Alicia de Lózar de la Viña, Gloria Andrade Vivero, Eduardo Palencia Herrejón, Eva Márquez Liétor, Tamar Talaván Zanón, Elia Pérez-Fernández, Fernando Cava Valenciano, Eduardo Tamayo Gómez
{"title":"基于脓毒症患者降钙素原监测的算法的实用性。","authors":"Alicia de Lózar de la Viña, Gloria Andrade Vivero, Eduardo Palencia Herrejón, Eva Márquez Liétor, Tamar Talaván Zanón, Elia Pérez-Fernández, Fernando Cava Valenciano, Eduardo Tamayo Gómez","doi":"10.1093/labmed/lmae074","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The aim of the study was to develop and validate an algorithm based on procalcitonin (PCT) monitoring to predict the prognosis of patients with sepsis.</p><p><strong>Design: </strong>The design was a retrospective and observational prospective study.</p><p><strong>Setting: </strong>The study was set in intensive care units (ICUs) in 2 different hospitals in Spain.</p><p><strong>Patients: </strong>Patients in the study included 101 patients with sepsis aged ≥18 years.</p><p><strong>Interventions: </strong>In the retrospective study, PCT results from patients admitted to the ICU in 2011-2012 were collected. In the prospective study, PCT was determined at specific time points as indicated by the algorithm from March 2018 to April 2019. The primary outcome measure, 28-day mortality, was the main variable of interest.</p><p><strong>Results: </strong>The study developed an algorithm based on early PCT monitoring for predicting the prognosis of patients with sepsis. The algorithm was initially developed retrospectively in 1 cohort and subsequently validated prospectively in another cohort.</p><p><strong>Conclusions: </strong>The developed algorithm provides information on the prognosis of patients with sepsis, distinguishing between those with a good prognosis and those with a poor prognosis (defined as mortality).</p>","PeriodicalId":94124,"journal":{"name":"Laboratory medicine","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The utility of an algorithm based on procalcitonin monitoring in patients with sepsis.\",\"authors\":\"Alicia de Lózar de la Viña, Gloria Andrade Vivero, Eduardo Palencia Herrejón, Eva Márquez Liétor, Tamar Talaván Zanón, Elia Pérez-Fernández, Fernando Cava Valenciano, Eduardo Tamayo Gómez\",\"doi\":\"10.1093/labmed/lmae074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The aim of the study was to develop and validate an algorithm based on procalcitonin (PCT) monitoring to predict the prognosis of patients with sepsis.</p><p><strong>Design: </strong>The design was a retrospective and observational prospective study.</p><p><strong>Setting: </strong>The study was set in intensive care units (ICUs) in 2 different hospitals in Spain.</p><p><strong>Patients: </strong>Patients in the study included 101 patients with sepsis aged ≥18 years.</p><p><strong>Interventions: </strong>In the retrospective study, PCT results from patients admitted to the ICU in 2011-2012 were collected. In the prospective study, PCT was determined at specific time points as indicated by the algorithm from March 2018 to April 2019. The primary outcome measure, 28-day mortality, was the main variable of interest.</p><p><strong>Results: </strong>The study developed an algorithm based on early PCT monitoring for predicting the prognosis of patients with sepsis. The algorithm was initially developed retrospectively in 1 cohort and subsequently validated prospectively in another cohort.</p><p><strong>Conclusions: </strong>The developed algorithm provides information on the prognosis of patients with sepsis, distinguishing between those with a good prognosis and those with a poor prognosis (defined as mortality).</p>\",\"PeriodicalId\":94124,\"journal\":{\"name\":\"Laboratory medicine\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Laboratory medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/labmed/lmae074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/labmed/lmae074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The utility of an algorithm based on procalcitonin monitoring in patients with sepsis.
Objective: The aim of the study was to develop and validate an algorithm based on procalcitonin (PCT) monitoring to predict the prognosis of patients with sepsis.
Design: The design was a retrospective and observational prospective study.
Setting: The study was set in intensive care units (ICUs) in 2 different hospitals in Spain.
Patients: Patients in the study included 101 patients with sepsis aged ≥18 years.
Interventions: In the retrospective study, PCT results from patients admitted to the ICU in 2011-2012 were collected. In the prospective study, PCT was determined at specific time points as indicated by the algorithm from March 2018 to April 2019. The primary outcome measure, 28-day mortality, was the main variable of interest.
Results: The study developed an algorithm based on early PCT monitoring for predicting the prognosis of patients with sepsis. The algorithm was initially developed retrospectively in 1 cohort and subsequently validated prospectively in another cohort.
Conclusions: The developed algorithm provides information on the prognosis of patients with sepsis, distinguishing between those with a good prognosis and those with a poor prognosis (defined as mortality).