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Record W4405891605 · doi:10.1164/rccm.202410-2096st

Updates on the Treatment of Drug-Susceptible and Drug-Resistant Tuberculosis: An Official ATS/CDC/ERS/IDSA Clinical Practice Guideline

2024· article· en· W4405891605 on OpenAlexfundno aff
Jussi Saukkonen, Raquel Duarte, Sonal S. Munsiff, Carla A. Winston, Manoj J. Mammen, Ibrahim Abubakar, Carlos Acuña-Villaorduña, Pennan M. Barry, Mayara Lisboa Bastos, Wendy Carr, Hassan Chami, Lisa Chen, Terence Chorba, Charles L. Daley, Anthony J. Garcia‐Prats, Kelly Holland, Ioannis Konstantinidis, Marc Lipman, Giovanni Battista Migliori, Farah M. Parvez, Adrienne E. Shapiro, Giovanni Sotgiu, Jeffrey R. Starke, Angela M. Starks, S. Thakore, Shuhua Wang, Jonathan M. Wortham, Payam Nahid

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
FundersUniversity of Colorado School of Medicine, Anschutz Medical CampusNational Center for HIV/AIDS, Viral Hepatitis, STD, and TB PreventionNational Institute of Allergy and Infectious DiseasesFaculty of Medicine and Health, University of SydneyMax Rady College of Medicine, University of ManitobaUniversity of California, San FranciscoNational Heart, Lung, and Blood InstituteSchool of Medicine and Public Health, University of Wisconsin-MadisonCenters for Disease Control and PreventionNational Institutes of HealthUniversidade do PortoUniversità degli Studi di SassariUniversiteit StellenboschUniversity College LondonInsmedPfizerUniversity of RochesterFaculty of Medicine, McGill UniversityU.S. Department of Health and Human ServicesCOPD FoundationMcGill UniversityMannKind CorporationUniversity of Wisconsin-MadisonJohns Hopkins UniversityUniversity of WashingtonUnited States Agency for International DevelopmentCalifornia Department of Public HealthGenentechNational Jewish HealthInfectious Diseases Society of AmericaAdministração Regional de Saúde do Norte, Ministério da SaúdeAstraZenecaCystic Fibrosis FoundationEli Lilly and CompanyUniversity of PittsburghAmerican Thoracic SocietyTexas Biomedical Research InstitutePatient-Centered Outcomes Research InstituteYale UniversityU.S. Department of Veterans AffairsBill and Melinda Gates FoundationOhio State University
KeywordsMedicineGuidelineDrugTuberculosisClinical PracticeDrug resistanceIntensive care medicineFamily medicinePharmacologyPathologyMicrobiology

Abstract

fetched live from OpenAlex

Abstract Background On the basis of recent clinical trial data for the treatment of drug-susceptible and drug-resistant tuberculosis (TB), the American Thoracic Society, U.S. Centers for Disease Control and Prevention, European Respiratory Society, and Infectious Diseases Society of America have updated clinical practice guidelines for TB treatment in children and adults in settings in which mycobacterial cultures, molecular and phenotypic drug susceptibility tests, and radiographic studies, among other diagnostic tools, are available on a routine basis. Methods A Joint Panel representing multiple interdisciplinary perspectives convened with American Thoracic Society methodologists to review evidence and make recommendations using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) and GRADE-ADOLOPMENT (adoption, adaptation, and, as needed, de novo development of recommendations) methodology. Results New drug-susceptible TB recommendations include the use of a novel 4-month regimen for people with pulmonary TB and a shortened 4-month regimen for children with nonsevere TB. Drug-resistant TB recommendation updates include the use of novel regimens containing bedaquiline, pretomanid, and linezolid with or without moxifloxacin. Conclusions All-oral, shorter treatment regimens for TB are now recommended for use in eligible individuals.

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 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)0.017
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.038
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0050.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0060.005

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 head0.048
GPT teacher head0.436
Teacher spread0.388 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations124
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Respiratory and Critical Care MedicineSame topicTuberculosis Research and EpidemiologyFrench-language works237,207