Social Impact of Peripheral Nerve Injuries
Bibliographic record
Abstract
BACKGROUND: Disorders involving the peripheral nervous system can have devastating impacts on patients' daily functions and routines. There is a lack of consideration of the impact of injury on social/emotional well-being and function. METHODS: We performed a retrospective database and chart review of adult patients presenting between 2010 and 2012 with peripheral nerve compression, brachial plexus injury, thoracic outlet syndrome (TOS), or neuromas. At the initial assessment, patients completed a questionnaire used to obtain demographic and psychosocial variable data including the (1) average level of pain over the last month, (2) self-perceived depression, (3) how much pain impacts quality of life (QoL), (4) current level of stress, and (5) ability to cope with stress. Statistical analyses were used to assess the differences between the dependent variables and diagnostic and demographic groups. RESULTS: This study included 490 patients (mean age 50 ± 15 years); the most common diagnosis was single nerve compression (n = 171). Impact on QoL was significantly greater in patients with TOS, cutaneous peroneal compressions, and neuroma versus single site nerve compressions. Average pain, impact on QoL, and stress at home were significantly higher in females versus males. Impact on QoL was correlated with average pain, depression, stress at home, and ability to cope with stress at home. CONCLUSIONS: Our study demonstrates that patients with single site nerve compression neuropathies experience fewer negative psychosocial effects compared to patients with more proximal upper extremity peripheral nerve disorders and neuromas. The impact on QoL was strongly correlated with pain and depression, where patients with neuromas and painful peroneal nerve entrapments reported greater detriments to QoL.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".