“Detection of Cognitive Impairment in Multicultural Communities” and the AD8 Dementia Screening

Last week, the Institute on Aging welcomed James E. Galvin, MD, MPHProfessor of Neurology, Psychiatry, and Nursing, New York University, to participate in the IOA Visiting Scholars Series. His presentation, titled “Detection of Cognitive Impairment in Multicultural Communities,” discussed different methods of diagnostic testing as well as the process and factors of these methods.

The risk of Alzheimer’s disease in African Americans and Hispanics is 1.5 – 2 times greater than in Caucasians, and the risk in women is 1.5 times greater than men. While most of Alzheimer’s and dementia cases are not caught until later in the disease, he explained that early detection of these conditions through clinical diagnoses is increasingly important, especially in order to enroll in research as soon as possible.

Patients or their family members are often the first to report any early signs or symptoms of cognitive impairment, most commonly after noticing a decline in memory. However, the process of a diagnosis does not end there. Clinical screenings such as the Mini Mental State Exam (MMSE), Mini-Cog, or Clinical Dementia Rating (CDR) can be administered, but some of these methods can be very time consuming and impractical for routine use. More formal neuropsychological testing can also be a very helpful tool, but depending on geographic location and the prevalence of specialists in your area, this option is not always readily available. For example, in New York, it is as if there is a psychologist on every corner, explained Dr. Galvin, however, in more Midwestern states such as Missouri, specialists are exceptionally more difficult to come by.

Dr. Galvin stressed the idea that regardless of what screening or evaluative method is used, one of the main factors to focus on during the detection of cognitive impairment is the onset of obvious change in a person’s mood or behavior. If an elderly person is experiencing symptoms related to dementia, it should only raise concern if these symptoms are recently developed, new occurrences.

Another common theme that seems to surround the issue of early diagnoses is the relatively low level of understanding, awareness, and familiarity with the detection of these conditions, both in the patient and the physician. Patients often recognize their symptoms, but not the severity of the problem, therefore they are not identifying with the condition. According to research, they are also typically very willing to undergo screening and evaluation, however, they are simply unaware that Primary Care Physicians are able to do so.

Dr. Galvin also revealed that generally speaking, physicians tend to “lack knowledge about dementia” and are much more likely to recognize a well developed disease compared to a new onset. More experienced physicians are also more likely to simply “screen” by asking a patient general questions such as “How is your memory?” whereas younger, less experienced physicians are more likely to provide a much more in-depth screening.

As previously mentioned, more formal screenings for dementia can be time consuming and very hard to come by, which can be quite an inconvenience toward the goal of early detection. In an effort to address this issue, Dr. Galvin and his colleagues developed the AD8 test (see image below), a “brief, valid, and reliable informant-based measure that is sensitive and predictive in discriminating nondemented older adults from those with even mild forms of dementia from all causes in an efficient, inexpensive, culturally sensitive and socially acceptable manner that is generalizable and translatable to the community-at-large.”

Screen Shot 2014-06-24 at 10.32.42 AM

Taking only a few minutes to administer, this “yes/no” format questionnaire provides a significantly more convenient way to detect change in a patient compared to their previous levels of function and ultimately detect even mild levels of cognitive impairment. It is often paired with performance measurement tests such as Mini-PPT (Mini Physical Performance Test) and the use of measurement tools such as Dynamometer to test grip strength, Body Composition Scales to measure impedance, and tape measures to determine girth. Such tests are very helpful in detecting sarcopenia, the loss of muscle mass and strength as you age, which has been linked to a higher risk of cognitive impairment.

View Dr. Galvin’s full description of AD8 here:



The 2014 Sylvan M. Cohen Annual Retreat

“The Gender Gap in Aging & the 21st Century Longevity Revolution”

This year the Institute on Aging’s Sylvan M. Cohen Annual Retreat was held on Wednesday, May 14 in the Smilow Center for Translational Research at the University of Pennsylvania. Its focus was on the cognitive differences between aging men and women and our growing efforts toward sustaining longevity.

To tackle these topics, the IOA partnered with the Penn Center for the Study of Sex and Gender in Behavioral Health and Medicine. The IOA was delighted to welcome Co-Directors, C. Neill Epperson, MD, and Tracy L. Bale, PhD, as well as visiting scholar Susan M. Resnick, PhD, Chief of the Laboratory of Neuroscience at the National Institute on Aging, NIH as presenters.

