Estimation of right ventricular dysfunction by computed tomography pulmonary angiography: a valuable adjunct for evaluating the severity of acute pulmonary embolism

The Role of the Pulmonary Artery Obstruction Index Ratio in Predicting the Clinical Course of Pulmonary Embolism

Background/Objective: This study aimed to investigate the relationship between the pulmonary arterial computed tomography obstruction index ratio (CTOI) and the simplified pulmonary embolism severity index (sPESI), one of the clinical probability scoring modalities, in determining the severity of PE and to determine whether CTOI is a mortality marker. Methods: The study included 117 patients diagnosed with PE via computed tomography pulmonary angiography (CTPA). The CTOI was determined according to the localization of the embolus and the obstruction caused by the embolus in the vessel. Patients were divided into two groups, namely low-risk and high-risk groups, according to their sPESI values. Patient deaths up to six months after PE diagnosis were recorded. Results: According to the sPESI classification, although the CTOI was higher in the high-risk group compared to the low-risk group, no significant difference was found between the groups. The mortality rate was significantly higher in the high-risk group. After six months of follow-up, there was no difference in the CTOI rate between the patients who died and those who survived. Conclusions: Although CTPA is the gold standard for diagnosing PE, it would be more appropriate to use it together with clinical findings to determine the severity of the disease. Further evaluation is needed to investigate the usefulness of the obstruction index and CT findings of right ventricular dysfunction for classifying patient risk and determining therapeutic options.

Alterations and Significance of Computed Tomography Pulmonary Angiography-Derived Parameters in Older Patients With Acute Pulmonary Embolism

OBJECTIVE

This study aimed to investigate changes of computed tomography pulmonary angiography (CTPA)-derived parameters in older adults with acute pulmonary embolism (APE).

METHODS

According to the pulmonary artery obstruction index (PAOI), patients with APE were divided into the A1 (PAOI ≥30%, n = 57) and A2 (PAOI <30%, n = 40) groups. Participants without APE were placed in group B (n = 170). The left atrial (LA) and left ventricular (LV) parameters among the three groups were compared, and the parameter changes in the 44 patients with APE were analyzed before and after treatment. The correlation between APE severity and the parameters was analyzed using correlation analysis.

RESULTS

The left-to-right diameters (LR) of LA, and LR × anteroposterior diameters (AP) of LA and LV: A1 < A2 < B; LR of LV: A1 < A2, B; AP of LA and LV: A1, A2 < B. After treatment, LR and LR × AP of the LA and LV were significantly increased in the group A1 and LR of the LV and LR × AP of the LA and LV were elevated in the group A2. Acute pulmonary embolism severity was closely associated with LR × AP ( r = -0.557) and LR ( r = -0.477) of LA.

CONCLUSIONS

With an increase in the degree of obstruction, older adults had a smaller LA and LV. Furthermore, the LR and LR × AP values of the LA were significantly decreased. These results contribute to in-time risk stratification.

Pulmonary artery diameter correlates with echocardiographic parameters of right ventricular dysfunction in patients with acute pulmonary embolism

Introduction

Right ventricular dysfunction (RVD) is a key component in the process of risk stratification in patients with acute pulmonary embolism (PE). Echocardiography remains the gold standard for RVD assessment, however, measures of RVD may be seen on CTPA imaging, including increased pulmonary artery diameter (PAD). The aim of our study was to evaluate the association between PAD and echocardiographic parameters of RVD in patients with acute PE.

Methods

Retrospective analysis of patients diagnosed with acute PE was conducted at large academic center with an established pulmonary embolism response team (PERT). Patients with available clinical, imaging, and echocardiographic data were included. PAD was compared to echocardiographic markers of RVD. Statistical analysis was performed using the Student's t test, Chi-square test, or one-way analysis of variance (ANOVA); P < 0.05 was considered statistically significant.

Results

270 patients with acute PE were identified. Patients with a PAD >30 mm measured on CTPA had higher rates of RV dilation (73.1% vs 48.7%, P < 0.005), RV systolic dysfunction (65.4% vs 43.7%, P < 0.005), and RVSP >30 mmHg (90.2% vs 68%, P = 0.004), but not TAPSE ≤1.6 cm (39.1% vs 26.1%, P = 0.086). A weak increasing linear relationship between PAD and RVSP was noted (r = 0.379, P = 0.001).

