Effectiveness of a home-based cardiovascular disease prevention program during the COVID-19 pandemic
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Background Home-based cardiovascular disease (CVD) primary prevention (HBPP) and cardiac rehabilitation (HBCR) programs which occupied a small proportion of the overall Preventive Cardiology work in the past have become mainstream during the COVID-19 pandemic. Purpose This study aims to analyse the effectiveness of a home-based CVD prevention program implemented during the pandemic in India. Methods A retrospective study was conducted on pre-pandemic and pandemic enrolees. Health behaviour, CVD risk factors, physical and mental component score (PCS, MCS) from SF-12 questionnaire, body mass index (BMI), 6-minute walk distance (6MWD), and clinical and biochemical parameters were assessed. A multidisciplinary team consisting of Physician, Physiotherapist, Dietician and Counselling Psychologist provided the program using tele-health platforms. Results Of the 66 subjects (55 ± 13 years, 73% male), 17 (26%) enrolled pre-pandemic and 49 (74%) enrolled during-pandemic, 28 (42%) were HBPP and 38 (58%) were HBCR participants. Majority of the subjects (n = 51, 77%), with significantly more HBCR than HBPP participants, harboured 4 or more risk factors (p = 0.04). In the 60 (91%) program completers, BMI, 6MWD, PCS and MCS had improved significantly. SBP, DBP, LVEF, HbA1c, total cholesterol and LDL had improved significantly in affected subjects. Completely home-based participants (n = 44, 67%) who never had any in-person contact with the team during the program also showed significant improvement. No adverse events were reported. Conclusion Comprehensive home-based CVD prevention programs are effective in improving anthropometric, clinical, biochemical and psychosocial parameters, are a safe alternative to conventional programs and could potentially become the standard-of-care in the post-pandemic era. Abstract Figure. Outcomes in program participants Abstract Figure. Management of ACS in participants
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".