MétaCan
Menu
Back to cohort
Record W4214696319 · doi:10.1177/10935266211064696

Fatal Pediatric Streptococcal Infection: A Clinico—Pathological Study

2022· article· en· W4214696319 on OpenAlexaff
Anita Nagy, Jeanette A. Reyes, David A. Chiasson

Bibliographic record

VenuePediatric and Developmental Pathology · 2022
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsAutopsyMedicinePathologicalSepsisStreptococcus pneumoniaePneumoniaMeningitisStreptococcusStreptococcus pyogenesCohortPediatricsInternal medicinePathologyAntibioticsMicrobiologyBiologyBacteria

Abstract

fetched live from OpenAlex

PURPOSE AND CONTEXT: Streptococcal Infection (SI) is an important cause of pediatric death in children, yet limited reports exist on autopsy findings in fatal SI cases. METHOD: Case records (1997-2019) of SI with no pre-existing risk factors were reviewed and selected. Their clinical and pathological findings in the autopsy reports were analyzed. RESULTS: (SPy; 37%). 92% of decedents had some prodromal symptoms prior to terminal presentation. The clinical course was often rapid, with 89% found unresponsive, suddenly collapsing, or dying within 24 hours of hospital admission. 64% of deaths were attributed to sepsis, more frequently diagnosed in the SPy group than in the SPn group (71% vs 48%). Pneumonia was found in both SPn and SPy groups, whereas meningitis was exclusively associated with SPn. CONCLUSION: Our study shows fatal SI is most commonly caused by either SPn or SPy, both of which are frequently associated with prodromal symptoms, rapid terminal clinical course, and evidence of sepsis. Postmortem diagnosis of sepsis is challenging and should be correlated with clinical features, bacterial culture results, and autopsy findings.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.309
Teacher spread0.275 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePediatric and Developmental PathologySame topicStreptococcal Infections and TreatmentsFrench-language works237,207