Stroke remains a leading cause of death globally, with increased risk linked to lifestyle factors

 With our non-existent stroke leadership no one will be looking at the 30-day death rates and figuring out what needs to be done to reduce them sharply!  

My suggestion with no medical training is to stop the 5 causes of the neuronal cascade of death in the first week thus saving millions to billions of neurons. 

But no one listens to stroke-addled survivors like me until they have had a stroke and then it's too late.

Stroke remains a leading cause of death globally, with increased risk linked to lifestyle factors

New global data reveals a rising stroke burden, particularly in low- and middle-income countries, with increasing incidence among younger populations and growing disparities across regions.Study: Global, regional, and national burden of stroke and its risk factors, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. Image Credit: illustrissima/Shutterstock.com

In a recent study published in The Lancet Neurology, a group of researchers provided up-to-date global, regional, and national estimates of stroke burden and attributable risks from 1990 to 2021 to inform evidence-based health care and resource allocation.

Background 

The Global Burden of Disease (GBD) study shows that cardiovascular disease, including stroke, nearly doubled in prevalence from 271 million in 1990 to 523 million in 2019.

While cardiovascular mortality rates declined during the late 20th century, this progress has slowed, and some countries, including Mexico, the United Kingdom (UK), and the United States of America (USA), have seen rising mortality rates since 2010.

Stroke incidence among individuals under 55 has also increased, alongside a surge in risk factors like hypertension and obesity. Further research is essential to track trends, evaluate interventions, and shape global health strategies for stroke prevention and management.

About the study 

The GBD 2021 study on stroke burden and risk factors employed established methodologies consistent with previous estimates.

Stroke was defined based on the World Health Organisation (WHO) clinical criteria and classified into three types: ischaemic stroke (Blocked blood flow to the brain), intracerebral hemorrhage (Bleeding within the brain), and subarachnoid hemorrhage (Bleeding between the brain and its covering).

Vital registration and surveillance data were used to produce independent models for each stroke type to ensure accurate modeling. Stroke incidence and prevalence were modeled using DisMod-MR 2.1, a Bayesian software that considers various disease parameters.

Death estimates were derived using Cause of Death Ensemble modeling (CODEm). The data for the analysis included a wide range of sources, including vital registration, verbal autopsy, and risk factor exposure data.

To assess stroke burden attributable to 23 risk factors, population attributable fractions (PAFs) of disability-adjusted life years (DALYs) were calculated. These factors were grouped into four categories: environmental, dietary, behavioral, and metabolic risks.

The analysis also considered interactions between risk factors, accounting for mediation effects in the overall calculation.

The study utilized meta-regression techniques to pool relative risk data and estimate the potential reduction in stroke burden if exposure to risk factors had been at optimal levels. This comprehensive approach allowed for stratification of estimates by region, age, sex, and Socio-demographic Index (SDI).

Study results 

In 2021, global stroke statistics revealed 93.8 million stroke survivors, 11.9 million new stroke cases, 7.3 million stroke-related deaths, and 160.5 million DALYs lost due to stroke, accounting for 10.7% of all deaths and 5.6% of total DALYs across all causes.

Stroke was the third leading cause of death, following ischemic heart disease and coronavirus disease 2019 (COVID-19), and the fourth leading cause of DALYs. The vast majority of stroke burden, including 83.3% of new strokes and 87.2% of stroke deaths, occurred in low- and middle-income countries (LMICs), highlighting a stark geographical disparity.

Stroke burden varied widely across regions. For instance, Luxembourg had the lowest age-standardized stroke incidence (57.7 per 100,000), while the Solomon Islands had the highest (355.0 per 100,000).

Similarly, Singapore had the lowest death rate from stroke (14.2 per 100,000), whereas North Macedonia had the highest (277.4 per 100,000). Substantial differences in stroke burden were observed between high-income and low-income regions, with Central Asia, East Asia, and Sub-Saharan Africa facing the highest stroke burden. In contrast, high-income regions like North America and Australasia saw the lowest.

Regarding pathological stroke types, ischemic stroke was the most common, accounting for 65.3% of all new strokes in 2021, followed by intracerebral hemorrhage (28.8%) and subarachnoid hemorrhage (5.8%). However, despite ischemic stroke being the most prevalent, intracerebral hemorrhage contributed a higher percentage of total DALYs (49.6%) compared to ischemic stroke (43.8%).

Subarachnoid hemorrhage caused 6.6% of all stroke-related DALYs. These types also displayed distinct geographic and socioeconomic trends. For example, ischemic strokes constituted 74.9% of new strokes in high-income countries but only 63.4% in LMICs, where intracerebral hemorrhage was more common.

From 1990 to 2021, age-standardized stroke incidence, prevalence, mortality, and DALY rates declined globally, with the most significant reductions occurring among those aged 70 and older.

However, the number of strokes, deaths, and DALYs increased during this period due to population growth and aging. Stroke incidence among those younger than 70 also showed a rising trend. In recent years, the decline in stroke incidence has slowed, particularly since 2015, with some regions experiencing a plateau or even an increase in rates.

