Phosphodiesterase-5 Inhibitor Treatment is Associated with Improved Survival in Pulmonary Hypertension Associated with COPD in the PVRI GoDeep Meta-Registry.

BACKGROUND: Patients with COPD frequently develop pulmonary hypertension (PH-COPD). Severe PH-COPD, identified by a pulmonary vascular resistance (PVR) >5 Wood Units (WU), is closely linked to impaired transplant-free survival. The impact of PH-targeting pharmacotherapy in this context remains unclear. RESEARCH QUESTION: Is PH-targeted therapy associated with improved transplant-free survival in PH-COPD? STUDY DESIGN AND METHODS: This study included PVRI GoDeep meta-registry patients with PH-COPD and available right heart catheterization at diagnosis. We investigated PH-targeted therapy prevalence and its association with transplant-free survival using diverse statistical methods, including Cox regression and subgroup analyses based on PH severity, comorbidities, and pulmonary function tests. Immortal time bias was addressed through a landmark approach. RESULTS: As of December 2023, the GoDeep meta-registry included 26981 patients (28% PH-Group 1, 13% PH-Group 2, 12% PH-Group 3, 10% PH-Group 4, 2% PH-Group 5, 26% undefined and 9% control). Out of these, 836 patients were diagnosed as PH-COPD and included in this analysis, with median age 66 [59,73]years, FEV1 51 [34,69]%predicted, mPAP 35 [28,44]mmHg, PVR 5 [4,8]WU, cardiac index 2.5 [2.0,2.9]L/min.m2, and mostly WHO functional class III were included. 5-year transplant-free survival was 42%, significantly worse than group 1 PH. A multivariable Cox proportional hazards model identified PVR, but not FEV1 as a major predictor of outcome. 418 patients (50%) received phosphodiesterase-5 inhibitor (PDE5i) therapy, which was associated with significantly reduced mortality: hazard ratio 0.65 [0.57,0.75] for the entire PH-COPD cohort and 0.83 [0.74,0.94] when performing landmark analysis. This PDE5i effect was robustly reproduced when performing subgroup analyses for patients with moderate/severe PH, various comorbidities, and supplemental oxygen requirement, and when assessing the impact of unobserved confounders. INTERPRETATION: PH-COPD patients exhibit poor transplant-free survival, with PVR being a predictor of mortality. In this meta-registry, PDE5i therapy was associated with a significant reduction in mortality across all tested models.

Chronic thromboembolic pulmonary hypertension is an uncommon complication of COVID-19: UK national surveillance and observational screening cohort studies.

BACKGROUND: Pulmonary embolism (PE) is a well-recognised complication of coronavirus disease 2019 (COVID-19) infection, and chronic thromboembolic pulmonary disease with and without pulmonary hypertension (CTEPD/CTEPH) are potential life-limiting consequences. At present the burden of CTEPD/CTEPH is unclear and optimal and cost-effective screening strategies yet to be established. METHODS: We evaluated the CTEPD/CTEPH referral rate to the UK national multidisciplinary team (MDT) during the 2017-2022 period to establish the national incidence of CTEPD/CTEPH potentially attributable to COVID-19-associated PE with historical comparator years. All individual cases of suspected CTEPH were reviewed by the MDT for evidence of associated COVID-19. In a separate multicentre cohort, the risk of developing CTEPH following hospitalisation with COVID-19 was calculated using simple clinical parameters at a median of 5 months post-hospital discharge according to existing risk scores using symptoms, ECG and N-terminal pro-brain natriuretic peptide. RESULTS: By the second year of the pandemic, CTEPH diagnoses had returned to the pre-pandemic baseline (23.1 versus 27.8 cases per month; p=0.252). Of 334 confirmed CTEPD/CTEPH cases, four (1.2%) patients were identified to have CTEPH potentially associated with COVID-19 PE, and a further three (0.9%) CTEPD without PH. Of 1094 patients (mean age 58 years, 60.4% male) hospitalised with COVID-19 screened across the UK, 11 (1.0%) were at high risk of CTEPH at follow-up, none of whom had a diagnosis of CTEPH made at the national MDT. CONCLUSION: A priori risk of developing CTEPH following COVID-19-related hospitalisation is low. Simple risk scoring is a potentially effective way of screening patients for further investigation.

