Forskningsartikler

Abstract:
Background/Objectives:
Old age and cognitive impairment/dementia are risk factors for falling and fall-related injuries. We have, in a previous study in persons with cognitive impairment, shown that falls were associated with frailty, reduced physical fitness, and cognitive reduction. Falls were independent of the disorders causing the impaired functions. Because most falls are innocent, knowledge of predictors of fall-related injuries seems more clinically relevant than the predictors of falls. Predictors of falls and fall-related injuries are not necessarily identical. The aim of this follow-up study to our previous one in the same population was to explore predictors of fall-related injuries in fallers and compare these predictors with those of falls.
Methods:
This study and our previous study used data from the “The Norwegian Registry of Persons Assessed for Cognitive Symptoms” (NorCog), a Norwegian research and quality registry with a biobank. The registry included consecutive home-dwelling persons referred to Norwegian specialist healthcare units for assessment of cognitive decline. This study included 3774 persons from our previous study who experienced falls last year and compared persons with and without a fall-related injury. A fall-related injury was defined as admittance to a hospital for the injury.
Results:
The annual incidence of fall-related injuries in the fallers was 884/3774 (23.4%). Female sex, older age, lower BMI, in need of public health service and walking assistance, and low Hb and Ca were independent predictors of fall-related injuries, indicating reduced physical fitness and state of health and a high burden of comorbidity. Injuries were not associated with the degree of cognitive impairment or the dementia diagnosis.

Conclusions:
In home dwelling persons with impaired cognitive functions and falls, fall-related injuries were associated with reduced physical fitness and state of health. In contrast to predictors of falls, neither the degree of cognitive impairment nor the dementia diagnosis was associated with fall-related injuries. The difference is comprehensible. Persons with cognitive impairment or dementia might have reduced power of judgment and be inattentive, unconcerned and careless, which increases the fall incidence but not the risk of injury once falling. Prevention of fall-related injuries should focus on relieving comorbidities, improving physical fitness and general health rather than on cognitive improvement.

Per G. Farup, Knut Hestad and Knut Engedal

Abstract:

Background: Studies have shown that quantitative EEG is useful in predicting conversion from mild cognitive impairment (MCI) to Alzheimer’s disease dementia (ADD) and dementia with Lewy bodies (DLB). As subcortical pathology is present and executive impairment is common in DLB, we hypothesized that EEG could predict conversion in patients with impaired executive function and any subcortical pathology.
Methods: We included 113 patients with MCI from five Nordic memory clinics, 80 (71%) with amnestic MCI, 17 (15%) with dysexecutive MCI (deMCI), 3 (3%) with aphasic, 2 (2%) with visuospatial and 11 (10%) with unspecific MCI. Patients were examined with EEG in a resting state applying the statistical pattern recognition (SPR) method and followed up for five years. Eleven drop-outs were assessed after baseline. Receiver operating characteristic (ROC) analyses were used to examine the ability of EEG to predict conversion.

Results: Sixty patients converted to dementia, 47 to ADD, eight to vascular dementia, two to DLB, one to frontotemporal dementia and two to unspecific dementia. Eight (11%) recovered and 45 (40%) remained MCI stable. ROC analyses revealed that EEG predicted conversion from dysexecutive MCI to dementia with area under the curve (AUC) of 0.92 (95% CI 0.76-100), sensitivity of 89% and specificity of 100%. Subcortical pathology was present in 89% of the dysexecutive MCI converters. EEG did not predict conversion from amnestic MCI to dementia.
Conclusion: This study demonstrates that quantitative EEG using the SPR method predicts conversion from deMCI to dementia disorders with subcortical pathology with high sensitivity and specificity.

