Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there. Did your doctor somehow miss the recovery protocol that Pedro Bach-y-Rita used to recover fully back in 1958 with only a partial brain?

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Tuesday, October 27, 2026

Development and validation of a simple clinical prediction model for post-stroke seizures in critically ill patients: a multicenter retrospective cohort study

 

Predicting a problem with NO solution is a fireable offense in any business!

Let's check how long you have NOT BEEN SOLVING THE PROBLEM!

Development and validation of a simple clinical prediction model for post-stroke seizures in critically ill patients: a multicenter retrospective cohort study


  • 1. Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China

  • 2. West School of Nursing, Sichuan University, Chengdu, China

Abstract


Background: 


Post-stroke seizures (PSS) are common in critically ill stroke patients, but ICU-specific risk prediction tools are lacking, and the independent impact of PSS on mortality remains controversial.


Methods: 


This retrospective multicenter cohort included 6,586 adult stroke patients from 208 US ICUs in the Collaborative Research Database (eICU-CRD). Patients were randomly divided 7:3 into training and internal validation sets. The primary endpoint was coded in-hospital post-stroke seizures identified via diagnosis codes during the index hospitalization. Candidate predictors were screened using logistic regression and least absolute shrinkage and selection operator (LASSO) regression. Model discrimination, calibration, and clinical utility were, respectively, evaluated using the area under the receiver operating characteristic curve (AUROC), calibration slopes and calibration plots, and decision curve analysis. Propensity score matching (PSM) was used to evaluate the association between PSS and in-hospital mortality and length of stay.


Results: 


The overall incidence of coded in-hospital PSS was 7.5%. Head-to-head comparison identified SOFA as the best-performing routine ICU severity score for coded PSS prediction, outperforming GCS, OASIS and APACHE II. Multivariate logistic regression analysis identified five independent clinical predictors for coded in-hospital PSS: younger age, elevated admission body temperature, pre-existing hypertension, lower mean corpuscular hemoglobin concentration, and lower Glasgow Coma Scale (GCS) score. The model achieved AUCs of 0.702 in the training set and 0.713 in the validation set, with stable performance across age, gender, and stroke subtype subgroups. A three-tier bedside risk stratification was derived, with observed coded PSS rates of 3.4, 6.8, and 16.2% for low-risk, intermediate-risk, and high-risk groups. After PSM, coded PSS was not associated with increased in-hospital mortality (adjusted OR = 0.84, p = 0.295) or prolonged hospital stay (mean difference = −0.30 days, p = 0.167).


Conclusion: 


We developed and internally validated a simple prediction model for coded in-hospital PSS in critically ill stroke patients. Coded PSS itself was not independently associated with increased mortality. This model remains a research tool that has not undergone external validation and cannot yet guide real-world clinical monitoring or pharmacological intervention. These findings are applicable to clinically evident, coded convulsive seizures and may not generalize to non-convulsive seizure phenotypes.

Prognostic performance of blood neurofilament light chain for functional outcomes in patients with ischemic stroke: a systematic review and meta-analysis

 

Prognosticating a problem with NO solution to recovery offered is a fireable offense in any business!

Prognostic performance of blood neurofilament light chain for functional outcomes in patients with ischemic stroke: a systematic review and meta-analysis


  • Neurology Department, Cangzhou Central Hospital of Hebei Medical University, Cangzhou City, China

Abstract


Introduction: 

This meta-analysis aimed to assess the association between blood neurofilament light chain (NfL) and functional outcomes in patients with ischemic stroke.


Methods: 


PubMed, Web of Science, Embase, Cochrane Library, and the China National Knowledge Infrastructure database were searched from inception through March 15, 2026. Odds ratios (ORs) and 95% confidence intervals (CIs) were pooled to quantify the association between blood NfL and functional outcomes in patients with ischemic stroke. We pooled the area under the curve (AUC), sensitivity, and specificity; conducted meta-regression and sensitivity analyses; and assessed publication bias.


