Evaluation of the pain in COVID-19 patients with musculoskeletal pain: A cross-sectional study
Bibliographic record
Abstract
Aim: There is no study that have assessed face-to-face using the multidimensional pain scale in COVID-19 patients with musculoskeletal pain. This study aimed to reveal the pain region, character and severity in COVID-19 patients with musculoskeletal pain. Material and Methods: This cross-sectional study was carried out in 214 patients who had a positive result of the polymerase chain reaction test within the last five days and at least one musculoskeletal pain symptom, such as fatigue, myalgia, and arthralgia/polyarthralgia. The cases were divided into groups as clinically severe and non-severe. Evaluations were made on the first day of admission. Myalgia symptoms were classified as diffuse and local. The McGill Pain Questionnaire was used for pain regions and caharacters while the Visual Analog Scale (VAS) was for pain intensity. Results: The frequency of involvement was myalgia (96.3%), fatigue (77.6%) and polyarthralgia (62.6%), respectively. The diffuse myalgia was (53.3%) in all patients. The mean myalgia VAS score in the non-severe group was 5.881.83 and 6.251.24 in the severe group (p=0.192). The most common pain areas were the back, feet, and knees respectively, and throbbing (40.7%), aching (30.8%), and pricking (26.1%) were the most common characteristics. The suffocating character of the pain was significantly higher in the severe group (p<0.05). Discussion: Defining disease-specific pain regions, character and severity in COVID-19 patients with musculoskeletal pain is important in managing possible chronic pain.
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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 | 0.054 | 0.040 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".