Prevalence, risk, and outcome of deep vein thrombosis in acute respiratory distress syndrome

Development of a Risk Assessment Tool for Venous Thromboembolism among Hospitalized Patients in the ICU

BACKGROUND

ICU patients have a high incidence of VTE. The American College of Chest Physicians antithrombotic practice guidelines recommend assessing the risk of VTE in all ICU patients. Although several VTE risk assessment tools exist to evaluate the risk factors among hospitalized patients, there is no validated tool specifically for assessing the risk of VTE in ICU patients.

METHODS

A retrospective corhort study was conducted between June 2018 and October 2022. We obtained data from the electronic medical records of patients with a variety of diagnoses admitted to a mixed ICU. Multivariable logistic regression analysis was used to evaluate the independent risk factors of VTE. Receiver operating characteristic (ROC) curves were used to analyse the predictive accuracy of different tools.

RESULTS

A total of 566 patients were included, and VTE occurred in 89 patients (15.7%), 62.9% was asymptomatic VTE. A prediction model (the ICU-VTE prediction model) was derived from the independent risk factors identified using multivariate analysis. The ICU-VTE prediction model included eight independent risk factors: history of VTE (3 points), immobilization ≥4 days (3 points), multiple trauma (3 points), age ≥70 years (2 points), platelet count >250 × 103/μL (2 points), central venous catheterization (1 point), invasive mechanical ventilation (1 point), and respiratory failure or heart failure (1 point). Patients with a score of 0-4 points had a low (1.81%) risk of VTE. Patients were at intermediate risk, scoring 5-6 points, and the overall incidence of VTE in the intermediate-risk category was 17.1% (odds ratio [OR], 11.1; 95% confidence interval [CI], 4.2-29.4). Those with a score ≥7 points had a high (44.1%) risk of VTE (OR, 42.6; 95% CI, 16.4-110.3). The area under the curve (AUC) of the ICU-VTE prediction model was 0.838, and the differences in the AUCs were statistically significant between the ICU-VTE prediction model and the other three tools (ICU-VTE score, Z = 3.723, P < 0.001; Caprini risk assessment model, Z = 6.212, P < 0.001; Padua prediction score, Z = 7.120, P < 0.001).

CONCLUSIONS

We identified eight independent risk factors for acquired VTE among hospitalized patients in the ICU, deriving a new ICU-VTE risk assessment model. The model aims to predict asymptomatic VTE in ICU patients. The new model has higher predictive accuracy than the current tools. A prospective study is required for external validation of the tool and risk stratification in ICU patients.

CT Approach to Lung Injury

Diffuse alveolar damage (DAD), which represents the pathologic changes seen after acute lung injury, is caused by damage to all three layers of the alveolar wall and can ultimately result in alveolar collapse with loss of the normal pulmonary architecture. DAD has an acute phase that predominantly manifests as airspace disease at CT owing to filling of the alveoli with cells, plasma fluids, and hyaline membranes. DAD then evolves into a heterogeneous organizing phase, with mixed airspace and interstitial disease characterized by volume loss, architectural distortion, fibrosis, and parenchymal loss. Patients with DAD have a severe clinical course and typically require prolonged mechanical ventilation, which may result in ventilator-induced lung injury. In those patients who survive DAD, the lungs will remodel over time, but most will have residual findings at chest CT. Organizing pneumonia (OP) is a descriptive term for a histologic pattern characterized by intra-alveolar fibroblast plugs. The significance and pathogenesis of OP are controversial. Some authors regard it as part of a spectrum of acute lung injury, while others consider it a marker of acute or subacute lung injury. At CT, OP manifests with various forms of airspace disease that are most commonly bilateral and relatively homogeneous in appearance at individual time points. Patients with OP most often have a mild clinical course, although some may have residual findings at CT. In patients with DAD and OP, imaging findings can be combined with clinical information to suggest the diagnosis in many cases, with biopsy reserved for difficult cases with atypical findings or clinical manifestations. To best participate in the multidisciplinary approach to patients with lung injury, radiologists must not only recognize these entities but also describe them with consistent and meaningful terminology, examples of which are emphasized in the article. © RSNA, 2023 See the invited commentary by Kligerman et al in this issue. Quiz questions for this article are available in the supplemental material.

Comparison of deep vein thrombosis risks in acute respiratory distress syndrome caused by COVID-19 and bacterial pneumonia: a retrospective cohort study

BACKGROUND

High incidence of deep vein thrombosis (DVT) has been observed in patients with acute respiratory distress syndrome (ARDS) caused by COVID-19 and those by bacterial pneumonia. However, the differences of incidence and risk factors of DVT in these two groups of ARDS had not been reported before.

STUDY DESIGN AND METHODS

We performed a retrospective cohort study to investigate the difference of DVT in incidence and risk factors between the two independent cohorts of ARDS and eventually enrolled 240 patients, 105 of whom with ARDS caused by COVID-19 and 135 caused by bacterial pneumonia. Lower extremity venous compression ultrasound scanning was performed whenever possible regardless of clinical symptoms in the lower limbs. Clinical characteristics, including demographic information, clinical history, vital signs, laboratory findings, treatments, complications, and outcomes, were analyzed for patients with and without DVT in these two cohorts.

RESULTS

The 28-days incidence of DVT was higher in patients with COVID-19 than in those with bacterial pneumonia (57.1% vs 41.5%, P = 0.016). Taking death as a competitive risk, the Fine-Gray test showed no significant difference in the 28-day cumulative incidence of DVT between these two groups (P = 0.220). Fine-Gray competing risk analysis also showed an association between increased CK (creatine kinase isoenzyme)-MB levels (P = 0.003), decreased PaO2 (partial pressure of arterial oxygen)/FiO2 (fraction of inspired oxygen) ratios (P = 0.081), increased D-dimer levels (P = 0.064) and increased incidence of DVT in COVID-19 cohort, and an association between invasive mechanical ventilation (IMV; P = 0.001) and higher incidence of DVT and an association between VTE prophylaxis (P = 0.007) and lower incidence of DVT in bacterial pneumonia cohort. The sensitivity and specificity of the corresponding receiver operating characteristic curve originating from the combination of CK-MB levels, PaO2/FiO2 ratios, and D-dimer levels ≥0.5 μg/mL were higher than that of the DVT Wells score (P = 0.020) and were not inferior to that of the Padua prediction score (P = 0.363) for assessing the risk of DVT in COVID-19 cohort.

CONCLUSIONS

The incidence of DVT in patients with ARDS caused by COVID-19 is higher than those caused by bacterial pneumonia. Furthermore, the risk factors for DVT are completely different between these two ARDS cohorts. It is suggested that COVID-19 is probably an additional risk factor for DVT in ARDS patients.