Conclusions

Increased PAD in patients with acute PE was significantly associated with echocardiographic markers of RVD. Increased PAD on CTPA in acute PE can serve as a rapid prognostic tool and assist with PE risk stratification at the time of diagnosis, allowing rapid mobilization of a PERT team and appropriate resource utilization.

Right ventricular area predicts short-term mortality in acute pulmonary embolism based on CT pulmonary angiography: A retrospective study

We performed this cohort study to assess the prognostic value of right ventricular size, including diameter, area, and volume, in short-term mortality of acute pulmonary embolism (APE) based on 256-slice computed tomography compared with D-dimer, creatine kinase muscle and brain isoenzyme, and Wells scores. A total of 225 patients with APE, who were followed up for 30 days were enrolled in this cohort study. Clinical data, laboratory indices (creatine kinase, creatine kinase muscle and brain isoenzyme, and D-dimer), and Wells scores were collected. The 256-slice computed tomography was used to quantify cardiac parameters (RVV/LVV, RVD/LVD-ax, RVA/LVA-ax, RVD/LVD-4ch, RVA/LVA-4ch) and the diameter of the coronary sinus. Participants were divided into non-death and death groups. The values mentioned above were compared between the 2 groups. The RVD/LVD-ax, RVA/LVA-ax, RVA/LVA-4ch, RVV/LVV, D-dimer, and creatine kinase levels were significantly higher in the death group than in the non-death group (P < .05). The active period of the malignant tumor, heart rate ≥ 100 beats/minutes, and RVA/LVA-ax were positively correlated with early death from APE (P < .05). Active stage of malignant tumor (OR:9.247, 95%CI:2.682-31.888, P < .001) and RVA/LVA-ax (OR:3.073, 95%CI:1.447-6.528, P = .003) were independent predictors of early death due to APE. According to the receiver operating characteristic curve, the cutoff point of RVA/LVA-ax was 1.68 with a sensitivity of 46.7% and specificity of 84.8%. The measurement of ventricular size in the short-axis plane is more convenient and reliable than that in the 4-chamber cardiac plane. RVA/LVA-ax is an independent predictor of early death from APE, and when RVA/LVA-ax > 1.68, the risk of early death from APE increases.

Machine Learning Based on Computed Tomography Pulmonary Angiography in Evaluating Pulmonary Artery Pressure in Patients with Pulmonary Hypertension

BACKGROUND

Right heart catheterization is the gold standard for evaluating hemodynamic parameters of pulmonary circulation, especially pulmonary artery pressure (PAP) for diagnosis of pulmonary hypertension (PH). However, the invasive and costly nature of RHC limits its widespread application in daily practice.

PURPOSE

To develop a fully automatic framework for PAP assessment via machine learning based on computed tomography pulmonary angiography (CTPA).

MATERIALS AND METHODS

A machine learning model was developed to automatically extract morphological features of pulmonary artery and the heart on CTPA cases collected between June 2017 and July 2021 based on a single center experience. Patients with PH received CTPA and RHC examinations within 1 week. The eight substructures of pulmonary artery and heart were automatically segmented through our proposed segmentation framework. Eighty percent of patients were used for the training data set and twenty percent for the independent testing data set. PAP parameters, including mPAP, sPAP, dPAP, and TPR, were defined as ground-truth. A regression model was built to predict PAP parameters and a classification model to separate patients through mPAP and sPAP with cut-off values of 40 mm Hg and 55 mm Hg in PH patients, respectively. The performances of the regression model and the classification model were evaluated by analyzing the intraclass correlation coefficient (ICC) and the area under the receiver operating characteristic curve (AUC).

RESULTS

Study participants included 55 patients with PH (men 13; age 47.75 ± 14.87 years). The average dice score for segmentation increased from 87.3% ± 2.9 to 88.2% ± 2.9 through proposed segmentation framework. After features extraction, some of the AI automatic extractions (AAd, RVd, LAd, and RPAd) achieved good consistency with the manual measurements. The differences between them were not statistically significant (t = 1.222, p = 0.227; t = -0.347, p = 0.730; t = 0.484, p = 0.630; t = -0.320, p = 0.750, respectively). The Spearman test was used to find key features which are highly correlated with PAP parameters. Correlations between pulmonary artery pressure and CTPA features show a high correlation between mPAP and LAd, LVd, LAa (r = 0.333, p = 0.012; r = -0.400, p = 0.002; r = -0.208, p = 0.123; r = -0.470, p = 0.000; respectively). The ICC between the output of the regression model and the ground-truth from RHC of mPAP, sPAP, and dPAP were 0.934, 0.903, and 0.981, respectively. The AUC of the receiver operating characteristic curve of the classification model of mPAP and sPAP were 0.911 and 0.833.

