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Record W3178856343 · doi:10.1080/14760584.2021.1921579

The epidemiologic and biologic basis for classifying older age as a high-risk, immunocompromising condition for pneumococcal vaccine policy

2021· review· en· W3178856343 on OpenAlexaff
Lindsay R. Grant, Mary Slack, Qi Yan, Krzysztof Trzciński, Jane Barratt, Elizabeth Sobczyk, James Appleby, Alejandro Cané, Luis Jódar, Raúl Istúriz, Bradford D. Gessner

Bibliographic record

VenueExpert Review of Vaccines · 2021
Typereview
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsInternational Federation on Ageing
FundersPfizer
KeywordsImmunosenescenceMedicinePneumococcal pneumoniaVaccinationImmunologyPneumococcal vaccineDiseasePneumococcal infectionsStreptococcus pneumoniaePublic healthInternal medicineImmune systemBiologyPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: . Pneumococcal vaccine recommendations are often limited to adults with specific medical conditions despite similar disease risks among older adults due to immunosenescence. AREAS COVERED: This article reviews epidemiologic, biologic, and clinical evidence supporting the consideration of older age due to immunosenescence as an immunocompromising condition for the purpose of pneumococcal vaccine policy and the role vaccination can play in healthy aging. EXPERT OPINION: Epidemiologic and biologic evidence suggest that pneumococcal disease risk increases with age and is comparable for healthy older adults and younger adults with immunocompromising conditions. Because immunocompromising conditions are already indicated for pneumococcal conjugate vaccines (PCVs), a comprehensive public health strategy would also recognize immunosenescence. Moreover, older persons should be vaccinated before reaching the highest risk ages, consistent with the approach for other immunocompromising conditions. To facilitate PCV use among older adults, vaccine technical committees (VTCs) could classify older age as an immunocompromising condition based on the process of immunosenescence. With global aging, VTCs will need to consider immunosenescence and vaccine use during healthy aging.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.061
GPT teacher head0.440
Teacher spread0.379 · 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 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

Citations23
Published2021
Admission routes1
Has abstractyes

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