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Background Although a general association between nocturnal hypoxemia or sleep-disordered breathing (SDB) and pulmonary arterial hypertension has been established, little is known about the unique pathophysiologic contributions of SDB and nocturnal hypoxemia to chronic thromboembolic pulmonary disease (CTEPD). We therefore chose to examine the associations of SDB and nocturnal hypoxemia with hemodynamic indices obtained via right heart catheterization (RHC) in hospitalized patients with CTEPD. We hypothesized that the severity of CTEPD would be associated with SDB and nocturnal hypoxemia severity. Methods Patients with CTEPD with or without pulmonary hypertension (PH) who had undergone polysomnography (PSG) between July 2022 and March 2024 were enrolled. A nocturnal mean oxygen saturation by pulse oximetry (MeanSpO 2 ) < 90% was defined as nocturnal hypoxemia, and a percentage of total sleep time with oxygen saturation < 90% (T90) exceeding 20% indicated severe nocturnal hypoxemia. The relationships between right heart catheterization measurements and T90 or MeanSpO 2 were calculated using multiple linear regression and logistic regression analyses. Results The prevalence of severe nocturnal hypoxemia in the entire cohort was 42.86%, and SDB (AHI ≥ 15/h) affected 55.84% of patients and was predominantly manifested as hypopnea. Nocturnal hypoxemia remained significantly associated with mean pulmonary artery pressure (mPAP) (T90: β = 0.296, P  = 0.019; MeanSpO 2 : β= -0.333, P  = 0.009) and pulmonary vascular resistance (PVR) (T90: β = 0.294, P  = 0.021; MeanSpO 2 : β=-0.310, P  = 0.015) after adjusting for age, sex, body mass index, apnea hypopnea index and diurnal arterial partial pressure of oxygen. Receiver operating characteristic (ROC) curves for the detection of a mPAP ≥ 25 mmHg, PVR > 3 WU and WHO FC III-IV indicated that nocturnal hypoxemia parameters had moderate predictive value. (T90: AUC mPAP =0.698, AUC PVR =0.733, AUC WHO−FC =0.729, respectively; MeanSpO 2 : AUC mPAP =0.691, AUC PVR =0.731, AUC WHO−FC =0.707, respectively). Conclusions SDB is highly prevalent in patients with CTEPD, which is predominantly manifested as hypopnea rather than apnea, and overweight is not a commonly reported characteristic. Independent of the severity of SDB, nocturnal hypoxemia is significantly correlated with hemodynamics in patients with CTEPD, which indicated the clinical necessity of promoting nocturnal oximetry monitoring among patients with CTEPD.

ObjectivesTo 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 methodsThe 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.ResultsThere 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.ConclusionsDL-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.

Abstract Background: Acute pulmonary embolism (APE) is a fatal cardiovascular disease, yet missed diagnosis and misdiagnosis often occur due to non-specific symptoms and signs. A simple, objective technique will help clinicians make a quick and precise diagnosis. In population studies, machine learning (ML) plays a critical role in characterizing cardiovascular risks, predicting outcomes, and identifying biomarkers. This work sought to develop an ML model for helping APE diagnosis and compare it against current clinical probability assessment models. Methods: This is a single-center retrospective study. Patients with suspected APE were continuously enrolled and randomly divided into two groups including training and testing sets. A total of 8 ML models, including random forest (RF), Naïve Bayes, decision tree, K-nearest neighbors, logistic regression, multi-layer perceptron, support vector machine, and gradient boosting decision tree were developed based on the training set to diagnose APE. Thereafter, the model with the best diagnostic performance was selected and evaluated against the current clinical assessment strategies, including the Wells score, revised Geneva score, and Years algorithm. Eventually, the ML model was internally validated to assess the diagnostic performance using receiver operating characteristic (ROC) analysis. Results: The ML models were constructed using eight clinical features, including D-dimer, cardiac troponin T (cTNT), arterial oxygen saturation, heart rate, chest pain, lower limb pain, hemoptysis, and chronic heart failure. Among eight ML models, the RF model achieved the best performance with the highest area under the curve (AUC) (AUC = 0.774). Compared to the current clinical assessment strategies, the RF model outperformed the Wells score (P = 0.030) and was not inferior to any other clinical probability assessment strategy. The AUC of the RF model for diagnosing APE onset in internal validation set was 0.726. Conclusions: Based on RF algorithm, a novel prediction model was finally constructed for APE diagnosis. When compared to the current clinical assessment strategies, the RF model achieved better diagnostic efficacy and accuracy. Therefore, the ML algorithm can be a useful tool in assisting with the diagnosis of APE.