CONCLUSIONS

The proposed machine learning framework on CTPA enables accurate segmentation of pulmonary artery and heart and automatic assessment of the PAP parameters and has the ability to accurately distinguish different PH patients with mPAP and sPAP. Results of this study may provide additional risk stratification indicators in the future with non-invasive CTPA data.

Right-to-left ventricle ratio determined by machine learning algorithms on CT pulmonary angiography images predicts prolonged ICU length of stay in operated chronic thromboembolic pulmonary hypertension

OBJECTIVE

Right-to-left ventricle diameter ratio (dRV/dLV) on CT pulmonary angiography (CTPA) is a predictor of outcomes in non-operated chronic thromboembolic pulmonary hypertension (CTEPH) patients. The purpose of this study is to evaluate the performance of a novel machine learning (ML) algorithm for dRV/dLV measurement in operated CTEPH patients and its association with post-operative outcomes.

METHODS

This retrospective study reviewed consecutive CTEPH patients who underwent pulmonary endarterectomy between 2013 and 2017. ML calculated dRV/dLV on pre-operative CTPA and compared with manual measures. Associations of dRV/dLV with patient characteristics and post-operative outcomes were evaluated including intensive care (ICU) and hospital length of stay (LOS) using multivariable linear regression analysis. Prolonged LOS was defined as greater than median.

RESULTS

ML segmented the ventricles in 99/125 (79%) patients. The most common cause of failure was misidentification of the moderator band as the interventricular septum (7.9%). Mean dRV/dLV by ML was 1.4 ± 0.4 and strongly correlated with manual measures (r = 0.9-0.96 p < 0.0001). dRV/dLV was moderately correlated with measures of pulmonary hypertension on right heart catheterization and RV dilatation on echocardiogram (r = 0.5-0.6, p < 0.0001). dRV/dLV ≥ 1.2 was associated with proximal Jamieson type disease (p = 0.032), longer cardiopulmonary bypass (p = 0.037), aortic cross-clamp (p = 0.022) and circulatory arrest (p < 0.001) at surgery and dRV/dLV ≥ 1.6 with post-operative ECMO (p = 0.006). dRV/dLV was independently associated with prolonged ICU LOS (OR = 3.79, 95% CI 1.1-13.06, p = 0.035).

CONCLUSION

dRV/dLV was associated with CTEPH severity and independently associated with prolonged ICU LOS. This CT parameter may therefore assist in perioperative planning. Further refinement of the ML algorithm or CTPA technique is required to avoid errors in ventricular segmentation.

ADVANCES IN KNOWLEDGE

Automated right-to-left ventricle ratio measurement by machine learning is feasible and is independently associated with outcome after pulmonary endarterectomy.

Clot burden of acute pulmonary thromboembolism: comparison of two deep learning algorithms, Qanadli score, and Mastora score

BACKGROUND

The deep learning convolution neural network (DL-CNN) benefits evaluating clot burden of acute pulmonary thromboembolism (APE). Our objective was to compare the performance of the deep learning convolution neural network trained by the fine-tuning [DL-CNN (ft)] and the deep learning convolution neural network trained from the scratch [DL-CNN (fs)] in the quantitative assessment of APE.

METHODS

We included the data of 680 cases for training DL-CNN by DL-CNN (ft) and DL-CNN (fs), then retrospectively included 410 patients (137 patients with APE, 203 males, mean age 60.3±11.4 years) for testing the models. The distribution and volume of clots were respectively assessed by DL-CNN(ft) and DL-CNN(fs), and sensitivity, specificity, and area under the curve (AUC) were used to evaluate their performances in detecting clots on a per-patient and clot level. Radiologists evaluated the distribution of clots, Qanadli score, and Mastora score and right ventricular metrics, and the correlation of clot volumes with right ventricular metrics were analyzed with Spearman correlation analysis.

