Remote history of VTE is associated with severe COVID-19 in middle and older age: UK Biobank cohort study

Inconsistency in UK Biobank Event Definitions From Different Data Sources and Its Impact on Bias and Generalizability: A Case Study of Venous Thromboembolism

The UK Biobank study contains several sources of diagnostic data, including hospital inpatient data and data on self-reported conditions for approximately 500,000 participants and primary-care data for approximately 177,000 participants (35%). Epidemiologic investigations require a primary disease definition, but whether to combine data sources to maximize statistical power or focus on only 1 source to ensure a consistent outcome is not clear. The consistency of disease definitions was investigated for venous thromboembolism (VTE) by evaluating overlap when defining cases from 3 sources: hospital inpatient data, primary-care reports, and self-reported questionnaires. VTE cases showed little overlap between data sources, with only 6% of reported events for persons with primary-care data being identified by all 3 sources (hospital, primary-care, and self-reports), while 71% appeared in only 1 source. Deep vein thrombosis-only events represented 68% of self-reported VTE cases and 36% of hospital-reported VTE cases, while pulmonary embolism-only events represented 20% of self-reported VTE cases and 50% of hospital-reported VTE cases. Additionally, different distributions of sociodemographic characteristics were observed; for example, patients in 46% of hospital-reported VTE cases were female, compared with 58% of self-reported VTE cases. These results illustrate how seemingly neutral decisions taken to improve data quality can affect the representativeness of a data set.

What We Know (and Do not Know) Regarding the Pathogenesis of Pulmonary Thrombosis in COVID-19

The clinical course of coronavirus disease 2019 (COVID-19) is often complicated by the onset of venous thrombosis and thromboembolism (VTE), encompassing also pulmonary thrombosis. Recent statistics attests that the cumulative frequency of VTE can be as high as 30% in COVID-19 hospitalized patients, increasing to nearly 40 to 70% (depending on systematic screening) in those with severe illness, mechanical ventilation, or intensive care unit admission. The risk of venous thrombosis seems mostly limited to the active phase of disease, and is directly associated with some genetic (i.e., inherited prothrombotic predisposition) and demographical factors (male sex, overweight/obesity), disease severity (risk increasing progressively from hospitalization to development of severe illness, being the highest in patients needing mechanical ventilation and/or intensive care), presence and extent of pulmonary disease, coexistence of multiple risk factors (immobilization, mechanical ventilation, co- or superinfections), along with increased values of inflammatory and thrombotic biomarkers. At least three different phenotypes of pulmonary thrombosis may develop in COVID-19 patients, one caused by typical embolization from peripheral venous thrombosis (e.g., deep vein thrombosis), a second type triggered by local inflammation of nearby pulmonary tissue, and a third one mostly attributable to the prothrombotic state consequent to the pronounced systemic inflammatory response (i.e., the so-called cytokine storm) that is frequently observed in COVID-19. Although the pathogenesis of these three conditions has different features, their discrimination is essential for diagnostic and therapeutic purposes. The prognosis of COVID-19 patients who develop pulmonary thrombosis is also considerably worse than those who do not, thus probably needing frequent monitoring and more aggressive therapeutic management.

3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19

Hypercoagulability is a recognized feature in SARS-CoV-2 infection. There exists a need for a dedicated risk assessment model (RAM) that can risk-stratify hospitalized COVID-19 patients for venous thromboembolism (VTE) and guide anticoagulation. We aimed to build a simple clinical model to predict VTE in COVID-19 patients. This large-cohort, retrospective study included adult patients admitted to four hospitals with PCR-confirmed SARS-CoV-2 infection. Model training was performed on 3531 patients hospitalized between March and December 2020 and validated on 2508 patients hospitalized between January and September 2021. Diagnosis of VTE was defined as acute deep vein thrombosis (DVT) or pulmonary embolism (PE). The novel RAM was based on commonly available parameters at hospital admission. LASSO regression and logistic regression were performed, risk scores were assigned to the significant variables, and cutoffs were derived. Seven variables with assigned scores were delineated as: DVT History = 2; High D-Dimer (>500−2000 ng/mL) = 2; Very High D-Dimer (>2000 ng/mL) = 5; PE History = 2; Low Albumin (<3.5 g/dL) = 1; Systolic Blood Pressure <120 mmHg = 1, Tachycardia (heart rate >100 bpm) = 1. The model had a sensitivity of 83% and specificity of 53%. This simple, robust clinical tool can help individualize thromboprophylaxis for COVID-19 patients based on their VTE risk category.

