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1.
BMC Neurol ; 23(1): 309, 2023 Aug 22.
Article in English | MEDLINE | ID: mdl-37608251

ABSTRACT

BACKGROUND: This systematic review synthesizes the most recent neuroimaging procedures and machine learning approaches for the prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia. METHODS: We systematically searched PubMed, SCOPUS, and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review guidelines. RESULTS: Our search returned 2572 articles, 56 of which met the criteria for inclusion in the final selection. The multimodality framework and deep learning techniques showed potential for predicting the conversion of MCI to AD dementia. CONCLUSION: Findings of this systematic review identified that the possibility of using neuroimaging data processed by advanced learning algorithms is promising for the prediction of AD progression. We also provided a detailed description of the challenges that researchers are faced along with future research directions. The protocol has been registered in the International Prospective Register of Systematic Reviews- CRD42019133402 and published in the Systematic Reviews journal.


Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Alzheimer Disease/diagnostic imaging , Cognitive Dysfunction/diagnostic imaging , Algorithms , Machine Learning , Neuroimaging
2.
Age Ageing ; 50(3): 608-616, 2021 05 05.
Article in English | MEDLINE | ID: mdl-33951151

ABSTRACT

BACKGROUND AND AIM: The aim of this systematic review was to quantify the association between frailty and COVID-19 in relation to mortality in hospitalised patients. METHODS: Medline, Embase, Web of Science and the grey literature were searched for papers from inception to 10 September 2020; the search was re-run in Medline up until the 9 December 2020. Screening, data extraction and quality grading were undertaken by two reviewers. Results were summarised using descriptive statistics, including a meta-analysis of overall mortality; the relationships between frailty and COVID-19 mortality were summarised narratively. RESULTS: A total of 2,286 papers were screened resulting in 26 being included in the review. Most studies were from Europe, half from the UK, and one from Brazil; the median sample size was 242.5, median age 73.1 and 43.5% were female. In total, 22/26 used the Clinical Frailty Scale; reported mortality ranged from 14 to 65%. Most, but not all studies showed an association between increasing frailty and a greater risk of dying. Two studies indicated a sub-additive relationship between frailty, COVID-19 and death, and two studies showed no association. CONCLUSIONS: Whilst the majority of studies have shown a positive association between COVID-19-related death and increasing frailty, some studies suggested a more nuanced understanding of frailty and outcomes in COVID-19 is needed. Clinicians should exert caution in placing too much emphasis on the influence of frailty alone when discussing likely prognosis in older people with COVID-19 illness.


Subject(s)
COVID-19/mortality , Frail Elderly , Frailty/complications , Hospital Mortality , Aged , Female , Humans , Male , Meta-Analysis as Topic , SARS-CoV-2 , Treatment Outcome
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