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.

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.

Showing posts with label status quo. Show all posts
Showing posts with label status quo. Show all posts

Friday, April 17, 2026

Call for more investment in vital rehabilitation for stroke survivors

 This is just calling for more of the failed status quo. STATUS QUO OF ONLY 10% FULL RECOVERY IS MASSIVE FAILURE! Ask for the correct solution: 100% recovery protocols! Your stroke medical 'professionals' will pooh pooh it and say it can't be done! BOLLOCKS,  have them contact me for remedial education(OC1Dean@gmail.com)

You don't need any medical training to see that stroke rehab is a complete shitshow!

And in the end they only talk of providing 'care' NOT RECOVERY! I'd fire anyone settling for 'care' and you should too! A lot of dead wood needs to be removed in stroke; start with your 'professionals' if they have nothing for 100% recovery!

Call for more investment in vital rehabilitation for stroke survivors

Video at link
ITV Meridian's Richard Slee reports from Highcliffe in Dorset

A man from Dorset who suffered a stroke is backing calls for more investment in vital rehabilitation after a new survey reveals that most regions are seriously underfunded and understaffed.

David Stadelman, 73, who lives in Highcliffe near Bournemouth, had a stroke two years ago.

He credits the excellent care(NOT RECOVERY!) he received and ongoing therapy for his good recovery, but he wants every patient to have that same benefit.

"The rehabilitation that I received started very quickly after I had the stroke," David said.

"People called physiotherapists came along with the view of getting me home.

"Gradually I realised that there was a future to be had."

David has continued with his recovery by joining an exercise classCredit: ITV Meridian

David is now fit enough to drive himself to a local heart health group.

The Chartered Society of Physiotherapy claims that community stroke services have on average 26% fewer physiotherapists than recommended, and Acute Stroke teams are down by 15% which is leaving some people with avoidable disabilities.The government says it accepts it is failing many patients, but is committed to reducing the number of people who die from heart disease and strokes by a quarter over the next ten years.

In a statement a spokesperson said: 'We're rolling out specialist stroke rehabilitation in people's homes, so more people can get the right care(NOT RECOVERY!) without having to rely on hospital stays."

Monday, February 16, 2026

Genetic risk impacts stroke mortality and pathogenesis in patients with ischemic stroke: a cohort study of BioBank Japan

Don't you dare use genetic risk as an excuse for not changing the status quo and getting these people recovered! Excuses won't be tolerated, you're fired! Leaders would solve such a problem; obviously you have NO LEADERSHIP potential!

Genetic risk impacts stroke mortality and pathogenesis in patients with ischemic stroke: a cohort study of BioBank Japan


Takashi Shimoyama
&#x;Takashi Shimoyama1*Yoichiro Kamatani&#x;Yoichiro Kamatani2Koichi Matsuda&#x;Koichi Matsuda3Hiroki Yamaguchi&#x;Hiroki Yamaguchi4Kazumi Kimura&#x;Kazumi Kimura1
  • 1Department of Neurology, Nippon Medical School, Tokyo, Japan
  • 2Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
  • 3Department of Computational Biology and Medical Science, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
  • 4Department of Hematology, Nippon Medical School, Tokyo, Japan

Background: Previous multi-ancestry genome-wide association studies (GWAS) of stroke reported 32 stroke risk loci in the MEGASTROKE study. Most studies on the genetic risk score (GRS) of stroke have reported a predominance in the European general population. We aimed to explore the association among GRS, clinical characteristics, and mortality in patients with ischemic stroke registered in the BioBank Japan (BBJ) database.

Methods: This is a cohort study of BBJ participants. The project participants were recruited between June 2003 and March 2018. We conducted a GWAS for stroke in 19,702 Japanese patients with ischemic stroke and 159,610 controls. GRS was generated using 29 stroke risk single nucleotide polymorphisms (SNPs) from 32 stroke-related loci identified in the MEGASTROKE. A multivariate logistic regression model was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for comorbidities and stroke etiology across the GRS. The Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% CIs for mortality associated with GRS.

