Pulmonary immuno-thrombosis in COVID-19 ARDS pathogenesis

Severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) is responsible for coronavirus disease 2019 (COVID-19). Recent data highlight a pivotal role for pulmonary immuno-thrombosis in COVID-19 in the pathogenesis of severe COVID-19

Distribution of RRRs greater than 1+1SE and smaller than 1-1SE for different subgroups of population.

<p>(¹) Young age at onset is defined as younger than 50 years old for women and 55 for men.</p><p>(²) Low risk for arterial thrombosis is defined as a risk comparable with the general population. High risk for arterial thrombosis is given to populations affected by one or more diseases with a high impact on cardiovascular risk (such as atrial fibrillation, end stage renal disease, previous cardiovascular event).</p><p>Distribution of RRRs greater than 1+1SE and smaller than 1-1SE for different subgroups of population.</p

Prothrombotic risk factors and their effect on myocardial infarction and ischemic stroke.

<p>Each point depicts the log odds ratio as a measure of effect of a particular risk factor on the risk of myocardial infarction (x-axis) as well as the effect on the risk of ischaemic stroke (y-axis). The red dashed lines indicate the null effect for either myocardial infarction (vertical line) or ischaemic stroke (horizontal line). The blue diagonal line represents the theoretical line along which all points would cluster when the role of thrombotic factors is similar in the aetiology of myocardial infarction and ischaemic stroke. <i>As an explicative example red dots represent</i>: <i>#312</i>: <i>KAL-C1-INH (RR</i>_<i>IS</i><i>5</i>.<i>14 e RR</i>_<i>MI</i><i>2</i>.<i>12)</i>. <i>#281</i>: <i>FXIIIA SNP rs3024462 allele (RR</i>_<i>IS</i><i>1</i>.<i>82 e RR</i>_<i>MI</i><i>0</i>.<i>49)</i>.</p

Flow chart of the steps of data collection.

<p>The figure shows the three steps in the data collection: (1) identification of publications which report on the effect of measures of hypercoagulability and the risk of myocardial infarction (MI) or ischaemic stroke (IS) (2) identification of study populations (3) identification of publications with comparable data. Comparable data can be found in the same publication or in two different publications.</p

Factors that showed a predominant association with ischaemic stroke or myocardial infarction (RRR>1+SE and RRR<1-SE).

<p>(¹) Normalised ratios for LA-screen and LA-confirm coagulation times. The positivity for lupus anticoagulant was considered when the ratio was 1.15 or higher, on the basis of the 99th percentile of the value recorded for 40 healthy volunteers. More details can be found in the original publication.</p><p>(*) Prothrombotic factors with an RRR greater than 1+2SE. No prothrombotic factor had an RRR less than 1-2SE.</p><p>Factors that showed a predominant association with ischaemic stroke or myocardial infarction (RRR>1+SE and RRR<1-SE).</p

Prothrombotic risk factors with RRR either >1+SE and <1-SE (left) and either > 1+SE and <1-SE (right).

<p>Each point depicts the log odds ratio as a measure of effect of a particular risk factor on the risk of myocardial infarction (x-axis) as well as the effect on the risk of ischaemic stroke (y-axis). The red dashed lines indicate the null effect for either myocardial infarction (vertical line) or ischaemic stroke (horizontal line). The blue diagonal line represents the theoretical line along which all points would cluster when the role of thrombotic factors is similar in the aetiology of myocardial infarction and ischaemic stroke. On the left are depicted RRR>1+SE and RRR<1-SE. on the right RRR>1+2SE. No factors had RRR<1-2SE. Numbers represent the ID of the corresponding marker in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133523#pone.0133523.t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133523#pone.0133523.s005" target="_blank">S2</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133523#pone.0133523.s006" target="_blank">S3</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133523#pone.0133523.s007" target="_blank">S4</a> Tables.</p

Demographic, clinical and laboratory characteristics in 32 patients with primary secretion defects.

<p>a Number and percentage of patients showing reduced ATP secretion upon stimulation by the reported agonist at the reported concentration.</p><p>IQR, interquartile range; ADP, adenosine diphosphate; TRAP, thrombin receptor-activating peptide.</p

Diagnosis and bleeding severity score values in 207 patients.

<p>Patients with clinical bleeding or coagulation abnormalities and bleeding severity score of 4 or more are presented.</p>a<p>Including hemophilia A and B or rare bleeding disorders.</p>b<p>Includes δ-storage pool deficiency and Glanzmanńs thrombasthenia.</p>c<p>Secondary to drugs or to underlying medical conditions.</p>d<p>Individual values are reported.</p><p>BSS, bleeding severity score.</p

Relationships between measures of bleeding severity and pattern of platelet defect.

<p>The Figure shows the distribution of bleeding severity score (top), age-normalized bleeding severity score (middle) and age of first bleeding requiring medical attention (bottom) in patients with different patterns of platelet defect. The asterisk (*) indicates a patient with age-normalized bleeding severity score of 1.89. P-values were calculated by Kruskal-Wallis test.</p

Association between bleeding severity score and platelet secretion testing results in 32 patients with primary secretion defects.

a<p>Adjusted for age at referral, sex, clinic of referral, region of residence.</p>b<p>Adjusted for sex, clinic of referral, region of residence.</p><p>CI, confidence intervals.</p