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Recent advances in managing HIV-associated cryptococcal meningitis

2019· preprint· en· W2947640686 on OpenAlexaff
Timothée Boyer‐Chammard, Elvis Temfack, Alexandre Alanio, Joseph N Jarvis, Thomas S. Harrison, Olivier Lortholary

Bibliographic record

VenueF1000Research · 2019
Typepreprint
Languageen
FieldMedicine
TopicFungal Infections and Studies
Canadian institutionsInstitute of Infection and Immunity
FundersEuropean and Developing Countries Clinical Trials PartnershipMedical Research CouncilWellcome TrustStyrelsen för Internationellt Utvecklingssamarbete
KeywordsCryptococcal meningitisFlucytosineMedicineFluconazoleIntensive care medicineMeningitisAmphotericin BAntifungalHuman immunodeficiency virus (HIV)CryptococcusImmunologyPediatricsBiologyMicrobiologyDermatologyViral disease

Abstract

fetched live from OpenAlex

The recent development of highly sensitive and specific point-of-care tests has made it possible to diagnose HIV-associated cryptococcal meningitis within minutes. However, diagnostic advances have not been matched by new antifungal drugs and treatment still relies on old off-patent drugs: amphotericin B, flucytosine and fluconazole. Cryptococcal meningitis treatment is divided in three phases: induction, consolidation and maintenance. The induction phase, aimed at drastically reducing cerebrospinal fluid fungal burden, is key for patient survival. The major challenge in cryptococcal meningitis management has been the optimisation of induction phase treatment using the limited number of available medications, and major progress has recently been made. In this review, we summarise data from key trials which form the basis of current treatment recommendations for HIV-associated cryptococcal meningitis.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.050
GPT teacher head0.382
Teacher spread0.332 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2019
Admission routes1
Has abstractyes

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