MétaCan
Menu
Back to cohort
Record W2807496383 · doi:10.1007/s13300-018-0448-7

Successful Management of Poorly Controlled Type 2 Diabetes with Multidisciplinary Neurobehavioral Rehabilitation: A Case Report and Review

2018· article· en· W2807496383 on OpenAlexaff
Zhihui Deng, John Davis, Flor Muniz-Rodriguez, Fran Richardson

Bibliographic record

VenueDiabetes Therapy · 2018
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsMedicineType 2 diabetesRehabilitationGlycemicDiabetes mellitusDepression (economics)Type 2 Diabetes MellitusAnxietyPhysical therapyIntensive care medicinePsychiatryEndocrinology

Abstract

fetched live from OpenAlex

Lifestyle modification with healthy diet and physical exercise is considered the basic strategy of prevention and treatment of type 2 diabetes, a commonly seen comorbidity in patients with acquired brain injury. Additionally, emotional stress with anxiety and depression is suggested to play a role in type 2 diabetes. Research studies have demonstrated the efficacy of multidisciplinary lifestyle intervention in patients with inadequate glycemic control. However, whether lifestyle approaches alone may be adequate for the management of poorly controlled type 2 diabetes is unknown. We report a 30-year-old male patient whose type 2 diabetes was inadequately controlled by 50 units of insulin glargine, 15 units of insulin aspart supplement with meals plus a correctional scale as well as multiple oral hypoglycemic drugs when admitted to a neurobehavioral rehabilitation unit subsequent to his brain injury. Following 3 months of multidisciplinary rehabilitation for his functional neurological symptom disorder, all his pharmacological agents were gradually discontinued and his diabetes was successfully managed solely by lifestyle approaches.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.295
Teacher spread0.280 · 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 designCase report
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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueDiabetes TherapySame topicBotulinum Toxin and Related Neurological DisordersFrench-language works237,207