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Record W4399041302 · doi:10.1016/j.cmi.2024.05.013

Cerebrospinal fluid galactomannan detection for the diagnosis of central nervous system aspergillosis: a diagnostic test accuracy systematic review and meta-analysis

2024· review· en· W4399041302 on OpenAlexafffund
Adam S. Komorowski, Clayton W. Hall, Sukhreet Atwal, Rochelle Johnstone, Robert Walker, Dominik Mertz, Eva Piessens, Deborah Yamamura, Ekkehard M. Kasper

Bibliographic record

VenueClinical Microbiology and Infection · 2024
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsHamilton Regional Laboratory Medicine ProgramMcMaster UniversityUniversity of TorontoUniversity Health NetworkHamilton Health SciencesSt. Joseph’s Healthcare HamiltonImpact
FundersTrinity College DublinMcMaster University
KeywordsGalactomannanCerebrospinal fluidDiagnostic accuracyAspergillosisDiagnostic testMeta-analysisMedicinePathologyRadiologyImmunologyPediatrics

Abstract

fetched live from OpenAlex

BACKGROUND: Cerebrospinal fluid (CSF) galactomannan is an adjunctive test for central nervous system (CNS) aspergillosis diagnosis with unclear diagnostic test characteristics. OBJECTIVES: To evaluate the diagnostic test characteristics of CSF galactomannan in CNS aspergillosis. METHODS: Systematic review and meta-analysis. DATA SOURCES: MEDLINE, Embase, Web of Science, and Scopus, from inception to 24 February 2023. STUDY ELIGIBILITY CRITERIA: Prospective and retrospective studies with 1-group and 2-group designs using any galactomannan assay on CSF to diagnose CNS aspergillosis. PARTICIPANTS: Adult and/or paediatric patients with CNS aspergillosis. TEST(S): Galactomannan testing on CSF specimens. REFERENCE STANDARD: European Organization for Research and Treatment of Cancer and the Mycoses Study Group Education and Research Consortium (EORTC/MSGERC) diagnostic criteria, or equivalent. ASSESSMENT OF RISK OF BIAS: QUADAS-2 assessment in duplicate. METHODS OF DATA SYNTHESIS: Bivariate restricted maximum likelihood estimation random-effects meta-analysis, summarized using forest and summary receiver operating characteristic plots; bivariate meta-regression models to investigate heterogeneity; and subgroup and sensitivity analyses to explore subgroup effects and methodologic choices (PROSPERO registration: CRD42022296331; funding: none). RESULTS: We included eight studies (n = 342 participants). The summary estimates of CSF galactomannan sensitivity and specificity were 69.0% (95% CI, 57.2-78.7%) and 94.4% (95% CI, 82.8-98.3%), respectively. Using meta-regression, galactomannan cut-off (p = 0.38), EORTC/MSGERC criteria version (p = 0.48), or whether the reference standard was defined as both proven and probable or only proven aspergillosis (p = 0.48) did not explain observed heterogeneity. No subgroup effects were demonstrated by analysing the EORTC/MSGERC criteria reference standard used (e.g. 2002 vs. 2008 definitions) or whether paediatric patients were included. Diagnostic sensitivity was improved using a galactomannan cut-off of 1.0, and by excluding high risk of bias and 1-group design studies. DISCUSSION: CSF galactomannan is a highly specific but insensitive test for use as a component of CNS aspergillosis diagnosis. Few included studies, no prospective studies, and a high risk of bias are study limitations.

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)0.008
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.026
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.405
Teacher spread0.308 · 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 designMeta-analysis
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

Citations19
Published2024
Admission routes2
Has abstractno

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