RESULTS

On a per-patient level, the two DL-CNN models had high sensitivities and moderate specificities [DL-CNN (ft): 100% and 77.29%; DL-CNN (fs): 100% and 75.82%], and their AUCs were comparable (Z=0.30, P=0.38). On a clot level, DL-CNN (ft) and DL-CNN (fs) sensitivities and specificities in detecting central clots were 99.06% and 72.61%, and 100% and 70.63%, respectively. DL-CNN (ft) sensitivities and specificities in detecting peripheral clots were mostly higher than those of DL-CNN (fs), and their AUCs were comparable. Clot volumes measured with the two models were similar (U=85094.500, P=0.741), and significantly correlated with Qanadli scores [DL-CNN(ft) r=0.825, P<0.001, DL-CNN(fs) r=0.827, P<0.001] and Mastora scores [DL-CNN(ft) r=0.859, P<0.001, DL-CNN(fs) r=0.864, P<0.001]. Clot volumes were also correlated with right ventricular metrics. Clot burdens were increased in the low-risk, moderate-risk, and high-risk patients. Binary logistic regression revealed that only the ratio of right ventricular area/left ventricular area (RVa/LVa) was an independent predictor of in-hospital death (odds ratio 6.73; 95% CI, 2.7-18.12, P<0.001).

CONCLUSIONS

Both DL-CNN (ft) and DL-CNN (fs) have high sensitivities and moderate specificities in detecting clots associated with APE, and their performances are comparable. While clot burdens quantitatively calculated by the two DL-CNN models are correlated with right ventricular function and risk stratification, RVa/LVa is an independent prognostic factor of in-hospital death in patients with APE.

Detection of right ventricular dysfunction in acute pulmonary embolism by computed tomography or echocardiography: A systematic review and meta-analysis

BACKGROUND

Right ventricular (RV) dysfunction predicts worse outcomes in acute pulmonary embolism (PE). Because computed tomography (CT) pulmonary angiography visualizes cardiac structures, it is a potential method for assessing RV function without the delays associated with inpatient echocardiography.

OBJECTIVES

We conducted a systematic review and meta-analysis to assess the diagnostic accuracy of CT scan findings for detecting RV dysfunction compared with echocardiography.

METHODS

We searched MEDLINE and EMBASE from inception to April 2020 for studies comparing RV dysfunction on CT scan with echocardiography standard. Study quality was assessed with the QUADAS-2 risk of bias tool. Meta-analysis was performed using a bivariate mixed effects regression framework.

RESULTS

After screening, 26 studies (3508 patients) were included. In a pooled analysis, septal deviation (5 studies; 459 patients) had a sensitivity of 0.31 (95% CI 0.25-0.38; I2  = 0%), specificity of 0.98 (95% CI 0.90-1.00; I2  = 59.4%), and positive likelihood ratio of 13.6 (95% CI 3.1-60.4) for RV dysfunction compared with echocardiography. The pooled sensitivity of increased RV/left ventricular ratio (21 studies; 3111 patients) was 0.83 (95% CI 0.78-0.87; I2  = 81.8%), whereas the pooled specificity was 0.75 (95% CI 0.66-0.82; I2  = 94.2%) and negative likelihood ratio was 0.23 (0.18-0.29).

CONCLUSIONS

Overall, RV dysfunction can be detected by CT imaging but the diagnostic accuracy when compared with echocardiography varies depending on specific findings. The presence of septal bowing appears to be highly specific for RV dysfunction. Our findings suggest that multiple CT findings of RV dysfunction may improve diagnostic accuracy and further studies are warranted.

Risk Stratification in Acute Pulmonary Embolism: The Latest Algorithms

Pulmonary embolism (PE) is a common clinical entity, which most clinicians will encounter. Appropriate risk stratification of patients is key to identify those who may benefit from reperfusion therapy. The first step in risk assessment should be the identification of hemodynamic instability and, if present, urgent patient consideration for systemic thrombolytics. In the absence of shock, there is a plethora of imaging studies, biochemical markers, and clinical scores that can be used to further assess the patients' short-term mortality risk. Integrated prediction models incorporate more information toward an individualized and precise mortality prediction. Additionally, bleeding risk scores should be utilized prior to initiation of anticoagulation and/or reperfusion therapy administration. Here, we review the latest algorithms for a comprehensive risk stratification of the patient with acute PE.

Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning

OBJECTIVES

To take advantage of the deep learning algorithms to detect and calculate clot burden of acute pulmonary embolism (APE) on computed tomographic pulmonary angiography (CTPA).

