Impact of Low-Level Blast Exposure From Military Training and Career Cumulation on Hearing Outcomes
Bibliographic record
Abstract
INTRODUCTION: Occupational trades expose military service members to unique sound exposure profiles, distinct in frequency and amplitude to those commonly studied in industrial settings. Characteristics of the energy exposure incurred through blast exposure exercises a distinct mechanism of injury in the auditory system that yield acute and cumulative health impacts. The following paper considers physiological and self-reported data attributed to repeated low-level blast exposure. We focused our analysis to examine objective audiological metrics of blast overpressure damage to quantify the impact of discrete and accumulated blast exposure for military service members. MATERIALS AND METHODS: This study was reviewed and approved by the Human Research Ethics Committee of Defense Research and Development Canada. Data were collected in a cross-sectional, repeated measures observational design. Participants comprised service members who took part in a training course using controlled explosives (n = 46) and an age- and sex-matched control group (n = 42) with noise exposure but no history of blast exposure. Extensive demographic and subjective health data were captured additional to a battery of quantitative health data. Nonlinear mixed effect models with bivariate generalized additive architecture, Friedman's test, and repeated measures ANOVA models were applied. RESULTS: Subjective tinnitus and hearing scores were sensitive to life-time blast overpressure exposure (P = .034) and a delta of low- (2-4 kHz) and high-frequency (4-8 kHz) audiometric threshold averages significantly differentiated by both cumulative (P = .0016) and training course exposure (P = .0142). Furthermore, audiometric values showed progressive increasing variance in high frequencies (>4 kHz) in blast-exposed participants with worsening audiometric outcomes. Variation in high-frequency hearing thresholds may be attributed to differences in energy exposure because of structural differences between individuals or differences in exposure profiles (produced either by diversity in PPE compliance or exposure sources). CONCLUSION: Military members exposed to blasts in a training environment and accumulated through a career experience adverse hearing and audiometric impacts. However, better measures of hearing injury should be pursued to improve understanding of injury mechanism and injury progression which may inform risk and medical interventions. Blast-induced hearing injuries are dynamic and change over time between acute and chronic phases which are further exacerbated with multiple blast exposures presented consecutively.
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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 | 0.000 |
| 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".