Lectures covered different cognitive aspects of the aging process, contributing stress factors, and how these factors differ between men and women. The Retreat concluded with the IOA’s annual Poster Session, ranging in a variety of topics in basic science, clinical research, and education & community.

Over 45 posters, submitted by Penn affiliates as well as from other area colleagues, universities, and community groups were displayed throughout the lobby of the Smilow Center. After thorough review and deliberation from our judges, first and second prizes were awarded to the best poster submissions in two separate categories; basic science and clinical research/education & community.

This slideshow requires JavaScript.


A Telephone-based Intervention for Chronic Pain in Older Adults Enrolled in a Behavioral Health  Care Management Program

By: J. Zimmerman, J. Haratz, S. Leong, A. Helstrom, A. Benson, S. DiFilippo, J.E. Streim, D.W. Oslin



“Penetrating Torso Injuries in an Elderly Population: An Urban Trauma Center’s Experience”

By: D. Scantling, K. Delgado, D. Holena, J. Pascual, P. Reilly, S. Allen




Defining Kapβ2 as a Protein Disaggregase for ALS Disease Protein: FUS”

By: L. Guo, H. Wang, N. Singh, J. Shorter




MMP-9 in Subsets of Spinal Motor Neurons Drives Loss of Fat Muscle Innervation in ALS

By: K. Spiller, A. Kaplan, C. Towne, K.C. Kanning, P. Aebisher, C.E. Henderson




The Success and Impact of Alzheimer’s Disease Centers is Confirmed

HughesHeadshotUsing social network analysis and examining all 12,170 articles published by an affiliated Alzheimer’s Disease Center between 1985-2012, corresponding author, Michael E. Hughes, PhD, and his colleagues* were able to verify the extraordinary impact and success of the ADC program over the past 25 years.

“Oddly enough, our efforts in this field of research started from an interest in baseball,” explains Dr. Hughes. “I’ve been a baseball fan my entire life, and I’ve followed Bill James’ work on sabermetrics for some time.  When I was a postdoc in John Hogenesch’s lab at Penn, we both read Michael Lewis’ “Moneyball” at around the same time… My mentor, John Hogenesch, was struck with the idea that market inefficiencies could be exploited through better and more quantitative evaluation methods, and over beer on Friday afternoon, he suggested we apply a Moneyball approach to the study of scientific productivity.”

Once Dr. Hughes and Dr. Hogenesch had published their first paper on this subject, the ADC study fell next in line. “We were approached by John Trojanowski, who suggested we apply the same computational tools to study the growth and productivity of Alzheimer’s Disease Centers (ADCs),” Dr. Hughes continued. As it turns out, Dr. Trojanowski’s instincts were right on target. As Dr. Hughes explained, “the scope, ambitions, and duration of the ADC project makes it ideal for doing these sorts of longitudinal, social networking studies.”

With the help of Dr. Trojanowski, Dr. Hughes and Dr. Hogenesch were able to reach a number of connections within the ADCs and the National Institutes of Health (NIH) for the support that they needed to move forward with their research.

While Dr. Hughes expected to see a fair level of inter-institutional collaborative projects, seeing that this is “exactly what the ADC program set out to do”, the rate of growth was much higher than his expectations. According to the findings, there continues to be a steady increase in the frequency of these collaborative studies and/or articles between the ADCs.  Moreover, Dr. Hughes revealed that in addition to ADC papers tending to have a higher level of impact than average Alzheimer’s disease publications to begin with, “the publications emerging from inter-ADC collaborations tend to be even more influential than that.” This is great news for Alzheimer’s Disease Centers and their supporters.

Screen Shot 2014-06-06 at 3.04.23 PM

The access to such an effective means of measuring success becomes increasingly important when considering the weight of its results. “The funding climate is extremely tight, and Alzheimer’s Disease and other neurodegenerative diseases are projected to become nothing short of catastrophic in our lifetime.  Given finite resources and an approaching public health crisis, it makes perfect sense to pay close attention to how to best spend every public dollar,” explains Dr. Hughes, but “the broadest interpretation of these results suggests that shared resources, shared tools, and open exchange of data and ideas makes everyone’s science better.”

While this is the first study of its kind to measure the productivity of Alzheimer’s Disease Centers, Dr. Hughes both suspects and encourages the continued use of social network analysis for future ADC research and in other scientific fields as well.

To read Hughes’ full investigation, visit: The Growth and Impact of Alzheimer Disease Centers as Measured by Social Network Analysis

* Affiliated authors: John Peeler, BA; John B. Hogenesch, PhD; John Q. Trojanowski, MD, PhD