Prevalence and risk factors for latent tuberculosis infection among healthcare workers in Morocco
Bibliographic record
Abstract
Increased prevalence of latent tuberculosis infection (LTBI) has been observed among high-risk populations such as healthcare workers (HCWs). The results may depend on the method of LTBI assessment, interferon-gamma release assay (IGRA) and/or tuberculin skin test (TST). Here, we investigated the prevalence and risk factors for LTBI assessed by both IGRAs and TST in HCWs living in Morocco, a country with intermediate tuberculosis (TB) endemicity and high BCG vaccination coverage. HCWs were recruited in two Moroccan hospitals, Rabat and Meknes. All the participants underwent testing for LTBI by both IGRA (QuantiFERON-TB Gold In-Tube, QFT-GIT) and TST. Different combinations of IGRA and TST results defined the LTBI status. Risk factors associated with LTBI were investigated using a mixed-effect logistic regression model. The prevalence of LTBI among 631 HCWs (age range 18-60 years) varied from 40.7% (95%CI 36.9-44.5%) with QFT-GIT to 52% (95%CI 48.2-56.0%) with TST using a 10 mm cut-off. The highest agreement between QFT-GIT and TST (κ = 0.50; 95%CI 0.43-0.56) was observed with the 10 mm cut-off for a positive TST. For a definition of LTBI status using a double positive result for both QFT-GIT and TST, significant associations were found with the following risk factors: being male (OR = 2.21; 95%CI 1.40-3.49; p = 0.0007), belonging to age groups 35-44 years (OR = 2.43; 95%CI 1.45-4.06; p = 0.0007) and even more 45-60 years (OR = 4.81; 95%CI 2.72-8.52; p = 7.10-8), having a family history of TB (OR = 6.62; 95%CI 2.59-16.94; p = 8.10-5), and working at a pulmonology unit (OR = 3.64; 95%CI 1.44-9.23; p = 0.006). Smoking was associated with LTBI status when defined by a positive QFT-GIT result (OR = 1.89; 95%CI 1.12-3.21; p = 0.02). A high prevalence of LTBI was observed among HCWs in two Moroccan hospitals. Male gender, increased age, family history of TB, and working at a pulmonology unit were consistent risk factors associated with LTBI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".