Are Inflammatory Markers an Indicator of Exposure or Effect in Firefighters Fighting a Devastating Wildfire? Follow-up of a Cohort in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVES: The Fort McMurray fire in Alberta, Canada, devastated the townsite in May 2016. First responders were heavily exposed to smoke particles. Blood samples taken from firefighters in May and August/September 2016 were used to measure concentrations of inflammatory markers in plasma and the relation of these markers to exposures and respiratory ill-health. METHODS: Blood samples were drawn from firefighters from two fire services, who also completed questionnaires about tasks and exposures during their deployment to the fire and about respiratory symptoms. Plasma was analysed for 42 inflammatory markers in a multiplex assay. At Service A, samples were collected twice, within 19 days of the start of the fire (early sample) and again 14-18 weeks later (late sample). At Service B, only late samples were collected, at 16-20 weeks. Principal component (PC) scores were extracted from markers in plasma from the early and late samples and, at both time periods, the first two components retained. PC scores were examined against estimated cumulative exposures to PM2.5 particles, self-rated physical stressors during the fire, and time since the last deployment to an active fire. The relation of component scores and exposure estimates to respiratory health were examined, using self-ratings at the time of the blood draw, a validated respiratory screening questionnaire (the European Community Respiratory Health Survey [ECRHS]) some 30 months after the fire, and clinical assessments in 2019-2020. RESULTS: Repeat blood samples were available for 68 non-smoking first responders from Service A and late samples from 160 non-smokers from both services. In the 68 with two samples, marker concentrations decreased from early to late samples for all but 3 of the 42 markers, significantly so (P < 0.05) for 25. The first component extracted from the early samples (C1E) was unrelated to respiratory symptoms but the second (C2E) was weakly related to increased cough (P = 0.079) and breathlessness (P = 0.068) and a lower forced expiratory volume in one second/forced expiratory capacity (FEV1/FVC)(β = -1.63, 95% CI -3.11 to -0.14) P = 0.032. The first PC at 14-20 weeks (C1L) was unrelated to exposure or respiratory health but the second PC (C2L) from these late samples, drawn from both fire services, related to cumulative PM2.5 exposure. In a multivariate model, clustered within fire service, cumulative exposure (β = 0.19, 95% CI 0.09-0.30), dehydration (β = 0.65, 95% CI 0.04-1.27) and time since last deployed to a fire (β = -0.04, 95% CI -0.06 to -0.01) were all related to the C2L score. This score was also associated with respiratory symptoms of wheezing, chest tightness, and breathlessness at the time of the blood draw but not to symptoms at later follow-up. However, apart from the lower FEV1/FVC at 15-19 days, the marker scores did not add to regression models that also included estimated cumulative PM2.5 exposure. CONCLUSIONS: Concentrations of persisting inflammatory markers in the plasma of firefighters deployed to a devastating fire decreased with time and were related to estimates of exposure. Although not a powerful independent predictor of later respiratory ill-health, they may serve as an indicator of previous high exposure in the absence of contemporary exposure estimates.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".