THU270 Efficacy Of Patient Support Program On Management Of Cardiovascular Risk Factors For Adults With Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Abstract Disclosure: A. Shah: None. S. Damse: None. P. Thiyagarajah: None. K. Soulat: None. T. Ahadome: None. Efficacy Of Patient Support Program On Management Of Cardiovascular Risk Factors For Adults With Type 2 Diabetes Mellitus. Type 2 diabetes mellitus (T2DM) is a major risk factor for cardiovascular disease. Patients with T2DM have 2 to 3 times the risk of cardiovascular mortality and morbidity.1 This study aimed to assess the efficacy of an intensive intervention strategy in improving cardiovascular risk factors, HbA1C level in high-risk patients with T2DM. Methods: An interventional program with a multi component strategy was delivered by Wellthy therapeutics over a period of 40 weeks. The program had interventions including customized dietary plans, behavioral interventions, including stress management and coping skills training, lifestyle counseling, disease awareness and self-management training of symptoms at home. Interventions were initiated by certified health coaches via chats and calls. A high-risk diabetic cohort whose HbA1C greater than 10% were recruited by convenience sampling method. Intervention Statistical analysis was done using SPSS version 21. Results: The mean age of patients was 48.49±14.46. The mean of HbA1C, Total Cholesterol, LDL, Triglycerides, BMI at baseline was 11.4, 195.42, 125.9, 247.26, 26.77 respectively. The mean of HbA1C, Total Cholesterol, LDL, Triglycerides, BMI at the endline was 9.70, 181.98, 119.82, 195.34, 25.95 respectively. The effect of the Paired Ttest witnessed that intensive intervention strategy had a statistically significant improvement in effect on the cardiovascular risk factors from baseline to follow up p<0.05.(HbA1C p=.001, Total cholesterol p=.019, Triglycerides p=.002, BMI p=.007). Conclusion: This program played a highly significant role in managing cardiovascular risk factors by training patients in self-monitoring, medication adherence, and knowledge on disease awareness. There is increasing evidence that these interventions can support modification of lifestyle risk factors among people with coronary T2DM; however, existing interventions are disparate. These types of interventions play a potential role in meeting the individual needs and preferences to optimize self-management of their disease. Presentation: Thursday, June 15, 2023
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".