ReviewJournal of public health policy2023
Prioritising research funding for cardiovascular disease and diabetes in Australia.
Review in Journal of public health policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 4 citations in OpenAlex.
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- Predictive modelling of metabolic syndrome in Ghanaian diabetic patients: an ensemble machine learning approach.Journal of diabetes and metabolic disorders · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Targeted Translation Research Accelerator program was created to address cardiovascular disease and diabetes in Australia. To maximise the impact of the considerable investment in this program, a structured prioritisation project was undertaken to determine the highest priority health and medical unmet needs in cardiovascular disease and diabetes. The project was led by Monash University's Behaviour Works Australia in collaboration with Australian National University, Research Australia, and MTPConnect. We conducted an online survey with 318 experts and community representatives to generate a 'long list' of unmet needs for (1) cardiovascular disease; (2) diabetes; and (3) interactions in the pathogenesis of Type 1 diabetes, Type 2 diabetes, and cardiovascular disease. We then convened roundtables of clinical, research, and community leaders to discuss survey results. They prioritised unmet needs against six predefined criteria then discussed results. We present the final priority areas for funding. We demonstrate how a feasible, reproducible, and collaborative prioritisation methodology can be used when designing research funding programs. Such approaches can ensure that funding is directed towards projects that are valuable to the community and reflective of expert opinion.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.