Conclusions 

To summarize, in 2021, stroke was the second leading cause of death and the third leading cause of DALYs among non-communicable disorders globally. Stroke burden was disproportionately higher in LMICs and regions with lower SDI, with intracerebral hemorrhage occurring nearly twice as often in LMICs compared to high-income countries.

This disparity is likely due to the higher prevalence and poorer control of hypertension in LMICs. Although there has been a global reduction in age-standardized stroke rates since 1990, the incidence, prevalence, and DALYs have increased in Southeast Asia, east Asia, and Oceania since 2015.

Journal reference:

• Feigin, Valery L et al. (2024) Global, regional, and national burden of stroke and its risk factors, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021, The Lancet Neurology. doi: https://doi.org/10.1016/S1474-4422(24)00369-7. https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(24)00369-7/fulltext 

How does climate change affect stroke risk?

If the WSO had competently solved stroke to 100% recovery it wouldn't make  a difference.  But they are completely incompetent in that regard!

Send me hate mail on this: oc1dean@gmail.com. I'll print your complete statement with your name and my response in my blog. Or are you afraid to engage with my stroke-addled mind?  You'll want 100% recovery when you are the 1 in 4 per WHO that has a stroke!

 

How does climate change affect stroke risk?

Mounting Stroke Crisis in India: A Systematic Review

 It's a crisis because you BLITHERING IDIOTS haven't figured out that the solution to this is 100% recovery protocols! Yeah that's a BHAG(Big Hairy Audacious Goal)

but leaders solve those. We have NO leaders in stroke. And the result is 10 million disabled stroke survivors every year!

Explain to me in precise terms where I'm wrong; oc1dean@gmail.com, I'm stroke-addled you know, so simple-minded me needs you to be precise in your explanation.

Looking forward to your excuses!

Mounting Stroke Crisis in India: A Systematic Review

Vedant N. Hedau • Tushar Patil

Published: March 27, 2024

DOI: 10.7759/cureus.57058 

  Peer-Reviewed

Cite this article as: Hedau V N, Patil T (March 27, 2024) Mounting Stroke Crisis in India: A Systematic Review. Cureus 16(3): e57058. doi:10.7759/cureus.57058

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Abstract

Stroke, a neurological disorder, has emerged as a formidable health challenge in India, with its incidence on the rise. Increased risk factors, which also correlate with economic prosperity, are linked to this rise, including hypertension, diabetes, obesity, sedentary lifestyle, and alcohol intake. Particularly worrisome is the impact on young adults, a pivotal segment of India's workforce. Stroke encompasses various clinical subtypes and cerebrovascular disorders (CVDs), contributing to its multifaceted nature. Globally, stroke's escalating burden is concerning, affecting developing nations. To combat this trend effectively and advance prevention and treatment strategies, comprehensive and robust data on stroke prevalence and impact are urgently required. In India, these encompass individuals with elevated BMIs, and those afflicted by hypertension, diabetes, or a familial history of stroke. Disparities in stroke incidence and prevalence manifest across India, with differences in urban and rural settings, gender-based variations, and regional disparities. Early detection, dietary changes, effective risk factor management, and equitable access to stroke care are required to address this issue. Government initiatives, like the National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases, and Stroke (NPCDCS) 2019, provide guidelines, but effective implementation and awareness campaigns are vital. Overcoming barriers to stroke care, especially in rural areas, calls for improved infrastructure, awareness campaigns, and support systems. Data standardization and comprehensive population studies are pivotal for informed public health policies.

Introduction & Background

Cerebrovascular disease (CVD) is a term used to describe all disorders that lead to stroke, which can be either ischemic or hemorrhagic. In low- and middle-income countries (LMICs), including India, the frequency of stroke increased by 100% between 1997 and 2008. This showed a 26% rise in stroke mortality worldwide during the previous 20 years [1]. Stroke continues to be the second most significant cause of death globally due to the increased mortality rate, according to the World Health Organization (WHO) 2020 [2]. Over the past four decades, there has been a statistically significant reduction in stroke incidence rates, with stroke incidence falling by 42% in high-income countries (HICs) and rising by more than 100% in LMICs [1]. Age, sex, low birth weight, ethnicity, and genetic variables are all irreversible risk factors for stroke [3]. A report of India's population-based stroke registries mentions that the majority of first-ever stroke cases reported hypertension (from Tirunelveli, 40.3%, to Cuttack, 75%), diabetes, and current tobacco use (from Varanasi, 19.3%, to Cuttack, 62.4%) [4]. Ischemic stroke (range 41.6% to 77.8%), hemorrhagic stroke (range 42.6% to 74%), and indeterminate stroke (range 2.0% to 35.9%) all had hypertension as their primary risk factor [4]. Young people's risk of stroke is considerably enhanced by smoking, drinking, having a higher BMI, having diabetes, and having high blood pressure [5,6]. A hospital-based multi-center prospective stroke registry in India to identify and recruit 10,000 acute stroke patients from 100 hospitals within the country conducted an interim analysis to determine aetiologies, clinical supervision, and outcomes with 5301 patients. According to the data, stroke patients had a number of highly hazardous factors, including heavy alcohol and cigarette use, diabetes, hypertension, and dyslipidemia [7].

