Miguel Palas, Beatriz Valente Silva, Cláudia Jorge, Ana G Almeida, Fausto J Pinto, Daniel Caldeira
{"title":"Hestia和简化PESI预测肺栓塞预后的准确性:系统评价和荟萃分析。","authors":"Miguel Palas, Beatriz Valente Silva, Cláudia Jorge, Ana G Almeida, Fausto J Pinto, Daniel Caldeira","doi":"10.1055/a-1942-2526","DOIUrl":null,"url":null,"abstract":"<p><p><b>Introduction</b> Pulmonary embolism (PE) patients at low risk of early complications may be considered for early discharge or home treatment. Last decades evidence has been growing about the safety of several clinical prediction rules for selecting those patients, such as simplified Pulmonary Embolism Severity Index (sPESI) and Hestia Criteria. The aim of this review was to compare the safety of both strategies regarding 30-days mortality, venous thromboembolism recurrence and major bleeding. <b>Methods</b> A systematic literature search was conducted using MEDLINE, CENTRAL and Web of Science on 6 <sup>th</sup> January 2022. We searched for studies that applied both Hestia Criteria and sPESI to the same population. Sensitivity, specificity and diagnostic odds ratio were calculated for both stratification rules. Both Hestia and sPESI criteria of low risk were evaluated to set the number of patients that could be misclassified for each 1000 patients with PE. The estimates were reported with their 95% confidence intervals (95%CI). <b>Results</b> This systematic review included 3 studies. Only mortality data was able to be pooled. Regarding mortality, the sensitivity, specificity and diagnostic odds ratio was 0.923 (95%CI: 0.843-0.964), 0.338 (95%CI: 0.262-0.423) and 6.120 (95%CI: 2.905-12.890) for Hestia Criteria; and 0.972 (95%CI: 0.917-0.991), 0.269 (95%CI: 0.209-0.338) and 12.738 (95%CI: 3.979-40.774) for sPESI score. The negative predictive values were higher than 0.977. The risk of misclassification of high-risk patients in low risk was 5 (95%CI: 3-11) with Hestia and 2 (95%CI: 1-6) with sPESI, for each 1000 patients with PE in terms of mortality. <b>Conclusion</b> The risk of misclassification of patients presenting with low-risk pulmonary embolism with the intent of early discharge or home treatment with both Hestia Criteria and sPESI score is low and these data supports methods for this purpose.</p>","PeriodicalId":22238,"journal":{"name":"TH Open: Companion Journal to Thrombosis and Haemostasis","volume":" ","pages":"e347-e353"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9593482/pdf/","citationCount":"4","resultStr":"{\"title\":\"The Accuracy of Hestia and Simplified PESI to Predict the Prognosis in Pulmonary Embolism: Systematic Review with Meta-analysis.\",\"authors\":\"Miguel Palas, Beatriz Valente Silva, Cláudia Jorge, Ana G Almeida, Fausto J Pinto, Daniel Caldeira\",\"doi\":\"10.1055/a-1942-2526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Introduction</b> Pulmonary embolism (PE) patients at low risk of early complications may be considered for early discharge or home treatment. Last decades evidence has been growing about the safety of several clinical prediction rules for selecting those patients, such as simplified Pulmonary Embolism Severity Index (sPESI) and Hestia Criteria. The aim of this review was to compare the safety of both strategies regarding 30-days mortality, venous thromboembolism recurrence and major bleeding. <b>Methods</b> A systematic literature search was conducted using MEDLINE, CENTRAL and Web of Science on 6 <sup>th</sup> January 2022. We searched for studies that applied both Hestia Criteria and sPESI to the same population. Sensitivity, specificity and diagnostic odds ratio were calculated for both stratification rules. Both Hestia and sPESI criteria of low risk were evaluated to set the number of patients that could be misclassified for each 1000 patients with PE. The estimates were reported with their 95% confidence intervals (95%CI). <b>Results</b> This systematic review included 3 studies. Only mortality data was able to be pooled. Regarding mortality, the sensitivity, specificity and diagnostic odds ratio was 0.923 (95%CI: 0.843-0.964), 0.338 (95%CI: 0.262-0.423) and 6.120 (95%CI: 2.905-12.890) for Hestia Criteria; and 0.972 (95%CI: 0.917-0.991), 0.269 (95%CI: 0.209-0.338) and 12.738 (95%CI: 3.979-40.774) for sPESI score. The negative predictive values were higher than 0.977. The risk of misclassification of high-risk patients in low risk was 5 (95%CI: 3-11) with Hestia and 2 (95%CI: 1-6) with sPESI, for each 1000 patients with PE in terms of mortality. <b>Conclusion</b> The risk of misclassification of patients presenting with low-risk pulmonary embolism with the intent of early discharge or home treatment with both Hestia Criteria and sPESI score is low and these data supports methods for this purpose.</p>\",\"PeriodicalId\":22238,\"journal\":{\"name\":\"TH Open: Companion Journal to Thrombosis and Haemostasis\",\"volume\":\" \",\"pages\":\"e347-e353\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9593482/pdf/\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TH Open: Companion Journal to Thrombosis and Haemostasis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1055/a-1942-2526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/10/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TH Open: Companion Journal to Thrombosis and Haemostasis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1055/a-1942-2526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/10/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
The Accuracy of Hestia and Simplified PESI to Predict the Prognosis in Pulmonary Embolism: Systematic Review with Meta-analysis.
Introduction Pulmonary embolism (PE) patients at low risk of early complications may be considered for early discharge or home treatment. Last decades evidence has been growing about the safety of several clinical prediction rules for selecting those patients, such as simplified Pulmonary Embolism Severity Index (sPESI) and Hestia Criteria. The aim of this review was to compare the safety of both strategies regarding 30-days mortality, venous thromboembolism recurrence and major bleeding. Methods A systematic literature search was conducted using MEDLINE, CENTRAL and Web of Science on 6 th January 2022. We searched for studies that applied both Hestia Criteria and sPESI to the same population. Sensitivity, specificity and diagnostic odds ratio were calculated for both stratification rules. Both Hestia and sPESI criteria of low risk were evaluated to set the number of patients that could be misclassified for each 1000 patients with PE. The estimates were reported with their 95% confidence intervals (95%CI). Results This systematic review included 3 studies. Only mortality data was able to be pooled. Regarding mortality, the sensitivity, specificity and diagnostic odds ratio was 0.923 (95%CI: 0.843-0.964), 0.338 (95%CI: 0.262-0.423) and 6.120 (95%CI: 2.905-12.890) for Hestia Criteria; and 0.972 (95%CI: 0.917-0.991), 0.269 (95%CI: 0.209-0.338) and 12.738 (95%CI: 3.979-40.774) for sPESI score. The negative predictive values were higher than 0.977. The risk of misclassification of high-risk patients in low risk was 5 (95%CI: 3-11) with Hestia and 2 (95%CI: 1-6) with sPESI, for each 1000 patients with PE in terms of mortality. Conclusion The risk of misclassification of patients presenting with low-risk pulmonary embolism with the intent of early discharge or home treatment with both Hestia Criteria and sPESI score is low and these data supports methods for this purpose.