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Record W2317257933 · doi:10.1155/2005/230396

Bacillary Angiomatosis in an HIV‐positive Man with Multiple Risk Factors: A Clinical and Epidemiological Puzzle

2005· article· en· W2317257933 on OpenAlexaffabout
Farrah J. Mateen, Jill Newstead, Karen McClean

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBartonella species infections research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBacillary angiomatosisBartonellaBacteremiaMedicinePathologyDermatologyBartonella henselaeImmunologyBiologyVirologyAntibioticsSerologyMicrobiology

Abstract

fetched live from OpenAlex

A 36-year-old man with advanced AIDS presented with skin lesions, fever and weight loss. Physical examination revealed skin lesions suggestive of bacillary angiomatosis. Diagnostic imaging identified bone lesions, soft tissue masses and a single hepatic lesion. His clinical presentation was most consistent with Bartonella quintana; however, his risk for infection with B quintana was limited to a remote, brief period of homelessness. In contrast, his frequent contact with cats presented substantial potential exposure to Bartonella henselae.Diagnosing a Bartonella infection presents challenges. The detection of bacteremia is hindered by slow growth in BACTEC media (BD Diagnostic Systems, Canada). In the present case, recovery of the organism required blind subcultures after at least eight days of incubation. Speciation by 16s ribosomal RNA analysis confirmed B quintana as the pathogen.Because the patient presented with skin lesions, the diagnosis was straightforward; however, skin lesions are nondiagnostic in some cases. Microbiological confirmation of the diagnosis rests on sufficient clinical suspicion to apply labour-intensive laboratory protocols.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 teacher head, 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

Citations18
Published2005
Admission routes2
Has abstractyes

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