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Record W4409729441 · doi:10.3390/antibiotics14050427

Overcoming Pseudomonas aeruginosa in Chronic Suppurative Lung Disease: Prevalence, Treatment Challenges, and the Promise of Bacteriophage Therapy

2025· review· en· W4409729441 on OpenAlexaff
Jagdev Singh, Melinda Solomon, Jonathan R. Iredell, Hiran Selvadurai

Bibliographic record

VenueAntibiotics · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCystic Fibrosis Foundation
KeywordsPseudomonas aeruginosaPhage therapyMedicineCystic fibrosisAntibioticsIntensive care medicineAntibiotic resistanceDiseaseBacteriophageClinical trialImmunologyMicrobiologyInternal medicineBacteriaBiology

Abstract

fetched live from OpenAlex

Pseudomonas aeruginosa, a multidrug-resistant pathogen, significantly impacts patients with chronic respiratory conditions like cystic fibrosis (CF) and non-CF chronic suppurative lung disease (CSLD), contributing to progressive lung damage and poor clinical outcomes. This bacterium thrives in the airway environments of individuals with impaired mucociliary clearance, leading to persistent infections and increased morbidity and mortality. Despite advancements in management of these conditions, treatment failure remains common, emphasising the need for alternative or adjunctive treatment strategies. Bacteriophage therapy, an emerging approach utilising viruses that specifically target bacteria, offers a potential solution to combat P. aeruginosa infections resistant to conventional antibiotics. This review examines the prevalence and disease burden of P. aeruginosa in CF and CSLD, explores the mechanisms behind antibiotic resistance, the promising role of bacteriophage therapy and clinical trials in this sphere.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.305
Teacher spread0.279 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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