ArticleClinical research in cardiology : official journal of the German Cardiac Society2021
New technologies for intensive prevention programs after myocardial infarction: rationale and design of the NET-IPP trial.
Article in Clinical research in cardiology : official journal of the German Cardiac Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Exercise-based cardiac rehabilitation for coronary heart disease.The Cochrane database of systematic reviews · 2021Pooled it
- Impact of educational attainment on preventive efforts after myocardial infarction: results of the IPP and NET-IPP trials.Clinical research in cardiology : official journal of the German Cardiac Society · 2025Trial
- Long-term risk factor management and adverse events in patients with early-onset myocardial infarction-a "real-world" study.Clinical research in cardiology : official journal of the German Cardiac Society · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCurrent health care data reveal suboptimal prevention in patients with coronary artery disease and an unmet need to develop effective preventive strategies. The New Technologies for Intensive Prevention Programs (NET-IPP) Trial will investigate if a long-term web-based prevention program after myocardial infarction (MI) will reduce clinical events and risk factors. In a genetic sub study the impact of disclosure of genetic risk using polygenic risk scores (PRS) will be assessed. STUDY
designPatients hospitalized for MI will be prospectively enrolled and assigned to either a 12-months web-based intensive prevention program or standard care. The web-based program will include telemetric transmission of risk factor data, e-learning and electronic contacts between a prevention assistant and the patients. The combined primary study endpoint will comprise severe adverse cardiovascular events after 2 years. Secondary endpoints will be risk factor control, adherence to medication and quality of life. In a genetic sub study genetic risk will be assessed in all patients of the web-based intensive prevention program group by PRS and patients will be randomly assigned to genetic risk disclosure vs. no disclosure. The study question will be if disclosure of genetic risk has an impact on patient motivation and cardiovascular risk factor control.
conclusionsThe randomized multicenter NET-IPP study will evaluate for the first time the effects of a long-term web-based prevention program after MI on clinical events and risk factor control. In a genetic sub study the impact of disclosure of genetic risk using PRS will be investigated.
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.