Thought Provoking Work May Reduce Later Life Cognitive Decline

 My last six years of working were as a mainframe computer programmer for IBM as a consultant, so I got dumped into problem situations with no systems employees still there(just offshore contractors) and no one on the business side knew what the systems were supposed to do. And we were expected to solve the problems in weeks, not months.

Thought Provoking Work May Reduce Later Life Cognitive Decline

Summary: Engaging in complex, thought-provoking work may lower the risk of mild cognitive impairment (MCI) in older age. Conducted by researchers at Oslo University Hospital, the study analyzed job demands of over 7,000 people across 305 occupations in Norway, linking higher cognitive job demands in one’s 30s through 60s to a reduced incidence of MCI post-70.

The research categorized jobs by the nature of tasks—routine manual, routine cognitive, non-routine analytical, and non-routine interpersonal—with teaching, a high cognitive demand job, showing lower rates of MCI compared to less demanding roles like mail carrying. Adjustments for demographic and lifestyle factors still showed a 66% higher risk of MCI in those with the least cognitively demanding jobs.

Key Facts:

1. The study involved an extensive demographic, assessing cognitive job demands and their impact on 7,000 individuals aged 70 and above.
2. Participants in the highest cognitive demand jobs had a significantly lower rate of mild cognitive impairment (27%) compared to those in the lowest demand jobs (42%).
3. The research supports the notion that intellectually stimulating work can serve as a protective factor against cognitive decline later in life, although further studies are needed to identify specific beneficial tasks.

Source: AAN

The harder your brain works at your job, the less likely you may be to have memory and thinking problems later in life, according to a new study published in the April 17, 2024, online issue of Neurology.

This study does not prove that stimulating work prevents mild cognitive impairment. It only shows an association.

“We examined the demands of various jobs and found that cognitive stimulation at work during different stages in life—during your 30s, 40s, 50s and 60s—was linked to a reduced risk of mild cognitive impairment after the age of 70,” said study author Trine Holt Edwin, MD, PhD, of Oslo University Hospital in Norway.

“Our findings highlight the value of having a job that requires more complex thinking as a way to possibly maintain memory and thinking in old age.”

The study looked at 7,000 people and 305 occupations in Norway.

Researchers measured the degree of cognitive stimulation that participants experienced while on the job. They measured the degree of routine manual, routine cognitive, non-routine analytical, and non-routine interpersonal tasks, which are skill sets that different jobs demand.

Routine manual tasks demand speed, control over equipment, and often involve repetitive motions, typical of factory work. Routine cognitive tasks demand precision and accuracy of repetitive tasks, such as in bookkeeping and filing.

Non-routine analytical tasks refer to activities that involve analyzing information, engaging in creative thinking and interpreting information for others. Non-routine interpersonal tasks refer to establishing and maintaining personal relationships, motivating others and coaching. Non-routine cognitive jobs include public relations and computer programing.

Researchers divided participants into four groups based on the degree of cognitive stimulation that they experienced in their jobs.

The most common job for the group with the highest cognitive demands was teaching. The most common jobs for the group with the lowest cognitive demands were mail carriers(My dad was one and ended up with Parkinsons and dementia) and custodians.

After age 70, participants completed memory and thinking tests to assess whether they had mild cognitive impairment. Of those with the lowest cognitive demands, 42% were diagnosed with mild cognitive impairment. Of those with the highest cognitive demands, 27% were diagnosed with mild cognitive impairment.

After adjustment for age, sex, education, income and lifestyle factors, the group with the lowest cognitive demands at work had a 66% higher risk of mild cognitive impairment compared to the group with the highest cognitive demands at work.  

“These results indicate that both education and doing work that challenges your brain during your career play a crucial role in lowering the risk of cognitive impairment later in life,” Edwin said.

“Further research is required to pinpoint the specific cognitively challenging occupational tasks that are most beneficial for maintaining thinking and memory skills.”

A limitation of the study was that even within identical job titles, individuals might perform different tasks and experience different cognitive demands.

Funding: The study is supported by the National Institutes of Health.