Results: The ORs for atrial fibrillation were significantly higher in those at Intermediate GRS [20–80th percentile of GRS; ORs 1.59 (1.25–1.90)] and High GRS [top 20th percentile of GRS; ORs 2.12 (1.69–2.67)] after a full adjustment than in those at Low GRS (bottom 20th percentile of GRS). Regarding stroke etiology, the ORs for cardioembolism were significantly higher in those at Intermediate GRS [ORs 1.31 (1.04–1.61)] and High GRS [ORs 1.44 (1.13–1.89)] than in those at Low GRS. During a median follow-up of 10.0 years, the risk of stroke mortality was significantly higher in those at High GRS [HRs 1.27 (1.04–1.56)] than in those at Low GRS in a fully adjusted model.

Conclusion: In Japanese, a higher GRS was significantly associated with atrial fibrillation, cardioembolism, and stroke mortality. Our findings suggest that the GRS may predict the risk of stroke mortality and provide insights into the pathogenesis of stroke.

Introduction

Stroke is the second-leading cause of death and the primary cause of neurological disability worldwide (12). Stroke is caused by a complex interplay of environmental and traditional risk factors, including older age, hypertension, diabetes mellitus, dyslipidemia, atrial fibrillation, chronic kidney disease, and smoking (3). Besides conventional clinical risk factors, the genetic contribution to the development of stroke is also widely recognized (4). Twin and family history studies suggest genetic factors are responsible for some of this unexplained risk for stroke. The heritability estimates were 0.32 for the liability to stroke death and 0.17 for stroke hospitalization or stroke death (5).

Over the last decades, several genome-wide association studies (GWAS) have identified genetic variants associated with stroke in different ethnic populations (611). Previous multi-ancestry GWAS of 52,000 subjects in predominantly European-ancestry groups have identified 32 loci associated with stroke and stroke subtypes (MEGASTROKE study) (11). Recent work has highlighted the potential of the genetic risk score (GRS) based on the MEGASTROKE study, which can be evaluated as a risk factor for stroke and used to predict incident stroke events in an independent population (1116). The risk of incident stroke was higher in those at high genetic risk than in those at low genetic risk (12). The polygenic risk score (PRS) using 3.6 million genetic variants predicts stroke incidents in a population of 12,792 healthy older individuals enrolled in the ASPREE trial (Aspirin in Reducing Events in the Elderly) (13). In a genetic cohort analysis pooling 51,288 subjects with cardiometabolic disease from five cardiovascular clinical trials, GRS using the set of 32 single nucleotide polymorphisms (SNPs) derived from the MEGASTROKE study was a strong, independent predictor of ischemic stroke incidence over a median follow-up period of 2.5 years (14). In the Northern Finland Birth Cohort 1966 of 12,058 children, higher PRS for stroke was associated with the risk for cerebrovascular disease in mid-life in Finnish population. Ischemic stroke (15). Although investigation of genetic risk for stroke has been limited in non-European populations, the Hisayama Study, which involved 3,038 Japanese individuals, reported the PRS for stroke using 350,000 SNPs was significantly associated with stroke incidence during long-term follow-up (median 10.2 years) (16). Most of the advanced literature on genetic risk for stroke has been reported in general populations regardless of ethnicity; however, solid evidence in the relevant literature has not described the clinical significance of genetic risk for stroke in non-European stroke patients.

To address these limitations, we developed a GRS for stroke from a set of 32 stroke risk loci identified in the MEGASTROKE study in Japanese patients with ischemic stroke. We hypothesized that subsets with a higher genetic risk influence stroke mechanisms and mortality compared to those with a lower genetic risk of ischemic stroke. This cohort study aimed to clarify the association between the GRS score, clinical characteristics, and mortality in stroke patients registered in the BioBank Japan (BBJ) database.

More at link.

Monday, February 9, 2026

EEG-based predictors of motor recovery during immersive VR-BCI rehabilitation

 

'Assessments', biomarkers and predictions don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT RECOVERY GET THERE!

I'd fire everyone involved with this crapola! You're predicting based on the failure of the status quo! Change the status quo, you blithering idiots!

The only possibility of assessments being useful is if they POINT DIRECTLY TO EXACT REHAB PROTOCOLS! This did nothing towards that so completely fucking useless!

Predictions like this NEVER GET ANYONE RECOVERED! I'd have you all fired for incompetency in not solving stroke!