Individualized survival predictions using state space model with longitudinal and survival data.

Monitoring disease progression often involves tracking biomarker measurements over time. Joint models (JMs) for longitudinal and survival data provide a framework to explore the relationship between time-varying biomarkers and patients' event outcomes, offering the potential for personalized survival predictions. In this article, we introduce the linear state space dynamic survival model for handling longitudinal and survival data. This model enhances the traditional linear Gaussian state space model by including survival data. It differs from the conventional JMs by offering an alternative interpretation via differential or difference equations, eliminating the need for creating a design matrix. To showcase the model's effectiveness, we conduct a simulation case study, emphasizing its performance under conditions of limited observed measurements. We also apply the proposed model to a dataset of pulmonary arterial hypertension patients, demonstrating its potential for enhanced survival predictions when compared with conventional risk scores.

Association of risk assessment at diagnosis with healthcare resource utilization and health-related quality of life outcomes in pulmonary arterial hypertension.

We aimed to describe the clinical characteristics, healthcare resource utilization (HCRU) and costs, health-related quality of life (HRQoL), and survival for patients with pulmonary arterial hypertension (PAH), stratified by 1-year mortality risk at diagnosis. Adults diagnosed with PAH at the Sheffield Pulmonary Vascular Disease Unit between 2012 and 2019 were included. Patients were categorized as low, intermediate, or high risk for 1-year mortality at diagnosis. Demographics, clinical characteristics, comorbidities, HCRU, costs, HRQoL, and survival were analyzed. Overall, 1717 patients were included: 72 (5%) at low risk, 941 (62%) at intermediate risk, and 496 (33%) at high risk. Low-risk patients had lower HCRU prediagnosis and 1-year postdiagnosis than intermediate- or high-risk patients. Postdiagnosis, there were significant changes in HCRU, particularly inpatient hospitalizations and accident and emergency (A&E) visits among high-risk patients. At 3 years postdiagnosis, HCRU for all measures was similar across risk groups. Low-risk patients had lower EmPHasis-10 scores (indicating better HRQoL) at diagnosis and at 1-year follow-up compared with intermediate- and high-risk patients; only the score in the high-risk group improved. Median overall survival decreased as risk category increased in analyzed subgroups. Low-risk status was associated with better 1-year survival and HRQoL compared with intermediate- and high-risk patients. HCRU decreased in high-risk patients postdiagnosis, with the most marked reduction in A&E admissions. The pattern of decreased per-patient inpatient hospitalizations and A&E visits at 3 years postdiagnosis suggests that a diagnosis of PAH helps to decrease HCRU in areas that are key drivers of costs.

Omada: robust clustering of transcriptomes through multiple testing.

BACKGROUND: Cohort studies increasingly collect biosamples for molecular profiling and are observing molecular heterogeneity. High-throughput RNA sequencing is providing large datasets capable of reflecting disease mechanisms. Clustering approaches have produced a number of tools to help dissect complex heterogeneous datasets, but selecting the appropriate method and parameters to perform exploratory clustering analysis of transcriptomic data requires deep understanding of machine learning and extensive computational experimentation. Tools that assist with such decisions without prior field knowledge are nonexistent. To address this, we have developed Omada, a suite of tools aiming to automate these processes and make robust unsupervised clustering of transcriptomic data more accessible through automated machine learning-based functions. FINDINGS: The efficiency of each tool was tested with 7 datasets characterized by different expression signal strengths to capture a wide spectrum of RNA expression datasets. Our toolkit's decisions reflected the real number of stable partitions in datasets where the subgroups are discernible. Within datasets with less clear biological distinctions, our tools either formed stable subgroups with different expression profiles and robust clinical associations or revealed signs of problematic data such as biased measurements. CONCLUSIONS: In conclusion, Omada successfully automates the robust unsupervised clustering of transcriptomic data, making advanced analysis accessible and reliable even for those without extensive machine learning expertise. Implementation of Omada is available at http://bioconductor.org/packages/omada/.

