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Record W4380793189 · doi:10.1183/13993003.00455-2023

Shorter duration of antibiotic therapy for exacerbation of COPD

2023· letter· en· W4380793189 on OpenAlexaff
Victor Leung, Colin Lee

Bibliographic record

VenueEuropean Respiratory Journal · 2023
Typeletter
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British ColumbiaProvidence Health Care
Fundersnot available
KeywordsCOPDExacerbationMedicineAntibioticsDuration (music)Intensive care medicineAntibiotic resistanceCopd exacerbationAntibiotic therapyInternal medicineAcute exacerbation of chronic obstructive pulmonary disease

Abstract

fetched live from OpenAlex

We would like to thank the authors of the recently released Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2023 report and express one area of concern related to the general recommendation for 5- to 7-day antibiotic therapy duration [1]. We believe the totality of evidence supports a shorter course (5 days or less) for treating mild to moderate exacerbations of COPD (ECOPD). Although longer courses of antibiotics have traditionally been recommended for many infections, the basis for this originated from dogma versus rigorous trial evidence [2]. Excessive antibiotic durations are not sustainable in the face of increasing antibiotic resistance, one of the top global public health threats. Highlighting the evidence that supports a more explicit statement recommending shorter duration of antibiotics for exacerbation of COPD http://bit.ly/3KmLmQR

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)0.002
metaresearch head score (Gemma)0.021
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0180.018
Insufficient payload (model declined to judge)0.0100.009

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 head0.058
GPT teacher head0.322
Teacher spread0.264 · 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
GenreCommentary

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

Citations1
Published2023
Admission routes1
Has abstractyes

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