Gulf War illness: an overview of events, most prevalent health outcomes, exposures, and clues as to pathogenesis
Bibliographic record
Abstract
INTRODUCTION: During or very soon after the 1990-1991 Persian Gulf War, veterans of the conflict began to report symptoms of illness. Common complaints included combinations of cognitive difficulties, fatigue, myalgia, rashes, dyspnea, insomnia, gastrointestinal symptoms and sensitivity to odors. Gradually in the USA, and later in the UK, France, Canada, Denmark and Australia, governments implemented medical assessment programs and epidemiologic studies to determine the scope of what was popularly referred to as "the Gulf War syndrome". Attention was drawn to numerous potentially toxic deployment-related exposures that appeared to vary by country of deployment, by location within the theater, by unit, and by personal job types. Identifying a single toxicant cause was considered unlikely and it was recognized that outcomes were influenced by genetic variability in xenobiotic metabolism. METHODS: Derived from primary papers and key reports by the Research Advisory Committee on Gulf War Veterans' Illnesses and the Institute of Medicine, a brief overview is presented of war related events, symptoms and diagnostic criteria for Gulf War illness (GWV), some international differences, the various war-related exposures and key epidemiologic studies. Possible exposure interactions and pathophysiologic mechanisms are discussed. RESULTS: Exposures to pyridostigmine bromide, pesticides, sarin and mustard gas or combinations thereof were most associated with GWI, especially in some genotype subgroups. The resultant oxidant stress and background exposome must be assumed to have played a role. CONCLUSION: Gulf War (GW) exposures and their potential toxic effects should be considered in the context of the human genome, the human exposome and resultant oxidant stress to better characterize this unique environmentally-linked illness and, ultimately, provide a rationale for more effective interventions and future prevention efforts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".