EEG-based predictors of motor recovery during immersive VR-BCI rehabilitation


We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Motor impairment following stroke frequently leads to long-term disability, limiting independence and quality of life. Brain–Computer Interface (BCI) systems integrating motor imagery (MI) with virtual reality (VR) offer promising avenues for enhancing neuroplasticity and engagement through immersive, real-time, and proprioceptive feedback. Yet, identifying reliable electroencephalography (EEG)-based biomarkers that reflect or predict recovery remains challenging. This study investigated the relationship between event-related desynchronization (ERD) dynamics during MI–VR training and motor recovery in individuals with chronic stroke. Fourteen participants with stroke (9 experimental, 5 control) completed a 4-week VR–BCI intervention and were compared with a non-stroke reference cohort (N = 35). Linear mixed-effects models assessed ERD modulation across sessions and groups, and a two-stage regression evaluated the predictive value of ERD features for Fugl–Meyer Assessment (FMA) gains. Results showed no significant ERD change across sessions, but stroke participants exhibited significantly reduced ERD compared to controls. Baseline ERD amplitude predicted motor improvement, whereas ERD progression did not. Ipsilateral ERD showed a compensatory trend in ischemic stroke. These findings indicate that baseline ERD may serve as a stronger prognostic biomarker than short-term ERD dynamics, supporting the development of personalized VR–BCI rehabilitation strategies for chronic stroke recovery.

Data availability

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Saturday, February 7, 2026

New risk assessment tool may help predict dementia after a stroke

 

'Assessments', biomarkers and predictions don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT RECOVERY/DEMENTIA PREVENTION! GET THERE!

I'd fire everyone involved with this crapola! You're predicting based on the failure of the status quo! Change the status quo, you blithering idiots!

The only possibility of assessments being useful is if they POINT DIRECTLY TO EXACT REHAB PROTOCOLS! This did nothing towards that so completely fucking useless!

Predictions like this NEVER GET ANYONE RECOVERED! I'd have you all fired for incompetency in not solving stroke!

New risk assessment tool may help predict dementia after a stroke

             American Stroke Association International Stroke Conference 2026, Abstract A109

Research Highlights:
  • A new risk prediction tool was able to accurately identify stroke survivors with the highest risk for developing dementia within a decade of having a stroke, according to a large study in Canada.
  • Factors linked with a higher risk of developing dementia after a stroke included being older, having any disability before the stroke, having a higher level of disability after the stroke, having an intracerebral hemorrhage (compared to an ischemic stroke), having diabetes, experiencing cognitive symptoms during hospitalization or suffering from depression.
  • Knowing the risk of developing dementia after a stroke can help researchers design better clinical trials and interventions. It can also guide the recruitment of patients who are eligible to participate in efforts to lower the risk of dementia.
  • Note: The study featured in this news release is a research abstract. Abstracts presented at the American Heart Association/American Stroke Association’s scientific meetings are not peer-reviewed, and the findings are considered preliminary until published as a full manuscript in a peer-reviewed scientific journal.

Embargoed until 4 a.m. CT/5 a.m. ET, Thursday, Jan. 29, 2026

DALLAS, Jan. 29, 2026 — A new risk calculator accurately estimated the likelihood of adults developing dementia within ten years after a stroke, according to a preliminary study to be presented at the American Stroke Association’s International Stroke Conference 2026. The meeting is in New Orleans, Feb. 4-6, 2026, and is a world premier meeting for researchers and clinicians dedicated to the science of stroke and brain health.

According to researchers, people with stroke and transient ischemic attack (TIA) are at high risk of subsequent dementia, but prediction tools for dementia are lacking.

“Our previous research found that about 1 in 3 adults developed dementia after stroke over the long-term. We created a new tool that can stratify people into five different levels of dementia risk after stroke based on underlying health, stroke characteristics and risk factors,” said lead study author Raed A. Joundi, M.D., D.Phil., M.Sc., an assistant professor in the department of medicine at McMaster University, a stroke neurologist at Hamilton Health Sciences, a scientist at the Population Health Research Institute, all in Hamilton, Ontario, Canada, and an adjunct scientist at ICES Central in Toronto (where the statistical analysis was done).

“The goal is to have a practical, bedside tool that can predict dementia risk after a stroke. Our tool predicts dementia rates that are very close to the observed rates and may help to enroll high-risk patients who have had transient ischemic attack, ischemic stroke or intracerebral hemorrhage in clinical trials that are focused on reducing the long-term risk of dementia.”

