Treating Type 2 Diabetes: A Cross-sectional Audit of Naturopathic Standards of Care Using the Naturopathic Patient Database
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Naturopathic Patient Database is a data management tool developed by the Canadian College of Naturopathic Medicine to collect patient data from its teaching clinic, the Robert Schad Naturopathic Clinic. This study investigated how type 2 diabetes mellitus was managed at the Robert Schad Naturopathic Clinic from May 2009 to February 2011. Cases of type 2 diabetes mellitus from the Robert Schad Naturopathic Clinic reported in the Naturopathic Patient Database were extracted based on an International Classification of Diseases, 10th revision code assessment of E11 (non-insulin-dependent diabetes mellitus) and files were audited. The American Diabetes Association 2010 standards of medical care in diabetes were used as guidelines for the audit. Multiple categories in diagnosis, physical exam, laboratory tests, and management were graded on a 0 to 2 scale. The average audit score was 55.5/90. The most common interventions being used are diet and aerobic exercise, followed by supplements (omega-3 fatty acids) and botanicals. These data suggest that the American Diabetes Association standards of care for type 2 diabetes mellitus are not followed stringently. Education and creation of a naturopathic standard of care may improve audit performance and patient outcomes.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it