MétaCan
Menu
Back to cohort
Record W2162308739 · doi:10.1093/infdis/jiu258

Frailty in People Aging With Human Immunodeficiency Virus (HIV) Infection

2014· article· en· W2162308739 on OpenAlexafffund
Thomas D. Brothers, Susan Kirkland, Giovanni Guaraldi, Julian Falutz, Olga Theou, Barbara Johnston, Kenneth Rockwood

Bibliographic record

VenueThe Journal of Infectious Diseases · 2014
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsCapital District Health AuthorityMcGill University Health CentreDalhousie University
FundersCanadian Institutes of Health Research
KeywordsHuman immunodeficiency virus (HIV)Vulnerability (computing)GerontologyMedicinePopulationImmunologyHealth careEnvironmental healthComputer security

Abstract

fetched live from OpenAlex

The increasing life spans of people infected with human immunodeficiency virus (HIV) reflect enormous treatment successes and present new challenges related to aging. Even with suppression of viral loads and immune reconstitution, HIV-positive individuals exhibit excess vulnerability to multiple health problems that are not AIDS-defining. With the accumulation of multiple health problems, it is likely that many people aging with treated HIV infection may be identified as frail. Studies of frailty in people with HIV are currently limited but suggest that frailty might be feasible and useful as an integrative marker of multisystem vulnerability, for organizing care and for comprehensively measuring the impact of illness and treatment on overall health status. This review explains how frailty has been conceptualized and measured in the general population, critically reviews emerging data on frailty in people with HIV infection, and explores how the concept of frailty might inform HIV research and care.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.011
GPT teacher head0.298
Teacher spread0.287 · 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 designObservational
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

Citations136
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Infectious DiseasesSame topicHIV-related health complications and treatmentsFrench-language works237,207