2021
DOI: 10.1016/j.carrev.2020.11.024
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Does Pulmonary Embolism in Critically Ill COVID-19 Patients Worsen the In-Hospital Mortality: A Meta-Analysis

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Cited by 9 publications
(9 citation statements)
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“…In our cohort, PE was more frequent in severe/critical and deceased patients, but PE diagnosis did not predict mortality in both Cox classical survival and multi-state models. Other observational studies in severe and critical patients reported similar results [ 13 , 30 ]. This can be reasonable if we consider most of PE in COVID-19 patients without overt DVT as a marker of disease severity rather than a severe VTE complication [ 31 ].…”
Section: Discussionsupporting
confidence: 72%
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“…In our cohort, PE was more frequent in severe/critical and deceased patients, but PE diagnosis did not predict mortality in both Cox classical survival and multi-state models. Other observational studies in severe and critical patients reported similar results [ 13 , 30 ]. This can be reasonable if we consider most of PE in COVID-19 patients without overt DVT as a marker of disease severity rather than a severe VTE complication [ 31 ].…”
Section: Discussionsupporting
confidence: 72%
“…Therefore, despite the improvement in our knowledge about the antithrombotic strategy for preventing VTE and mortality in COVID-19 patients, some questions remain unanswered. For example, it is uncertain the effective preventive dose of heparin for hospitalized patients according to disease severity [ 10 ], the role of a PE diagnosis on mortality [ 11 13 ], or the usefulness of d-dimer levels to guide timing and dosing of heparin treatment [ 14 ].…”
Section: Introductionmentioning
confidence: 99%
“…The publication bias was illustrated graphically with Harbord’s weighted linear regression [ 18 ]. "The vertical axis of the plot used standard error to estimate the sample size of the study, plotting large population studies on top and smaller at the bottom" [ 5 ]. "The horizontal spread reflected the power and effect size of the included studies" [ 5 ].…”
Section: Resultsmentioning
confidence: 99%
“…"The vertical axis of the plot used standard error to estimate the sample size of the study, plotting large population studies on top and smaller at the bottom" [ 5 ]. "The horizontal spread reflected the power and effect size of the included studies" [ 5 ]. Harbord’s weighted linear regression indicated the absence of publication bias among the 10 studies [t=-0.08, p=0.48 (95% CI: -0.80-0.41)] (Figure 6 ).…”
Section: Resultsmentioning
confidence: 99%
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