| Literature DB >> 34242477 |
Jana J Anderson1, Frederick K Ho1, Claire L Niedzwiedz1, Srinivasa Vittal Katikireddi2, Carlos Celis-Morales3, Stamatina Iliodromiti4, Paul Welsh3, Pierpaolo Pellicori5, Evangelia Demou2, Claire E Hastie1, Donald M Lyall1, Stuart R Gray3, John F Forbes6, Jason M R Gill3, Daniel F Mackay1, Colin Berry3, John G F Cleland5, Naveed Sattar3, Jill P Pell1.
Abstract
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.Entities:
Keywords: COVID-19 severity; DVT; PE; SARS-CoV2 infection; venous thromboembolism
Mesh:
Year: 2021 PMID: 34242477 PMCID: PMC8420476 DOI: 10.1111/jth.15452
Source DB: PubMed Journal: J Thromb Haemost ISSN: 1538-7836 Impact factor: 16.036
Characteristics of study participants by history of venous thromboembolism
| History of VTE |
| ||
|---|---|---|---|
|
No
|
Yes
| ||
| Median (IQR) | Median (IQR) | ||
| Age (years) | 59 (51, 64) | 61 (54, 65) | <.001 |
| Deprivation index | −2.1 (−3.6, 0.6) | −1.9 (−3.5, 1.0) | <.001 |
|
|
| ||
| Sex | |||
| Male | 135 520 (44.8) | 3899 (38.9) | <.001 |
| Female | 166 824 (55.2) | 6135 (61.1) | |
| Ethnic group | |||
| White | 283 180 (94.1) | 9570 (95.4) | <.001 |
| South Asian | 6644 (2.2) | 128 (1.3) | |
| Black | 5427 (1.8) | 171 (1.7) | |
| Chinese | 858 (0.29) | 5 (0.1) | |
| Mixed | 1844 (0.6) | 59 (0.6) | |
| Any other | 2900 (0.96) | 70 (0.7) | |
| Smoking status | |||
| Current | 29 070 (9.7) | 1089 (10.9) | <.001 |
| Past | 108 441 (36.1) | 3717 (37.2) | |
| Never | 163 213 (54.3) | 5175 (51.8) | |
| Body mass index | |||
| Underweight | 1260 (0.4) | 22 (0.2) | <.001 |
| Normal weight | 88 037 (29.7) | 2113 (21.9) | |
| Overweight | 127 918 (43.1) | 3900 (40.4) | |
| Obese | 79 518 (26.8) | 3615 (37.5) | |
| Alcohol frequency | |||
| Never | 25 601 (8.5) | 1171 (11.7) | <.001 |
| Special occasions only | 36 556 (12.1) | 1508 (15.1) | |
| 1–3 times/month | 34 119 (11.3) | 1182 (11.8) | |
| 1–2 times/week | 75 930 (25.2) | 2377 (23.7) | |
| 3–4 times/week | 67 961 (22.5) | 1968 (19.6) | |
| Daily or almost daily | 61 465 (20.4) | 1811 (18.1) | |
| Physically active | 159 794 (52.9) | 5066 (50.5) | <.001 |
| Cardiovascular disease | 20 897 (6.9) | 1236 (12.3) | <.001 |
| Diabetes | 19 228 (6.4) | 789 (7.9) | <.001 |
| Anticoagulants | |||
| Yes | 2341 (0.9) | 1162 (13.7) | <.001 |
| No | 247 015 (99.1) | 7313 (86.3) | |
| Antiplatelets | |||
| Yes | 48 919 (19.6) | 2261 (26.7) | <.001 |
| No | 200 437 (80.4) | 6214 (73.3) | |
| COCP/HRT | |||
| Yes | 16 950 (10.2) | 414 (6.8) | <.001 |
| No | 148 848 (89.8) | 5668 (93.2) | |
Categorical variables compared by χ2 test; continuous variables compared by Mann‐Whitney U test.
Abbreviations: COCP, combined oral contraceptive pill; HRT, hormone replacement therapy; IQR, interquartile range; VTE, venous thromboembolism.
Associations between remote history of venous thromboembolism and COVID‐19 infection outcomes (N = 312 378)
| COVID‐19 Severity |
Model 1 RR (95% CI) |
|
Model 2 RR (95% CI) |
|
Model 3 RR (95% CI) |
|
Model 3 Men only RR (95% CI) |
|
Model 3 Women Only RR (95% CI) |
|
|---|---|---|---|---|---|---|---|---|---|---|
| Nonfatal community | 1.74 (1.12–2.69) | .014 | 1.63 (1.04–2.57) | .034 | 1.61 (1.02–2.54) | .039 | 2.23 (1.18–4.23) | .014 | 1.28 (0.67–2.44) | .456 |
| Hospitalized nonfatal | 1.91 (1.37–2.64) | <.001 | 1.55 (1.08–2.22) | .018 | 1.52 (1.06–2.17) | .024 | 1.88 (1.18–2.98) | .007 | 1.07 (0.59–1.96) | .827 |
| Died from COVID‐19 | 1.24 (0.74–2.08) | .415 | 1.22 (0.73–2.04) | .456 | 1.21 (0.72–2.03) | .467 | 1.32 (0.68–2.57) | .405 | 1.06 (0.46–2.41) | .893 |
| Severe (hospitalized/died from COVID‐19) | 1.66 (1.26–2.18) | <.001 | 1.42 (1.06–1.91) | .019 | 1.40 (1.04–1.89) | .025 | 1.68 (1.14–2.42) | .009 | 1.07 (0.66–1.74) | .786 |
Model 1: Adjusted for sociodemographic factors at baseline (sex, age, deprivation, ethnicity).
Model 2: Also adjusted for lifestyle factors at baseline (body mass index, smoking, physical activity, alcohol consumption).
Model 3: Also adjusted for comorbid cardiovascular disease (myocardial infarction, heart failure, angina, stroke, transient ischemic attack, atrial fibrillation/flutter, valve disease) and prevalent diabetes mellitus; also adjusted for use of exogenous oestrogens in women only.