Researchers examined health records for nearly 50,000 adults hospitalized with stroke to create and validate a risk model to estimate which stroke survivors have the highest risk of developing dementia. The data from the Ontario Stroke Registry included hospital admissions due to stroke between 2002 and 2013 in Canada. Study participants drawn from the registry for derivation of the risk score included 7,554 adults with transient ischemic attack (TIA), 13,833 with ischemic stroke and 2,340 with intracerebral hemorrhage. The participants were discharged from the hospital without a diagnosis of dementia, and all were followed for a diagnosis of dementia through March 2024 (average of 7.5 years after stroke) based on administrative health data.

Researchers examined the rates of dementia calculated by the new tool and compared them to the observed rates of dementia. The score was derived in the Ontario Stroke Registry (11 regional stroke centers) and validated in the Ontario Stroke Audit, a separate, randomly selected sample of patients from all hospitals in the province.

The analysis found:

  • For people who had a transient ischemic attack, the top factors associated with increased dementia risk were older age, needing help with activities of daily living prior to TIA, having diabetes, depression, cognitive symptoms on presentation (such as memory, judgment or attention) and any disability at hospital discharge.
  • The main risk factors associated with developing dementia for people with stroke were being older, being female, having diabetes, depression, intracerebral hemorrhage (compared to ischemic stroke), cognitive symptoms during hospitalization or greater disability at hospital discharge.
  • The risk calculator used the top risk factors for dementia to categorize individuals into different levels of estimated risk over the next 10 years after a stroke. Those in the highest category of estimated risk had a 50% probability of dementia over 10 years, versus participants in the lowest category of risk who had a 5% probability of dementia.

The study authors note that the current focus of the dementia risk prediction tool is to stratify patients into different levels of risk for research studies and clinical trials of dementia prevention, rather than clinical decision-making or treatment.

“Dementia is a serious condition that commonly occurs in the aftermath of a stroke,” Joundi said. “While our traditional focus has been on preventing another stroke, which is very important, we need to pay more attention to the development of dementia and how to prevent it. Over the long-term, dementia is more common than a recurrent stroke. Healthy lifestyle choices and controlling vascular risk factors can lower the risk of dementia, but we need new and effective targeted interventions for dementia prevention.”

Study limitations include that data were not available about the type of dementia that may develop. Researchers did not have access to imaging scans of the study participants, which would offer more detailed information about their stroke location and size or the presence of covert infarcts (small ischemic brain lesions).

American Stroke Association volunteer expert, Deborah A. Levine, M.D., M.P.H., said, “Dementia after a stroke is very difficult for patients and their loved ones, and there aren’t enough effective treatments to help. This well-done study provides a useful tool that could make research faster, so new treatments can get to stroke survivors sooner.” Levine is a professor of internal medicine and neurology, the departments of internal medicine and neurology, the Cognitive Health Services Research and Stroke Programs and the Institute for Healthcare Policy and Innovation at the University of Michigan. Levine was not involved in this study.

Study details, background and design:

  • The average age of all participants was 70; 53% of participants were men, and 47% women.
  • Using the new risk predictor tool, researchers calculated 1-, 5- and 10-year dementia risk scores, and participants were divided into five groups, ranging from the lowest to the highest risk, based on the risk factors that were present. The risk calculator evaluated the number and the degree of each factor’s contribution to dementia risk, resulting in a composite score that indicates the likelihood of developing dementia in the future.
  • Researchers identified risk factors and other characteristics, such as age, diabetes status, depression, disability and sex, then divided patients into five categories of dementia risk based on these risk factors.
  • To validate the results, researchers reviewed data on a similar number of stroke admissions from the Ontario Stroke Audit. Dementia risk scores were calculated separately for participants who had a transient ischemic attack vs. a stroke.
  • This tool, used prior to discharge from the hospital, has the potential to help physicians assess whether patients might develop long-term dementia.

Co-authors, disclosures and funding sources are listed in the abstract.

Statements and conclusions of studies that are presented at the American Heart Association/American Stroke Association’s scientific meetings are solely those of the study authors and do not necessarily reflect the Association’s policy or position. The Association makes no representation or guarantee as to their accuracy or reliability. Abstracts presented at the Association’s scientific meetings are not peer-reviewed, rather, they are curated by independent review panels and are considered based on the potential to add to the diversity of scientific issues and views discussed at the meeting. The findings are considered preliminary until published as a full manuscript in a peer-reviewed scientific journal.

The Association receives more than 85% of its revenue from sources other than corporations. These sources include contributions from individuals, foundations and estates, as well as investment earnings and revenue from the sale of our educational materials. Corporations (including pharmaceutical, device manufacturers and other companies) also make donations to the Association. The Association has strict policies to prevent any donations from influencing its science content and policy positions. Overall financial information is available here.

