Timing of Onset and Rate of Decline in Learning and Retention in the Pre-Dementia phase of Alzehimer’s Disease
Learning and memory are impact our lives every single day. We are constantly retrieving old information from our long term memory and simultaneously learning new information through our sensory memory. However, time goes by and human age the brain decays and memories that were once strong and easy to recall are challenging. The hypothesis of this study to analyze the trajectories of declines in retention as well as the learning process of the phase before the original diagnosis of Alzheimer’s disease (AD) researchers in this study used the picture version of the Free and Cued Selective Reminding Test with Immediate Recall (pFCSRTþIR) to measure this process. Additionally, in this study researchers defined learning to be measured by the overall sum of free recall over three tests. Moreover, researchers tested the retention which was interpreted in two ways. One way was by delayed free recall (DFR) and by savings and the other was DFR adjusted for learning. The hypothesis was supported because simultaneously both learning and delayed free recall displayed commensurate figures of deterioration in prior years before the official diagnosis of AD.
The participants in this study were 217 Baltimore Longitudinal Study of Ageing (BLSA) participants who had in time developed Alzehimers diseased between January 1985 and December 2015 and was subjected to the pFCSRT+IR. All the participants signed a consent form which was given before each evaluation. All of the participants data was recorded and analyzed even after the onset of AD.
As stated before, the assessment of three tests were used to conduct this study. Initially, the overall evaluation of 217 participants with AD from BLSA started when the participants were diagnosed. Change point models were used to measure the participants before the initial diagnosis of AD. During this time, retention decay and learning was measured. Retention was determined in two different methods. By, saving and by DFR which was adjusted for learning.
Diagnosis of Dementia
All neuropsychological and clinical information gathered everyone who participated in this study was reviewed if their Clinical Dementia Rating score was equal to or above .5. Additionally, if the participants attained three or more errors on their Blessed Information-Memory Concentration Test. Additionally, the participants in this study were reviewed upon withdrawal or death. The diagnosis of acute onset of dementia depended on the information report, broad battery of neuro cognitive tests which include the pFCSRT+IR scores and the patient's clinical history.
Prior to the pFCSRT+IR was provided to the participants the 16-line drawing was tested for naming. All participants were instructed to seek out a card which held four of the drawing (e.g. oranges) for an artifact that was specific to a category cue (e.g., fruit or vegetables). The procedure went as follows; out of all of the four items that were pointed out, they were immediately tested for recall which was then followed up by cued recall for specific items. The researchers tested and replicated this phase16 times for the drawings. The order that the researchers used to test this phase was by first having free recall, cued recall for remembered item that failed to be retrieved. Overall, the sum for learning was measured and the maximum of 48 was reached. The two retention measures: savings defined by dFR divided by a third and final trial free recall. TheDFR was then tested15-20 minutes after learning without representation of artifacts so that all participants had a delayed free recall time.
In this study, to measure the accumulation and the amount of times the change points deviated from baseline or showed abnormal activity, three models were used with sumFR, DFR and the savings measures are used. These as separate outcomes with the time, which is measured in years to diagnosis of Alzehimers was used as the central predictor and normal baseline for this study. These three models that were used to conduct this study was the no-change point model, one-change point model and two-change point model. The models were used to approximate utilized maximum likelihood method. The selection of the models were founded upon the Akaike Information criterion and the likelihood ratio test. The model display revealed just how many change points there were in these measurements as well as noting the time of the change points in those with AD and how long each stage lasted.
All estimates were measured in SAS 9.4.
For clinical Alzheimer’s disease, the participants had a mean age of 75.3. Of these participants, 51% were male and 49% female. This test consisted of 19 evaluations up to 23 years that averaged to be 8 years. The foundation of the mean was 10 years of all participants who developed dementia. As for learning, the first change point was indicated to be 6 years before diagnosis. Whereas, the second change point is 1 year. These two change points show the rate of decline in three stages: Before, the first change point it is −0.14 per year. In between the first and second stage, the point is −1.54 per year and after the second is −2.50 per year. For sumFR, the first change point is 31 and the second is 24. For DFR, the results showed that the first change point is 7 years before the diagnosis of AD, second is 2.9 years. The DFR was 11.7 initially but then dropped to 9.2. The rate of these declines are -0.031 per year, -.56 per year and -1.06 per year. These grounding results show that there was no significant different in the DFR change points for the first and second position. Overall, the savings index revealed that pre-dementia symptoms started around 5 years before participants attained their diagnosis of Alzheimers.
