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Record W7116973033 · doi:10.1056/evidtt2400447

Do Antibiotics Improve Survival, Quality of Life, and Comfort in Patients with Advanced Dementia and Pneumonia?

2025· article· en· W7116973033 on OpenAlexaff
Aisha Ahmad, Jenny T van der Steen

Bibliographic record

VenueNEJM Evidence · 2025
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMcMaster UniversitySinai Health System
Fundersnot available
KeywordsAntibioticsDementiaPneumoniaQuality (philosophy)PopulationClinical trial

Abstract

fetched live from OpenAlex

AbstractPatients with advanced dementia and suspected pneumonia are at high risk of death. Antibiotics are commonly prescribed for these patients; however, there is little evidence that treatment meaningfully prolongs life, improves quality of life, or promotes comfort. At the same time, treatment with antibiotics in this population has potential side effects, contributes to antibiotic overuse, and may be burdensome for these frail patients who are near the end of life. This Tomorrow's Trial reviews the existing evidence, and the article proposes a trial to address the question, "Do Antibiotics Improve Survival, Quality of Life, and Comfort in Patients with Advanced Dementia and Pneumonia?"

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)0.004
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.019
GPT teacher head0.316
Teacher spread0.297 · 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 designRandomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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