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Record W2981674121 · doi:10.1093/ofid/ofz359.041

856. Invasive Haemophilus influenzae Disease in Children: A Canadian MultiCenter Study on Emerging Serotypes

2019· article· en· W2981674121 on OpenAlexaffabout
Craig Frankel, Mohammad Alghounaim, Jane McDonald, John Gunawan, Joan Robinson, Sarah Khan, Jacqueline Wong, Alison Lopez, Sergio Fanella, Jeannette Comeau, Jennifer Bowes, Robert Slinger, Angela Kalia, Ashley Roberts, Kirk Leifso, Michelle Barton

Bibliographic record

VenueOpen Forum Infectious Diseases · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsBC Children's HospitalChildren's Hospital of Eastern OntarioMcMaster UniversityLondon Health Sciences CentreMcMaster Children's HospitalKingston Health Sciences CentreChildren's Hospital of WinnipegStollery Children's HospitalIzaak Walton Killam Health CentreUniversity of ManitobaMontreal Children's HospitalWestern University
Fundersnot available
KeywordsMedicineBacteremiaMeningitisInternal medicinePneumoniaSeptic arthritisEpiglottitisCellulitisSerotypePediatricsGastroenterologySurgeryImmunologyArthritisMicrobiologyAntibiotics

Abstract

fetched live from OpenAlex

Abstract Background Our objective was to describe the serotype distribution and clinical spectrum of invasive Haemophilus influenza (Hi) disease in children admitted to participating centers within the Paediatric Investigator’s Collaborative Network on Infections in Canada (PICNIC). Methods All cases of Hi bacteremia were identified from the PICNIC Database of Gram-negative bacteremia (2013–2017). Disease was defined as complicated if the following occurred: (a) >2 sites were affected, (b) surgical intervention was required, (c) organ failure, (d) ICU admission, (e) seizures, (f) sensory or motor deficits, (g) treatment-related complications, or (h) death. Results There were 98 cases of Hi bacteremia. Male to female ratio was 64:34 and median age was 12 (IQR: 7–48; range 0–216) months. Hi serotypes included: a (N = 31; 32%), b (N = 9; 9%), f (N = 15; 13%), c (N = 1;1%), e (N = 1; 1%), nontypeable (N = 34; 35%) and unknown (N = 7; 7%). Clinical foci included: bacteremia without a focus (N = 19; 19%), meningitis (N = 29; 30%), cellulitis (N = 8; 8%), septic arthritis (N = 6; 6%), pneumonia (n = 33; 34%), epiglottitis (N = 1; 1%), and endovascular infection (n = 3; 3%). Complicated disease occurred in 29 (30%) cases; there was one (1%) death. Where serotyping was available, complication rates were: 42%, 22%, 100%, 0%, 33%, and 21% for Hia, Hib, Hic, Hie, Hif and nontypeable Hi, respectively. Factors associated with complicated disease were: age <5 years (P = 0.009), bacteremia without a focus (P = 0.006) and a CNS focus (P < 0.001). Hia was the leading serotype in meningitis (55%; P = 0.022). Nontypeable Hi was most frequent in pneumonia cases (56%; P = 0.003) and never caused cellulitis (0% vs. 14%; P = 0.023). Neonatal disease (N = 5) was predominantly caused by nontypeable Hi (80%; P = 0.040). Of note, 26 (27%) of our Hi isolates were ampicillin resistant. Conclusion In the era of efficacious conjugate Hib vaccines, serotype has emerged as the leading cause of typeable Hi disease in Canada and is highly associated with meningitis, especially in young children. Strategies for preventing Hi disease need to target this emerging serotype and efforts should be focused toward developing an effective vaccine for serotype a disease. Disclosures All Authors: No reported Disclosures.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.009
GPT teacher head0.259
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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