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Record W3048938803 · doi:10.1097/qad.0000000000002651

HIV infection and COVID-19: risk factors for severe disease

2020· letter· en· W3048938803 on OpenAlexaff
Nicolas Etienne, Marina Karmochkine, Laurence Slama, Juliette Pavie, Dominique Batisse, Rafael Usubillaga, V. Letembet, Patricia Brazille, Étienne Canouï, Dorsaf Slama, Hassan Joumaa, Florence Canouï‐Poitrine, Lauriane Ségaux, Laurence Weiss, Jean-Paul Viard, Dominique Salmon

Bibliographic record

VenueAIDS · 2020
Typeletter
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Observational studyMedicineMultivariate analysisHuman immunodeficiency virus (HIV)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DiseaseRisk factorProspective cohort studyInternal medicineImmunologyVirologyOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

: We performed an observational prospective monocentric study in patients living with HIV (PLWH) diagnosed with COVID-19. Fifty-four PLWH developed COVID-19 with 14 severe (25.9%) and five critical cases (9.3%), respectively. By multivariate analysis, age, male sex, ethnic origin from sub-Saharan Africa and metabolic disorder were associated with severe or critical forms of COVID-19. Prior CD4 T cell counts did not differ between groups. No protective effect of a particular antiretroviral class was observed.

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: Editorial · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.415
Teacher spread0.345 · 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
GenreEditorial

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

Citations74
Published2020
Admission routes1
Has abstractyes

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