Occupational risk for <i>Legionella</i> infection among dental healthcare workers: meta-analysis in occupational epidemiology
Bibliographic record
Abstract
Objective The occupational risk for Legionella infection among dental healthcare workers (DHCWs) is conjectured because of the risk of routine inhalation of potentially contaminated aerosols produced by the dental instruments. Nevertheless, occupational epidemiology studies are contrasting. This meta-analysis assessed the level of scientific evidence regarding the relative occupational risk for Legionella infection among DHCWs. Methods Literature search was performed without time and language restrictions, using broad data banks (PubMed, Scopus, Web of Science, GOOGLE Scholar) and generic keywords (‘legionella’ AND ‘dent*’). Analytical cross-sectional studies comparing prevalence of high serum Legionella antibody levels in DHCWs and occupationally unexposed individuals were considered. The relative occupational risk was assessed through prevalence ratio (PR) with 95% CI. Between-study heterogeneity was assessed (Cochran’s Q test) and was used to choose the meta-analytic method. Study quality (modified Newcastle-Ottawa Scale) and publication bias (Begg and Mazumdar’s test, Egger and colleagues’ test, trim and fill R 0 method) were assessed formally and considered for the sensitivity analysis. Sensitivity analysis to study inclusion, subgroup analyses (dental staff categories; publication year, before vs after 1998, ie, 5 years after the release by the Centers for Disease Control and Prevention of the infection control guidelines in dental healthcare setting) were performed. Results Seven studies were included (2232 DHCWs, 1172 occupationally unexposed individuals). No evidence of publication bias was detected. The pooled PR estimate was statistically non-significant at 95% level (1.7; 95% CI 0.8 to 3.2), study-quality adjustment did not change the PR considerably (PR, 1.5; 95% CI 0.5 to 4.1). PR was statistically significant before 1998 and no longer significant after 1998. Subgroup analysis according to DHCW categories was inconclusive. Conclusions There is no scientific evidence that DHCWs are at high occupational risk. The differences between former and recent studies could be due to different characteristics of municipal water systems and the infection control guideline dissemination.
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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 | 0.030 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.082 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".