| Literature DB >> 36128845 |
Yubin Wang1, Yinhe Feng2, Rao Du1, Xiaoya Yang1, Jifeng Huang1, Hui Mao1.
Abstract
Previous studies have suggested that Hestia criteria could effectively identifying patients with acute pulmonary embolism (PE) who were at low risk of mortality for outpatient treatment or early discharge. But the performance of Hestia criteria in stratifying patients at different risk class is still unknown. We sought to comprehensively evaluate the prognostic impact of Hestia criteria for PE. The literatures search was conducted in PubMed, Web of Science and EMBASE from 1 August 2011 to 31 October 2021. Finally, Eight studies with 4110 patients were included in our meta-analysis. Overall, the pool percentage of patients classified as low-risk group and high-risk group were 41.4%% and 58.6% respectively, and the all-course mortality rates of each group were 2.3% and 10.6%, respectively. The pooled rate of PE-related composite adverse outcomes in high-risk group was increasingly higher than in low-risk group (15.7% vs 4.4%). High risk group was also markedly associated with overall mortality (OR: 7.21, 95%CI: 4.96-10.46, p < 0.00001), and PE-related adverse outcomes (OR:5.38, 95% CI:3.95-7.32, p < 0.00001). The pooled sensitivity, specificity, PLR, NLR of Hestia criteria for overall mortality were 0.90 (95% CI:0.83-0.94), 0.43 (95% CI:0.31-0.55), 1.6 (95% CI:1.3-1.9), 0.23 (95% CI: 0.15-0.35), respectively. The area under SROC curve (AUC) was 0.81 (95% CI: 0.77-0.84). The result of our meta-analysis indicate that Hestia criteria can effectively identify PE patients at low risk of poor prognosis with high sensitivity and NPV, but its prognostic role in patients with higher risk class still need to be verified.Entities:
Keywords: Hestia criteria; meta-analysis; prognosis; pulmonary embolism
Mesh:
Year: 2022 PMID: 36128845 PMCID: PMC9500309 DOI: 10.1177/10760296221126173
Source DB: PubMed Journal: Clin Appl Thromb Hemost ISSN: 1076-0296 Impact factor: 3.512
Figure 1.Flow chart of literature selection.
Characteristics of Included Studies in this Meta-Analysis
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| Zondag 2013 | Netherlands | 2008-2010 | Prospective | 530 | 58.1 | 54.3% | 14.3% | 54.2% | 45.8% | 3 months | RecurrentVTE,major bleeding,all-cause mortality | 8 |
| Weeda 2016 | USA | 2010-2015 | Retrospective | 573 | 64.1 ± 16.4 | 64.9% | 44.3% | 28.0% | 72.0% | 30 days | All-cause mortality | 7 |
| Vanni 2018 | Italy | 2014-2017 | Prospective | 547 | 76(65-83) | 46.1% | 39.5% | 41.7% | 58.3% | 30 days | RecurrentVTE,major bleeding,all-cause mortality | 8 |
| Quezada 2019 | Spain | 2015-2017 | Prospective | 488 | 69.0 ± 17.1 | 50.6% | 11.3% | 27.0% | 73.0% | 30 days | All-cause mortality | 7 |
| Weeda 2019 | USA | 2010-2014 | Retrospective | 124 | 66.2 ± 12.8 | 50.0% | 100.0% | 18.5% | 81.5% | 30 days | All-cause mortality | 7 |
| Hendriks 2020 | Netherlands | 2013-2015 | Retrospective | 404 | 59 ± 16 | 48.3% | 13.1% | 46.0% | 54.0% | 3 months | RecurrentVTE,major bleeding,all-cause mortality | 8 |
| Li 2021 | China | 2014-2019 | Retrospective | 460 | 63(52-71) | 57.1% | 100.0% | 65.4% | 34.6% | 30 days | RecurrentVTE,major bleeding,all-cause mortality | 8 |
| Roy 2021 | Europe | 2017-2019 | Prospective | 984 | 63.5 ± 17.7 | 51.7% | 37.1% | 38.4% | 61.6% | 3 months | RecurrentVTE,major bleeding,all-cause mortality | 8 |
Data are shown as numbers (%), mean ± standard deviation or median (first quartile–third quartile).
