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Record W2164876339 · doi:10.3810/pgm.2010.05.2150

Approach to Managing Hypoglycemia in Elderly Patients with Diabetes

2010· article· en· W2164876339 on OpenAlexaff
Kannayiram Alagiakrishnan, Laurie Mereu

Bibliographic record

VenuePostgraduate Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHypoglycemiaMedicineGlycemicDiabetes mellitusIntensive care medicineBlood sugarPolypharmacyInsulinPediatricsInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Hypoglycemia is a common clinical problem in elderly patients with diabetes. Aging modifies the counterregulatory and symptomatic responses to hypoglycemia. Hypoglycemia in the elderly is not only due to tight blood sugar control, but also due to a multitude of other factors. Hypoglycemia often occurs with insulin, sulfonylureas, or meglitinide therapy. However, other causes may also contribute to hypoglycemia, such as decreased cognition, renal impairment, or polypharmacy. The presenting features of hypoglycemia may be atypical and misinterpreted, resulting in delayed treatment. Morbidity is greater in elderly patients, and the risk of progression to severe hypoglycemia is high because of their altered symptom profile, diminished symptom intensity, and altered glycemic thresholds. Hypoglycemia seems to be the main limiting factor in their glycemic control. In this article we discuss strategies to prevent hypoglycemic episodes.

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 score0.096
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.013
GPT teacher head0.255
Teacher spread0.242 · 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

Citations29
Published2010
Admission routes1
Has abstractyes

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