Pulmonary hypertension associated with sickle cell disease
Bibliographic record
Abstract
PH is recognised as a major chronic complication of sickle cell disease (SCD), significantly impacting both morbidity and mortality. It encompasses a broad spectrum of haemodynamic profiles, including high cardiac output-associated PH, postcapillary PH, and precapillary PH, the latter characterised by elevated PVR due to pulmonary vasculopathy. This vasculopathy results from pulmonary vascular remodelling and/or thrombotic phenomena, driven by complex pathophysiologic processes such as increased blood viscosity and chronic haemolysis-induced endothelial dysfunction. Accurate haemodynamic classification via RHC is essential to guide appropriate therapeutic decisions, as clinical and echocardiographic findings are often nonspecific and overlapping. Management should be multidisciplinary and tailored to the specific PH phenotype, beginning with optimisation of SCD-specific care and complemented by general supportive measures. In the absence of robust clinical trial data, the role of targeted PAH therapies remains uncertain in this context. Furthermore, clinicians must recognise the higher prevalence of CTEPH in SCD patients, which necessitates specific diagnostic and therapeutic approaches. Ongoing research is urgently needed to define effective, evidence-based therapies that may improve outcomes in this high-risk population. Cite as: Savale L, Budhram B. Pulmonary hypertension associated with sickle cell disease. In: Boucly A, Kovacs G, Condliffe R, eds. Pulmonary Hypertension (ERS Monograph). Sheffield, European Respiratory Society, 2025; pp. 356–368 [ https://doi.org/10.1183/2312508X.10021224 ].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".