Additional Resources:

Wednesday, January 28, 2026

A new hand assessment instrument for severely affected stroke patients

 

'Assessments', biomarkers and predictions don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT RECOVERY! GET THERE!

I'd fire everyone involved with this crapola! You're predicting based on the failure of the status quo! Change the status quo, you blithering idiots!

The only possibility of assessments being useful is if they POINT DIRECTLY TO EXACT REHAB PROTOCOLS! This did nothing towards that so completely fucking useless!

Predictions like this NEVER GET ANYONE RECOVERED! I'd have you all fired for incompetency in not solving stroke!

A new hand assessment instrument for severely affected stroke patients


Background:
Standard assessment instruments cannot differentiate patients with minimal residual hand function after stroke. As a result, changes in motor recovery are difficult to document using currently-available tests. In a controlled study with chronic stroke patients without residual finger extension, a new hand function test has been developed. This instrument, called Broetz Hand Test (BzH), allows to assess small variations in hand function in severely paralyzed stoke patients. The instrument is easy to use, and was developed using principles of motor learning and behavioral assessment.

Methods:
The instrument consists of seven daily life-oriented tasks, each of which asks for movement of the paralyzed hand. BzH of 20 patients after stroke was evaluated before and after a behavioral physiotherapy treatment. Sensitivity, inter-observer reliability, test-retest reliability and construct validity was calculated.

Results:
Two-tailed paired-samples t-test before and after treatment demonstrated sufficient sensitivity. Mean agreement between the raters resulted in an excellent interrater-reliability. Test-retest reliability between the pre- and post-treatment scores was 0.9. The correlation between BzH and standard test scores was statistically significant and demonstrated sufficient validity.

Conclusion:

The BzH is a valid and reliable tool to assess changes in hand function in severely paralyzed patients after stroke.
I would fail every single test due to spasticity; the research needed is CURING SPASTICITY NOT THIS 'ASSESSMENT' CRAPOLA!

AI-driven low-cost rehabilitation exergame as a lightweight framework for stroke assessment

 

'Assessments', biomarkers and predictions don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT RECOVERY! GET THERE!

I'd fire everyone involved with this crapola! You're predicting based on the failure of the status quo! Change the status quo, you blithering idiots!

The only possibility of assessments being useful is if they POINT DIRECTLY TO EXACT REHAB PROTOCOLS! This did nothing towards that so completely fucking useless!

'Assessments' like Fugl-Meyer NEVER GET ANYONE RECOVERED! I'd have you all fired for incompetency in not solving stroke!

AI-driven low-cost rehabilitation exergame as a lightweight framework for stroke assessment


We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

Stroke is a leading cause of long-term disability, often affecting upper-limb motor function and requiring continuous assessment. The Fugl-Meyer Assessment (FMA), though a clinical gold standard, is time-consuming and demands specialized personnel. This study presents an AI-driven, low-cost rehabilitation exergame that simultaneously provides therapy and automatically estimates upper-limb motor performance during gameplay using only a standard camera. Sixteen kinematic and spatiotemporal features were extracted from 2D hand and arm trajectories of twelve post-stroke individuals (24 limbs, 14 affected) using the MediaPipe framework. Features such as hand angle, range of motion, movement area, traveled distance, and shoulder–elbow coordination showed strong correlations with FMA scores and stratified participants by motor severity. A lightweight linear regression model achieved high predictive performance (Spearman ρ = 0.92, R² = 0.89, RMSE = 4.42) and classified severity levels with 86–93% accuracy. This interpretable approach outperformed complex machine learning models, highlighting the clinical relevance of transparent metrics embedded in gameplay. The proposed framework is sensor-free, scalable, and reproducible, offering immediate feedback while reducing clinical workload and enabling accessible digital biomarkers for telerehabilitation and remote monitoring after stroke.

Data availability

The datasets generated and analyzed during the current study are not publicly available at this stage but are available from the corresponding author (J.T.) upon reasonable request. We also intend to make the anonymized dataset publicly accessible through an open research repository following publication. The custom Python scripts used for data preprocessing, feature extraction, and regression analysis are available from the corresponding author upon request.

References

  1. Tsao, C. W. et al. Heart Disease and Stroke Statistics-2022 Update: a report from the american heart association. Circulation 145, e153–e639 (2022).

