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Record W2884368954 · doi:10.2196/10770

Viral Loads Within 6 Weeks After Diagnosis of HIV Infection in Early and Later Stages: Observational Study Using National Surveillance Data

2018· article· en· W2884368954 on OpenAlexvenueno aff
Richard M. Selik, Laurie Linley

Bibliographic record

VenueJMIR Public Health and Surveillance · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsViral loadMedicineIndeterminateStage (stratigraphy)AntibodyNucleic acid testHuman immunodeficiency virus (HIV)ImmunologyInternal medicineVirologyDiseaseCoronavirus disease 2019 (COVID-19)BiologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

BACKGROUND: Early (including acute) HIV infection is associated with viral loads higher than those in later stages. OBJECTIVE: This study aimed to examine the association between acute infection and viral loads near the time of diagnosis using data reported to the US National HIV Surveillance System. METHODS: We analyzed data on infections diagnosed in 2012-2016 and reported through December 2017. Diagnosis and staging were based on the 2014 US surveillance case definition for HIV infection. We divided early HIV-1 infection (stage 0) into two subcategories. Subcategory 0α: a negative or indeterminate HIV-1 antibody test was ≤60 days after the first confirmed positive HIV-1 test or a negative or indeterminate antibody test or qualitative HIV-1 nucleic acid test (NAT) was ≤180 days before the first positive test, the latter being a NAT or detectable viral load. Subcategory 0β: a negative or indeterminate antibody or qualitative NAT was ≤180 days before the first positive test, the latter being an HIV antibody or antigen/antibody test. We compared median earliest viral loads for each stage and subcategory in each of the first 6 weeks after diagnosis using only the earliest viral load for each individual. RESULTS: Of 203,392 infections, 56.69% (115,297/203,392) were reported with a quantified earliest viral load within 6 weeks after diagnosis and criteria sufficient to determine the stage at diagnosis. Among 5081 infections at stage 0, the median earliest viral load fell from 694,000 copies/mL in week 1 to 125,022 in week 2 and 43,473 by week 6. Among 30,910 infections in stage 1, the median earliest viral load ranged 15,412-17,495. Among 42,784 infections in stage 2, the median viral load declined from 44,973 in week 1 to 38,497 in week 6. Among 36,522 infections in stage 3 (AIDS), the median viral load dropped from 205,862 in week 1 to 119,000 in week 6. The median earliest viral load in stage 0 subcategory 0α fell from 1,344,590 copies/mL in week 1 to 362,467 in week 2 and 47,320 in week 6, while that in subcategory 0β was 70,114 copies/mL in week 1 and then 32,033 to 44,067 in weeks 2-6. The median viral load in subcategory 0α was higher than that in subcategory 0β in each of the first 6 weeks after diagnosis (P<.001). CONCLUSIONS: In the 1st week after diagnosis, viral loads in early infections are generally several times higher than those in later stages at diagnosis. By the 3rd week, however, most are lower than those in stage 3. High viral loads in early infection are much more common in subcategory 0α than in subcategory 0β, consistent with 0α comprising mostly acute infections and 0β comprising mostly postacute early infections. These findings may inform the prioritization of interventions for prevention.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.105
GPT teacher head0.367
Teacher spread0.262 · 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".

Quick stats

Citations24
Published2018
Admission routes1
Has abstractyes

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