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Record W2768535052 · doi:10.1001/jamaneurol.2017.3036

Association of Brain Structure Changes and Cognitive Function With Combination Antiretroviral Therapy in HIV-Positive Individuals

2017· article· en· W2768535052 on OpenAlexafffund
Ryan Sanford, Lesley K. Fellows, Beau M. Ances, D. Louis Collins

Bibliographic record

VenueJAMA Neurology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Nursing ResearchCanadian Institutes of Health Research
KeywordsAntiretroviral therapyAssociation (psychology)Human immunodeficiency virus (HIV)CognitionBrain functionBrain Structure and FunctionMedicineClinical psychologyPsychologyNeurosciencePsychiatryViral loadPsychotherapistImmunology

Abstract

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Importance: Despite the introduction of combination antiretroviral therapy (cART), HIV-associated neurocognitive disorders continue to be a problem for treated HIV-positive individuals. The cause of this impairment remains unclear. Objective: To determine if detectable brain changes occur during a 2-year period in HIV-positive individuals who were aviremic and treated with cART. Design, Setting, and Participants: In this longitudinal case-control study, participants underwent neuroimaging and neuropsychological assessment approximately 2 years apart. Data were collected from October 26, 2011, to March 1, 2016. Data from 92 HIV-positive individuals were acquired at Washington University in St Louis from ongoing studies conducted in the infectious disease clinic and AIDS Clinical Trial Unit. A total of 55 HIV-negative control participants were recruited from the St Louis community and a research participant registry. A total of 48 HIV-positive individuals who were aviremic and treated with cART and 31 demographically similar HIV-negative controls met the study requirements and were included in the analyses. Main Outcomes and Measures: Brain volumes were extracted with tensor-based and voxel-based morphometry and cortical modeling. Raw scores from neuropsychological tests quantified cognitive performance. Multivariable mixed-effects models assessed the effect of HIV serostatus on brain volumes and cognitive performance, and determined if HIV serostatus affected how these measures changed over time. With HIV-positive participants, linear regression models tested whether brain volumes and cognitive performance were associated with measures of infection severity and duration of infection. Results: The 2 groups were demographically similar (HIV-positive group: 23 women and 25 men; mean [SD] age, 47.7 [13.2] years; mean [SD] educational level, 13.3 [3.4] years; and HIV-negative group, 16 women and 15 men; mean [SD] age, 51.2 [12.9] years; mean [SD] educational level, 14.5 [2.1] years). The HIV-positive participants had poorer neuropsychological test scores compared with controls on the Trail Making Test Part A (5.9 seconds; 95% CI, 1.5-10.3; P = .01), Trail Making Test Part B (27.3 seconds; 95% CI, 15.0-39.6; P < .001), Digit Symbol Substitution Task (-12.5 marks; 95% CI, -18.9 to -6.0; P < .001), Letter-Number Sequencing (-2.5 marks; 95% CI, -3.7 to -1.3; P < .001), Letter Fluency (-6.6 words; 95% CI, -11.5 to -1.6; P = .01), and Hopkins Verbal Learning Test-Revised immediate recall (-2.4 words; 95% CI, -4.4 to -0.4; P = .05), after adjusting for age, sex, and educational level. Only changes in Trail Making Test Part A significantly differed between the groups. Cortical thickness and subcortical volumes were smaller in HIV-positive individuals compared with controls. However, changes in brain volume over time were similar between the groups. Conclusions and Relevance: These findings are consistent with the idea that cognitive and structural brain changes may occur early after seroconversion, and argue that maintaining aviremia with cART can prevent or minimize progressive brain injury.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 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".

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Citations118
Published2017
Admission routes2
Has abstractyes

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