A Sustainable Community-Based Model of Noncommunicable Disease Risk Factor Surveillance (Shraddha-Jagrithi Project): Protocol for a Cohort Study
Bibliographic record
Abstract
BACKGROUND: India has a massive noncommunicable disease (NCD) burden, at an enormous cost to the individual, family, society, and health system at large, despite which prevention and surveillance are relatively neglected. If diagnosed early and treated adequately, risk factors for atherosclerotic cardiovascular disease would help decrease the mortality and morbidity burden. Surveillance for NCDs, creating awareness, positive lifestyle changes, and treatment are the proven measures known to prevent the progression of the disease. India is in a stage of rapid epidemiological transition, with the state of Kerala being at the forefront, pointing us towards likely disease burden and outcomes for the rest of the country in the future. A previous study done by the same investigators in a population of >100,000 revealed poor awareness, treatment of NCDs, and poor adherence to medicines in individuals with CVD. OBJECTIVE: This study aimed at assessing a sustainable, community-based surveillance model for NCDs with corporate support fully embedded in the public health system. METHODS: Frontline health workers will check all individuals in the target group (≥age 30 years) with further follow-up and treatment planned in a "spoke and hub" model using the public health system of primary health centers as spokes to the hubs of taluk or district hospitals. All data entry done by frontline health workers will be on a tablet PC, ensuring rapid acquisition and transfer of participant health details to primary health centers for further follow-up and treatment. RESULTS: The model will be evaluated based on the utilization rate of various services offered at all tier levels. The proportions of the target population screened, eligible individuals who reached the spoke or hub centers for risk stratification and care, and community-level control for hypertension and diabetes in annual surveys will be used as indicator variables. The model ensures diagnosis and follow-up treatment at no cost to the individual entirely through the tiered public health system of the state and country. CONCLUSIONS: Surveillance for NCDs is an essential facet of health care presently lacking in India. Atherosclerotic cardiovascular disease has a long gestation period in progression to the symptomatic phase of the disease, during which timely preventive and lifestyle measures would help prevent disease progression if implemented. Unfortunately, several asymptomatic individuals have never tested their plasma glucose, serum lipid levels, or blood pressure and are unaware of their disease status. Our model, implemented through the public health system using frontline health workers, would ensure individuals aged≥30 years at risk of disease are identified, and necessary lifestyle modifications and treatments are given. In addition, the surveillance at the community level would help create a general awareness of NCDs and lead to healthier lifestyle habits. TRIAL REGISTRATION: Clinical Trial Registry India CTRI/2018/07/014856; https://tinyurl.com/4saydnxf. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/27299.
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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 | 0.036 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.078 | 0.017 |
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".