The study found that stroke patients with higher frequencies of risk variables had higher short-term mortality [8]. Adopting coordinated care for stroke in LMICs is limited and insufficient, particularly in a nation like India, where the facilities available for rehabilitation are sparse [9]. The global burden of CVD has been rising, with stroke being the second most significant factor in fatalities worldwide, after ischemic heart disease in 1990 and the WHO 2020 factsheet [2,10]. A sizeable share of stroke deaths occur in LMICs, and these nations also experience more years of life lost to disability-adjusted life than high-income nations [11]. India has a greater cumulative incidence and crude prevalence of stroke than high-income nations [1]. This suggests that stroke is a significant health burden in India. Globally, there were around 25.7 million stroke survivors in 2013, along with 6.5 million stroke fatalities, 113 million years of life lost to disability, and 10.3 million new stroke cases [12]. Worldwide, the incidence of stroke is rising, mostly as a result of an older population and more risk factors such as type 2 diabetes and high blood pressure. Stroke occurrence among young people is increasing in LMICs [13]. There are regional, national, and ethnic differences in cardiovascular disease incidence, prevalence, and mortality. Due to their altered cardio-metabolic profiles and propensity for cardio-metabolic dysfunction, people from South Asian nations, especially India, have a disproportionately increased risk of cardiovascular disease [14]. To address the concerns of stroke prevention and treatment, reliable data on the burden of CVD in the Indian population is needed. To meet this demand, a comprehensive analysis of all community-based studies providing data on the mortality, prevalence, and incidence of stroke in rural, urban, and both population contexts is required. The present article aims to focus on the stroke crisis in India.

Motor and Premotor Cortices in Subcortical Stroke: Proton Magnetic Resonance Spectroscopy Measures and Arm Motor Impairment

 Absolutely NOTHING HERE WILL GET SURVIVORS RECOVERED! Stroke research, if any good at all, creates EXACT REHAB PROTOCOLS for recovery!

When you are the 1 in 4 per WHO that has a stroke, you just might want to recover! So maybe you want to do useful research NOW! Just a passing thought from a stroke addled brain! And look at all these Ph.D's not knowing that solving stroke is their job and they are completely fucking failing at it!

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

Telling supposedly smart 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.

Motor and Premotor Cortices in Subcortical Stroke: Proton Magnetic Resonance Spectroscopy Measures and Arm Motor Impairment

 
Motor and premotor cortices in subcortical stroke: protonmagnetic resonance spectroscopy measures and arm motorimpairment
Sorin C. Craciunas, MD, PhD
a,1
,
William M. Brooks, PhD
a,c
,
Randolph J. Nudo, PhD
b,d
,
Elena A. Popescu, PhD
a
,
In-Young Choi, PhD
a,c
,
Phil Lee, PhD
a,d
,
Hung-Wen Yeh, PhD
e
,
Cary R Savage, PhD
f
, and
Carmen M. Cirstea, MD, PhD
a,c,g,*
a
Hoglund Brain Imaging Center, University of Kansas Medical Center
b
Landon Center on Aging; Departments of, University of Kansas Medical Center
c
Neurology, University of Kansas Medical Center
d
Molecular and Integrative Physiology, University of Kansas Medical Center
e
Biostatistics, University of Kansas Medical Center
f
Psychiatry and Behavioral Sciences, University of Kansas Medical Center
g
Physical Therapy and Rehabilitation Science, University of Kansas Medical Center

Abstract

Background—
 

Although functional imaging and neurophysiological approaches revealalterations in motor and premotor areas after stroke, insights into neurobiological eventsunderlying these alterations are limited in human studies.
Objective—
 

We tested whether cerebral metabolites related to neuronal and glial compartmentsare altered in the hand representation in bilateral motor and premotor areas and correlated withdistal and proximal arm motor impairment in hemiparetic persons.
Methods—
 

In twenty participants at >6 months post-onset of a subcortical ischemic stroke andsixteen age and sex-matched healthy controls, the concentrations of N-acetylaspartate and myoinositol were quantified by proton magnetic resonance spectroscopy (1H-MRS). Regions of interest, identified by functional MRI, included primary (M1), dorsal premotor (PMd), and supplementary (SMA) motor areas. Relationships between metabolite concentrations and distal(hand) and proximal (shoulder/elbow) motor impairment using Fugl-Meyer Upper Extremity(FMUE) subscores were explored.
Results—
 

N-acetylaspartate was lower in M1 (p=0.04) and SMA (p=0.004) and myoinositol was higher in M1 (p=0.003) and PMd (p=0.03) in the injured (ipsilesional) hemisphere after stroke compared to the left hemisphere in controls. N-acetylaspartate in ipsilesional M1 was positively correlated with hand FMUE subscores (p=0.04). Significant positive correlations were also found between N-acetylaspartate in ipsilesional M1, PMd, and SMA and in contralesional M1 and shoulder/elbow FMUE subscores (p=0.02, 0.01, 0.02 and 0.02 respectively).
*
Corresponding author
 Hoglund Brain Imaging Center University of Kansas Medical Center 3901 Rainbow Blvd Mail Stop 1052Kansas City, Kansas US, 66160 Tel: (913) 588-4373 Fax: (913) 588-9071 .1
Present address
: Neurosurgery Department IV, Bagdasar-Arseni Hospital
NIH Public Access
Author Manuscript
 Neurorehabil Neural Repair
. Author manuscript; available in PMC 2014 June 01.

