Pain Prevalence in Multiple Sclerosis in a Lisbon Tertiary Hospital: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis is a chronic neurological disease with increasing incidence and prevalence worldwide being the main cause of non-traumatic disability in young adults. Both acute and chronic pain have been mentioned as the most common symptoms among those patients. OBJECTIVE: This study was designed to evaluate the pain experience among patients with multiple sclerosis by describing its prevalence, characteristics, analgesic treatment and its efficacy, and also the impact of pain on quality of life. METHODS: A cross-sectional observation survey was carried out on patients with multiple sclerosis followed in a tertiary hospital. Data were collected between December 2019 and March 2021 from a structured telephone inquiry, applying two questionnaires, the Brief Pain Inventory and the McGill Pain Questionnaire (MPQ), to evaluate the prevalence of pain and its impact on quality of life (QoL). Clinical records were also consulted to obtain data on disease duration, year of diagnosis, MS type, Expanded Disability Status Scale (EDSS) score. RESULTS: Our sample included 305 patients in a universe of 1500, mainly women, with mean age of 44.27 years, and most of them presented with an outbreak-remission subtype of disease. One hundred twenty-four patients experienced pain which corresponds to 41% of the patients. Considering the patients who experienced pain, 67.7% were under treatment and of these, 64.3% with only one painkiller. Pain significantly interfered with general activity, mood, and regular work. CONCLUSION: Pain was an important symptom in this group of patients with MS and significantly interfered with mood, general activity, and regular work. The maximum intensity of pain felt by patients was significant and only 67.7% of patients were under analgesic treatment with mean pain relief of 54. NSAIDs were the most used drugs followed by gabapentinoids and acetaminophen for the management of pain. Medical community must continue to study this population in order to improve the approach to pain in these patients and improve quality of life.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".