Sensitivity of the DN4 in Screening for Neuropathic Pain Syndromes
Bibliographic record
Abstract
OBJECTIVES: Several tools have been developed to screen for neuropathic pain. This study examined the sensitivity of the Douleur Neuropathique en 4 Questions (DN4) in screening for various neuropathic pain syndromes. MATERIALS AND METHODS: This prospective observational study was conducted in 7 Canadian academic pain centers between April 2008 and December 2011. All newly admitted patients (n=2199) were approached and 789 eligible participants form the sample for this analysis. Baseline data included demographics, disability, health-related quality of life, and pain characteristics. Diagnosis of probable or definite neuropathic pain was on the basis of history, neurological examination, and ancillary diagnostic tests. RESULTS: The mean age of study participants was 53.5 years and 54.7% were female; 83% (n=652/789) screened positive on the DN4 (≥4/10). The sensitivity was highest for central neuropathic pain (92.5%, n=74/80) and generalized polyneuropathies (92.1%, n=139/151), and lowest for trigeminal neuralgia (69.2%, n=36/52). After controlling for confounders, the sensitivity of the DN4 remained significantly higher for individuals with generalized polyneuropathies (odds ratio [OR]=4.35; 95% confidence interval [CI]: 2.15, 8.81), central neuropathic pain (OR=3.76; 95% CI: 1.56, 9.07), and multifocal polyneuropathies (OR=1.72; 95% CI: 1.03, 2.85) compared with focal neuropathies. DISCUSSION: The DN4 performed well; however, sensitivity varied by syndrome and the lowest sensitivity was found for trigeminal neuralgia. A positive DN4 was associated with greater pain catastrophizing, disability and anxiety/depression, which may be because of disease severity, and/or these scales may reflect magnification of sensory symptoms and findings. Future research should examine how the DN4 could be refined to improve its sensitivity for specific neuropathic pain conditions.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".