Two prospective, multicenter studies for the identification of biomarker signatures for early detection of pulmonary hypertension (PH): The CIPHER and CIPHER-MRI studies.

A blood test identifying patients at increased risk of pulmonary hypertension (PH) could streamline the investigative pathway. The prospective, multicenter CIPHER study aimed to develop a microRNA-based signature for detecting PH in breathless patients and enrolled adults with a high suspicion of PH who had undergone right heart catheterization (RHC). The CIPHER-MRI study was added to assess the performance of this CIPHER signature in a population with low probability of having PH who underwent cardiac magnetic resonance imaging (cMRI) instead of RHC. The microRNA signature was developed using a penalized linear regression (LASSO) model. Data were modeled both with and without N-terminal pro-brain natriuretic peptide (NT-proBNP). Signature performance was assessed against predefined thresholds (lower 98.7% CI bound of ≥0.73 for sensitivity and ≥0.53 for specificity, based on a meta-analysis of echocardiographic data), using RHC as the true diagnosis. Overall, 926 CIPHER participants were screened and 888 were included in the analysis. Of 688 RHC-confirmed PH cases, approximately 40% were already receiving PH treatment. Fifty microRNA (from 311 investigated) were algorithmically selected to be included in the signature. Sensitivity [97.5% CI] of the signature was 0.85 [0.80-0.89] for microRNA-alone and 0.90 [0.86-0.93] for microRNA+NT-proBNP, and the corresponding specificities were 0.33 [0.24-0.44] and 0.28 [0.20-0.39]. Of 80 CIPHER-MRI participants with evaluable data, 7 were considered PH-positive by cMRI whereas 52 were considered PH-positive by the microRNA signature. Due to low specificity, the CIPHER miRNA-based signature for PH (either with or without NT-proBNP in model) did not meet the prespecified diagnostic threshold for the primary analysis.

Comparison of Contemporary Risk Scores in All Groups of Pulmonary Hypertension: A Pulmonary Vascular Research Institute GoDeep Meta-Registry Analysis.

BACKGROUND: Pulmonary hypertension (PH) is a heterogeneous disease with a poor prognosis. Accurate risk stratification is essential for guiding treatment decisions in pulmonary arterial hypertension (PAH). Although various risk models have been developed for PAH, their comparative prognostic potential requires further exploration. Additionally, the applicability of risk scores in PH groups beyond group 1 remains to be investigated. RESEARCH QUESTION: Are risk scores originally developed for PAH predictive in PH groups 1 through 4? STUDY DESIGN AND METHODS: We conducted a comprehensive analysis of outcomes among patients with incident PH enrolled in the multicenter worldwide Pulmonary Vascular Research Institute GoDeep meta-registry. Analyses were performed across PH groups 1 through 4 and further subgroups to evaluate the predictive value of PAH risk scores, including the Registry to Evaluate Early and Long-Term PAH Disease Mangement (REVEAL) Lite 2, REVEAL 2.0, European Society of Cardiology/European Respiratory Society 2022, Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) 3-strata, and COMPERA 4-strata. RESULTS: Eight thousand five hundred sixty-five patients were included in the study, of whom 3,537 patients were assigned to group 1 PH, whereas 1,807 patients, 1,635 patients, and 1,586 patients were assigned to group 2 PH, group 3 PH, and group 4 PH, respectively. Pulmonary hemodynamics were impaired with median mean pulmonary arterial pressure of 42 mm Hg (interquartile range, 33-52 mm Hg) and pulmonary vascular resistance of 7 Wood units (WU) (interquartile range, 4-11 WU). All risk scores were prognostic in the entire PH population and in each of the PH groups 1 through 4. The REVEAL scores, when used as continuous prediction models, demonstrated the highest statistical prognostic power and granularity; the COMPERA 4-strata risk score provided subdifferentiation of the intermediate-risk group. Similar results were obtained when separately analyzing various subgroups (PH subgroups 1.1, 1.4.1, and 1.4.4; PH subgroups 3.1 and 3.2; group 2 with isolated postcapillary PH vs combined precapillary and postcapillary PH; patients of all groups with concomitant cardiac comorbidities; and severe [> 5 WU] vs nonsevere PH). INTERPRETATION: This comprehensive study with real-world data from 15 PH centers showed that PAH-designed risk scores possess predictive power in a large PH cohort, whether considered as common to the group or calculated separately for each PH group (1-4) and various subgroups. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT05329714; URL: www. CLINICALTRIALS: gov.