MATERIALS AND METHODS

The training set in this retrospective study consisted of 590 patients (460 with APE and 130 without APE) who underwent CTPA. A fully deep learning convolutional neural network (DL-CNN), called U-Net, was trained for the segmentation of clot. Additionally, an in-house validation set consisted of 288 patients (186 with APE and 102 without APE). In this study, we set different probability thresholds to test the performance of U-Net for the clot detection and selected sensitivity, specificity, and area under the curve (AUC) as the metrics of performance evaluation. Furthermore, we investigated the relationship between the clot burden assessed by the Qanadli score, Mastora score, and other imaging parameters on CTPA and the clot burden calculated by the DL-CNN model.

RESULTS

There was no statistically significant difference in AUCs with the different probability thresholds. When the probability threshold for segmentation was 0.1, the sensitivity and specificity of U-Net in detecting clot respectively were 94.6% and 76.5% while the AUC was 0.926 (95% CI 0.884-0.968). Moreover, this study displayed that the clot burden measured with U-Net was significantly correlated with the Qanadli score (r = 0.819, p < 0.001), Mastora score (r = 0.874, p < 0.001), and right ventricular functional parameters on CTPA.

CONCLUSIONS

DL-CNN achieved a high AUC for the detection of pulmonary emboli and can be applied to quantitatively calculate the clot burden of APE patients, which may contribute to reducing the workloads of clinicians.

KEY POINTS

• Deep learning can detect APE with a good performance and efficiently calculate the clot burden to reduce the physicians' workload. • Clot burden measured with deep learning highly correlates with Qanadli and Mastora scores of CTPA. • Clot burden measured with deep learning correlates with parameters of right ventricular function on CTPA.

Diagnosis of Deep Venous Thrombosis and Pulmonary Embolism: New Imaging Tools and Modalities

Imaging continues to be the modality of choice for the diagnosis of venous thromboembolic disease, particularly when incorporated into diagnostic algorithms. Improvement in imaging techniques as well as new imaging modalities and processing methods have improved diagnostic accuracy and additionally are being leveraged in prognostication and decision making for choice of intervention. In this article, we review the role of imaging in diagnosis and prognostication of venous thromboembolism. We also discuss emerging imaging approaches that may in the near future find clinical usefulness in improving diagnosis and prognostication as well as differentiating disease phenotypes.

The use of echocardiographic indices in defining and assessing right ventricular systolic function in critical care research

PURPOSE

Many echocardiographic indices (or methods) for assessing right ventricular (RV) function are available, but each has its strengths and limitations. In some cases, there might be discordance between the indices. We conducted a systematic review to audit the echocardiographic RV assessments in critical care research to see if a consistent pattern existed. We specifically looked into the kind and number of RV indices used, and how RV dysfunction was defined in each study.

METHODS

Studies conducted in critical care settings and reported echocardiographic RV function indices from 1997 to 2017 were searched systematically from three databases. Non-adult studies, case reports, reviews and secondary studies were excluded. These studies' characteristics and RV indices reported were summarized.

RESULTS

Out of 495 non-duplicated publications found, 81 studies were included in our systematic review. There has been an increasing trend of studying RV function by echocardiography since 2001, and most were conducted in ICU. Thirty-one studies use a single index, mostly TAPSE, to define RV dysfunction; 33 used composite indices and the combinations varied between studies. Seventeen studies did not define RV dysfunction. For those using composite indices, many did not explain their choices.

CONCLUSIONS

TAPSE seemed to be the most popular index in the last 2-3 years. Many studies used combinations of indices but, apart from cor pulmonale, we could not find a consistent pattern of RV assessment and definition of RV dysfunction amongst these studies.

Prognostic value of cardiovascular parameters in computed tomography pulmonary angiography in patients with acute pulmonary embolism

The value of various computed tomography parameters for prognosis and risk stratification in acute pulmonary embolism is controversial. Our objective was to evaluate the impact of specific cardiovascular computed tomography pulmonary angiography parameters on short- and long-term clinical outcomes.

We analysed radiological and clinical data of 1950 patients with acute pulmonary embolism who participated in an international randomised clinical trial on anticoagulants. Parameters included right/left ventricular ratio, septal bowing, cardiothoracic ratio, diameters of pulmonary trunk and aorta, and intrahepatic/azygos vein contrast medium backflow. Associations with mortality, recurrent venous thromboembolism (VTE), hospitalisation, bleeding and adverse events were assessed over the short term (1 week and 1 month) and long term (12 months).

