ArticleNature communications2026
Interventional applications of a Stroke Heat Risk Prediction Model produce health benefits.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Interventional applications of a Stroke Heat Risk Prediction Model produce health benefits.Nature communications · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Although heat exposure increases stroke risk, targeted individualized interventions remain limited. This study develops and validates a Stroke Heat Risk Grading Prediction Model for precision intervention using 28,116 stroke deaths from 304 Chinese counties. Meteorological and stroke mortality data from 2013-2018 are analyzed with time-series methods, revealing a nonlinear temperature-mortality relationship. Four risk levels are established and validated using 2019-2022 data through case-crossover and time-series analyses considering sex, age, and geography. At the highest risk level of our model, stroke mortality increases by 13.8% in the general population and 16.4% in older adults, whereas the China Meteorological Administration warning system poorly predicts stroke mortality. Interventions guided by our model achieve nearly a two-fold increase in the proportion of avoidable heat-attributable excess deaths compared to existing approaches. These findings support this model as a digital tool to mitigate heat-related stroke risk under climate change.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.