Sunday, January 18, 2026

Identifying and predicting gait stability metrics in people with stroke in uneven-surface walking using machine learning

 

'Assessments', biomarkers and predictions don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT 100% RECOVERY! GET THERE!

I'd fire everyone involved with this crapola! You're predicting based on the failure of the status quo! Change the status quo, you blithering idiots!

Identifying and predicting gait stability metrics in people with stroke in uneven-surface walking using machine learning


We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Abstract

People with stroke (PwS) face increased fall risk on uneven surfaces; however, gait stability under such conditions remains unexplored. This study used machine learning (ML) to identify acceleration features distinguishing PwS from healthy controls (HC) during uneven-surface walking and to predict them from even-surface gait parameters. Trunk acceleration data from 71 PwS and 39 HC were analyzed using classification and regression models. The ML classifiers achieved an accuracy of over 95%. The key discriminative features included the vertical root mean square (RMS_VT), anterior-posterior sample entropy (SampEn_AP), and harmonic ratio (HR_AP). In PwS, even-surface gait speed < 0.8 m/s predicted reduced speed and higher RMS_VT on uneven surfaces. SampEn_AP and HR_AP were influenced by ankle kinematics and their even-surface values, respectively, showing nonlinear associations. These findings support the use of wearable sensor data and interpretable ML to assess gait stability and adaptability, facilitating development of digital biomarkers for personalized stroke rehabilitation aimed at improving outdoor mobility.

Apraxia as a Clinical Marker for Stroke Rehabilitation Outcomes

 

'Assessments' and predictions don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT 100% RECOVERY! GET THERE!

I'd fire everyone involved with this crapola! You're 'assessing' based on the failure of the status quo! Change the status quo, you blithering idiots!

Apraxia as a Clinical Marker for Stroke Rehabilitation Outcomes


Rounis E, Ramanan S, Bickerton WL, Demeyere N, Lambon Ralph MA. Apraxia as a Predictor of Poststroke Recovery: Insights From the Birmingham Cognitive Screening Program. Stroke. 2025;56:3522–3526.

Although stroke remains a leading global cause of long-term morbidity, the persistent disabilities faced by survivors are not fully captured by the functional recovery measures most frequently used in clinical practice. Cognitive impairments are becoming recognized as key determinants of functional recovery, but several domains remain underassessed despite evidence linking them to prolonged disability and dependence. Limb apraxia, a disorder of skilled and purposeful action not attributable to motor weakness or sensory loss, is one such domain that can affect patient autonomy and safety in routine daily tasks such as grooming, dressing, and tool use. However, comprehensive assessment is challenging due to the time-intensive nature of neuropsychological testing and the heterogeneity of apraxic presentations. As a result, many patients leave acute stroke units without adequate identification of their praxis deficits or corresponding management strategies. Additionally, few studies have deployed broad neuropsychological assessments capable of capturing the range of cognitive deficits, including praxis disturbances, that influence poststroke outcomes or assessed long-term recovery trajectories to help guide poststroke care.

To address these gaps, Rounis et al. analyzed data from the Birmingham Cognitive Screen (BCoS), a large, multicenter stroke cohort in the United Kingdom specifically designed to deliver a time-efficient yet wide-ranging cognitive assessment inclusive of patients with aphasia or spatial neglect,1 to assess the effect of early praxis scores on predicting long-term activities of daily living outcomes. The study included 256 participants from the original BCoS cohort who had a first CT-confirmed stroke, no prior neurologic or psychiatric conditions, and complete data at early subacute (<1 month) and chronic (>9 months) stages. Participants completed 34 neuropsychological tasks across domains of executive function, memory, language, calculation, visuospatial attention, tactile extinction, and orientation, as well as four praxis-related tasks: meaningless gesture imitation, gesture production, gesture recognition, and multistep object use. Functional independence was assessed using the 20-point Barthel Index for Activities of Daily Living (BI-ADL) at both time points.

Using a multivariate stepwise linear regression model, the authors examined whether early subacute cognitive and praxis performance predicted changes in BI-ADL scores at nine months. The model accounted for 60% of the variance in functional outcomes (adjusted R² = 0.59), with early BI scores emerging as the strongest predictor. Importantly, multiple limb praxis measures including gesture production, gesture recognition, and meaningless gesture imitation significantly predicted ADL recovery. Additional cognitive predictors of ADL recovery included orientation measures, specific language tasks (reading and sentence construction), and tactile extinction. Sensitivity analyses comparing models with and without limb praxis measures confirmed that praxis significantly enhanced predictive accuracy: removing praxis tasks reduced explained variance to 56%, with ANOVA revealing a significant decrement in model fit.

