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Record W2037969646 · doi:10.1016/j.ijid.2015.01.004

Sputum induction is a safe procedure to use in prisoners and MGIT is the best culture method to diagnose tuberculosis in prisons: a cohort study

2015· article· en· W2037969646 on OpenAlexfundno aff
Zulma Vanessa Rueda, Lucelly López, Diana Marín, Lázaro Vélez, María Patricia Arbeláez

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
FundersUniversity of ManitobaUniversidad de AntioquiaDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsSputumMedicineConcordanceTuberculosisInternal medicineSputum culturePulmonary tuberculosisGastroenterologyConfidence intervalPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the concordance and safety of induced sputum (IS) and spontaneous sputum (SS), and estimate concordance and time to detection of M. tuberculosis between Lowenstein-Jensen (LJ), thin-layer agar (TLA), and the Mycobacteria Growth Indicator Tube system (MGIT). METHODS: This was a cohort study. Prisoners with pulmonary tuberculosis (PTB) were followed for 2 years. At baseline and every follow-up visit, three sputum samples were taken on consecutive days (one IS and two SS) and adverse events occurring before, during, and 30 min after IS were registered. All sputum samples were stained with auramine and cultured in LJ, TLA (to test resistance), and MGIT. RESULTS: Five hundred eighty-six IS and 532 SS were performed on 64 PTB patients. Breathlessness (1.6%), cough (1.2%), hemoptysis (0.3%), and cyanosis (0.2%) were the only complications. Concordance between IS and SS was 0.78 (95% confidence interval 0.69-0.87); 11 positive cultures from IS samples were negative in SS, and 11 positive cultures from SS samples were negative in IS. One hundred seventy-eight cultures were positive by any technique: MGIT 95%, LJ 73%, and TLA 57%. Time to detection of M. tuberculosis in LJ, TLA, and MGIT was 31, 18, and 11 days, respectively. CONCLUSIONS: The IS procedure is safe in prisons. The MGIT system is better and faster than LJ and TLA in the diagnosis of M. tuberculosis.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.391
Teacher spread0.355 · 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

Labeled directly by 2 models reading the full record.

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

Citations9
Published2015
Admission routes1
Has abstractyes

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