Knut Engedal, Lars-Olof Wahlund, Christian Sandøe Musaeu,  Peter Hoegh, Maria Lage Barca, Thorkell Eli Gudmundsson, Birgitte Bo Andersen, Daniel Ferreira, Mala Naik, Anne Rita Oeksengaard, Jon Snaedal

Abstract:

Delirium is a common cause and complication of hospitalization in the elderly and is associated with higher risk of future dementia and progression of existing dementia, of which 70% is Alzheimer’s disease (AD). AD and delirium, which are known to be aggravated by one another, represent significant societal challenges, especially in light of the absence of effective treatments capable. The intricate biological mechanisms have led to numerous clinical trial setbacks and likely contribute to the limited efficacy of existing therapeutics. Artificial intelligence (AI) presents a promising avenue for overcoming these hurdles by deploying algorithms to uncover hidden patterns across diverse data types. This review explores the pivotal role of AI in revolutionizing drug discovery for AD and delirium from target identification to the development of small molecule and protein-based therapies. Recent advances in deep learning, particularly in accurate protein structure prediction, are facilitating novel approaches to drug design and expediting the discovery pipeline for biological and small molecule therapeutics. This review concludes with an appraisal of current achievements and limitations, and touches on prospects for the use of AI in advancing drug discovery in AD and delirium, emphasizing its transformative potential in addressing these two and possibly other neurodegenerative conditions.

Ruixue Ai, Xianglu Xiao, Shenglong Deng, Nan Yang, Xiaodan Xing, Leiv Otto Watne, Geir Selbæk, Yehani Wedatilake, Chenglong Xie, David C. Rubinsztein, Jennifer E. Palmer, Bjørn Erik Neerland, Hongming Chen, Zhangming Niu, Guang Yang, Evandro Fei Fang

Abstarct: 

We examined associations between body mass index (BMI), waist circumference (WC), and dementia risk, and differences in BMI and WC trajectories before dementia diagnosis. We included 9,739 participants (54% women) aged 70+ from the Trøndelag Health Study (HUNT4 70+). BMI was measured four times (1984-2019) and WC three times (1995-2019). Dementia diagnoses were clinically assessed at HUNT4 70+ . Women and men with dementia had higher midlife BMI and WC than those without dementia. These differences diminished closer to diagnosis, especially in women. Midlife obesity in both sexes and midlife overweight, high WC, and overweight/obesity with high WC in men were linked to higher dementia risk. Lower dementia risk was observed with late-life overweight for both sexes, late-life high WC in women, late-life overweight/obesity with normal WC in men or high WC in women. Adiposity measures and their changes influence dementia risk differently in women and men.

Ekaterina Zotcheva, Bjørn Heine Strand, Vegard Skirbekk, Kay Deckers, Steinar Krokstad, Gill Livingston, Archana Singh-Manoux, Geir Selbæk

Abstarct:

Despite a well-known inverse association between education and dementia risk, the mediating mechanisms are not well understood. We explored how lifestyle and health risk factors across the life-course mediate the relationship between education and dementia among adults aged 70 + years. We included 7,655 participants with dementia diagnoses and education information, using a historical cohort design linking prospective exposure data across the life course from the HUNT4 70 + Study with registry data from Statistics Norway and earlier HUNT surveys. We conducted causal mediation analysis to assess the mediating roles of occupational characteristics, lifestyle factors (smoking, physical inactivity), and health risk factors (obesity, hypertension, diabetes, hearing impairment, cardiovascular diseases, LDL cholesterol, depression, anxiety) assessed during early, middle, and late adulthood in the relationship between education and dementia in later life. Participants with lower education were more likely to have dementia with odds ratios of 1.99, 1.88, 1.83 for the model’s accounting exposure to mediators during early, middle, and late adulthood, respectively. These associations were partially mediated by the joint effect of health and lifestyle risk factors from early through late adulthood (mediated 11.55-19.50%). Health risk factors from early to late adulthood jointly mediated 6.85-13.06% of the effect of low education on dementia risk later in life. Additionally, lifestyle factors during middle and late adulthood jointly mediated 4.11-4.96% of the total effect of low education on dementia risk later in life. Educational differences in dementia risk can partly mediated by lifestyle and health factors across the life course. These findings suggest potential targets to address varying dementia risks linked to education levels.

Teferi Mekonnen, Vegard Skirbekk, Asta Kristine Håberg, Bo Engdahl, Ekaterina Zotcheva, Astanand Jugessur, Catherine Bowen, Geir Selbaek, Hans-Peter Kohler, Jennifer R Harris, Sarah E Tom, Steinar Krokstad, Trine Holt Edwin, Dana Kristjansson, Merete Ellingjord-Dale, Yaakov Stern, Bernt Bratsberg, Bjørn Heine Strand