Incidence of PE Related Adverse Outcomes Regarding Different Risk Classes.
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| Zondag 2013 | 4.8% | 1.0% | 9.4% | 10.0% | 3.7% | 18.0% |
| Weeda 2016 | 3.7% | 0.0% | 5.1% | NR | NR | NR |
| Vanni 2018 | 8.0% | 2.2% | 12.2% | 9.9% | 2.6% | 15.4% |
| Quezada 2019 | 6.3% | 2.3% | 7.9% | NR | NR | NR |
| Weeda 2019 | 20.2% | 13.0% | 21.8% | NR | NR | NR |
| Hendriks 2020 | 3.9% | 1.1% | 6.4% | 6.9% | 3.2% | 10.0% |
| Li 2021 | 18.0% | 7.3% | 38.4% | 20.2% | 8.9% | 41.5% |
| Roy 2021 | 5.2% | 0.5% | 8.1% | 7.5% | 2.9% | 10.4% |
NR, not reported; PE, pulmonary embolism.
Figure 2.Forrest plots of overall mortality(a) and adverse outcomes(b) with regard to high risk and low risk.
Figure 3.Subgroup analysis for overall mortality (high risk vs low risk) according to follow-up time.
Figure 4.Subgroup analysis for adverse outcomes (high risk vs low risk) according to follow-up time.
Figure 5.Subgroup analysis for overall mortality (high risk vs low risk) in PE patients with cancer.
Prognostic Performance of Hestia Criteria for Predicting All-Course Mortality.
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| Zondag 2013 | 88.0(75.2-100) | 58.2(53.9-62.5) | 9.4(5.7-13.2) | 98.9(97.8-100) | 2.11(1.76-2.51) | 0.21(0.07-0.59) |
| Weeda 2016 | 100(87.0-100) | 29.6(25.8-33.7) | 8.0(5.6-11.1) | 100(97.1-100) | 1.41(1.33-1.48) | NA |
| Vanni 2018 | 88.6(79.2-98.0) | 44.3(39.9-48.6) | 12.2(8.6-15.8) | 97.8(95.9-99.7) | 1.59(1.39-1.81) | 0.25(0.11-0.58) |
| Quezada 2019 | 90.3(79.9-100) | 28.2(24.1-32.3) | 7.8(5.1-10.7) | 97.7(95.2-100) | 1.26(1.11-1.43) | 0.34(0.11-1.01) |
| Weeda 2019 | 88.0(75.3-100) | 20.2(12.3-28.1) | 21.8(13.7-29.8) | 86.9(73.2-100) | 1.10(0.92-1.31) | 0.59(0.19-1.84) |
| Hendriks 2020 | 87.5(71.3-100) | 46.9(41.9-51.9) | 6.3(3.1-9.6) | 98.9(97.4-100) | 1.64(1.33-2.02) | 0.26(0.07-0.98) |
| Li 2021 | 73.5(63.9-82.9) | 74.0(69.5-78.4) | 38.3(30.8-45.9) | 92.7(89.7-95.6) | 2.82(2.28-3.50) | 0.36(0.25-0.51) |
| Roy 2021 | 96.1(90.7-100) | 40.3(37.1-43.4) | 8.1(5.9-10.2) | 99.5(98.7-100) | 1.61(1.49-1.73) | 0.09(0.02-0.38) |
PPV, positive predictive value; NPV, negative predictive value; PLR, positive likelihood ratio; NLR, negative likelihood ratio; NA, not available.
Figure 6.Summary receiver operator characteristic curve (SROC) of the prognostic performance of Hestia criteria for overall mortality. Each circle indicates a study. The red diamond shows the summary operating points.
Figure 7.Funnel plots for publication bias: (a) for all-course mortality studies; (b) for adverse outcomes studies.