About this cognition and aging research news

Author: Natalie Conrad
Source: AAN
Contact: Natalie Conrad – AAN
Image: The image is credited to Neuroscience News

Michael J. Fox Foundation and IBM use AI to uncover multiple underlying types of Parkinson’s disease

If we had any leadership at all in stroke we could accomplish so much. But no, we have shit for brains instead. 

Oops, I'm not playing by the polite rules of Dale Carnegie,  'How to Win Friends and Influence People'. 

Telling stroke medical persons they know nothing about stroke is a no-no even if it is true. 

Politeness will never solve anything in stroke. Yes, I'm a bomb thrower and proud of it. Someday a stroke 'leader' will try to ream me out for making them look bad by being truthful , I look forward to that day.

Michael J. Fox Foundation and IBM use AI to uncover multiple underlying types of Parkinson’s disease

No one knows why some people with Parkinson’s will have their disease turn severe while others may not, but artificial intelligence researchers at IBM and the Michael J. Fox Foundation think they may have cracked the code.

Using Big Blue’s machine learning algorithms to analyze data gathered from patients over as many as seven years, the programs were able to spot patterns in their symptoms linked with neurodegeneration.

This led to a computer model that could help predict how a patient’s particular case may progress—assisting physicians in prescribing the right therapies at the right time, or determining who may benefit the most from a clinical trial.

In fact, the AI helped uncover a series of overlapping courses that the disease may take—while accounting for the differences among individuals and the effects of different medications—suggesting that a rigid classification of Parkinson’s by simple subtype might not be enough to illustrate the whole picture.

In a paper published in The Lancet Digital Health, researchers identified eight unique states in Parkinson’s, with both motor and non-motor symptoms, and found that the disease could move among them over time in no particular order.

RELATED: IBM to install its first private-sector quantum computer at Cleveland Clinic

This could include different periods where the patient may have more trouble balancing their posture or walking, and when tremors and muscle rigidity may vary from mild to severe—all before terminal disease, the eighth category, which includes severe cognitive impairment.

When held up against the effects of different medications, dopaminergic drugs helped improve slow muscle movements and rigidity, also might increase sleepiness, a symptom more common in certain disease states the team identified.

The trove of data was collected from the Michael J. Fox Foundation’s Parkinson’s Progression Markers Initiative, a clinical study first launched in 2010 in partnership with more than 30 biotech, pharmaceutical, non-profit and private companies.

RELATED: Parkinson's discovery could yield new treatment strategy for young onset patients

Enrolling more than 1,400 patients worldwide, the study has collected years of patient information from health records, wearable devices and smartphones, while sequencing genomes and analyzing specimens taken over the course of their disease.

The project also compares its results to a control group of healthy volunteers, which helped validate the AI model that IBM researchers have been developing since mid-2018.

RELATED: IBM uses machine learning to detect early Alzheimer’s in blood samples

Next, the team said it plans to further refine the computer model for a more granular look into different Parkinson’s disease states while incorporating genomic and brain-imaging biomarkers. The researchers have also said their AI approach may be useful in other chronic, neurodegenerative diseases, such as Alzheimer’s and ALS.

 

Could a language test diagnose Alzheimer's? IBM is laying the groundwork

But can it distinguish between all the different types of dementia? 

You still need EXACT STROKE PROTOCOLS TO PREVENT DEMENTIA  POST STROKE. DEMAND THEM, NO EXCUSES ALLOWED FROM YOUR DOCTOR! YOU DON'T ALLOW INCOMPETENT PEOPLE IN THE REST OF YOUR LIFE, DEMAND COMPETENCY FROM YOUR DOCTOR.

 

Your chances of getting dementia.

1. A documented 33% dementia chance post-stroke from an Australian study?   May 2012.

2. Then this study came out and seems to have a range from 17-66%. December 2013.

3. A 20% chance in this research.   July 2013.

4. Dementia Risk Doubled in Patients Following Stroke September 2018 

The latest here:

Could a language test diagnose Alzheimer's? IBM is laying the groundwork

Doctors use brain scans and spinal taps to diagnose Alzheimer’s disease, but these methods can be expensive, invasive and usually aren’t done until after a person has shown signs of cognitive decline—at which point it can be difficult to head off the progression of the disease.

