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Record W2923421859 · doi:10.1016/j.mmcr.2019.03.004

Chronic Candida dubliniensis meningitis in a lung transplant recipient

2019· article· en· W2923421859 on OpenAlexaff
Sabina Herrera, Paolo Pavone, Deepali Kumar, L. Singer, Atul Humar, Cecilia Chaparro, Shaf Keshavjee, Shahid Husain, Coleman Rotstein

Bibliographic record

VenueMedical Mycology Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsCandida dubliniensisMedicineLungMeningitisCandida albicansEsophageal candidiasisMicrobiologyImmunologyInternal medicineAntifungalDermatologyBiologySurgeryHuman immunodeficiency virus (HIV)Corpus albicans

Abstract

fetched live from OpenAlex

Candida spp. are common colonizers of the oral mucosa and respiratory tract in lung transplant recipients. Although thought to be non-pathogenic in most cases, donor derived infections related to Candida spp. have been described. Among the manifestations of invasive candidiasis, chronic meningitis is one of the rarest and one of the most challenging to diagnose, due to the indolence of the disease and the low yield of the CSF cultures. It is associated with severe morbidity and a high mortality. Fungal PCR and BD glucan assays can be assistance in its diagnosis, although these tests are not widely available. We report a case of a possible donor derived Candida dubliniensis infection in a lung transplant recipient, who initially presented with empyema that was treated successfully, but subsequently developed chronic meningitis. Diagnosis was delayed due to the low yield of CSF cultures, and was confirmed with fungal PCR and BD glucan assay.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
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 head0.008
GPT teacher head0.284
Teacher spread0.275 · 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 designCase report
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
Published2019
Admission routes1
Has abstractyes

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