Sudden-Onset Widespread Body Pain (Fibromyalgia) with or without an Inciting Event: A Case Series
Bibliographic record
Abstract
Background: The presence of sudden-onset fibromyalgia (FM) is poorly understood, characterized, and appreciated in both previous literature and the clinical setting. In this case series, we present 10 cases of sudden-onset FM seen in a community-based pain clinic, to characterize the presentation of this condition, stemming from both external trauma and idiopathic etiology. Methods: This retrospective case series identified 10 patients diagnosed with FM attending the pain clinic. These patients were referred to chronic pain management clinic in Thunder Bay, Ontario, Canada, from January 2019 until December 2021 and met the diagnostic criteria for FM. Information was collected on sex, gender, age, details of signs and symptoms, and FM severity score as well as clinical findings and outcomes. Results: The case series identified 10 community residents (9 women and 1 man, F/M: 9/1, age range: 34-64 years, mean age: 51.7 years), with symptoms attributed to FM. Majority of patients suffered from total body pain and mental disorders such as depression. 60% of patients were on opioids at the time of referral. Combination of pharmacological and non-pharmacological management improved their pain symptoms within 3-6 months on follow-up. Conclusion: Overall, effectively identifying sudden-onset FM can help clinicians improve patient-oriented outcomes and avoid the use of unnecessary narcotics in addition to better treating their patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".