Mendelian Randomization Study With Clinical Follow-Up Links Metabolites to Risk and Severity of Pulmonary Arterial Hypertension.

BACKGROUND: Pulmonary arterial hypertension (PAH) exhibits phenotypic heterogeneity and variable response to therapy. The metabolome has been implicated in the pathogenesis of PAH, but previous works have lacked power to implicate specific metabolites. Mendelian randomization (MR) is a method for causal inference between exposures and outcomes. METHODS AND RESULTS: Using genome-wide association study summary statistics, we implemented MR analysis to test for potential causal relationships between serum concentration of 575 metabolites and PAH. Five metabolites were causally associated with the risk of PAH after multiple testing correction. Next, we measured serum concentration of candidate metabolites in an independent clinical cohort of 449 patients with PAH to check whether metabolite concentrations are correlated with markers of disease severity. Of the 5 candidates nominated by our MR work, serine was negatively associated and homostachydrine was positively associated with clinical severity of PAH via direct measurement in this independent clinical cohort. Finally we used conditional and orthogonal approaches to explore the biology underlying our lead metabolites. Rare variant burden testing was carried out using whole exome sequencing data from 578 PAH cases and 361 675 controls. Multivariable MR is an extension of MR that uses a single set of instrumental single-nucleotide polymorphisms to measure multiple exposures; multivariable MR is used to determine interdependence between the effects of different exposures on a single outcome. Rare variant analysis demonstrated that loss-of-function mutations within activating transcription factor 4, a transcription factor responsible for upregulation of serine synthesis under conditions of serine starvation, are associated with higher risk for PAH. Homostachydrine is a xenobiotic metabolite that is structurally related to l-proline betaine, which has previously been linked to modulation of inflammation and tissue remodeling in PAH. Our multivariable MR analysis suggests that the effect of l-proline betaine is actually mediated indirectly via homostachydrine. CONCLUSIONS: Our data present a method for study of the metabolome in the context of PAH, and suggests several candidates for further evaluation and translational research.

Blood DNA methylation profiling identifies cathepsin Z dysregulation in pulmonary arterial hypertension.

Pulmonary arterial hypertension (PAH) is characterised by pulmonary vascular remodelling causing premature death from right heart failure. Established DNA variants influence PAH risk, but susceptibility from epigenetic changes is unknown. We addressed this through epigenome-wide association study (EWAS), testing 865,848 CpG sites for association with PAH in 429 individuals with PAH and 1226 controls. Three loci, at Cathepsin Z (CTSZ, cg04917472), Conserved oligomeric Golgi complex 6 (COG6, cg27396197), and Zinc Finger Protein 678 (ZNF678, cg03144189), reached epigenome-wide significance (p < 10-7) and are hypermethylated in PAH, including in individuals with PAH at 1-year follow-up. Of 16 established PAH genes, only cg10976975 in BMP10 shows hypermethylation in PAH. Hypermethylation at CTSZ is associated with decreased blood cathepsin Z mRNA levels. Knockdown of CTSZ expression in human pulmonary artery endothelial cells increases caspase-3/7 activity (p < 10-4). DNA methylation profiles are altered in PAH, exemplified by the pulmonary endothelial function modifier CTSZ, encoding protease cathepsin Z.

Risk assessment and real-world outcomes in chronic thromboembolic pulmonary hypertension: insights from a UK pulmonary hypertension referral service.