Results: 


A total of 18 studies involving 3,448 patients were included in this meta-analysis. The pooled results demonstrated that blood NfL was associated with poor functional outcomes after ischemic stroke (OR = 1.78, 95% CI: 1.41–2.24, p < 0.001, I2 = 87.5%, p < 0.01). The pooled AUC for blood NfL in predicting functional outcomes in patients with ischemic stroke was 0.79 (95% CI: 0.75–0.82), with 71% (95% CI: 62–79%) sensitivity and 74% (95% CI: 67–80%) specificity. Subgroup analyses and meta-regression revealed that participant age, sample size, study design, blood sample type, assay method, proportion of poor functional outcomes, blood sampling time, reperfusion therapy rate, National Institutes of Health Stroke Scale score, definition of poor functional outcome, and the proportion of large artery atherosclerosis were not identified as significant sources of heterogeneity. Sensitivity analysis indicated that the pooled estimate was robust. Begg’s test also showed no evidence of publication bias (p = 0.753), although Egger’s test suggested the presence of publication bias (p < 0.001). The trim-and-fill method showed that the overall effect of this meta-analysis was stable.


Conclusion: 


This meta-analysis showed that elevated blood NfL levels may have prognostic value for functional outcomes in patients with ischemic stroke. However, given the substantial between-study heterogeneity and the presence of publication bias, these findings should be interpreted with caution.


Systematic review registration:

https://www.crd.york.ac.uk/PROSPERO/view/CRD420261297284, identifier PROSPERO (CRD420261297284).


A clinical and biomarker model for predicting post-stroke cognitive impairment: a prospective cohort study

 

 Describing a problem with NO solution is a fireable offense in any business!

Let's check how long you have NOT BEEN SOLVING THE PROBLEM!

A clinical and biomarker model for predicting post-stroke cognitive impairment: a prospective cohort study


  • X

    Xinyu Zhang 1†

  • X

    Xiangwen Hao 2†

  • Y

    Yanyang Li 2

  • J

    Jingqi Chen 2

  • X

    Xiaoyan Zheng 2

  • A

    Anren Zhang 3*

  • Qiuhong Man

    Qiuhong Man 2*

  • 1. School of Health Preservation and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, China

  • 2. Department of Clinical Laboratory, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, China

Abstract


Background and objectives: 


Post-stroke cognitive impairment (PSCI) is highly prevalent and substantially compromises functional recovery and quality of life; however, early identification remains challenging. This study aimed to develop and validate an early prediction model for PSCI by integrating routinely available blood biomarkers with clinical characteristics.


Methods: 


Patients with acute ischemic stroke were prospectively enrolled at Shanghai Fourth People's Hospital between March and November 2024. Cognitive function was assessed 3 months after stroke using the Telephone Montreal Cognitive Assessment (T-MoCA), a telephone-based cognitive screening instrument, with PSCI defined as a corrected T-MoCA score <19. Univariable logistic regression, Spearman correlation analysis, and variance inflation factor analysis were performed to characterize associations and predictor redundancy. Bootstrap least absolute shrinkage and selection operator (LASSO) logistic regression with 1,000 resampling iterations was used to assess variable-selection stability, followed by multivariable logistic regression and nomogram construction. Model performance was evaluated using receiver operating characteristic (ROC) analysis, calibration analysis, decision curve analysis (DCA), and clinical impact curves (CIC), with 1,000 bootstrap iterations used for internal validation.


Results: 


A total of 198 patients were included, of whom 138 developed PSCI and 60 were classified as post-stroke cognitively normal (PSCN, non-PSCI group). The final prediction model incorporated age, prior stroke history, diabetes mellitus, small dense low-density lipoprotein (sdLDL), apolipoprotein A-I (ApoA-I), homocysteine, cystatin C, and D-dimer. The model achieved an apparent AUC of 0.798. Following 1,000 bootstrap resampling iterations, the mean AUC was 0.777 (95% CI, 0.733–0.802), and the optimism-corrected AUC was 0.762. Calibration analysis suggested reasonable agreement between predicted and observed risks, while DCA and CIC analyses indicated potential utility for PSCI risk stratification.


Conclusions: 


This study developed and internally validated a multivariable model combining clinical characteristics and circulating biomarkers to estimate PSCI risk after acute ischemic stroke. The model showed acceptable predictive performance and may support early risk stratification.

The New Science of Moving Again After a Stroke

 Rose colored world here; not seeing reality!

