Comparing Stroke Profiles and Outcomes between Urban and Rural India: A Secondary Analysis of the SPRINT INDIA Trial
Bibliographic record
Abstract
INTRODUCTION: Stroke causes significant death and disability, with urban-rural disparities in healthcare and limited studies in India, despite its rural majority of 70%. The post hoc study aimed to explore differences in stroke profiles, risk factors, and outcomes between urban and rural participants using data from the Secondary Prevention by Structured Semi-Interactive Stroke Prevention Package in India (SPRINT INDIA) trial. METHODS: The SPRINT INDIA trial was a multi-center randomized clinical trial across 31 Indian sites. Data were collected between April 28, 2018, and November 30, 2021. Index stroke patients, aged 18 and older, presenting within 2 days to 3 months of symptom onset, were randomized using a centralized web-based system into intervention or control groups. The intervention included SMS, videos, and an interactive educational workbook for secondary stroke prevention in 11 Indian languages. Baseline data captured in a case report form included participants' urban or rural locations. The primary outcome was a composite endpoint that included recurrent stroke, high-risk transient ischemic attack (TIA), acute coronary syndrome (ACS), and all-cause mortality within 1 year after randomization. The trial is registered by <ext-link ext-link-type="uri" xlink:href="http://Clinicaltrials.gov" xmlns:xlink="http://www.w3.org/1999/xlink">Clinicaltrials.gov</ext-link> (NCT03228979) and Clinical Trials Registry-India (CTRI/2017/09/009600). RESULTS: The trial enrolled 4,298 sub-acute stroke patients, out of which 3,038 (70.68%) were followed up, of which 1,620 (53.32%) were urban and 1,418 (46.68%) were rural. The primary composite outcome (recurrent stroke, high-risk TIA, ACS, and mortality) was higher in urban areas compared to rural areas (61 [3.8%] vs. 34 [2.4%]; p = 0.018) at 1-year follow-up. All cases of high-risk TIA occurred in urban participants (p < 0.001). Urban participants were more educated (795 [49.1%] vs. rural 394 [27.8%]; p < 0.001), with higher rates of dyslipidemia (335 [20.7%] vs. 247 [17.4%]; p = 0.023), and higher body mass index (25.17 ± 4.31 vs. 24.76 ± 4.23; p = 0.008). Behavioral risk factors of alcohol intake and smoking tobacco were higher in rural patients compared to urban patients (65 [4.6%] vs. 73 [4.5%]; p < 0.001 and 59 [4.2%] vs. 65 [4.0%]; p < 0.001, respectively). CONCLUSION: Urban patients show higher stroke recurrence and lifestyle-related conditions, while rural patients face more behavioral risks like smoking and alcohol use. To address these disparities, requires targeted interventions; urban patients would benefit from lifestyle-focused programs, such as dietary improvements and stress management. For rural patients, programs should focus on reducing behavioral risks like smoking and alcohol use through community-based education and accessible cessation support services.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".