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Record W2109122200 · doi:10.1177/1545109708323132

Nonadherence Increases the Risk of Hospitalization Among HIV-Infected Antiretroviral Naïve Patients Started on HAART

2008· article· en· W2109122200 on OpenAlexaff
Sarah J. Fielden, Melanie Rusch, Benita Yip, Evan Wood, Kate Shannon, Adrian R. Levy, Julio Montaner, Robert S. Hogg

Bibliographic record

VenueJournal of the International Association of Physicians in AIDS Care · 2008
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsSimon Fraser UniversityAIDS VancouverUniversity of British Columbia
FundersInternational AIDS Society
KeywordsMedicineAntiretroviral therapyHuman immunodeficiency virus (HIV)Antiretroviral treatmentViral loadEmergency medicinePediatricsInternal medicineVirology

Abstract

fetched live from OpenAlex

BACKGROUND: Since the advent of highly active antiretroviral therapy (HAART), AIDS-related hospitalizations have decreased. The objective of this study was to assess the impact of adherence on hospitalization among antiretroviral-naïve HIV-infected persons initiating HAART. METHODS: Analysis was based on a cohort of individuals initiating HAART between 1996 and 2001. The primary outcome was hospitalization for one or more days. Survival methods were used to assess the impact of adherence on hospitalization. RESULTS: Of 1605 eligible participants, 672 (42%) were hospitalized for one or more days after initiating HAART. Median adherence levels were 92 (IQR: 58, 100) and 100 (IQR: 83, 100) among those ever and never hospitalized, respectively. After controlling for confounders, those with <95% adherence had 1.88 times (95% CI: 1.60, 2.21) higher risk for hospitalization. CONCLUSIONS: Suboptimal adherence among HIV-infected patients taking HAART predicts hospitalization. Identifying and addressing factors contributing to poor adherence early in treatment could improve patient care and lower hospitalization costs.

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)0.003
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 score0.012
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.006
GPT teacher head0.257
Teacher spread0.251 · 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

Citations60
Published2008
Admission routes1
Has abstractyes

Explore more

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