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Record W2053890147 · doi:10.1097/ta.0b013e31817db0de

Characterization of Persistent Hyperglycemia: What Does It Mean Postinjury?

2009· article· en· W2053890147 on OpenAlexaff
Jason L. Sperry, Heidi L. Frankel, Avery B. Nathens, Grant E. O’Keefe, Joseph Cuschieri, Ernest E. Moore, Ronald V. Maier, Joseph P. Minei

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2009
Typearticle
Languageen
FieldMedicine
TopicHyperglycemia and glycemic control in critically ill and hospitalized patients
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical Sciences
KeywordsMedicineGlycemicProportional hazards modelHazard ratioInternal medicineCohortProspective cohort studyPopulationCohort studySurgeryInsulinConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND: Strict glycemic control has been shown to reduce both morbidity and mortality in critically ill surgical patients; however, overly aggressive management of hyperglycemia may also be associated with deleterious effects. We sought to characterize clinical outcomes associated with different levels of persistent hyperglycemia (PH) in a cohort of severely injured patients with trauma, when a strict glycemic control protocol (target glucose 80-110 mg/dL) was implemented. METHODS: Data were obtained from a multicenter prospective cohort study evaluating clinical outcomes in blunt injured adults with hemorrhagic shock. Glycemic control was analyzed using the average maximum daily glucose values from postinjury day 2 (>48 hours after injury) to postinjury day 5. PH was defined as a mean glucose value >130 mg/dL, and was categorized into three different severity levels (I-III) based on the distribution of mean 4-day glucose values for the cohort. Separate Cox proportional hazard regression models were then used to determine whether PH was independently associated with mortality and nosocomial infection (NI), and the level of glycemic control that was associated with these poor outcomes. RESULTS: Overall mortality and NI rates for the study population (n = 862) were 10.8% and 49.6%, respectively. Cox proportional hazard regression revealed that PH was independently associated with almost an 80% higher mortality in patients with mean 4-day glucose values >145 mg/dL (group II) and almost a twofold higher mortality in patients with >165 mg/dL (group III). However, PH was not independently associated with a higher risk of NI at any level. Patients with PH did have a higher incidence of early multiple organ failure (within first 48 hours: 30.2% vs. 41.6% p = 0.001), which preceded the documentation of PH in the majority of patients. CONCLUSION: Maintenance of daily maximum glucose values <145 mg/dL was independently associated with a survival benefit after injury. Patients with PH, despite aggressive insulin therapy, had a higher incidence of multiple organ failure and an associated higher risk of mortality. However, the strict glycemic control protocol in the current trauma cohort seems to have prevented the association of PH and infectious complications, which has been documented in prior studies. This analysis further validates the importance of strict glycemic control after injury, and highlights the need for further studies on the mechanism responsible for these 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)0.003
metaresearch head score (Gemma)0.008
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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
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 head0.013
GPT teacher head0.291
Teacher spread0.278 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

Explore more

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