The effects of a primary care low-carbohydrate, high-fat dietary educational intervention on laboratory and anthropometric data of patients with chronic disease: a retrospective cohort chart review
Bibliographic record
Abstract
BACKGROUND: Low-carbohydrate and high-fat (LCHF) diets are shown to have health benefits such as weight loss and improved cardiovascular health. Few studies, however, on LCHF diets have been completed in a real-world primary care setting over an extended period of time. OBJECTIVES: To examine the efficacy of a low-carbohydrate, high-fat dietary educational intervention delivered in a family practice setting on weight, body mass index (BMI), blood pressure, glycated haemoglobin (HbA1c), fasting insulin, estimated glomerular filtration rate (eGFR), and albumin to creatinine ratio (ACR). A secondary objective was to determine whether compliance to the program had an effect on outcomes. METHODS: In this retrospective chart review, we collected laboratory and anthropometric data from an electronic medical record system for patients (n = 122) at least 19 years of age, who attended at least 2 LCHF educational sessions between January 2018 and May 2020. Pre-post mean differences of outcome were analysed using paired sample t-tests. Independent sample t-tests examined the effect of compliance on the outcomes. RESULTS: Statistically significant reductions in weight (3.96 kg [P < 0.001]) and BMI (1.46 kg/m2 [P = 0.001]) were observed. Compared with patients who participated in ≤5 educational visits, patients who participated in >5 visits showed trends towards more clinically significant changes in weight, BMI, systolic blood pressure, diastolic blood pressure, HbA1c, eGFR, and ACR. CONCLUSION: Improvements in weight and BMI indicate the utility of providing LCHF health promotion interventions in primary care settings. Greater compliance to LCHF interventions results in greater improvement in laboratory and anthropometric outcomes, including HbA1c.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".