COVID-19 in pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension: a reference centre survey
Bibliographic record
Abstract
According to the US Centers for Disease Control and Prevention (CDC), patients with underlying health conditions, including all types of lung and cardiovascular diseases, have an increased risk of developing serious disease when infected by SARS-CoV-2 [1]. Based on prior publications on the effects of acute right heart failure superimposed on systemic infection [2–5], Ryan et al. [6] suggested that right heart failure and concomitant COVID-19 infection may result in increased mortality in pulmonary arterial hypertension (PAH) patients. Surprisingly, the number of hospitalised PAH-COVID-19 patients remained rather low in Italy and the USA so far [7]. In late March 2020, experts from over 32 US PH expert centres answered a query endorsed by the US Pulmonary Hypertension Association. COVID-19 infection was reported in 13 PAH patients, among whom three required intubation and one died. This is consequently raising the question whether and why PAH patients appear to be at lower risk of developing severe COVID-19 [7]. This international survey highlights that a limited number of PAH and CTEPH patients suffered from severe #COVID19 infection This survey is a common initiative of European Respiratory Society (ERS) Assembly 13 on Pulmonary Vascular Diseases, ERS Clinical Research Collaboration PHAROS and European Reference Network for Rare Lung Diseases (ERN-lung), and is endorsed by patient association PHA Europe. We thank Valerija Arsovski from the ERS office in Lausanne (Switzerland) for logistic support and the survey participants: Yochai Adir (Carmel Medical Center, Haifa, Israel), Joan Barbera (Hospital Clínic, Barcelona, Spain), Roberto J. Bernardo (Stanford University, CA, USA), Laurent Bertoletti (University Hospital, Saint-Etienne, France), Aleksandar Bokan (Institute for pulmonary diseases of Vojvodina, Sremska Kamenica, Serbia), Karin Boomars (Erasmus Medical Center, Rotterdam, The Netherlands), Jørn Carlsen (Rigshospitalet, University of Copenhagen, Copenhagen, Denmark), Michele D'Alto (Monaldi Hospital, University “L. Vanvitelli”, Naples, Italy), Anna Doboszynska (Pulmonary Department, Warmia-Mazury University, Olsztyn, Poland), Aleksandra Furdyna (Department of Internal Medicine, Medical University of Warsaw, Warshaw, Poland), Sean Gaine (Mater Dublin, Dublin, Ireland), Henning Gall (Lung Center, University of Giessen, Giessen, Germany), Pitsiou Georgai (Aristotle University Thessaloniki, G.H.G.Papanikolaou, Thessaloniki, Greece), Pavel Jansa (General University Hospital, Prague, Czech Republic), Wojciech Jacheć (Department of Cardiology Zabrze, Medical University of Silesia, Katowice, Poland), Carlos Jardim (Heart Institute, University of Sao Paulo, Sao Paulo, Brazil), Elena Jurevičienė (University Hospital Santaros Klinikos, Vilnius, Lithuania), Dominic Keating (Alfred Hospital, Melbourne, Australia), Derya Kocakaya (Marmara University Hospital, Istambul, Turkey), Lisa Kohlbacher (Medical University, Vienna, Austria), Yaroslav Kondratsky (Regional Clinical Hospital, Lviv, Ukraine), Beata Kusmierczyk (National Institute of Cardiology, Warsaw, Poland), Irene Lang (Medical University, Vienna, Austria), Tobias Lange (University Medical Center, Regensburg, Germany), Skaidrius Miliauskas (Hospital of Lithuanian university of health sciences, Kaunas, Lithuania), Karen Olsson (Medical School, Hannover, Germany), Gul Öngen (Cerrahpaşa Medical Faculty, Istambul, Turkey), Caneva Jorge Osvaldo (Fundacion Favaloro, Buenos Aires, Argentina), Małgorzata Peregud-Pogorzelska (Department of Cardiology, Pomeranian Medical University, Szczecin, Poland), Georgai Pitsiou (Aristotle University Thessaloniki, G.H.G.Papanikolaou, Thessaloniki, Greece), Rui Plácido (Academic Medical Centre, Lisbon, Portugal), Tomas Pulido (National Heart Institute, Mexico City, Mexico), Farid Rashidi (University of Medical Sciences, Tabriz, Iran), Abilio Reis (Centro Hospitalar Universitário, Porto, Portugal), Olivier Sitbon (Kremlin-Bicêtre Hospital, Paris, France), Jesús Ribas Sola (Hospital Universitari de Bellvitge, Barcelona, Spain), John Ryan (University of Utah, Salt Lake City, UT, USA), Sandeep Sahay (Houston Methodist Hospital, Houston, TX, USA), Silvia Ulrich (University Hospitals, Zurich, Switzerland), Jolanda van Haren-Willems (Radboud University Medical Centre, Nijmegen, The Netherla,ds), Alexander Volkov (Institute of Rheumatology, Moscow, Russian Federation), Anton Vonk Noordegraaf (University Medical Center Amsterdam, The Netherlands), Jason Weatherald (University of Calgary, Calgary, Canada), Helen Whitford (The Alfred Hospital, Melbourne, Australia) and Katarzyna Widejko (Copper Medical Centre, Legnica, Poland), for having kindly answered the survey.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".