These findings extend prior work suggesting an association between apraxia and functional outcome by demonstrating that multiple, distinct praxis tasks collected in the early subacute period independently contribute to long-term ADL recovery. The longitudinal duration (>9 months) for follow-up analyzed in this study is a better predictor of poststroke outcomes as previous large cohorts assessing cognitive measures, such as the Oxford Cognitive Screen program, only follow patients for six months or only incorporate one praxis task, which potentially misses later stages of praxis recovery or does not fully assess their baseline deficits. The broad cognitive sampling and extended follow-up in the study by Rounis et al. provide a more accurate characterization of the relationship between praxis impairments and functional trajectories, especially as prior studies have shown apraxia recovery can take between two to eight months poststroke.2

Despite its contributions, the study acknowledges limitations, including uncertainty about the predictive thresholds of specific praxis tasks due to the relatively high baseline praxis scores. The two-time-point design precluded mixed-effects modeling, and external validation was not possible due to the absence of comparable data sets with similarly detailed praxis and cognitive measures. However, despite the limitations, the results still highlight a critical gap in clinical practice: Limb apraxia remains undertested in acute stroke care, often overshadowed by language and general motor assessments. Systematic praxis evaluation that is integrated alongside other cognitive domains could improve identification of patients at elevated risk for persistent ADL limitations and inform targeted rehabilitative strategies. Overall, this study highlights the importance of comprehensive cognitive screening, including detailed praxis assessment, in predicting long-term stroke recovery and guiding personalized poststroke care.

References:

  1. Humphreys GW, Bickerton WL, Samson D, Riddoch MJ. Birmingham cognitive screen. Hove, UK: Psychology Press; 2012.
  2. Stamenova V, Black SE, Roy EA. A model-based approach to long-term recovery of limb apraxia after stroke. J Clin Exp Neuropsychol. 2011;33:954–971. 

Friday, January 9, 2026

Predicting activities of daily living at discharge in stroke patients using rehabilitation robot training-induced functional connectivity

I don't consider any prediction of recovery useful at all. You're supposed to deliver EXACT RECOVERY PROTOCOLS AS SURVIVORS NEED! This is fucking useless for survivors! You're fired!

'Assessments' don't get you recovered, only EXACT PROTOCOLS DO! SURVIVORS WANT RECOVERY! GET THERE!

I'd fire everyone involved with this crapola! You're 'assessing' based on the failure of the status quo! Change the status quo, you blithering idiots!

 Predicting activities of daily living at discharge in stroke patients using rehabilitation robot training-induced functional connectivity


ABSTRACT


Background
Predicting activities of daily living (ADL) in stroke patients optimizes discharge planning, which relies on accurate functional assessment. Recent studies have shown that functional connectivity (FC) of brain networks induced by upper extremity rehabilitation robotic training (UE-RAT) effectively reflects functional status, but its prognostic value for ADL remains unclear.

Objective
Utilize functional near-infrared spectroscopy (fNIRS) to measure FC during UE-RAT and develop machine learning models to evaluate the predictive value of task-FC for ADL.

Methods
This study recruited 86 patients with subacute stroke. Activation and FC features of key brain regions, such as the superior frontal cortex (SFC) and primary motor cortex (M1), were measured in the resting state and during UE-RAT using fNIRS. Concurrently, 38 clinical features were collected. With modified Barthel Index (mBI) ≥75 at discharge as the prediction target, machine learning algorithms such as artificial neural network (ANN) were used to construct resting-state fNIRS model, task-state fNIRS model, clinical model, and combined model, and analyze the importance of the predictor variables based on the Shapley additive interpretation (SHAP).

Results
The combined model constructed by combining clinical and task-state fNIRS features had the best predictive performance (AUC_mean: 0.955, 95% CI: 0.948–0.962). Higher connectivity between the ipsilateral premotor cortex (iPMC) and primary motor cortex (iM1) during the task state, along with higher mBI scores and lower mRS scores, predict significant improvement in functional independence for patients.

Conclusions
UE-RAT induced FC can be a valid biomarker for mBI prediction and can improve the accuracy of rehabilitation prediction.