aimed to develop and validate a bacteremia prediction model for ED patients, with specific focus on the benefit of incorporating procalcitonin.</p></div><div><h3>Methods</h3><p>We included adult patients with suspected bacteremia from a Dutch ED for a one-year period. We defined 23 candidate predictors for a “full model”, of which nine were used for an automatable \\\"basic model”. Variations of both models with C-reactive protein and procalcitonin were constructed using LASSO regression, with bootstrapping for internal validation. External validation was done in an independent cohort of patients with confirmed infection from 71 Spanish EDs. We assessed discriminative performance using the C-statistic and calibration with calibration curves. Clinical usefulness was evaluated by sensitivity, specificity, saved BCs, and Net Benefit.</p></div><div><h3>Results</h3><p>Among 2111 patients in the derivation cohort (mean age 63 years, 46% male), 273 (13%) had bacteremia, versus 896 (20%) in the external cohort (n = 4436). Adding procalcitonin substantially improved performance for all models. The basic model with procalcitonin showed most promise, with a C-statistic of 0.87 (0.86–0.88) upon external validation. At a 5% risk threshold, it showed a sensitivity of 99% and could have saved 29% of BCs while only missing 10 out of 896 (1.1%) bacteremia patients.</p></div><div><h3>Conclusions</h3><p>Procalcitonin-based bacteremia prediction models can safely reduce unnecessary BCs at the ED. Further validation is needed across a broader range of healthcare settings.</p></div>\",\"PeriodicalId\":50180,\"journal\":{\"name\":\"Journal of Infection\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":14.3000,\"publicationDate\":\"2024-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0163445324001853/pdfft?md5=e49f0fd005e16187df59fc3617f0bf8b&pid=1-s2.0-S0163445324001853-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Infection\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0163445324001853\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Infection","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0163445324001853","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
Procalcitonin for safe reduction of unnecessary blood cultures in the emergency department: Development and validation of a prediction model
Objectives
Blood cultures (BCs) are commonly ordered in emergency departments (EDs), while a minority yields a relevant pathogen. Diagnostic stewardship is needed to safely reduce unnecessary BCs. We aimed to develop and validate a bacteremia prediction model for ED patients, with specific focus on the benefit of incorporating procalcitonin.
Methods
We included adult patients with suspected bacteremia from a Dutch ED for a one-year period. We defined 23 candidate predictors for a “full model”, of which nine were used for an automatable "basic model”. Variations of both models with C-reactive protein and procalcitonin were constructed using LASSO regression, with bootstrapping for internal validation. External validation was done in an independent cohort of patients with confirmed infection from 71 Spanish EDs. We assessed discriminative performance using the C-statistic and calibration with calibration curves. Clinical usefulness was evaluated by sensitivity, specificity, saved BCs, and Net Benefit.
Results
Among 2111 patients in the derivation cohort (mean age 63 years, 46% male), 273 (13%) had bacteremia, versus 896 (20%) in the external cohort (n = 4436). Adding procalcitonin substantially improved performance for all models. The basic model with procalcitonin showed most promise, with a C-statistic of 0.87 (0.86–0.88) upon external validation. At a 5% risk threshold, it showed a sensitivity of 99% and could have saved 29% of BCs while only missing 10 out of 896 (1.1%) bacteremia patients.
Conclusions
Procalcitonin-based bacteremia prediction models can safely reduce unnecessary BCs at the ED. Further validation is needed across a broader range of healthcare settings.
期刊介绍:
The Journal of Infection publishes original papers on all aspects of infection - clinical, microbiological and epidemiological. The Journal seeks to bring together knowledge from all specialties involved in infection research and clinical practice, and present the best work in the ever-changing field of infection.
Each issue brings you Editorials that describe current or controversial topics of interest, high quality Reviews to keep you in touch with the latest developments in specific fields of interest, an Epidemiology section reporting studies in the hospital and the general community, and a lively correspondence section.