CENTRAL SENSITIZATION AND MEDICATION IN SPINAL CORD INJURED IN-PATIENTS. A CROSS-SECTIONAL CLINICAL STUDY
Bibliographic record
Abstract
Background and aims: A major proportion of spinal cord injured subjects (SCIS) suffers from chronic pain. A majority with neuropathic pain, being: shooting, burning and stabbing. Neurological examination reveals signs of central sensitization (CS) e.g. allodynia and hyperalgesia. CS plays an important role in maintained neuropathic pain conditions and may lead to or be induced by analgesics. Medication-overuse-headaches (MOH) alter CNS pain processing systems, and the situation is reversed after discontinuation of headache medication. Aim: To determine the occurrence of CS and conditions similar to MOH in: a) sub-acute traumatic, b) chronic traumatic, c) non-traumatic patients with SCI compared with a healthy control group. The study is on-going. Methods: In this cross-sectional study of in-patients and age- and gender-matched healthy non-medicated controls, CS will be examined using pressure algometry, Von Frey filaments and pinprick test. Patients fulfill McGill Pain Questionnaire and the International SCI pain data-set. All participants undergo examination of the Pressure Pain Detection Threshold, Pressure Pain Tolerance Threshold, Mechanical Detection Threshold, and Wind-up. Furthermore, medication, day equivalent dose of analgesic, anti-spasmodic and anti-epileptic, will be determined. Preliminary results: 15 patients (planned 24) and 5 controls gave informed consent and were included and examined in the study. When the remaining patients and controls have been identified and examined the results will be analyzed using statistical approaches compatible with the cross sectional study design. Conclusions: The CS examination method is feasible in SCI-inpatients, at highly-specialized SCI hospital, the clinical examinations will be finalized in March and data presented at the meeting.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".