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Chronic Granulomatous Disease (CGD): Commonly Associated Pathogens, Diagnosis and Treatment

2023· review· en· W4386457280 on OpenAlexaff
Angel A Justiz-Vaillant, Arlene Williams, Rodolfo Arozarena-Fundora, Darren Gopaul, Sachin Soodeen, Odalis Asin-Milan, Reinand Thompson, Chandrashekhar Unakal, Patrick Eberechi Akpaka

Bibliographic record

VenueMicroorganisms · 2023
Typereview
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsChronic granulomatous diseasePrimary immunodeficiencyItraconazoleImmunologyMicrobiologyMedicineBiologyImmune systemAntifungal

Abstract

fetched live from OpenAlex

Chronic granulomatous disease (CGD) is a primary immunodeficiency caused by a defect in the phagocytic function of the innate immune system owing to mutations in genes encoding the five subunits of the nicotinamide adenine dinucleotide phosphatase (NADPH) oxidase enzyme complex. This review aimed to provide a comprehensive approach to the pathogens associated with chronic granulomatous disease (CGD) and its management. Patients with CGD, often children, have recurrent life-threatening infections and may develop infectious or inflammatory complications. The most common microorganisms observed in the patients with CGD are Staphylococcus aureus, Aspergillus spp., Candida spp., Nocardia spp., Burkholderia spp., Serratia spp., and Salmonella spp. Antibacterial prophylaxis with trimethoprim-sulfamethoxazole, antifungal prophylaxis usually with itraconazole, and interferon gamma immunotherapy have been successfully used in reducing infection in CGD. Haematopoietic stem cell transplantation (HCT) have been successfully proven to be the treatment of choice in patients with CGD.

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.053
GPT teacher head0.293
Teacher spread0.239 · 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

Citations34
Published2023
Admission routes1
Has abstractyes

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