Cumulative Evidence for the Association of Thrombosis and the Prognosis of COVID-19: Systematic Review and Meta-Analysis

Background

Although thrombosis events have been reported in patients with coronavirus disease 2019 (COVID-19), the association between thrombosis and COVID-19-related critical status or risk of mortality in COVID-19 has been inconsistent.

Objective

We conducted a meta-analysis of reports assessing the association between thrombosis and the prognosis of COVID-19.

Methods

The EMBASE, Ovid-MEDLINE, and Web of Science databases were searched up to December 9, 2021, and additional studies were retrieved via manual searching. Studies were included if they reported the risk of COVID-19-related critical status or COVID-19-related mortality in relation to thrombosis. The related data were extracted by two authors independently, and a random effects model was conducted to pool the odds ratios (ORs). In addition, stratified analyses were conducted to evaluate the association.

Results

Among 6,686 initially identified studies, we included 25 studies published in 2020 and 2021, with a total of 332,915 patients according to predefined inclusion criteria. The associations between thrombosis and COVID-19-related mortality and COVID-19-related critical status were significant, with ORs of 2.61 (95% CI, 1.91–3.55, p < 0.05) and 2.9 (95% CI, 1.6–5.24, p < 0.05), respectively. The results were statistically significant and consistent in stratified analyses.

Conclusions

Thrombosis is associated with an increased risk of mortality and critical status induced by COVID-19. Further prospective studies with large sample sizes are required to establish whether these associations are causal by considering more confounders and to clarify their mechanisms.

Observational studies cannot prove causality. However, autopsy studies show thrombosis events preceding COVID-19-related deaths. The results of this meta-analysis reported that thrombosis was associated with a 161% increased risk of mortality from COVID-19 and a 190% increased risk of COVID-19-related critical status. The type of thrombosis included in the original studies also seemed to be related to the results.

Remote history of VTE is associated with severe COVID-19 in middle and older age: UK Biobank cohort study

BACKGROUND

Venous thromboembolism (VTE) is a common, life-threatening complication of COVID-19 infection. COVID-19 risk-prediction models include a history of VTE. However, it is unclear whether remote history (>9 years previously) of VTE also confers increased risk of COVID-19.

OBJECTIVES

To investigate possible association between VTE and COVID-19 severity, independent of other risk factors.

METHODS

Cohort study of UK Biobank participants recruited between 2006 and 2010. Baseline data, including history of VTE, were linked to COVID-19 test results, COVID-19-related hospital admissions, and COVID-19 deaths. The risk of COVID-19 hospitalization or death was compared for participants with a remote history VTE versus without. Poisson regression models were run univariately then adjusted stepwise for sociodemographic, lifestyle, and comorbid covariates.

RESULTS

After adjustment for sociodemographic and lifestyle confounders and comorbid conditions, remote history of VTE was associated with nonfatal community (RR 1.61, 95% CI 1.02-2.54, p = .039), nonfatal hospitalized (RR 1.52, 95% CI 1.06-2.17, p = .024) and severe (hospitalized or fatal) (RR 1.40, 95% CI 1.04-1.89, p = .025) COVID-19. Associations with remote history of VTE were stronger among men (severe COVID-19: RR 1.68, 95% CI 1.14-2.42, p = .009) than for women (severe COVID-19: RR 1.07, 95% CI 0.66-1.74, p = .786).

CONCLUSION

Our findings support inclusion of remote history of VTE in COVID-19 risk-prediction scores, and consideration of sex-specific risk scores.