Precision medicine and personalising therapy in pulmonary hypertension: seeing the light from the dawn of a new era
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pulmonary hypertension (PH) and pulmonary arterial hypertension (PAH) include different cardiopulmonary disorders in which the interaction of multiple genes with environmental and behavioural factors modulates the onset and the progression of these severe conditions. Although the development of therapeutic agents that modulate abnormalities in three major pathobiological pathways for PAH has revolutionised our approach to the treatment of PAH, the long-term survival rate remains unsatisfactory. Accumulating evidence has underlined that clinical outcomes and responses to therapy in PAH are modified by multiple factors, including genetic variations, which will be different for each individual. Since precision medicine, also known as stratified medicine or personalised medicine, aims to better target intervention to the individual while maximising benefit and minimising harm, it has significant potential advantages. This article aims to assemble and discuss the different initiatives that are currently underway in the PH/PAH fields together with the opportunities and prospects for their use in the near future.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it