Objective Emerging evidence suggests a potential role for soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cardiovascular pathophysiology. However, plasma sTREM2 levels in patients with acute decompensated heart failure and their possible association with adverse clinical outcomes have not been fully characterized. Methods In this retrospective cohort study, we enrolled patients with acute decompensated heart failure between 2020 and 2023 and defined a composite endpoint comprising all-cause mortality and heart failure–related readmission. Baseline plasma sTREM2 levels were compared across clinical categories and acute decompensated heart failure phenotypes using appropriate statistical tests. The prognostic value of sTREM2 was evaluated using Kaplan–Meier survival curves, restricted cubic splines, and Cox proportional hazards regression models. Model calibration was validated using bootstrap-corrected plots with 1000 resamples. Furthermore, time-dependent receiver operating characteristic curves, net reclassification improvement, and integrated discrimination improvement were used to assess the incremental predictive value of sTREM2 over N-terminal pro-B-type natriuretic peptide. Finally, subgroup analyses were performed to assess the robustness of the findings. Results A total of 128 patients (median age, 75.5 years) were enrolled, with 58 (45.3%) reaching the composite endpoint during follow-up. Plasma sTREM2 levels were significantly higher in patients with acute decompensated heart failure than in healthy controls (P < 0.001) and showed a progressive increase with worsening New York Heart Association functional class. Multivariable Cox regression analysis demonstrated that each 50 pg/mL increment in sTREM2 was independently associated with an increased risk of the composite endpoint (adjusted hazard ratio: 1.594; 95% confidence interval: 1.170–2.173) and heart failure–related readmission (adjusted hazard ratio: 1.802; 95% confidence interval: 1.310–2.480). Restricted cubic spline analysis confirmed a linear association between sTREM2 levels and clinical outcomes (all P for nonlinear > 0.05). Although adding sTREM2 to N-terminal pro-B-type natriuretic peptide did not significantly increase the area under the curve, it provided incremental predictive value for heart failure–related readmission. Subgroup analyses revealed no significant interactions (all P for interaction > 0.05). Conclusion Our findings demonstrate that sTREM2 is a potential biomarker in acute decompensated heart failure. Elevated sTREM2 levels are independently associated with an increased risk of adverse clinical outcomes, particularly heart failure–related readmission, underscoring its potential utility in risk stratification and clinical management of acute decompensated heart failure.

BackgroundPulmonary artery involvement (PAI) in Takayasu arteritis (TAK) can cause pulmonary hypertension (PH). We aimed to compare clinical and imaging features between TAK patients with and without PH, identify factors associated with PH and describe long-term outcomes.MethodsA prospective cohort of 147 TAK patients was studied from 2016 to 2024. Eligibility required fulfilment of established TAK criteria or multidisciplinary confirmation of CT-proven PAI after exclusion of other causes. Baseline demographics, clinical symptoms, laboratory and imaging findings, haemodynamic parameters and treatments were collected. The primary endpoint was all-cause mortality. Logistic regression identified factors associated with PH, and Cox proportional hazards regression evaluated predictors of mortality.ResultsAmong 87 TAK-PAI patients, 40 (46%) had PH. Compared with non-PH patients, those with PH had higher Qanadli scores, longer diagnostic delay (median 20.5 vs 6.0 months, p=0.011), more severe symptoms, worse cardiopulmonary function, and higher N-terminal pro-B-type natriuretic peptide and right ventricular dimension (all p<0.01). During a median follow-up of 32 months, all eight deaths occurred in the PH group, seven without balloon pulmonary angioplasty. Kaplan-Meier survival was significantly worse for PH (p=0.0025). Multivariable analysis identified female sex (OR 4.543; 95% CI 1.103 to 18.717, p=0.036), higher Qanadli score (OR 14.729; 95% CI 2.718 to 79.809, p=0.002), uric acid (OR 1.007; 95% CI 1.002 to 1.013, p=0.010) and diagnostic delay per month (OR 1.036; 95% CI 1.010 to 1.063, p=0.006) as independent risk factors for PH. Worse WHO-functional class predicted mortality (HR 4.832; 95% CI 1.121 to 20.832, p=0.035).ConclusionsPH occurs in nearly half of TAK-PAI patients and is linked to severe symptoms, functional impairment and increased mortality. Higher Qanadli score, hyperuricaemia and delayed diagnosis are independent risk factors. Early recognition and timely intervention may improve outcomes.Trial registration numberNCT07184814.