The evidence for turning the tide on #stroke is clear. What is needed is a commitment to implementation, write @sheilambrasil & @tamer_roushdy , @WorldStrokeOrg in their blog. Read it & learn more about stroke policies

What absolute fucking bullshit. I see nothing even remotely suggesting anyone is working on 100% recovery. 

Point me directly to what you consider turning the tide and I'll prove you completely wrong! Come on, it ought to be easy to take on stroke-addled me.

The evidence for turning the tide on #stroke is clear. What is needed is a commitment to implementation, write

@sheilambrasil

&

@tamer_roushdy

,

@WorldStrokeOrg

in their blog. Read it & learn more about stroke policies

Motor recovery after stroke: Lessons from functional brain imaging

FYI. I don't see how anything here helps survivors recover but since I'm stroke addled I shouldn't speak truth to stroke medical 'professionals'.

Motor recovery after stroke: Lessons from functional brain imaging

Parthasarathy Thirumala

,

Daniel B. Hier

&

Pratik Patel

Pages 453-458 | Published online: 19 Jul 2013

• Cite this article
• https://doi.org/10.1179/016164102101200320

 

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Abstract

Several theories have been proposed to explain recovery from stroke. Functional brain imaging offers an opportunity to evaluate these theories and visualize recovery after stroke. Functional brain imaging has proven to be an effective tool to map brain areas activated during a specific task. This paradigm can extend our understanding of the mechanisms of motor recovery after stroke. Functional brain imaging tools such as functional MRI, PET, transcranial Doppler ultrasonography, and transcranial magnetic stimulation can be used to evaluate motor activation after stroke. Functional imaging is proving useful in identifying areas, pathways and mechanisms involved in motor recovery after stroke. Studies have shown changes in motor organization with rehabilitation. Functional brain imaging may assist in the selection of rehabilitation methods that best foster recovery. [Neurol Res 2002; 24: 453-458]

Patterns and Outcomes of Intensive Care on Acute Ischemic Stroke Patients in the US

You can easily tell how fucking bad stroke recovery is when they don't even measure 100% recovery. As if the survivor means nothing in this regard.   Proving beyond a  doubt that survivors need to be in charge. Tell me, stroke addled as I am, EXACTLY WHERE I'M WRONG.

Patterns and Outcomes of Intensive Care on Acute Ischemic Stroke Patients in the US

Daniel Santos,

Luke Maillie and

Mandip S. Dhamoon

Originally published3 Feb 2023https://doi.org/10.1161/CIRCOUTCOMES.122.008961Circulation: Cardiovascular Quality and Outcomes. 2023;0:e008961

Abstract

BACKGROUND:

Up to 20% of acute ischemic stroke (AIS) patients may benefit from intensive care unit (ICU)-level care; however, there are few studies evaluating ICU availability for AIS. We aim to summarize the proportion of elderly AIS patients in the United States who are admitted to an ICU and assess the national availability of ICU-level care in AIS.

METHODS:

We performed a retrospective cohort study using de-identified Medicare inpatient datasets from January 1, 2016 through December 31, 2019 for US individuals aged ≥65 years. We used validated International Classification of Diseases, Tenth Revision, Clinical Modification codes to identify AIS admission and interventions. ICU-level care was identified by revenue center code. AIS patient characteristics and interventions were stratified by receipt of ICU-level care, comparing differences through calculated standardized mean difference score due to large sample sizes.

RESULTS:

From 2016 through 2019, a total of 952 400 admissions by 850 055 individuals met criteria for hospital admission for AIS with 19.9% involving ICU-level care. Individuals were predominantly >75 years of age (58.5%) and identified as white (80.0%). Hospitals on average admitted 11.4% (SD 14.6) of AIS patients to the ICU, with the median hospital admitting 7.7% of AIS patients to the ICU. The ICU admissions were younger and more likely to receive reperfusion therapy but had more comorbid conditions and neurologic complications. Of the 5084 hospitals included, 1971 (38.8%) reported no ICU-level AIS care. Teaching hospitals (36.9% versus 1.6%, P<0.0001) with larger AIS volume (P<0.0001) or in larger metropolitan areas (P<0.0001) were more likely to have an ICU available.

CONCLUSIONS:

We found evidence of national variation in the availability of ICU-level care for AIS admissions. Since ICUs may provide comprehensive care for the most severe AIS patients, continued effort is needed to examine ICU accessibility and utility among AIS.

