Lifestyle factors in patients with chronic neuropathic pain after COVID-19: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Lifestyle after a social restriction caused by the COVID-19 pandemic pointed to influence on chronic pain scenarios. The aim of this study was to identify lifestyle factors related to patients with chronic neuropathic pain after COVID-19 infection. METHODS: This is a cross-sectional observational analytical study with 62 patients diagnosed with chronic neuropathic pain and belonging to a Pain Clinic, where a form with sociodemo-graphic data was applied and they were evaluated using the Neuropathic Symptoms and Signs Pain Scale (S-LANSS) and the Fantastic Lifestyle Questionnaire (FLQ), respectively, which provides a wide range of information regarding lifestyle behaviors. RESULTS: The sample was composed of 62 participants, mean age 56.2±12.9 years, predominance of women (60%), married people (64%) and with children (80%). S-LANSS revealed 48 patients (77%) with neuropathic mechanisms on sensitivity examination, 80%(n=50) reported allodynia only in the painful area. Almost 80% of patients had regular lifestyle (n=48), with the activity and nutrition components being self-perceived negatively. CONCLUSION: In the present study, patients with chronic neuropathic pain showed that the level of activity and the presence of alcohol compromised their lifestyle. These components are aspects of these patients lifestyle that must be understood and validated in order to think of countering strategies that can influence new forms of approach and organization of services. HIGHLIGHTS The lifestyle of chronic pain patients was altered post-COVID.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".