Risk Factors for Suicidal Ideation among Patients with Complex Regional Pain Syndrome
Bibliographic record
Abstract
OBJECTIVE: Chronic pain frequently coexists with psychiatric symptoms in patients diagnosed with complex regional pain syndrome (CRPS). Previous studies have shown a relationship between CRPS and the risk of suicide. The purpose of this study was to assess risk factors for suicidal ideation in patients with CRPS. METHODS: Based on criteria established by the International Association for the Study of Pain, 39 patients diagnosed with CRPS Type 1 or Type 2 were enrolled in this study. Suicidal ideation was assessed using item 3 of the Hamilton Depression Rating Scale (HAMD), and symptoms of pain were evaluated using the short form of the McGill Pain Questionnaire (SF-MPQ). Psychiatric symptoms were assessed in using the Structured Clinical Interview for DSM-IV Disorders (SCID-I, SCID-II), the HAMD, the Hamilton Anxiety Rating Scale (HAMA), the Global Assessment of Functioning Scale (GAF), and the Pittsburgh Sleep Quality Index (PSQI). RESULTS: Twenty-nine patients (74.4%) were at high risk and 10 (25.6%) were at low risk for suicidal ideation. Risk factors significantly associated with suicidal ideation included depression (p=0.002), severity of pain (p=0.024), and low scores on the GAF (p=0.027). No significant correlations were found between suicidal ideation and anxiety or quality of sleep. CONCLUSION: Significant risk factors for suicidal ideation in patients with CRPS include severity of pain, depressive symptoms, and decreased functioning. These results suggest that psychiatric evaluation and intervention should be included in the treatment of CRPS.
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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 | 0.002 |
| 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) | 0.002 | 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".