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Record W2515429879 · doi:10.1093/cid/ciw592

Galactomannan, β-D-Glucan, and Polymerase Chain Reaction–Based Assays for the Diagnosis of Invasive Fungal Disease in Pediatric Cancer and Hematopoietic Stem Cell Transplantation: A Systematic Review and Meta-Analysis

2016· review· en· W2515429879 on OpenAlexaff
Thomas Lehrnbecher, Paula D. Robinson, Brian T. Fisher, Elio Castagnola, Andreas H. Groll, William J. Steinbach, Theoklis E. Zaoutis, Zelalem Negeri, Joseph Beyene, Bob Phillips, Lillian Sung

Bibliographic record

VenueClinical Infectious Diseases · 2016
Typereview
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsInstitute for Clinical Evaluative SciencesHospital for Sick ChildrenMcMaster UniversityPediatric Oncology Group
FundersNational Institute for Health and Care Research
KeywordsGalactomannanMedicineHematopoietic stem cell transplantationImmunosuppressionPolymerase chain reactionNeutropeniaAspergillosisTransplantationInternal medicineDiseaseCancerGold standard (test)OncologyImmunologyBiologyChemotherapy

Abstract

fetched live from OpenAlex

We systematically reviewed and analyzed the available data for galactomannan (GM), β-D-glucan (BG), and polymerase chain reaction (PCR)-based assays to detect invasive fungal disease (IFD) in patients with pediatric cancer or undergoing hematopoietic stem cell transplantation when used as screening tools during immunosuppression or as diagnostic tests in patients presenting with symptoms such as fever during neutropenia (FN). Of 1532 studies screened, 25 studies reported on GM (n = 19), BG (n = 3), and PCR (n = 11). All fungal biomarkers demonstrated highly variable sensitivity, specificity, and positive predictive values, and these were generally poor in both clinical settings. GM negative predictive values were high, ranging from 85% to 100% for screening and 70% to 100% in the diagnostic setting, but failure to identify non-Aspergillus molds limits its usefulness. Future work could focus on the usefulness of combinations of fungal biomarkers in pediatric cancer and HSCT.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.399
Teacher spread0.305 · 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.

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

Citations162
Published2016
Admission routes1
Has abstractyes

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