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Record W2810892104 · doi:10.1177/0956462418778705

Long-term HIV/AIDS survivors: Patients living with HIV infection retained in care for over 20 years. What have we learned?

2018· article· en· W2810892104 on OpenAlexaff
HB Krentz, M. John Gill

Bibliographic record

VenueInternational Journal of STD & AIDS · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsAlberta Hip and Knee ClinicUniversity of Calgary
Fundersnot available
KeywordsMedicineInterquartile rangeAntiretroviral therapyHuman immunodeficiency virus (HIV)PediatricsViral loadHealth careInternal medicineFamily medicine

Abstract

fetched live from OpenAlex

Individuals diagnosed with HIV before 1996 had poor prognoses. Few HIV care centers can track patients continuously from the 1980s to present. We determined the sociodemographic, clinical, and health care utilization characteristics of patients diagnosed and followed for >20 years (i.e. long-term HIV/AIDS survivors) to understand what factors contributed to survival. All HIV-positive patients diagnosed before 1996 were categorized as active, moved/lost, or died as of 1 January 2016. Baseline sociodemographic, clinical characteristics, antiretroviral therapy (ART) usage, retention, HIV care costs, and health status were analyzed. Of 876 patients, 49.5% died, 30.3% moved or left, 20.3% remained active in care for a median of 23.4 years. At diagnosis, continuously-followed patients were younger with a higher CD4 cell count, attended regular clinic visits at higher frequencies, and had received more ART than patients who moved or died. As of 1 January 2016, their median age was 57 years (interquartile range 53–62), 15% were aged >65 years, median CD4 cell count was 591 cells/mm 3 (475–863) with 68% >500 cells/mm 3 . Sixty-two percent remained employed. The total cost of HIV care was $32,251,030 (Cdn$); median cost per patient per year $15,418 ($13,697–$18,392). Individuals diagnosed prior to 1996 benefited from early diagnosis and engagement to care, regular follow-ups, and timely initiation of ART, strongly supporting the modern guidelines of 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)0.001
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 score0.073
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.336
Teacher spread0.317 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

Explore more

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