ArticleThe British journal of general practice : the journal of the Royal College of General Practitioners2018
Use of primary care data to predict those most vulnerable to cold weather: a case-crossover analysis.
Article in The British journal of general practice : the journal of the Royal College of General Practitioners, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Article
- Effect of weather on GP home visits: a cross-sectional study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe National Institute for Health and Care Excellence (NICE) recommends that GPs use routinely available data to identify patients most at risk of death and ill health from living in cold homes.
aimTo investigate whether sociodemographic characteristics, clinical factors, and house energy efficiency characteristics could predict cold-related mortality. DESIGN AND
settingA case-crossover analysis was conducted on 34 777 patients aged ≥65 years from the Clinical Practice Research Datalink who died between April 2012 and March 2014. The average temperature of date of death and 3 days previously were calculated from Met Office data. The average 3-day temperature for the 28th day before/after date of death were calculated, and comparisons were made between these temperatures and those experienced around the date of death.
methodConditional logistic regression was applied to estimate the odds ratio (OR) of death associated with temperature and interactions between temperature and sociodemographic characteristics, clinical factors, and house energy efficiency characteristics, expressed as relative odds ratios (RORs).
resultsLower 3-day temperature was associated with higher risk of death (OR 1.011 per 1°C fall; 95% CI = 1.007 to 1.015;
conclusionIt is unlikely that GPs can identify older patients at highest risk of cold-related death using routinely available data, and NICE may need to refine its guidance.
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