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This study was used to compare the brain’s understanding of learning and retention deficits in the pre-diagnosis phase of AD. By evaluating the predementia stages researchers are able to capture trends in this disease and hopefully prevent or even slow down the rate of dementia. Overall, this study was supported because there were similarities for each measure: the common age that participants received dementia was around the age 66. However, 7 years before diagnosis of AD, there was an progressive decay over the next 5 years leading up to the diagnosis. Additionally, at the genesis of this study it showed that 1.9-2.9 years before the Alzheimer's diagnosis, the participants showed an acute progressive decline for retention decay and learning. There was an allotted 4 years between the first two change points in the retention decay and learning. In this study, the failure to learn new material was apparent in participants before clinical diagnosis lines up parallel with studies that revealed that pFCSRTþIR may be helpful in prevention trials of AD. These prevention trials will have focused on the reduction of symptoms in individuals who display trace symptoms of Alzheimer’s disease but whom have not been officially diagnosed with yet. In the pFCSRTþIR, retention and learning did not differentiate in the sensitivity for any detection of accelerated decline in AD, which was the opposite of the DFR. The DFR, was less sensitive to detecting any accelerated decline in the pre-dementia stages. A reason could be due to the pFCSRTþIR using controlled learning, which searches for specific articles in a category that solidifies semantic processing of the items presented to the participants. The participants in this study had cognitive control throughout this study which promoted learning during the test phase. By doing this the researches are enabled to measure the retention of material that is inadequately learned due to the reasons that the learning conditions are uncontrolled which additionally is an additional factor which contributes to the contradictory outcomes in the consistency of retention decay and learning in the predementia phase of AD. In conclusion to this study, the researchers display that both retention decay and learning happen years before the onset of clinical symptoms of Alzheimer's disease.
In this study, the methods that were lacking were the normal baseline of participants without Alzeihmers disease. Additionally, this study there is a need for further research examination into obtaining a larger sample and perhaps people who do not have dementia. By including a more variety of participants, researchers are able to establish a healthy and normal baseline that can be compared to those who have symptoms of dementia. A limitation of the pFCSRTþIR scores included was from the diagnostic case conferences which was up to 2010 relied on all the information at that time. While this use of measurement was apt and accurate for that time, this study perhaps needs a more timely and up-to-date use of measurement which would be helpful to current research. The stimuli were chosen from a small sample from 217 Baltimore Longitudinal Study of Ageing (BLSA). To improve this study, gathering participants from different areas would help create a broader look at Alzheimer's Disease. I believe that this area of study was worth the investigation and research because it allows researchers to examine ways to prevent and even slow down the decay of the brain with those who develop early onset symptoms of alzheimer's disease. This is extremely beneficial to those who have a past medical history of dementia in their family. This interference at the earliest sign could be beneficial to try and prevent this disease moving forward into the next generations. This study seemed to fit the conclusion that there was a similarity between learning and retention decay in early onset of dementia. Specifically, I liked that the researchers used the pFCSRTþIR to measure the free recall and cued recall for the items for the participants. I have never heard of this method before and it was very intriguing to see how these researchers measured how accurate participants with pre-dementia scored. I found it interesting when free recall failed that they used cued recall to aid participants forward. I would like to see participants be tested with more categories than fruit. I would love to see more complex information and personal information be tested as well to see where specifically failed memory starts. I would also like more information on whether or not the character of the person changed with time. Did they get more aggressive over time? I wonder if this measurement would have also worked with retrieval of memory after a patient experiences a stroke or transient ischemic attack. I am intrigued to understand if cued recall could work if a patient sees evidence which could perhaps act like cues from their TIA and see if they could recall the events from their accident. Personally, I would be interested in learning how the brain and its network neurons work and if there are effects of learning memory and retention, in areas specifically affected by TIA and if resolution by using these methods can help “rebuild” neurons that were harmed by this stroke. Perhaps, using this method will help attain the integrity of the brain or build it back up so that dementia or effects of TIA are slowed down or even haltered.
- Grober, E., An, Y., Lipton, R. B., Kawas, C., & Resnick, S. M. (2019). Timing of onset and rate of decline in learning and retention in the pre-dementia phase of Alzheimer’s disease.
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