IBM thinks it has the beginnings of a solution: an artificial intelligence model, developed with Pfizer, that could eventually predict if a person will develop Alzheimer’s using a simple language test. This model, trained and tested on data from a decades-long health study, correctly predicted whether healthy people would eventually develop Alzheimer’s 74% of the time. The findings appear in the journal The Lancet eClinical Medicine.

The researchers trained AI algorithms on hundreds of short, noninvasive, standardized speech samples from the Framingham Heart Study, a well-known study tracking various health measures in more than 5,000 people and their families since the 1940s. The samples are from a test called the Cookie Theft Task, where people are asked to describe a drawing in their own words.

“Through our work in other disease conditions, we know this is an extremely descriptive cognitive assessment. Each person uses cognitive processes to visually receive input, think about it and turn that into a bunch of words,” said Ajay Royyuru, IBM Fellow and vice president of healthcare and life sciences research at IBM. “It’s a round-trip of cognitive processes occurring in the head.”

RELATED: Alzheimer's blood tests show new promise, giving decades of early warning

Participants in the Framingham Heart Study took the test over and over again, providing their own baseline data and allowing the researchers to look into how early the tests could signal cognitive decline, Royyuru added.

The researchers tested the model on speech samples taken from 80 people in the study before they showed signs of cognitive decline. The model predicted the onset of Alzheimer’s disease an average of seven and a half years before patients were officially diagnosed, the study found. But the test won’t necessarily replace today’s clinical standard; it could be used, rather, as an early step to recommend a brain scan.

“It doesn’t mean diagnosing Alzheimer’s at that point, but simply being able to see the abnormality here. It’s enough to consult a neurologist to get to an assessment that is more thorough,” Royyuru said. But further on, IBM’s work could lead to the development of new digital biomarkers and noninvasive tests that may move the timeline of Alzheimer’s diagnosis earlier, he said.

In the future, this model could be applied to a consented phone conversation, or through an app on a mobile phone, Royyuru said. It could become a test that people take routinely, to get snapshots of their cognitive state throughout their life.

RELATED: In a test for Hahn's FDA, Biogen submits controversial Alzheimer's drug aducanumab

The ability to catch Alzheimer’s early could play a key role in developing new treatments for the disease, an area that has been rife with failure. Digital biomarkers that can quantitatively gauge the progression of a person’s disease could help drug developers design better Alzheimer’s trials.

“If we look back to some failed Alzheimer’s clinical trials, they’ve not had success because the majority of the time, they recruited patients who were all over the place in progression from a disease biology viewpoint,” Royyuru said. In other words, it’s no surprise that a drug that should work at a certain stage of the disease would fail in heterogeneous population of patients at different stages.

“There is a need to characterize the state of an individual through biomarkers, particularly through digital biomarkers that allow for targeted staging and recruitment into appropriate interventional trials,” he added.

Speech and language are just one aspect of cognitive function that IBM is looking at. In a study published early last year, IBM researchers described a model that assesses proteins in the blood to predict the buildup of amyloid-beta in people’s spinal fluid, a key marker of Alzheimer’s disease. The test was accurate up to 77% of the time.

 

IBM Watson to integrate MedyMatch's AI-based brain bleed detector

Notice that nothing here is being directed from our fucking failures of stroke associations.

IBM Watson to integrate MedyMatch's AI-based brain bleed detector

MedyMatch and IBM are teaming up to bring a decision-support tool that detects bleeding in the brain to emergency rooms. The artificial intelligence-driven application will be integrated in IBM Watson Health Imaging’s offerings.
The tool is designed to help physicians identify areas in the brain where there could be potential bleeding, said MedyMatch CEO Gene Saragnese. When a patient undergoes a head CT scan in a hospital, it is sent either to an onsite processor or an offsite processor through the cloud, he said. The application uses deep learning, other patient data and clinical insights to indicate where bleeding may be present.
While the tool itself is complex, the workflow is simple, Saragnese said. Once the case is interpreted, it is returned to the hospital’s information system, so multiple physicians may view it at the same time. The whole process is designed to take less than five minutes, he said. Other detection systems are under that, 5 minutes is way too long.

