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Record W3011268009 · doi:10.3138/jammi.2019-0019

Underutilization of nontuberculous mycobacterial drug susceptibility testing in Ontario, Canada, 2010–2015

2020· article· en· W3011268009 on OpenAlexaffvenueabout
Elizabeth R. Andrews, Alex Marchand‐Austin, Jennifer Ma, Kirby Cronin, Meenu K. Sharma, Sarah K. Brode, Theodore K. Marras, Frances Jamieson

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2020
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsSinai Health SystemWest Park Healthcare CentreUniversity of ManitobaPublic Health Agency of CanadaUniversity of British ColumbiaPublic Health OntarioUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAmikacinMycobacterium abscessusNontuberculous mycobacteriaMedicineMoxifloxacinClarithromycinInternal medicineCefoxitinPopulationDrug resistanceRifabutinMicrobiologyAntibioticsMycobacteriumPathologyTuberculosisBiologyStaphylococcus aureusEnvironmental health

Abstract

fetched live from OpenAlex

Background: Drug susceptibility testing (DST) in nontuberculous mycobacterial pulmonary disease (NTM-PD) is useful for some Mycobacterium species. International guidelines recommend routine use of DST for clinically relevant mycobacteria. DST use and results are poorly studied at the population level. We sought to identify the frequency of DST utilization for nontuberculous mycobacteria (NTMs) and describe the potential relevance of these results in Ontario. Methods: Using public health laboratory data, we performed a population-based retrospective analysis of NTM DST utilization in Ontario from May 2010 to June 2015. We determined the proportion of incident NTM-PD infections for which DST was performed and analyzed minimum inhibitory concentration (MIC) distributions from NTM testing overall, using thresholds recommended by the Clinical and Laboratory Standards Institute. Results: The proportion of incident cases of NTM-PD tested for DST was 6.3% (240/3,806) for Mycobacterium avium complex (MAC), 36.2% (67/185) for M. abscessus, and 1.8% (19/1,057) for M. xenopi. Among specimens from all body sites, MAC resistance to clarithromycin occurred in 8.0% of specimens (21/262) and MAC resistance to amikacin (intravenous, MIC > 64 µg/mL) occurred in 22.6% (19/84). M. abscessus resistance occurred as follows: to amikacin, 3.8% (3/79); cefoxitin, 14.0% (11/79); imipenem, 30.4% (14/46); linezolid, 39.2% (31/79); clarithromycin, 54.2% (13/24); ciprofloxacin, 92.4% (73/79); and moxifloxacin, 91.1% (51/56). M. xenopi analysis was limited by few DST requests and a lack of DST clinical correlation. Conclusions: We found that NTM DST is underutilized in Ontario and observed a very high frequency of amikacin resistance among MAC isolates.

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)0.001
metaresearch head score (Gemma)0.009
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 score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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

Citations14
Published2020
Admission routes3
Has abstractyes

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