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Record W2917614353 · doi:10.1093/occmed/50.6.395

Methicillin-Resistant Staphylococcus aureus and Multidrug Resistant Tuberculosis: Part 2

2000· review· en· W2917614353 on OpenAlexaff
D. Patel, Ira Madan

Bibliographic record

VenueOccupational Medicine · 2000
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsTuberculosisMedicineInfection controlRifampicinCommunicable diseaseIntensive care medicineEpidemiologyIsoniazidDrug resistanceTransmission (telecommunications)Multiple drug resistancePublic healthExtensively drug-resistant tuberculosisEnvironmental healthMycobacterium tuberculosisMicrobiologyInternal medicinePathologyBiology

Abstract

fetched live from OpenAlex

Drug resistant tuberculosis has been recognized since chemotherapy first became available. However, drug resistance has increased in many countries, and recently strains resistant to both rifampicin and isoniazid (multidrug resistant tuberculosis) have emerged. This review discusses the epidemiology of multidrug resistant tuberculosis (MDRTB), and the control of MDRTB in healthcare facilities. Relevant papers for this review were identified by a systematic literature search on Medline. MDRTB is already established world-wide, and although the overall problem of resistance remains low in the UK, it is of significant clinical importance due to its high case-fatality, higher transmission risk, and complex treatment. The key elements of MDRTB control are prompt recognition, confirmation and treatment of cases, and the institution of strict infection control procedures to reduce the airborne spread of infection from infectious patients to others. This review emphasizes the importance of a multidisciplinary approach to management, with liaison between tuberculosis physicians, the microbiology department, infection control team, consultant in communicable disease, and occupational health.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.097
GPT teacher head0.412
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations3
Published2000
Admission routes1
Has abstractyes

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