Hats off to Helmet of Hope - stroke diagnosis in 30 seconds

Microwave Imaging for Brain Stroke Detection and Monitoring using High Performance Computing in 94 seconds

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Quickly identifying intracranial bleeding in the case of hemorrhagic stroke can minimize the long-term effects and could prevent death, according to the American Stroke Association. Stroke is the fourth leading cause of death in the U.S.
Launched early last year, Tel Aviv-based MedyMatch aims to deploy decision-support tools to improve healthcare, starting with the emergency room. Under the agreement, Watson Health’s imaging group will distribute the brain bleed detection tool through its established sales channels, according to a statement.
“[MedyMatch] is focused on creating new applications that help physicians make decisions in acute care settings,” Saragnese said. “… We’re not actually interested in creating a very, very large distribution network or sales force because they exist today.” The collaboration allows MedyMatch to leverage IBM’s existing infrastructure to bring its decision-support to more hospitals around the world.
Last summer, MedyMatch joined forces with New Jersey’s Capital Health to apply artificial intelligence to the analysis of stroke patients’ medical images.

VA partners with IBM to use supercomputer Watson to treat cancer

Just when the fuck will our fucking failures of stroke associations ask IBM and Dr. Watson for help in solving all the problems in stroke? They already have proven they are not smart enough to solve even easy problems themselves mainly because they haven't even tried.  IBM is already engaged in other medical questions. WHY NOT STROKE?

IBM, Pfizer team on remote monitoring for Parkinson’s care - Why not stroke?

IBM Watson Health GM: Partnerships set us apart

IBM Watson, Boston Children’s team on rare pediatric diseases

IBM Starts New Precision Medicine Program - for cancer

Massive IBM deal gives Watson purpose and puts it in pole position to transform healthcare - What about stroke?

IBM's Watson Comes to the Bedside

Why And How Healthcare Institutions Should Prepare For IBM Watson

Pharma puts Watson brain to work to speed up R&D, cut drug development costs

IBM's Watson Supercomputer May Soon Be The Best Doctor In The World

MD Anderson Cancer Center to Use IBM Watson

IBM's Watson Does Drug Discovery?

 

 

 

 The latest here:

VA partners with IBM to use supercomputer Watson to treat cancer 

IBM, Pfizer team on remote monitoring for Parkinson’s care - Why not stroke?

If our fucking failures of stroke associations actually wanted to help survivors they would be partnering with Dr. Watson/IBM to objectively monitor survivor movements so our therapists could then apply the correct stroke protocols to correct those deficits. Yes, this is totally pie in the sky, but much better to at least try something rather than the lazy press releases and prevention ideas.
It should be simple to attach monitors registering position and movement to appropriate joints and muscles on the body sending signals to the smartphone app collecting such data. Such monitors are already in Fitbits.
http://medcitynews.com/2016/04/ibm-pfizer-remote-monitoring-parkinsons/?
Watson Health may be getting all the headlines lately, but IBM’s research division is busy trying to improve healthcare as well. Thursday, Big Blue announced that it was collaborating with Pfizer to develop remote monitoring technology for treating Parkinson’s disease.
IBM and Pfizer will build an Internet-of-Things ecosystem to measure the health and quality of life of Parkinson’s patients. They want data collection to be as continuous and unobtrusive to the patient as possible.
Their sensors will gather real-time information from patients outside of a clinical environment. Then, IBM will apply machine learning to the data to help researchers advance their understanding of the disease and treatments.
“The problem in the field of chronic neurological diseases like Parkinson’s is that the symptoms that the patient experiences vary minute by minute,” Ajay Royyuru, director of healthcare and life sciences for IBM Research, said in a video supplied by the two companies. “You pretty much have to monitor the symptoms that the individual is having pretty much on a continuous basis.”
“We have an opportunity to potentially redefine how we think about patient outcomes and 24/7 monitoring, by combining Pfizer’s scientific, medical and regulatory expertise with IBM’s ability to integrate and interpret complex data in innovative ways,” Pfizer global R&D head Dr. Mikael Dolsten said in a statement.
“The key to our success will be to deliver a reliable, scalable system of measurement and analysis that would help inform our clinical programs across important areas of unmet medical need, potentially accelerating the drug development and regulatory approval processes and helping us to get better therapies to patients, faster,” Dolsten added.