ReviewEuropean journal of nuclear medicine and molecular imaging2012
The prognostic value of amyloid imaging.
Review in European journal of nuclear medicine and molecular imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Pooled it
- Development and Validation of the Communities Geriatric Mild Cognitive Impairment Risk Calculator (CGMCI-Risk).Healthcare (Basel, Switzerland) · 2024Article
- Comparison of deep learning architectures for predicting amyloid positivity in Alzheimer's disease, mild cognitive impairment, and healthy aging, from T1-weighted brain structural MRI.Frontiers in neuroscience · 2024Article
- Negative 11C-PIB PET Predicts Lack of Alzheimer's Disease Pathology in Postmortem Examination.Journal of Alzheimer's disease : JAD · 2018Article
- Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer's disease patients from non-demented subjects.Oncotarget · 2017Article
- Phantom criteria for qualification of brain FDG and amyloid PET across different cameras.EJNMMI physics · 2016Article
- Ethical issues when using digital biomarkers and artificial intelligence for the early detection of dementia.Wiley interdisciplinary reviews. Data mining and knowledge discoveryReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Mild cognitive impairment is characterized by a decline in cognitive performance without interference with activities of daily living. The amnestic subtype of mild cognitive impairment progresses to Alzheimer's disease at a rate of 10-15% per year and in the majority the neuropathology is intermediate between the neuropathological changes of typical ageing and Alzheimer's disease. Amyloid deposition occurs over a decade before the development of noticeable cognitive symptoms in a continuous process that starts in healthy elderly individuals. Newly developed PET amyloid imaging agents provide noninvasive biomarkers for the early in vivo detection of Alzheimer's pathology in healthy elderly individuals and those with mild cognitive impairment. Exclusion of amyloid pathology should allow a more accurate prognosis to be given and ensure appropriate recruitment into clinical trials testing the efficacy of new putative antiamyloid agents at an earlier disease stage. The development of (18)F-labelled amyloid imaging agents has increased the availability of this new technology for clinical and research use since they can be used in PET centres where a cyclotron and radiochemistry are not available. This review discusses the role of PET imaging for assessing the amyloid load in cognitively normal elderly subjects and subjects with mild cognitive impairment at risk of conversion to Alzheimer's disease.
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.