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Record W2616479650 · doi:10.1186/s12916-017-0865-x

Revisiting annual screening for latent tuberculosis infection in healthcare workers: a cost-effectiveness analysis

2017· article· en· W2616479650 on OpenAlexafffund
Guillaume A. Mullie, Kevin Schwartzman, Alice Zwerling, Dieynaba S. N’Diaye

Bibliographic record

VenueBMC Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill University Health CentreMontreal Heart InstituteMcGill University
FundersCanadian Institutes of Health ResearchFaculty of Medicine, McGill UniversityMcGill University
KeywordsMedicineTuberculosisTuberculinLatent tuberculosisHealth careCohortContext (archaeology)Environmental healthEmergency medicineInternal medicineMycobacterium tuberculosisPathology

Abstract

fetched live from OpenAlex

BACKGROUND: In North America, tuberculosis incidence is now very low and risk to healthcare workers has fallen. Indeed, recent cohort data question routine annual tuberculosis screening in this context. We compared the cost-effectiveness of three potential strategies for ongoing screening of North American healthcare workers at risk of exposure. The analysis did not evaluate the cost-effectiveness of screening at hiring, and considered only workers with negative baseline tests. METHODS: A decision analysis model simulated a hypothetical cohort of 1000 workers following negative baseline tests, considering duties, tuberculosis exposure, testing and treatment. Two tests were modelled, the tuberculin skin test (TST) and QuantiFERON®-TB-Gold In-Tube (QFT). Three screening strategies were compared: (1) annual screening, where workers were tested yearly; (2) targeted screening, where workers with high-risk duties (e.g. respiratory therapy) were tested yearly and other workers only after recognised exposure; and (3) post exposure-only screening, where all workers were tested only after recognised exposure. Workers with high-risk duties had 1% annual risk of infection, while workers with standard patient care duties had 0.3%. In an alternate higher-risk scenario, the corresponding annual risks of infection were 3% and 1%, respectively. We projected costs, morbidity, quality-adjusted survival and mortality over 20 years after hiring. The analysis used the healthcare system perspective and a 3% annual discount rate. RESULTS: Over 20 years, annual screening with TST yielded an expected 2.68 active tuberculosis cases/1000 workers, versus 2.83 for targeted screening and 3.03 for post-exposure screening only. In all cases, annual screening was associated with poorer quality-adjusted survival, i.e. lost quality-adjusted life years, compared to targeted or post-exposure screening only. The annual TST screening strategy yielded an incremental cost estimate of $1,717,539 per additional case prevented versus targeted TST screening, which in turn cost an incremental $426,678 per additional case prevented versus post-exposure TST screening only. With the alternate "higher-risk" scenario, the annual TST strategy cost an estimated $426,678 per additional case prevented versus the targeted TST strategy, which cost an estimated $52,552 per additional case prevented versus post-exposure TST screening only. In all cases, QFT was more expensive than TST, with no or limited added benefit. Sensitivity analysis suggested that, even with limited exposure recognition, annual screening was poorly cost-effective. CONCLUSIONS: For most North American healthcare workers, annual tuberculosis screening appears poorly cost-effective. Reconsideration of screening practices is warranted.

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)0.005
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.134
GPT teacher head0.448
Teacher spread0.313 · 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.

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

Citations27
Published2017
Admission routes2
Has abstractyes

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