Extracorporeal membrane oxygenation (ECMO) during aplasia: A bridge towards myopericarditis recovery after autologous hematopoietic stem cell transplant for systemic sclerosis and recent Coronarovirus disease (COVID-19) vaccination
Bibliographic record
Abstract
Systemic sclerosis (SSc) is a rare autoimmune disease (AD), characterised by early diffuse vasculopathy, activation of the immune response and progressive skin and internal organ fibrosis. In severe progressive diffuse SSc (dSSc), autologous hematopoietic stem cell transplantation (aHSCT) improves survival, despite its own risk of complications and transplant related mortality (TRM). We present herein the case of a dSSc patient undergoing aHSCT with low dose cyclophosphamide conditioning and sudden acute myopericarditis and cardiogenic shock, four weeks after a second mRNA SARS-CoV-2 vaccine (Pfizer) injection. Four days of extracorporeal membrane oxygenation (ECMO) support during the aplasia period, allowed to observe full cardiac function recovery and progressive SSc rehabilitation with sustained disease response at 30 months follow-up. This report illustrates, for the first time to our knowledge, that ECMO can be indicated despite aplasia during aHSCT and successfully used as a bridge towards heart function recovery in highly selected and fragile AD patients. We review the factors that may contribute to endothelial and myocardial stunning and acute reversible cardiac failure in SSc and aggravate intrinsic endothelial injury during the aHSCT procedure. These classically include: cyclophosphamide drug toxicity, viral infections and autoimmune activation with disease flair per se. In the COVID-19 pandemic times, acute myocarditis due to recent viral infection or mRNA vaccine per se, must also be considered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".