OBJECTIVES: This study was conducted to evaluate the ability of risk assessment to predict healthcare resource utilisation (HCRU), costs, treatments, health-related quality of life (HRQoL) and survival in patients diagnosed with chronic thromboembolic pulmonary hypertension (CTEPH). DESIGN: Retrospective observational study. SETTING: Pulmonary hypertension referral centre in the UK. PARTICIPANTS: Adults diagnosed with CTEPH between 1 January 2012 and 30 June 2019 were included. Cohorts were retrospectively defined for operated patients (received pulmonary endarterectomy (PEA)) and not operated; further subgroups were defined based on risk score (low, intermediate or high risk for 1-year mortality) at diagnosis. PRIMARY AND SECONDARY OUTCOME MEASURES: Demographics, clinical characteristics, comorbidities, treatment patterns, HRQoL, HCRU, costs and survival outcomes were analysed. RESULTS: Overall, 683 patients were analysed (268 (39%) operated; 415 (61%) not operated). Most patients in the operated and not-operated cohorts were intermediate risk (63%; 53%) or high risk (23%; 31%) at diagnosis. Intermediate-risk and high-risk patients had higher HCRU and costs than low-risk patients. Outpatient and accident and emergency visits were lower postdiagnosis for both cohorts and all risk groups versus prediagnosis. HRQoL scores noticeably improved in the operated cohort post-PEA, and less so in the not-operated cohort at 6-18 months postdiagnosis. Survival at 5 years was 83% (operated) and 49% (not operated) and was lower for intermediate-risk and high-risk patients compared with low-risk patients. CONCLUSIONS: Findings from this study support that risk assessment at diagnosis is prognostic for mortality in patients with CTEPH. Low-risk patients have better survival and HRQoL and lower HCRU and costs compared with intermediate-risk and high-risk patients.

Unsupervised machine learning to investigate trajectory patterns of COVID-19 symptoms and physical activity measured via the MyHeart Counts App and smart devices.

Previous studies have associated COVID-19 symptoms severity with levels of physical activity. We therefore investigated longitudinal trajectories of COVID-19 symptoms in a cohort of healthcare workers (HCWs) with non-hospitalised COVID-19 and their real-world physical activity. 121 HCWs with a history of COVID-19 infection who had symptoms monitored through at least two research clinic visits, and via smartphone were examined. HCWs with a compatible smartphone were provided with an Apple Watch Series 4 and were asked to install the MyHeart Counts Study App to collect COVID-19 symptom data and multiple physical activity parameters. Unsupervised classification analysis of symptoms identified two trajectory patterns of long and short symptom duration. The prevalence for longitudinal persistence of any COVID-19 symptom was 36% with fatigue and loss of smell being the two most prevalent individual symptom trajectories (24.8% and 21.5%, respectively). 8 physical activity features obtained via the MyHeart Counts App identified two groups of trajectories for high and low activity. Of these 8 parameters only 'distance moved walking or running' was associated with COVID-19 symptom trajectories. We report a high prevalence of long-term symptoms of COVID-19 in a non-hospitalised cohort of HCWs, a method to identify physical activity trends, and investigate their association. These data highlight the importance of tracking symptoms from onset to recovery even in non-hospitalised COVID-19 individuals. The increasing ease in collecting real-world physical activity data non-invasively from wearable devices provides opportunity to investigate the association of physical activity to symptoms of COVID-19 and other cardio-respiratory diseases.

Wearable technology and the cardiovascular system: the future of patient assessment.

The past decade has seen a dramatic rise in consumer technologies able to monitor a variety of cardiovascular parameters. Such devices initially recorded markers of exercise, but now include physiological and health-care focused measurements. The public are keen to adopt these devices in the belief that they are useful to identify and monitor cardiovascular disease. Clinicians are therefore often presented with health app data accompanied by a diverse range of concerns and queries. Herein, we assess whether these devices are accurate, their outputs validated, and whether they are suitable for professionals to make management decisions. We review underpinning methods and technologies and explore the evidence supporting the use of these devices as diagnostic and monitoring tools in hypertension, arrhythmia, heart failure, coronary artery disease, pulmonary hypertension, and valvular heart disease. Used correctly, they might improve health care and support research.

