MétaCan
Menu
Back to cohort
Record W2046524126 · doi:10.1097/mph.0000000000000070

Predictors of Bacteremia Among Children With Sickle Cell Disease Presenting With Fever

2013· article· en· W2046524126 on OpenAlexaff
Deena Savlov, Carolyn E Beck, Julie DeGroot, Isaac Odame, Jeremy Friedman

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineBacteremiaOdds ratioSepsisInternal medicineConfidence intervalPopulationPediatricsAntibiotics

Abstract

fetched live from OpenAlex

INTRODUCTION: Bacterial sepsis is more common and potentially life threatening in children with sickle cell disease (SCD). Identification of variables that predict bacteremia may aid clinicians in recognizing patients with SCD at higher risk for sepsis. OBJECTIVE: To determine whether absolute neutrophil count (ANC) >20×10/L is an independent risk factor for bacteremia in children with SCD and to identify other predictors of bacteremia in this population. METHODS: A case-control study was conducted. Subjects were 0 to 18 years of age admitted to a tertiary care pediatric hospital over a 17-year period with SCD and fever at presentation. Cases had bacteremia, whereas controls had negative blood cultures. RESULTS: Data were analyzed for 40 cases and 120 controls. ANC>20×10/L was significantly more prevalent among cases (odds ratio [OR], 7.0; 95% confidence interval [CI], 2.6-18.9). Cases were more likely to have emesis (OR, 2.9; 95% CI, 1.0-8.4) and a higher proportion of band cells (OR, 1.3; 95% CI, 1.1-1.4) at presentation. CONCLUSIONS: In a febrile child with SCD, an ANC>20×10/L, a higher proportion of band cells, and the presence of vomiting were associated with an increased likelihood of bacteremia.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.222
Teacher spread0.218 · 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.

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

Citations21
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pediatric Hematology/OncologySame topicHemoglobinopathies and Related DisordersFrench-language works237,207