Impact of Three Different Algorithms for the Screening of SSc-PAH and Comparison with the Decisions of a Multidisciplinary Team

Attitudes and barriers to pulmonary arterial hypertension screening in systemic sclerosis patients: A survey of UK-based rheumatologists

Objectives

The objectives were to explore rheumatologists' current clinical screening practices of pulmonary arterial hypertension in patients with systemic sclerosis in the United Kingdom and to identify barriers to screening and consider potential solutions.

Methods

A survey of 31 questions was developed and included six sections: clinician demographics, the importance of screening, screening practices, barriers to screening, treatment and patient education. The survey was disseminated among rheumatologists working in the United Kingdom.

Results

Forty-four rheumatologists working in the United Kingdom participated in the study, and the majority completed all the questions. Around one-third (37.0%) worked in specialised systemic sclerosis units (university or general hospitals (54.5% and 45.4%, respectively)). The majority recognised that systemic sclerosis-pulmonary arterial hypertension is a major cause of morbidity and mortality. Over half (60.0%) reported using the DETECT algorithm to screen for systemic sclerosis-pulmonary arterial hypertension, although other algorithms were also sometimes used. All of the respondents utilised transthoracic echocardiogram, and almost all (95.0%) performed pulmonary function tests for screening purposes. Various challenges and barriers were identified relating to systemic sclerosis-pulmonary arterial hypertension screening, with the difficulty in interpreting results from other hospitals and extended wait times for diagnostic tests being the most reported (76.0% and 74.0%, respectively). Most respondents agreed that access to key investigations (87.0%), ongoing clinician education (82.0%), multidisciplinary meetings (79.5%) and a better understanding of proposed screening algorithms (79.5%) could be potential solutions.

Conclusion

Screening patients with systemic sclerosis for pulmonary arterial hypertension is crucial to improve survival, but variable practices exist among UK rheumatologists. Solutions include educating healthcare professionals on guidelines, sharing information between centres and integrating care services.

[Diagnostic Algorithm and Screening of Pulmonary Hypertension]

The new guidelines for the diagnosis and treatment of pulmonary hypertension include a new diagnostic algorithm and provide specific recommendations for the required diagnostic procedures, including screening methods. These recommendations are commented on by national experts under the auspices of the DACH. These comments provide additional decision support and background information, serving as a further guide for the complex diagnosis of pulmonary hypertension.

Multidisciplinary team discussion: the emerging gold standard for management of cardiopulmonary complications of connective tissue disease

Cardiopulmonary complications of connective tissue diseases (CTDs), particularly pulmonary arterial hypertension (PAH) and interstitial lung disease (ILD), are major determinants of morbidity and mortality. Multidisciplinary meetings may improve diagnostic accuracy and optimise treatment. We review the literature regarding multidisciplinary meetings in CTD-ILD and PAH and describe our tertiary centre experience of the role of the multidisciplinary meeting in managing CTD-PAH.

Scleroderma pulmonary arterial hypertension: the same as idiopathic pulmonary arterial hypertension?

PURPOSE OF REVIEW

Pulmonary arterial hypertension (PAH) is a common complication of systemic sclerosis (SSc), which confers significant morbidity and mortality. The current therapies and treatment strategies for SSc-associated PAH (SSc-PAH) are informed by those used to treat patients with idiopathic PAH (IPAH). There are, however, important differences between these two diseases that impact diagnosis, treatment, and outcomes.

RECENT FINDINGS

Both SSc-PAH and IPAH are incompletely understood with ongoing research into the underlying cellular biology that characterize and differentiate the two diseases. Additional research seeks to improve identification among SSc patients in order to diagnose patients earlier in the course of their disease. Novel therapies specifically for SSc-PAH such as rituximab and dimethyl fumarate are under investigation.

SUMMARY

Although patients with SSc-PAH and IPAH present with similar symptoms, there are significant differences between these two forms of PAH that warrant further investigation and characterization of optimal detection strategies, treatment algorithms, and outcomes assessment.