Mentally exhausted? Study blames buildup of key chemical in brain

 WHOM  in stroke will look at this and question what research is needed to see if this is causing mental exhaustion post stroke? It will never occur, there is NO stroke leadership and NO stroke strategy. All you stroke survivors can just pound sand.

But since  glutamate poisoning is already suggested as one of the 5 causes of the neuronal cascade of death in the first days. just maybe this is a following result.  And I'm obviously stroke-addled to even think that I might know more that all these Ph.D. researchers.

Mentally exhausted? Study blames buildup of key chemical in brain

Toxicity of excess glutamate may contribute to cognitive fatigue, but some experts are skeptical

• 11 Aug 2022
• 12:40 PM
• ByEmily Underwood

SolisImages/iStock

You know the feeling. You’ve been cramming for a test or presentation all day, when suddenly you can’t remember simple things, like what you ate for breakfast, or where exactly Belize is. Now, a study hints at why we get so unraveled after hours of hard mental labor: a toxic buildup of glutamate, the brain’s most abundant chemical signal.

The study isn’t the first to try to explain cognitive fatigue—and it is bound to stir up controversy, says Jonathan Cohen, a neuroscientist at Princeton University who wasn’t involved with the work. Many scientists once thought doing difficult mental tasks used up more energy than easy tasks, exhausting the brain like exercise can do to muscles. Some even suggested drinking a sugary milkshake would make you mentally sharper than an artificially sweetened one, he says. But Cohen and many others in the field are skeptical of such simplistic explanations. “It's all been debunked,” he says.

In the new study, researchers looked at whether levels of glutamate are related to behavior that so often manifests when we’re mentally exhausted. Seeking easy, immediate gratification, for example, or acting impulsively. Glutamate typically excites neurons, playing key roles in learning and memory, but too much of it can wreak havoc on brain function, causing problems ranging from cell death to seizures.

The scientists used a noninvasive technique called magnetic resonance spectroscopy, which can detect glutamate through a combination of radio waves and powerful magnets. They chose to focus on a brain region called the lateral prefrontal cortex, which helps us stay focused and make plans. When a person becomes mentally exhausted, this region becomes less active.

The researchers divided 39 paid study participants into two groups, assigning one to a series of difficult cognitive tasks that were designed to induce mental exhaustion. In one, participants had to decide whether letters and numbers flashing on a computer screen in quick succession were green or red, uppercase or lowercase, and other variations. In another, volunteers had to remember whether a number matched one they’d seen three characters earlier. The experiment lasted for about 6 hours, with two 10-minute breaks and a simple lunch of a sandwich and piece of fruit. In the second group, people did much easier versions of the same tasks.

As the day dragged on, the researchers repeatedly measured cognitive fatigue by asking participants to make choices that required self-control—deciding to forgo cash that was immediately available so they could earn a larger amount later, for example. The group that had been assigned to more difficult tasks made about 10% more impulsive choices than the group with easier tasks, the researchers observed. At the same time, their glutamate levels rose by about 8% in the lateral prefrontal cortex—a pattern that did not show up in the other group, the scientists report today in Current Biology.

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“We’re still far from the point where we can say that working hard mentally causes a toxic buildup of glutamate in the brain,” says the study’s first author, Antonius Weihler, a computational psychiatrist at the GHU Paris Psychiatry and Neurosciences. But if it does, it underscores the well-known restorative powers of sleep, which “cleanses” the brain by flushing out metabolic waste. It might be possible to use glutamate levels in the prefrontal cortex to detect severe fatigue and monitor recovery from conditions such as depression or cancer, the team suggests.

Abnormal glutamate signaling occurs in many brain disorders. There are already drugs that target the neuronal receptors for glutamate, including esketamine, a form of the anesthetic ketamine which is used to treat depression, and memantine, which is used to treat the symptoms of Alzheimer’s disease. Researchers are also exploring glutamate-based therapies for a number of other disorders, such as schizophrenia and epilepsy.

One important limitation of the study is that the scanners used aren’t powerful enough to distinguish between glutamate and another closely related molecule, glutamine, notes Alexander Lin, a clinical spectroscopist at Brigham and Women’s Hospital. But the findings “provide the basis for examining how glutamate could potentially be modulated by medications or devices such as neurostimulation,” he says.

Sebastian Musslick, a neuroscientist at Brown University, doubts metabolic waste will turn out to be a key contributor to cognitive fatigue. He suspects instead that the uptick in glutamate as the brain tires serves a purpose. The organs in our bodies are in constant communication with our brains, letting us know when we need to eat, sleep, drink water, and go to the bathroom. Maybe the prefrontal cortex’s glutamate is sending a similar status update to the brain’s internal monitoring system, Musslick suggests.

For Cohen, the most compelling reason to be skeptical of the idea that waste products play an important role in cognitive fatigue is that it can’t explain the human ability to often push through cognitive fatigue, or effortlessly perform demanding computational tasks such as face recognition that require megawatts of energy for computers to perform. To juggle this many demanding tasks, the brain has to have a more sophisticated computational system for allocating effort than the simple buildup or depletion of metabolic byproducts, he says. “It just can’t be that easy.”