The New Science of Moving Again After a Stroke

 

Key takeaways

  • Stroke rehabilitation has advanced dramatically in the past 25 years. (What a complete fucking lie! You're no closer to 100% recovery!)
  • Modern rehabilitation focuses on matching therapies to each patient’s specific recovery needs.(Bullshit! You are NOT MAPPING exact protocols to the objective damage diagnosis! You don't even have anything objective in stroke at all! NIHSS and mRS are totally subjective, they can't be used for protocol mapping!) 
  • Devices such as vagus nerve stimulation implants and wearable technologies are expanding options for individualized recovery after stroke.
 Stevie Dickens was 48 years old and living in Vernon Hills, Illinois, when he woke up one September morning in 2003 and couldn’t get off the couch. The night before, while watching football with friends, his speech had begun to slur and he had felt off balance, but didn’t understand that these were warning signs of a stroke. The next morning, he realized he was paralyzed on his right side. A friend’s son had to help him to the floor.

What followed was a yearslong journey through hospitals and rehabilitation centers in which Dickens, a veteran of the Army and the Marine Corps, applied the same mental discipline he had learned in the military to the grinding repetitions of physical therapy. He started in a wheelchair. He graduated to a cane. He eventually discarded the ankle-foot brace strapped around his calf that had helped him walk, after his leg grew strong enough to manage without it. Seeking to push further, he found his way into research.

For nearly two decades Dickens has been a regular participant in motor recovery studies at the Shirley Ryan AbilityLab in Chicago. He’s enrolled in walking and arm studies, robotics trials and exoskeleton experiments. “He came in when I came here about 19 years ago,” says Arun Jayaraman, scientific chair for technology and innovation at the Shirley Ryan AbilityLab. He calls Dickens' experience “a classic clinical scenario.” He was “super impaired when he came in.”

Today, at 71, Dickens walks with a cane. He cooks, mows the lawn and goes to stores. “I understand I ain’t gonna get 100 percent back,” he says. “But I’m gonna get at least 90 percent.”

Intense, repetitive practice

Dickens is a living demonstration of how far the field has come. When he had his stroke, most of what is now available to stroke survivors didn’t exist.

The transformation has been driven largely by more sophisticated understanding of how the injured brain recovers and by technologies that enable clinicians and researchers to apply that understanding in precise new ways.

When a stroke damages the neural circuits that govern movement, the signals that once flowed from brain to muscle at full strength through thousands of fibers are suddenly diminished, rerouted and degraded. The goal of modern rehab is to amplify whatever signal remains — stimulating the nervous system along the injured pathway or pushing the brain to find alternative routes. At the same time, coupling that stimulation to the intense, repetitive, task-specific practice that drives the reforming of brain networks.

In one recent study, Dickens wore a robotic device called an exoskeleton. It’s a powered frame that fits over the limbs and torso and moves the wearer’s body through programmed or guided motions. In stroke rehab, exoskeletons are used to move paralyzed or weakened limbs through repetitive walking and movement patterns to exploit the brain’s neuroplasticity and help rebuild motor pathways. In the study, published earlier this year in Science Robotics, researchers from the Shirley Ryan AbilityLab and Northwestern University introduced what they call therapist-exoskeleton-patient interaction. A therapist and a stroke survivor each wear a lower-limb exoskeleton, the two systems virtually linked at the hips and knees, so that the therapist can guide the patient’s walking through their own leg movements. 

The approach produced greater joint range of motion and increased step length and height compared to conventional therapy, while requiring less physical effort from the therapist.

“By combining the hands-on adaptability of physical therapy with the scalability and precision of robotic systems,” says Lorenzo Vianello, a postdoctoral researcher at the Shirley Ryan AbilityLab who coauthored the study, “it can enable more comprehensive whole-body gait training without requiring multiple therapists, while also introducing real-time responsiveness to patient performance.” For patients, that translates to a workout that adjusts to them stride by stride.

Stimulating the vagus nerve

For upper limb recovery — restoring function to a paralyzed arm or hand — one of the most significant developments in recent years has been the Vivistim Paired VNS System, which received U.S. Food and Drug Administration approval in 2021 and became commercially available in 2022. The device, about the size of a small pacemaker, is implanted in the upper chest; a connected lead is implanted against the vagus nerve on the left side of the neck.

During rehab sessions, electrical stimulation pulses through the nerve each time the patient performs a prescribed arm movement. The stimulation triggers the release of brain chemicals that promote synaptic plasticity — essentially telling the brain to pay particular attention to whatever it is doing at that moment and to strengthen the connections within the networks of brain cells involved in performing the task.

In the pivotal clinical trial, published in The Lancet in 2021, patients receiving vagus stimulation during rehab showed two to three times more improvement in upper limb function than those receiving rehabilitation alone; long-term follow-up data published in 2025 found that 66 percent of patients achieved sustained, clinically meaningful improvements at a one-year check.