Longitudinal Lung Function Assessment of Patients Hospitalized With COVID-19 Using 1H and 129Xe Lung MRI.

BACKGROUND: Microvascular abnormalities and impaired gas transfer have been observed in patients with COVID-19. The progression of pulmonary changes in these patients remains unclear. RESEARCH QUESTION: Do patients hospitalized with COVID-19 without evidence of architectural distortion on structural imaging exhibit longitudinal improvements in lung function measured by using 1H and 129Xe MRI between 6 and 52 weeks following hospitalization? STUDY DESIGN AND METHODS: Patients who were hospitalized with COVID-19 pneumonia underwent a pulmonary 1H and 129Xe MRI protocol at 6, 12, 25, and 51 weeks following hospital admission in a prospective cohort study between November 2020 and February 2022. The imaging protocol was as follows: 1H ultra-short echo time, contrast-enhanced lung perfusion, 129Xe ventilation, 129Xe diffusion-weighted, and 129Xe spectroscopic imaging of gas exchange. RESULTS: Nine patients were recruited (age 57 ± 14 [median ± interquartile range] years; six of nine patients were male). Patients underwent MRI at 6 (n = 9), 12 (n = 9), 25 (n = 6), and 51 (n = 8) weeks following hospital admission. Patients with signs of interstitial lung damage were excluded. At 6 weeks, patients exhibited impaired 129Xe gas transfer (RBC to membrane fraction), but lung microstructure was not increased (apparent diffusion coefficient and mean acinar airway dimensions). Minor ventilation abnormalities present in four patients were largely resolved in the 6- to 25-week period. At 12 weeks, all patients with lung perfusion data (n = 6) showed an increase in both pulmonary blood volume and flow compared with 6 weeks, although this was not statistically significant. At 12 weeks, significant improvements in 129Xe gas transfer were observed compared with 6-week examinations; however, 129Xe gas transfer remained abnormally low at weeks 12, 25, and 51. INTERPRETATION: 129Xe gas transfer was impaired up to 1 year following hospitalization in patients who were hospitalized with COVID-19 pneumonia, without evidence of architectural distortion on structural imaging, whereas lung ventilation was normal at 52 weeks.

Computational platform for doctor-artificial intelligence cooperation in pulmonary arterial hypertension prognostication: a pilot study.

Background: Pulmonary arterial hypertension (PAH) is a heterogeneous and complex pulmonary vascular disease associated with substantial morbidity. Machine-learning algorithms (used in many PAH risk calculators) can combine established parameters with thousands of circulating biomarkers to optimise PAH prognostication, but these approaches do not offer the clinician insight into what parameters drove the prognosis. The approach proposed in this study diverges from other contemporary phenotyping methods by identifying patient-specific parameters driving clinical risk. Methods: We trained a random forest algorithm to predict 4-year survival risk in a cohort of 167 adult PAH patients evaluated at Stanford University, with 20% withheld for (internal) validation. Another cohort of 38 patients from Sheffield University were used as a secondary (external) validation. Shapley values, borrowed from game theory, were computed to rank the input parameters based on their importance to the predicted risk score for the entire trained random forest model (global importance) and for an individual patient (local importance). Results: Between the internal and external validation cohorts, the random forest model predicted 4-year risk of death/transplant with sensitivity and specificity of 71.0-100% and 81.0-89.0%, respectively. The model reinforced the importance of established prognostic markers, but also identified novel inflammatory biomarkers that predict risk in some PAH patients. Conclusion: These results stress the need for advancing individualised phenotyping strategies that integrate clinical and biochemical data with outcome. The computational platform presented in this study offers a critical step towards personalised medicine in which a clinician can interpret an algorithm's assessment of an individual patient.

Transcriptional profiling unveils molecular subgroups of adaptive and maladaptive right ventricular remodeling in pulmonary hypertension.

