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Record W2118897297 · doi:10.1093/occmed/kqu107

Pre-placement screening for tuberculosis in healthcare workers

2014· article· en· W2118897297 on OpenAlexaff
Prosenjit Giri, Subhashis Basu, T. Sargeant, Abi Rimmer, Omar Pirzada, Anil Adisesh

Bibliographic record

VenueOccupational Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsSaint John Regional HospitalCanada East Spine CentreUniversity of New Brunswick
Fundersnot available
KeywordsTuberculosisMedicineHealth careHealthcare workerFamily medicinePathologyEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Healthcare workers (HCWs) are at occupational risk of contracting and transmitting tuberculosis (TB). Despite national guidance, the optimal process for the pre-placement screening of new entrant HCWs for TB in the UK is not certain, nor the appropriateness of using a one-step interferon gamma release assay (IGRA) screening programme. AIMS: To assess the potential for an IGRA-only TB screening programme for new entrant HCWs, and identify cost savings achieved through this process. METHODS: We conducted a retrospective analysis of IGRA and tuberculin skin tests (TST) within our occupational health service over a 3-year period. HCWs with markedly discordant test results (IGRA negative, TST positive) were followed up to determine whether they developed active TB. We also estimated the yearly cost savings if the existing two-step process was replaced with an IGRA-only programme. RESULTS: Totally, 96/1258 (8%) HCWs had positive IGRA results; 788 TSTs were performed for newly screened IGRA-negative HCWs without Bacille Calmette-Guérin scars, among which 597 (76%) tested negative (TST <6 mm). None of the 10 individuals with grossly discordant test results (TST >15 mm) developed active TB during the study period. We calculated savings of £20,453 if the two-step process was replaced with an IGRA-only programme. CONCLUSIONS: The absence of disease progression in individuals with markedly discordant results in this study suggest that an IGRA-only screening programme for new HCWs in the UK is feasible, and may be safe although our follow-up period was insufficient. Our results also suggest that substantial cost savings can be made by using this programme.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.412
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2014
Admission routes1
Has abstractyes

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