Evaluation of the predisposing factors associated with reaching end-stage complications during early adulthood in indigenous peoples with type 2 diabetes mellitus: a system literature review
Bibliographic record
Abstract
Background: Type 2 diabetes is a common disease found amongst Canadians. The estimated prevalence of diabetes among Canadians was 3.4 million or 9.3% of the population in 2015 and continues to climb (3). The prevalence of diabetes among Indigenous peoples is significantly higher than those who are non-Indigenous. They are more susceptible to early onset of the disease when compared to their non-Indigenous counterpart. In addition to this, they are more likely to reach end stage complications of the disease early in adulthood. There are various reasons for this that need to be investigated further. Objective: The purpose of this study was to investigate whether there is a genetic component that influences early diagnosis, and whether social barriers and transition from pediatric to adult care play a role in reaching end-stage complications in early adulthood of Indigenous patients. Methods: A literature search was completed using the databases PubMed, Scopus and the University of Manitoba online database. Relevant articles were reviewed and were chosen based on an inclusion criterion. Results: A total of 4 studies were deemed eligible for review. Of the 4, 2 demonstrated that there is a genetic mutation among the Oji-Cree population that can be associated with early-onset of diabetes. Of the remaining 2 studies, 1 collected information about the experiences shared among Indigenous groups with diabetes in the health care system and found that many have experienced discrimination, racism and insensitivity to their culture. The final article collected information from a survey that found that there are various challenges associated with transition from pediatric to adult care, of which can be associated with a loss of care. Conclusion: Individually, these 3 themes can be attributed to the problems we find in health care when it comes to Indigenous health. When they are all tied into the patient’s life, it can be determined that they may all play a part in reaching end stage complications in early adulthood. Being genetically predisposed to early onset of the disease, having a care provider who is insensitive to their needs or desires in care, and being lost in the transition from pediatric to adult care can lead to improper follow up and loss of control of blood sugar, and this may result in reaching complications at a younger age than the non-Indigenous counterpart.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".