Pain-Related Factors and Their Impact on Quality of Life in Chinese Patients With Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Objectives: Pain is considered a common symptom in amyotrophic lateral sclerosis (ALS). However, the results of studies on pain in ALS are limited and inconsistent. The aim of our study was to comprehensively evaluate the potential factors of pain and effects on quality of life (QoL) in patients with ALS from China. Participants and Methods: Patients were eligible if they fulfilled the criteria of probable and definitive ALS according to the revised El Escorial criteria. Pain was assessed by the Brief Pain Inventory (BPI). Disease severity, sleep quality, fatigue, anxiety, depression, and quality of life (QoL) were evaluated in ALS patients by the ALS Functional Rating Scale-revised (ALSFRS-R) and ALS severity scale (ALSSS), Pittsburgh Sleep Quality Index (PSQI), Fatigue Severity Scale (FSS), Hamilton Anxiety Rating Scale (HARS), Hamilton Depression Rating Scale (HDRS) and McGill Quality of Life Questionnaire (MQOL). Then, the clinical characteristics of ALS patients with pain were compared with those without pain. Last, associated factors of pain, as well as impact on QoL in Chinese ALS patients, were assessed. Results: A total of 86 ALS patients were included. ALS patients with pain tended to have higher FSS scores and poorer QoL. The FSS score and ALSSS [lower extremity (LE) + upper extremity (UE)] were associated with pain in ALS patients. The ALS Functional Rating Scale-revised (ALSFRS-R), Pain Severity Index (PSI), HARS and HDRS scores were significantly associated with both the physical and psychological domains of QoL. Conclusion: Our study was the first to comprehensively evaluate factors associated with pain in Chinese ALS patients, finding that fatigue can be a risk factor for pain and ALSSS (LE + UE) score was related with pain intensity. Additionally, we identified the adverse effects of ALSSS (LE + UE), HARS and HDRS scores on QoL in Chinese ALS patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".