Genome-wide association studies (GWAS) have identified numerous risk loci for venous thromboembolism (VTE), but it is challenging to decipher the underlying mechanisms. We employed an integrative analytical pipeline to transform genetic associations to identify novel plasma proteins for VTE. Proteome-wide association studies (PWAS) were determined by functional summary-based imputation leveraging data from a genome-wide association analysis (14,429 VTE patients, 267,037 controls), blood proteomes (1348 cases), followed by Mendelian randomization, Bayesian colocalization, protein-protein interaction, and pathway enrichment analysis. Twenty genetically regulated circulating protein abundances (F2, F11, ABO, PLCG2, LRP4, PLEK, KLKB1, PROC, KNG1, THBS2, SERPINA1, RARRES2, CEL, GP6, SERPINE2, SERPINA10, OBP2B, EFEMP1, F5, and MSR1) were associated with VTE. Of these 13 proteins demonstrated Mendelian randomized correlations. Six proteins (F2, F11, PLEK, SERPINA1, RARRES2, and SERPINE2) had strong support in colocalization analysis. Utilizing multidimensional data, this study suggests PLEK, SERPINA1, and SERPINE2 as compelling proteins that may provide key hints for future research and possible diagnostic and therapeutic targets for VTE.

Background Atrial fibrillation (AF) after acute pulmonary embolism (PE) may lead to a poor prognosis. We conducted this study to explore influencing factors of new-onset AF in patients after acute PE. Methods Patients with objectively confirmed acute PE at the China-Japan Friendship Hospital from first January 2015 to 31st May 2022 were retrospectively included in the study, and patients with new-onset AF confirmed by electrocardiography were defined as the case group. The control group was obtained from the above PE patients without new-onset AF in age matching. Patients with a history of AF, pulmonary hypertension, acute myocardial infarction, valvular heart disease and hyperthyroidism were excluded. Logistic regression was conducted to identify potential influencing factors for the development of new-onset AF in patients with acute PE. To assess the prediction value of potential variables, receiver operating characteristic curves were plotted. Results Among 853 patients diagnosed with acute PE, 732 patients met the including criteria, and 29 patients with new-onset AF were identified. The median age of all patients was 74 years, with 77.6% being male. No statistically significant differences were observed between the case and control groups regarding demographic characteristics. Patients with new-onset AF had significantly enlarged right atrium, right ventricle and left atrium in echocardiography compared with control group, but no significant differences were observed in the diameter of the left ventricle and the proportion of left ventricular ejection fraction (LVEF) ≤ 40%. Right atrial enlargement (OR, 4.19; 95%CI, 1.24-15.09; P = 0.023), left atrial enlargement (OR, 14.76; 95%CI, 4.79–57.28; P < 0.001) and the simplified pulmonary embolism severity index (sPESI) (OR, 2.04; 95%CI, 1.19–3.67; P = 0.012) were associated with increased risk of new-onset AF. Conclusions Both severity of acute PE and enlargement of left and right atrium were associated with an increased risk of new-onset AF in patients with acute PE. In patients with high-risk acute PE, greater vigilance is needed for the occurrence of new-onset AF.

Genetic risk factors are important for the occurrence and prognosis of venous thromboembolism (VTE). The studies of thrombophilia families are important for dissecting the genetic background of the thrombotic disease. We conducted the systematic review of all published family-based studies on VTE genetics across all racial groups through PubMed and Embase prior to 13th April 2020. This systematic review of 287 families (including 225 Caucasian families, 52 East Asian families, and families of other ethnicities) revealed a total of 21 different genes; the five most reported mutated genes were F5 (88/287, 30.7%), SERPINC1 (67/287, 23.3%), PROC (65/287, 22.6%), F2 (40/287, 13.9%) and PROS1 (48/287, 16.7%). For Caucasian families, F5 mutations were most frequently reported at 37.8% (85/225), while PROS1 mutations were most frequently reported, at 40.4% (21/52), for East Asian families (Chinese, Japanese and Korean). Factor V Leiden was reported more frequently in Caucasians than in East Asians. Missense mutations were reported frequently in the SERPINC1, PROC and PROS1 genes. In conclusion, our study found the most likely mutated genes associated with VTE among different ethnic groups and provided indications for VTE genetic testing and research in the future.