Temporal trend analysis of stroke and salt intake: a 15-year population-based study
Bibliographic record
Abstract
Objectives: The aim of this study was to evaluate temporal trends of salt intake with stroke incidence, stroke subtypes, and blood pressure in an adult population.Methods: Data were extracted from Isfahan Salt Study. The stroke incidence rate, average salt intake, systolic and diastolic blood pressure in adults, aged over 18 years were considered from 2000 to 2014. The Average Annual Percent Changes (AAPC), parallelism, and the coincidence of trends were estimated, using a permutation test.Results: The trend of salt intake was increased from 2010 to 2014 (AAPC = +1.59, P-value = 0.004). The trend of the stroke incidence rate was nonlinear with two change points in 2003 and 2009. The overall stroke incidence rate increased by 6.65% per year (95% CI: 1.66, 11.8, P-value = 0.015). The temporal trend changes of stroke incidence rate were steeper in patients who aged 40–45 and over 50 years (+6 to +11.5%) than in patients who aged 19–40 and 45–50 (range: −3.3% to 0). The parallelism hypothesis of longitudinal changes between salt intake and ischemic stroke was accepted in patients, aged <50 years (P-value = 0.871).Conclusions: The average salt intake and its cone-shaped variance over 15 years of the study, indicated that salt intake reduction programs and policies were effective to stop associating intake increase until 2007, however, associated intake was increased since that time, which necessitates performing preventive programs. More importantly, the trend of salt intake and ischemic stroke was similar in patients who aged <50 years, regardless of considering their blood pressure.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".