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Record W2105211444 · doi:10.1155/2014/149070

Abnormal Blood Glucose as a Prognostic Factor for Adverse Clinical Outcome in Children Admitted to the Paediatric Emergency Unit at Komfo Anokye Teaching Hospital, Kumasi, Ghana

2014· article· en· W2105211444 on OpenAlexaff
Emmanuel Ameyaw, Kwame Amponsah-Achiano, Peter Yamoah, Jean‐Pierre Chanoine

Bibliographic record

VenueInternational Journal of Pediatrics · 2014
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsBC Children's Hospital
FundersEuropean Society for Paediatric Endocrinology
KeywordsMedicineAlgorithmEmergency departmentInternal medicineMathematicsPsychiatry

Abstract

fetched live from OpenAlex

Dysglycaemia (hyper- or hypoglycaemia) in critically ill children has been associated with poor outcome. We compared the clinical outcomes in children admitted to Pediatric Emergency Unit (PEU) at Komfo Anokye Teaching Hospital (KATH) for acute medical conditions and presenting with euglycaemia or dysglycaemia. This is a prospective case matching cohort study. Eight hundred subjects aged between 3 and 144 months were screened out of whom 430 (215 with euglycaemia and 215 with dysglycaemia) were enrolled. The median age was 24 months (range: 3-144 months). In the dysglycaemia group, 28 (13%) subjects had hypoglycemia and 187 (87%) had hyperglycemia. Overall, there were 128 complications in 116 subjects. The number of subjects with complications was significantly higher in dysglycaemia group (n = 99, 46%) compared to euglycaemia group (n = 17, 8%) (P < 0.001). Forty subjects died out of whom 30 had dysglycaemia (P = 0.001). Subjects with dysglycaemia were 3 times (95% CI: 1.5-6.0) more likely to die and 4.8 times (95% CI: 3.1-7.5) more likely to develop complications (P = 0.001). Dysglycaemia is associated with increased morbidity and mortality in children with acute medical conditions and should lead to intensive management of the underlying condition.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.013
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.343
Teacher spread0.321 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of PediatricsSame topicHyperglycemia and glycemic control in critically ill and hospitalized patientsFrench-language works237,207