The pace of development across the field is striking. Jayaraman describes a suite of wearable sensors now being deployed at the Shirley Ryan AbilityLab that can assess a stroke patient’s walking ability in minutes and generate, at the time of admission, a prediction of their likely recovery trajectory for up to a year.

Lightweight robotic exoskeletons can be worn to the grocery store. Shoes with variable-friction soles — which glide when a wearer can’t lift their foot and grip when they put weight on the shoe — were studied by Shirley Ryan AbilityLab researchers and are now sold commercially. They can potentially correct functional balance and stability issues caused by foot drop, dramatically reducing fall risk.

The Healthiest Carbs for Healthy Aging, According to a 30-Year Study

 How soon will your competent? doctor get this updated in your current diet protocol?

Don't even have a diet protocol? PURE INCOMPETENCE! And that doctor hasn't been fired yet?

The Healthiest Carbs for Healthy Aging, According to a 30-Year Study

New research following more than 47,000 women suggests that the quality of the carbohydrates you eat in midlife may help shape how well you age.

Carbohydrates have spent decades being cast as the nutritional villain. Bread gets blamed for weight gain. Pasta gets swapped for protein. Potatoes disappear from dinner plates. And “cut the carbs” has become shorthand for eating healthier.

But carbohydrates aren't one thing. A long-running study offers a useful reminder that where your carbs come from may matter far more than simply eating fewer of them.

TL;DR

Carb quality — not carb quantity — tracked with healthy aging across three decades. Whole grains, fruit, vegetables and legumes were associated with better outcomes; refined grains and added sugars with worse ones. Fiber may explain much of the effect.

✥Every 10% of calories from high-quality carbs: 31% higher odds of healthy aging.
✥The same increase in refined carbs: 13% lower odds.
✥Only 7.8% of the 47,513 women met every criterion for healthy aging.
✥Observational study — associations, not proof of cause.


The study

Chapter 01 · JAMA Network Open, 2025

In a 2025 study published in JAMA Network Open, researchers examined the diets of 47,513 women in the Nurses' Health Study and followed their health for more than three decades. They wanted to know whether the kinds of carbohydrates women ate in midlife were associated with how healthy they were in their 70s, 80s, and early 90s.

The finding was striking: women who consumed more high-quality carbohydrates from whole grains, fruits, vegetables, and legumes had greater odds of what researchers called healthy aging — and healthy aging meant considerably more than simply living longer. Researchers looked for women who reached older adulthood without 11 major chronic diseases, physical limitations, memory problems, or poor mental health.

The women were an average of about 48 years old when researchers began assessing their diets in the mid-1980s. Their health was evaluated decades later, when participants were between 70 and 93.

Keep in mind: the study was observational, which means it can identify associations but cannot prove that eating a particular kind of carbohydrate caused someone to age better. And a 31% increase in odds does not mean someone becomes 31% healthier.

Still, the larger pattern was consistent. Carbohydrates from fruits, vegetables, whole grains, and legumes were associated with better aging outcomes. Dietary fiber was, too. Diets with a higher glycemic index and a higher ratio of carbohydrate to fiber were associated with poorer outcomes.

Carbohydrates aren't automatically healthy or unhealthy. Their source matters.

What Makes a Carb “High Quality”?

Chapter 02 · The package, not the macro

Picture two breakfasts. One is a bowl of oatmeal topped with berries and walnuts. The other is a frosted pastry. Both contain carbohydrates — your body can break both down into glucose. But nutritionally, they're very different packages.

Whole carbohydrate foods tend to arrive with other things your body can use: fiber, vitamins, minerals, plant compounds, and intact food structures that influence how quickly they're digested. Highly refined carbohydrates have often had much of that structure — and particularly fiber — removed during processing.

In this study, researchers classified carbohydrates from whole grains, fruits, non-starchy vegetables, and legumes as high quality. Refined grains and added sugars were among the lower-quality sources they examined.

The Carb Quality Test

When choosing a carbohydrate, ask what comes with it.

More often
Whole grains
Whole fruit
Vegetables
Beans and lentils
Fiber
Less often
Refined grains
Foods high in added sugars
Highly processed starches
Low-fiber packaged foods
Little or no fiber

The idea: don't judge a food simply because it contains carbohydrates. Look at the entire nutritional package.