Pulmonary trunk enlargement was the only parameter significantly associated with mortality over both the short and long term (OR 4.18 (95% CI 1.04–16.76) at 1 week to OR 2.33 (95% CI 1.36–3.97) after 1 year), as well as with recurrent VTE and hospitalisation.

Most of the evaluated radiological parameters do not have strong effects on the short- or long-term outcome in patients with acute pulmonary embolism. Only an enlarged pulmonary trunk diameter carries an increased risk of mortality and recurrent VTE up to 12 months, and can be used for risk stratification.

A new method of CT for the cardiac measurement: correlation of computed tomography measured cardiac parameters and pulmonary obstruction index to assess cardiac morphological changes in acute pulmonary embolism patients

Acute pulmonary embolism (APE) is a serious disease which is life-threatening. Since it is crucial for APE patients to assess the changes of cardiac function safely and timely, the imaging research of cardiac morphology and function is becoming more and more important. The correlation of computed tomography (CT) measured cardiac parameters and pulmonary obstruction index (POI) was analyzed to discuss the morphological changes of the heart of APE patients in order to provide a new method to evaluate cardiac functions accurately and effectively. 118 APE patients confirmed with CT pulmonary angiography (CTPA) were divided into high-risk group (47 cases, POI ≥ 20) and low-risk group (71 cases, POI < 20) according to the Qanadli Score. The left to right diameter (RL) and the anteroposterior diameter (AP) of the cardiac chambers were compared among the high-risk group, the low-risk group, and the normal group (60 cases). The correlation between CT measured cardiac parameters and the POI was analyzed. Except for left ventricular AP and right atrial AP, there were statistically significant differences (P < 0.05) in the RL and AP of the each cardiac cavity, these parameters meant that right hearts were enlarged and the left hearts were decreased in size. The ratio of right/left heart diameter was statistically significant among the three groups, a < b < c (P < 0.05). Moreover, the POI of 118 APE patients was 14.29 ± 9.53, and there was significant linear correlation between CT measured cardiac parameters and the POI (P < 0.05), excluding the left ventricular AP and right atrial AP. The correlation coefficient reached 0.5 or more in terms of the right atrial LR, the right ventricular LR, the ratio of right/left atrial diameter and the ratio of right/left ventricular diameter. With the increasing value of POI, the right atrium and right ventricular of APE patients were enlarged, and the left atrium and left ventricular were decreased in size. These heart changes can be observed by using CTPA, even non-enhanced chest CT.

Rapid on-site evaluation of routine biochemical parameters to predict right ventricular dysfunction in and the prognosis of patients with acute pulmonary embolism upon admission to the emergency room

INTRODUCTION

Patients with acute pulmonary embolism(APE)who present with right ventricular dysfunction (RVD) have a worse prognosis. This study aimed to evaluate the value of routine biochemical parameters in predicting RVD and 30-day mortality in patients with APE.

METHODS

We retrospectively collected the clinical data for 154 enrolled patients, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), D-dimer, cardiac troponin I (cTnI), and N-terminal pro-brain natriuretic peptide (NT-proBNP). We analyzed the correlation between RVD and the parameters and conducted a receiver operating characteristic (ROC) curve to confirm the cut-off values for predicting RVD and 30-day mortality. Formulas were built with relevant parameters to predict RVD and 30-day mortality.

RESULTS

Age, NLR, PLR, D-dimer, the ratio of cTnI (+), and NT-proBNP (+) were significantly higher in RVD (+) patients. The ratio of cTnI (+) and NT-proBNP (+) in 30-day mortality (+) patients was significantly higher than that in 30-day mortality (-) patients. According to the logistic regression analysis, NLR, cTnI (+), and NT-proBNP (+) correlated with RVD. The formula for the RVD risk score is 0.072 × NLR+1.460 × NT-proBNP (+)+2.113 × cTnI (+), and the area under the curve (AUC) = 0.890 (95% CI: 0.839-0.941, P = .001). The formula for the 30-day mortality risk score is 0.115 × NLR + 2.046 × NT-proBNP (+) + 1.946 × cTnI (+) -0.016 × PLR, and the AUC = 0.903 (95% CI: 0.829-0.976, P = .001).

CONCLUSIONS

The rapid on-site evaluation of routine biochemical parameters, including NLR, cTnI, and NT-proBNP levels, and the formula developed using these parameters are valuable for predicting RVD and 30-day mortality in patients with APE.