A signal recognition particle-related joint model of LASSO regression, SVM-RFE and artificial neural network for the diagnosis of systemic sclerosis-associated pulmonary hypertension

Background: Systemic sclerosis-associated pulmonary hypertension (SSc-PH) is one of the most common causes of death in patients with systemic sclerosis (SSc). The complexity of SSc-PH and the heterogeneity of clinical features in SSc-PH patients contribute to the difficulty of diagnosis. Therefore, there is a pressing need to develop and optimize models for the diagnosis of SSc-PH. Signal recognition particle (SRP) deficiency has been found to promote the progression of multiple cancers, but the relationship between SRP and SSc-PH has not been explored. Methods: First, we obtained the GSE19617 and GSE33463 datasets from the Gene Expression Omnibus (GEO) database as the training set, GSE22356 as the test set, and the SRP-related gene set from the MSigDB database. Next, we identified differentially expressed SRP-related genes (DE-SRPGs) and performed unsupervised clustering and gene enrichment analyses. Then, we used least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) to identify SRP-related diagnostic genes (SRP-DGs). We constructed an SRP scoring system and a nomogram model based on the SRP-DGs and established an artificial neural network (ANN) for diagnosis. We used receiver operating characteristic (ROC) curves to identify the SRP-related signature in the training and test sets. Finally, we analyzed immune features, signaling pathways, and drugs associated with SRP and investigated SRP-DGs' functions using single gene batch correlation analysis-based GSEA. Results: We obtained 30 DE-SRPGs and found that they were enriched in functions and pathways such as "protein targeting to ER," "cytosolic ribosome," and "coronavirus disease-COVID-19". Subsequently, we identified seven SRP-DGs whose expression levels and diagnostic efficacy were validated in the test set. As one signature, the area under the ROC curve (AUC) values for seven SRP-DGs were 0.769 and 1.000 in the training and test sets, respectively. Predictions made using the nomogram model are likely beneficial for SSc-PH patients. The AUC values of the ANN were 0.999 and 0.860 in the training and test sets, respectively. Finally, we discovered that some immune cells and pathways, such as activated dendritic cells, complement activation, and heme metabolism, were significantly associated with SRP-DGs and identified ten drugs targeting SRP-DGs. Conclusion: We constructed a reliable SRP-related ANN model for the diagnosis of SSc-PH and investigated the possible role of SRP in the etiopathogenesis of SSc-PH by bioinformatics methods to provide a basis for precision and personalized medicine.

Predicting the Progression of Very Early Systemic Sclerosis: Current Insights

Systemic sclerosis (SSc) is a complex autoimmune connective tissue disease with distinct pathological hallmarks (ie, inflammation, vasculopathy, fibrosis) that may predominate at different stages in the disease course with varying severity. Initial efforts to classify patients with SSc identified a subset of patients with very early SSc. These patients possessed signs of SSc (eg, Raynaud phenomenon, SSc specific autoantibodies and/or nailfold capillary abnormalities) without fulfilling complete SSc classification criteria. Recognizing the inherent value in early diagnosis and intervention in SSc, researchers have endeavored to identify risk factors for progression from very early SSc to definite SSc. The present review summarizes the clinical phenotype of patients with very early and early SSc. Through a scoping review of recent literature, this review also describes risk factors for progression to definite SSc with a focus on the specific clinical features that arise early in the SSc disease course (eg, diffuse cutaneous sclerosis, interstitial lung disease, esophageal dysfunction, renal crisis, cardiac involvement). In addition to clinical risk factors, this review provides evidence for how biological data (ie, serological, genomic, proteomic profiles, skin bioengineering methods) can be integrated into risk assessment models in the future. Furthering our understanding of biological features of very early SSc will undoubtedly provide novel insights into SSc pathogenesis and may illuminate new therapeutic targets to prevent progression of SSc.