Exploring the role of viscosity–vaso‐occlusion and haemolysis–endothelial dysfunction in pain sensitization among Jamaicans with sickle cell disease
Bibliographic record
Abstract
Viscosity-vaso-occlusion (VVO) and haemolysis-endothelial dysfunction (HED) are pathophysiological mechanisms and clinical subphenotypes of sickle cell disease (SCD). Recurrent vaso-occlusive crises (VOC) may lead to neuroplastic changes and pain sensitization. Among 257 SCD participants, we assessed the relationship of subphenotypes with pain sensitivity using quantitative sensory testing to identify heat pain thresholds (HPT) and pressure pain thresholds (PPT). VOC history and sleep, social and emotional functioning were assessed using the Adult Sickle Cell Quality of Life Measurement Information System. The 'elbow method' determined the optimal number of clusters as three. Clustering was performed using K-prototypes. Among clusters 2 and 3, VOC frequency and severity were higher. Clusters 1 and 3 had lower haemoglobin, higher reticulocytes and lactate dehydrogenase and more leg ulcers. In multivariate regression, cluster 3 was associated with approximately 13.6% lower PPT compared to cluster 1, and female sex was associated with decreases in PPT and HPT at the hands and feet (p < 0.001). Hydroxyurea use and unit increases in sleep functioning and age were associated with approximately 20.1% higher foot-PPT, 6.8% higher hand-PPT and 2.5% higher hand-HPT and foot-HPT respectively. Findings suggest that a third subphenotype with mixed VVO and HED features and worse pain sensitization may exist.
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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 | 0.001 |
| 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 | 0.000 |
| 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".