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Record W2997523154 · doi:10.3138/jammi.2019-0022

<i>Haemophilus influenzae</i> type b necrotizing fasciitis in an adult with common variable immunodeficiency

2020· article· en· W2997523154 on OpenAlexaffvenue
Liam Finlay, Anna Cvetkovic, Zain Chagla

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2020
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsSt. Joseph's HospitalMcMaster University
Fundersnot available
KeywordsCommon variable immunodeficiencyHaemophilus influenzaeFasciitisMicrobiologyMedicineVirologyImmunologyBiologyAntibioticsSurgery

Abstract

fetched live from OpenAlex

Necrotizing fasciitis of an extremity due to Haemophilus influenzae is exceptionally uncommon in adults, particularly since the advent of widespread vaccination with conjugated H. influenzae type b (Hib). We report a previously vaccinated, 39-year-old male with a history of common variable immunodeficiency (CVID), poorly compliant with intravenous immunoglobulin (IVIG) therapy, who required emergent treatment for left leg necrotizing fasciitis. The patient was initially treated with piperacillin-tazobactam, vancomycin, and clindamycin, in tandem with surgical debridement and wash-out. The patient responded well and completed a 2-week course of ceftriaxone following blood culture results that demonstrated beta-lactamase–positive Hib. This is the fifth documented case of necrotizing fasciitis caused by H. influenzae, and the first affecting an adult with prior Hib vaccination. This case highlights the importance of IVIG compliance for CVID patients and advocates considering encapsulated organisms as part of the differential diagnosis for severe skin and soft tissue infections in this patient population.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.007
GPT teacher head0.233
Teacher spread0.227 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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