Right ventricular (RV) function is critical to prognosis in all forms of pulmonary hypertension. Here we perform molecular phenotyping of RV remodeling by transcriptome analysis of RV tissue obtained from 40 individuals, and two animal models of RV dysfunction of both sexes. Our unsupervised clustering analysis identified 'early' and 'late' subgroups within compensated and decompensated states, characterized by the expression of distinct signaling pathways, while fatty acid metabolism and estrogen response appeared to underlie sex-specific differences in RV adaptation. The circulating levels of several extracellular matrix proteins deregulated in decompensated RV subgroups were assessed in two independent cohorts of individuals with pulmonary arterial hypertension, revealing that NID1, C1QTNF1 and CRTAC1 predicted the development of a maladaptive RV state, as defined by magnetic resonance imaging parameters, and were associated with worse clinical outcomes. Our study provides a resource for subphenotyping RV states, identifying state-specific biomarkers, and potential therapeutic targets for RV dysfunction.

Healthcare resource utilization and quality of life in patients with sarcoidosis-associated pulmonary hypertension.

A retrospective, observational cohort study was conducted to generate real-world evidence in adult patients diagnosed with sarcoidosis-associated pulmonary hypertension (SAPH) at a referral center in England between 2012 and 2019. Data from the referral center electronic medical record database were linked to the National Health Service Hospital Episode Statistics database to collect and analyze patient demographics, clinical characteristics, comorbidities, treatment patterns, health-related quality of life (HRQoL; assessed using the EmPHasis-10 questionnaire), healthcare resource utilization (HCRU), costs, and survival. Sixty-two patients with SAPH were identified. At diagnosis, 84% were in WHO functional class III and presented with significant pulmonary hemodynamic impairment. Cardiovascular and respiratory comorbidities were commonly reported prediagnosis. Median EmPHasis-10 score at diagnosis was 34, indicative of poor HRQoL. In the 1st year after diagnosis, median (Q1, Q3) per-patient HCRU was 1 (0, 2) all-cause inpatient hospitalizations; 3 (2, 4) same-day hospitalizations; and 9 (6, 11) outpatient consultations. In 24 patients who were hospitalized longer than 1 day in the 1st year after diagnosis, the median duration of hospitalization was 4 days. With a median follow-up of 1.8 years, the median overall survival was 2.9 years. In this cohort of patients with SAPH, poor HRQoL and high HCRU were observed following diagnosis. To our knowledge, this is the first study to report on HRQoL and HCRU in patients with SAPH. More research is needed on treatment options for this population with high unmet needs.

Pulmonary Vascular Research Institute GoDeep: A meta-registry merging deep phenotyping datafrom international PH reference centers.

The Pulmonary Vascular Research Institute GoDeep meta-registry is a collaboration of pulmonary hypertension (PH) reference centers across the globe. Merging worldwide PH data in a central meta-registry to allow advanced analysis of the heterogeneity of PH and its groups/subgroups on a worldwide geographical, ethnical, and etiological landscape (ClinTrial. gov NCT05329714). Retrospective and prospective PH patient data (diagnosis based on catheterization; individuals with exclusion of PH are included as a comparator group) are mapped to a common clinical parameter set of more than 350 items, anonymized and electronically exported to a central server. Use and access is decided by the GoDeep steering board, where each center has one vote. As of April 2022, GoDeep comprised 15,742 individuals with 1.9 million data points from eight PH centers. Geographic distribution comprises 3990 enrollees (25%) from America and 11,752 (75%) from Europe. Eighty-nine perecent were diagnosed with PH and 11% were classified as not PH and provided a comparator group. The retrospective observation period is an average of 3.5 years (standard error of the mean 0.04), with 1159 PH patients followed for over 10 years. Pulmonary arterial hypertension represents the largest PH group (42.6%), followed by Group 2 (21.7%), Group 3 (17.3%), Group 4 (15.2%), and Group 5 (3.3%). The age distribution spans several decades, with patients 60 years or older comprising 60%. The majority of patients met an intermediate risk profile upon diagnosis. Data entry from a further six centers is ongoing, and negotiations with >10 centers worldwide have commenced. Using electronic interface-based automated retrospective and prospective data transfer, GoDeep aims to provide in-depth epidemiological and etiological understanding of PH and its various groups/subgroups on a global scale, offering insights for improved management.