Wearable airbag technology and machine learned models to mitigate falls after stroke

 Didn't your hospital bring in this 7 years ago?

Hip protector saves you when you slip February 2015

 

Do you prefer your  hospital incompetence NOT KNOWING? OR NOT DOING?

I personally prefer massive perturbations as you walk  so you know the movement necessary to prevent falls. That would build your confidence in safely walking more that this airbag technology. But since I'm not medically trained and stroke-addled besides, you can't listen to me.

The latest here:

Wearable airbag technology and machine learned models to mitigate falls after stroke

• Olivia K. Botonis,
• Yaar Harari,
• Kyle R. Embry,
• Chaithanya K. Mummidisetty,
• David Riopelle,
• Matt Giffhorn,
• Mark V. Albert,
• Vallery Heike &
• Arun Jayaraman 

Journal of NeuroEngineering and Rehabilitation volume 19, Article number: 60 (2022) Cite this article

• 2 Altmetric

• Metrics details

Abstract

Background

Falls are a common complication experienced after a stroke and can cause serious detriments to physical health and social mobility, necessitating a dire need for intervention. Among recent advancements, wearable airbag technology has been designed to detect and mitigate fall impact. However, these devices have not been designed nor validated for the stroke population and thus, may inadequately detect falls in individuals with stroke-related motor impairments. To address this gap, we investigated whether population-specific training data and modeling parameters are required to pre-detect falls in a chronic stroke population.

Methods

We collected data from a wearable airbag’s inertial measurement units (IMUs) from individuals with (n = 20 stroke) and without (n = 15 control) history of stroke while performing a series of falls (842 falls total) and non-falls (961 non-falls total) in a laboratory setting. A leave-one-subject-out crossvalidation was used to compare the performance of two identical machine learned models (adaptive boosting classifier) trained on cohort-dependent data (control or stroke) to pre-detect falls in the stroke cohort.

Results

The average performance of the model trained on stroke data (recall = 0.905, precision = 0.900) had statistically significantly better recall (P = 0.0035) than the model trained on control data (recall = 0.800, precision = 0.944), while precision was not statistically significantly different. Stratifying models trained on specific fall types revealed differences in pre-detecting anterior–posterior (AP) falls (stroke-trained model’s F₁-score was 35% higher, P = 0.019). Using activities of daily living as non-falls training data (compared to near-falls) significantly increased the AUC (Area under the receiver operating characteristic) for classifying AP falls for both models (P < 0.04). Preliminary analysis suggests that users with more severe stroke impairments benefit further from a stroke-trained model. The optimal lead time (time interval pre-impact to detect falls) differed between control- and stroke-trained models.

Conclusions

These results demonstrate the importance of population sensitivity, non-falls data, and optimal lead time for machine learned pre-impact fall detection specific to stroke. Existing fall mitigation technologies should be challenged to include data of neurologically impaired individuals in model development to adequately detect falls in other high fall risk populations.

Trial registration https://clinicaltrials.gov/ct2/show/NCT05076565; Unique Identifier: NCT05076565. Retrospectively registered on 13 October 2021

Background

Every year, approximately 13 million individuals around the world experience a stroke [1, 2]. Falls are one of the most common medical complications experienced by individuals after a stroke, reported in up to 65% of the stroke population during hospitalization and up to 75% in the community [3, 4]. Individuals who have experienced a stroke are at an increased vulnerability for falling, related to common correlates of high fall risk in this population such as impaired mobility, medication use, and cognitive impairment [5]. Falling after a stroke can have serious consequences. There are a high incidence of severe physical injuries, including fractures, soft tissue and head injuries, and at worst, death [6, 7]. Psychologically, individuals often develop a fear of falling, leading to reduced mobility, increased social isolation, and significant reduction in quality of life [8, 9]. Financially speaking, fall related injuries constitute a burden on healthcare systems through prolonged use of services and incurred high healthcare costs [10,11,12]. Despite evidence that multifactorial rehabilitation approaches such as improving strength, balance, and visual impairments can reduce fall incidence in the older adult population [13], a recent Cochrane review concluded that there is little to no evidence of interventions that can prevent falls from occurring in individuals experiencing falls after stroke [14]. Therefore, individuals who suffer from mobility deficits after a stroke continue to experience falls, frequently and repeatedly. Without a way to prevent these falls from occurring, there is a compelling need to develop methods and tools to detect these falls before impact with the ground and reduce the associated consequences.

One conventional solution to achieve some degree of fall impact mitigation is wearing padded hip protectors in or underneath clothing, yet their significance in reducing fractures and associated injuries is limited and their current usage in the community is insignificant (likely due to discomfort and poor compliance) [15, 16]. A more novel and recent fall impact mitigation approach to address these concerns is wearable airbag technology [17,18,19,20]. These devices generally include three design components: (1) at least one sensor, such as an inertial measurement unit (IMU), to record user motion; (2) a computational model that processes the sensor signals to pre-detect fall impact; and (3) an inflatable airbag mechanism that deploys upon detection of a fall, to mitigate contact forces with the ground.

