Deciphering Pain Experience in Adult Patients With Sickle Cell Disease: A Network Analysis of Pain‐Related Factors in a Single French Sickle Cell Centre
Bibliographic record
Abstract
BACKGROUND: Sickle cell disease (SCD) is the most prevalent inherited haemoglobinopathy characterised by chronic pain with acute painful episodes due to vaso-occlusion. The effective management of pain by adults with SCD influences their health outcomes. Opioids remain essential for most pain syndromes, but non-pharmacological interventions are preferred for daily pain due to the risk of addiction. However, their effectiveness is variable. Understanding the underlying processes associated with pain is crucial for developing more effective non-pharmacological strategies. This study aimed to enhance comprehension of the pain mechanisms in SCD to identify potential areas of action for effective non-pharmacological interventions. METHOD: An evaluation was conducted on the severity and interference of pain, pain-related cognitions and emotions. We used network analysis to simultaneously examine the intricate relationships between these variables. RESULTS: A pain intensity exceeding 4 at a steady state distinguishes a subgroup at elevated risk of negative pain-related emotions and cognitions. The network analysis revealed intricate interconnections, with three distinct subgroups of variables mimicking the Neuromatrix model (cognitive-evaluative, motivational-affective and sensory-discriminative subgroups). The derived directed acyclic graph suggests potential mechanisms between these three subgroups, with catastrophising having a pivotal role. CONCLUSION: This study extends previous research by providing a comprehensive network analysis of pain-related variables in SCD, offering novel insights into the complex interplay between pain experience, cognitions and emotions. These findings have important clinical implications, as they suggest that targeting dysfunctional pain cognitions and/or negative emotions may be beneficial for improving pain management and quality of life in SCD. SIGNIFICANCE STATEMENT: This study was the first to use network analyses to understand simultaneously multiple relationships between variables referring to pain, and pain-related negative emotions and cognitions in adults with SCD. Findings, providing support to the Neuromatrix model, offer novel insight to better understand pain and the associated negative emotions and cognition in SCD. The derived directed acyclic graph explored potential underlying psychological processes associated with pain that could be specifically targeted by future effective psychological interventions.
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 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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 teacher head, 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".