Fiber May Be the Quiet Star

Chapter 03 · One nutrient kept reappearing

One nutrient kept showing up throughout the research: fiber. Women who consumed more total dietary fiber in midlife had greater odds of healthy aging decades later. Fiber from fruits, vegetables, and cereal grains was also associated with better outcomes.

When researchers statistically accounted for fiber, some of the associations between carbohydrate intake and healthy aging became weaker. That suggests fiber may explain at least part of the relationship — and it would make biological sense.

Fiber does much more than keep digestion regular. Certain types can slow digestion and moderate the rise in blood sugar after eating. Soluble fiber can help lower LDL cholesterol. Other fibers reach the colon, where gut microbes ferment them and produce compounds that help support the intestinal environment. And unlike many headline-grabbing nutrients, fiber is abundant in remarkably ordinary foods.

The Fiber Upgrade

You don't need an exotic superfood. Start here.

Beans + lentils

Fiber, plant protein, and resistant starch in one inexpensive package.

Oats + barley

Whole grains rich in soluble fiber.

Berries + apples + pears

Whole fruit delivers fiber alongside its naturally occurring sugars.

Vegetables

Enormous variety, different vitamins and plant compounds in each.

Nuts + seeds

Fiber plus unsaturated fats, protein, and minerals.

Whole grains

More of the original grain means more of its fiber and nutrients.

5 Carbohydrate Sources Worth Eating More Often

What About Glycemic Index?

Chapter 05 · A number with limits

You've probably encountered the term glycemic index, or GI. It describes how quickly carbohydrate-containing foods raise blood glucose compared with a reference food. In this study, diets with a higher overall glycemic index were associated with lower odds of healthy aging, and a higher carbohydrate-to-fiber ratio with poorer outcomes.

But that doesn't mean you need to memorize the glycemic index of everything in your pantry. Meals are complicated. We rarely eat one carbohydrate in isolation, and protein, fat, fiber, preparation method, portion size, and the other foods on your plate can all influence the blood-sugar response.

Chapter 04 · Where to start

The study wasn't designed to crown individual foods as longevity champions. Instead, it identified broader carbohydrate categories associated with healthier aging. Within those categories, these are useful places to start.

01

Whole Grains

Oats, barley, quinoa, brown rice, farro, whole-wheat bread, and even popcorn all qualify. Whole grains retain more of the original grain — including fiber-rich components often removed during refining. In the study, greater carbohydrate intake from whole grains was associated with higher odds of healthy aging.

When shopping for bread or cereal, look beyond the color of the package or words like “multigrain.” Checking whether a whole grain appears near the beginning of the ingredient list can tell you more.

02

Whole Fruit

Apples, oranges, berries, pears, and peaches provide carbohydrates alongside fiber, water, vitamins, and plant compounds. Importantly, the researchers classified carbohydrates from whole fruit — not fruit juice — as high quality.

Eating an orange means consuming its fiber and intact structure along with its naturally occurring sugars. Juice removes much of that structure. You don't need to fear the sugar in an apple; the package matters.

03

Vegetables

In the study, carbohydrates from non-starchy vegetables were positively associated with healthy aging. Think leafy greens, broccoli, peppers, carrots, tomatoes, and cauliflower.

There is no need to identify one perfect vegetable. Variety — and finding vegetables you genuinely enjoy enough to eat regularly — matters more.

04

Beans and Lentils

Beans, chickpeas, peas, and lentils are nutritional multitaskers: carbohydrates, fiber, plant protein, minerals, and resistant starch in the same food. They're also inexpensive, shelf-stable, and easy to add to soups, salads, grain bowls, tacos, stews, and pasta dishes.

05

Fiber-Rich Foods in General

Perhaps the clearest lesson isn't about any particular food at all. Rather than obsessing over whether a food technically contains carbohydrates, looking at what comes with those carbohydrates — including fiber — can tell you much more about its nutritional quality.

What About Glycemic Index?

Chapter 05 · A number with limits

You've probably encountered the term glycemic index, or GI. It describes how quickly carbohydrate-containing foods raise blood glucose compared with a reference food. In this study, diets with a higher overall glycemic index were associated with lower odds of healthy aging, and a higher carbohydrate-to-fiber ratio with poorer outcomes.

But that doesn't mean you need to memorize the glycemic index of everything in your pantry. Meals are complicated. We rarely eat one carbohydrate in isolation, and protein, fat, fiber, preparation method, portion size, and the other foods on your plate can all influence the blood-sugar response.