Despite continued development, wearable airbag technologies are currently only developed with the non-neurologically impaired older adult population in mind. Furthermore, the internal fall impact detection algorithms are often developed on data from young participants [21,22,23,24,25]. The algorithms have neither been specifically designed nor validated for detecting falls of individuals presenting with stroke-related motor impairments. A presumption is that the design and computational models should seamlessly transfer to users in the stroke population. However, the underlying pathophysiology of a stroke, fundamentally related to the cerebrovascular territory that is compromised in the brain, may manifest with alterations in movement kinematics and a loss of ability to control movements. These characteristic changes in movement have been observed and quantified in existing literature [26,27,28] and may translate to observed and measurable differences leading up to or during falls [29,30,31,32,33]. For example, earlier studies have analyzed and compared falls between older able-bodied and stroke individuals, and found significantly different motor responses including postural stability, trunk control, fall velocity, and timely step compensation [29, 31,32,33]. Furthermore, Dusane et al. found that within a stroke population, kinematic responses differed depending on the side of the body which a fall was initiated on (paretic vs. non-paretic) [34]. Given falls in stroke may have distinct kinematic profiles, current fall mitigation technology developed on data of generally healthy individuals might not be sufficiently sensitive or specific to detect falls in individuals who have experienced a stroke. Such inaccuracy could result in failure to deploy the airbag during a fall or cause unnecessary airbag deployments (i.e. false positives) and consequently, may lead to poor user engagement.

To address these issues, we suggest that systematic fall detection models should consider incorporating training data of individuals specific to the intended user population. Using machine learning to tune movement recognition algorithms to unique movements of particular mobility-impaired populations has been demonstrated in various applications for Parkinson’s disease [35], incomplete spinal cord injury [36, 37], and stroke [38], yet has not been applied to pre-impact fall detection in stroke populations. Thus, this paper presents considerations for a sensor-based, machine learned wearable airbag system to demonstrate the importance of pre-impact fall detection models specific to stroke-related movement impairments. We hypothesize that for fall detection in the stroke population, a pre-impact fall detection model trained on data from a stroke population would perform better than models trained on data from a control population. In other words, failure to train a model on fall movements specific to individuals with a history of stroke will result in decreased pre-impact detection performance for users of the stroke population. Furthermore, we explore secondary considerations for model development, including dataset activity composition, severity of gait impairments across users, and lead time parameter tuning.

More at link.

 

Dubious Diet Science: On the Perils of Ultraprocessed Food for Thought

An apologist on why we can't ever get specific diet protocols.  I think it's rather simple; measure the circulating micronutrients and what is the appropriate level for the benefits needed, then calculate the food needed to provide those micronutrient levels.  But I'm obviously stroke-addled and have no medical training, thus can't understand squat about anything.

Dubious Diet Science: On the Perils of Ultraprocessed Food for Thought

David Katz 16/05/2022

There is a vociferous choir of critics that makes its living, or some portion thereof, implying we know nothing reliably about dietary intake patterns and human health outcomes. 

This is, in a word, wrong. In two words, it is egregiously wrong. 

We absolutely, confidently, and irrefragably know the fundamentals of feeding Homo sapiens well- as we know the same for lions and tigers and bears; chicken, sheep, and horses. I will debate anybody, any time, on this topic- and if I lose, I will become a hula dancer.

What, then, is the basis for the critical claims? One is a misguided sanctimony about righteous research methods, as if one kind of study is the correct way to answer every question. That is no more true than the notion that one tool is best for every job. A hammer, for instance, makes an excellent hammer and a lousy saw.

Another is the wayward idea that if we don’t know everything, we can’t know anything. There are, of course, many details of nutrition we do not know, and in some cases never will, even while knowing the fundamentals. Somehow, in nutrition rather uniquely, the details we do not know are invited to obviate all we do know. Consider if the same rationale were applied to exercise.

We do not know if step 326 or step 623 is the “active ingredient” in the benefits of walking a mile; therefore, we must not know the benefits of walking. We do not know if blood flow to the right earlobe is better enhanced by a step with the left foot, or a step with the right- so again, we cannot know the benefit of walking. We cannot say with confidence that hiking is “better” than biking, or vice versa, to say nothing of swimming or dancing- and thus, we must not know anything about the benefits of any of these.

Such thinking is not applied to physical activity, presumably for the obvious reason that it is insipid to the point of idiocy. Yet such thinking passes for erudition in nutrition. It should not- but likely will so long as we, the people, are willing to stomach it.

And finally, a third is the ignominious treatment of nutrition research as the ball in a game of Ping-Pong.

The immediate provocation for this rhetorical hurl is a paper just out in the Lancet, entitled “Long-term secondary prevention of cardiovascular disease with a Mediterranean diet and a low-fat diet (CORDIOPREV): a randomised controlled trial.” To be clear, I am a fan of the Mediterranean diet for many reasons, and my vote, as a member of the US News & World Report judging panel, is among those that lifts it to the top of the “best diets” rankings year after year.

