Evaluation of a Clinical Protocol to Assess and Diagnose Neuropathic Pain During Acute Hospital Admission
Bibliographic record
Abstract
OBJECTIVES: A clinical protocol was developed for clinicians to routinely assess and initiate treatment for patients with neuropathic pain (NP) in an acute care setting. The objectives of this study were to: (1) determine the incidence and onset of NP in patients with traumatic spinal cord injury during acute care and (2) describe how the implementation of a clinical protocol impacts the assessment and diagnosis of NP. MATERIALS AND METHODS: The study was a cohort analysis with a pre-post-test utilizing a historical control. Data were retrospectively collected from a patient registry and charts. Participants were randomly selected in cohort 1 (control) and cohort 2 (NP clinical protocol). RESULTS: The incidence of NP was 56% without significant difference between the cohorts (P=0.3). Onset of NP was 8 days (SD=14) across the study and >85% of the participants with NP were diagnosed within 2 weeks. Participants with incomplete injuries had a significant earlier onset than participants with complete injuries (6.2±12.8, 10.9±15.8 d; P=0.003). The mean number of days from hospital admission to initial assessment decreased with use of the NP clinical protocol (3.7±5.7 d; P=0.02). DISCUSSION: This study demonstrates a high incidence and early onset of NP in traumatic spinal cord injury during acute hospital care, with an earlier emergence in participants with incomplete injury. The NP clinical protocol ensured continuous assessment and documentation of NP while decreasing the time to an initial screen, but did not impact diagnosis.
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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 | 0.154 | 0.142 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".