But what, really, does this title mean? There is latitude for the “Mediterranean diet,” to be sure, but there is also an established anatomy, and a validated measure of conformity to it. We can have some confidence what the designation denotes.

Not so at all for the “low-fat” diet. At the extremes, that could mean a stellar diet made up of diverse, whole plant foods that just happen to be low in fat: vegetables, most fruits, beans, lentils, whole grains- with some allowance for the higher fat content of certain fruits (e.g., olives, avocados), nuts, and seeds. At the other end of the diet quality spectrum, ingestion of- and only of- Coca Cola and Snackwell cookies would qualify as “low-fat.” For that matter, 2000kcal daily of sugar would presumably qualify, too. 

In other words, in characterizing diet quality- something that can and should be measured objectively, and should be matched between diets if the research question is about the differential effects of diet composition- the stipulation of “low-fat” is of no use whatsoever. Diet quality cannot be inferred from it, and the field of nutrition has long abandoned the idea that summary avoidance of fat is beneficial or sensible. The concept derived from good intentions, but these were coopted and corrupted early, and has proven in practice to be misguided and now obsolete.

The particulars of the dietary assignments in this study- which enrolled roughly a thousand Spanish adults, mostly men-  reveal that the Mediterranean diet was intended to be of reliably high-quality, while the low-fat diet was mediocre at best. Even more importantly- for those concerned with truth in advertising- it was not meaningfully low in fat either. The Mediterranean diet assignment aimed at 35% of total calories from fat, while the “low-fat” diet assignment aimed at 30%- and achieved a mean of just over 32%. This difference is inconsequential, and none of my colleagues devoted to studying the health effects of immanently low-fat whole food, plant-based diets would agree that this qualifies as low in fat. Nor do I.

So, the low-fat diet was not actually low in fat. But, it did exclude fatty fish (known to be the most health-promoting) and required lean fish (less healthful) in their place. It limited nut intake (known to be healthful); limited extra virgin olive oil (EVOO; known to be healthful) while allowing only for other, less healthful oils; and required consumption of low-fat dairy products 2 to 3 times daily. There are low-fat dietary patterns I could recommend with the same enthusiasm I have for the Mediterranean diet; to put it bluntly, this is not among them. Of note, the drop-out rate in the study was significantly higher, and adherence to the assignment considerably lower, for the so-called low-fat than for the Mediterranean group. Interpret that as the spirit moves you.

I trust you see the problem here. The next set of comparably qualified researchers may happen to favor some version of low-fat eating, and might use these exact methods to compare a high-quality, low-fat diet with a marginal Mediterranean diet, and “prove” the opposing conclusion. The nihilists, then, will be quick to chime in with: “see, we told you that nobody knows anything about nutrition.”

I hasten to note that I am not impugning the efforts of the researchers responsible for this particular paper; their work conforms to the prevailing standard, as affirmed by securing a rarefied perch on the prestigious pages of the Lancet. I am impugning the prevailing standard in which medicine, media, and we are all complicit.

Imagine a headline like this: “In Stunning Upset, Female Boxer Defeats Male Opponent.” The invitation here is clearly to picture two comparably qualified contestants, which, if true, would justify the titillating headline. But now imagine further that we learn only in paragraph 7 that the woman in question is an Olympian in her prime, and the “male” in question is a 9-year-old taking boxing lessons at the local gym. We would feel cheated by the divide between implication and reality, and the journalists, editors, and periodical involved would likely pay the price of our disdain.

But not so for nutrition. Peddle us just this sort of overcooked, ultraprocessed misrepresentation, and we eat it up again and again. A whole cottage industry of nutritional contrarianism runs on it, in fact, spawning professional notoriety, morning show segments, fad-diet best-sellers, and disheartening trends in the health and weight trajectories of a gullible public.

Food can be ultraprocessed to manipulate and harm us. I contend the same is true of nutrition research as food for thought.

I am a fan of the Mediterranean diet. I am neither friend nor foe to “low-fat” diets because the term is meaningless with regard to what actually matters: wholesome foods in a balanced, sensible assembly and overall diet quality. When that balance is achieved, such diets can be among the best; when not, the rubric is a convenient straw-man in research that has determined the answer before asking the question. From my perspective, that is not genuine research; it is theater.

We absolutely, irrefutably, and decisively know the fundamentals of feeding our kind of animal well. They allow for diets both high and low in total fat.

Until or unless we can affirm that we know what we know, while allowing for all the particulars we as yet do not- the appetite for ultraprocessed, uninformative diet science shared among peer-reviewed journals, the media, and us- will go perpetually fed, and forever unsated. The contrarians will profit, and public health will suffer. 

Eaters, beware.

David Katz

Healthcare Expert

David L. Katz, MD, MPH, FACPM, FACP, FACLM, is the Founding Director (1998) of Yale University’s Yale-Griffin Prevention Research Center, and current President of the American...

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