Alteplase Also Shows Its Mettle for Late Strokes in HOPE Trial

 When are researchers going to use proper terminology? 'This percent got 100% recovered?' All the other stroke scales are not objective and really should be discontinued as useless.

I consider the Rankin scale useless, not objective except for #6, dead?

NIHSS and the Berthel Index ARE NOT DAMAGE DIAGNOSES, they do not give you the 3d location of your dead and damaged neurons. In my opinion, they are FUCKING WORTHLESS to getting you recovered! 

Alteplase Also Shows Its Mettle for Late Strokes in HOPE Trial

Positive data for patients considered non-candidates for endovascular therapy

by Nicole Lou, Senior Staff Writer, MedPage Today February 8, 2025

LOS ANGELES -- The HOPE trial made another case for extending the therapeutic window for IV thrombolysis in acute ischemic stroke, potentially widening the pool of people eligible for therapy.

Among patients with stroke clots in large and medium vessels not planned for endovascular therapy (EVT), those who got alteplase at 4.5-24 hours after stroke onset were disproportionately more likely to achieve excellent functional outcomes(NOT GOOD ENOUGH!  What will it take for all to get excellent outcomes?) at 90 days than controls (modified Rankin Scale [mRS] scores 0-1: 40.3% vs 26.3%, adjusted RR 1.52, 95% CI 1.14-2.02).

The IV alteplase group also showed a significantly better distribution of mRS scores as whole, reported Min Lou, MD, PhD, of the Second Affiliated Hospital of Zhejiang University in China, at the International Stroke Conference (ISC).

The caveat: the alteplase tested did confer excess symptomatic intracranial hemorrhages within 36 hours (3.8% vs 0.5%, adjusted RR 7.34, 95% CI 1.54-34.84). Meanwhile, a trend for more parenchymal hematomas with the approach did not reach statistical significance (7.6% vs 3.3%, adjusted RR 2.14, 95% CI 0.87-5.26).

In any case, there was no mortality signal associated with alteplase administered up to 24 hours after a stroke in HOPE. Alteplase and usual care groups had the same 10.8% incidence of 90-day mortality (adjusted RR 0.91, 95% CI 0.52-1.62).

Lou concluded that the study's results support extending the therapeutic window for IV thrombolysis in stroke patients for whom thrombectomy is not available or indicated.

Indeed, HOPE builds on a growing evidence base for the concept of going as far out as 24 hours.

Previously, the TRACE-III found that late administration of another thrombolytic, tenecteplase, was of clinical benefit in the 4.5-24 hour window after a stroke in situations where thrombectomy was not available immediately. The TRACE-III patients were those with ischemic stroke due to large vessel occlusion (LVO) and proof of salvageable brain tissue identified on CT perfusion or perfusion-diffusion MRI using iStroke software.

That trial marked a comeback for late lytics after the TIMELESS trial failed to prove tenecteplase's benefit in LVO patients with evidence of salvageable tissue on perfusion imaging at 4.5-24 hours. Given that TIMELESS had 77.3% of people also receiving endovascular thrombectomy due to the participation of comprehensive stroke centers, however, it was deemed not applicable to non-EVT patients.

At ISC, Lou pointed out that with the inclusion of medium-distal vessel occlusion strokes, HOPE had less restrictive criteria than either TRACE-III and TIMELESS. Also, the study had no mandate for any specific software for CT perfusion and was therefore more representative of real-world clinical practice.

HOPE had screened for suitable candidates, namely those who showed salvageable tissue. Salvageable tissue was defined as ischemic core volumes 70 mL or lower, penumbra at least 10 mL, and mismatch of at least 20% based on CT perfusion imaging.

The open-label trial was conducted at 26 sites across China. Patients were eligible if they presented 4.5-24 hours after stroke onset with a NIH Stroke Scale score 4-26. Both LVO and medium-distal vessel occlusion strokes were included in the trial.

Investigators had 372 patients randomly assigned alteplase (0.9 mg/kg) or standard treatment. Across the cohort, the median age was 72-73 and over half were men. Over 15% of participants had had a previous ischemic stroke. The baseline NIH Stroke Scale score was 10 in both alteplase and control groups. Median ischemic cores were 12.4 mL and 13.9 mL, respectively, and perfusion lesions were 48.8 mL and 51.9 mL.

On subgroup analysis, the benefit of alteplase seemed to hinge on whether the patient had an occlusion at the M2 segment of the middle cerebral artery as opposed to one in M1 or the internal carotid artery. Additionally, strokes related to intracranial atherosclerosis responded disproportionately better to alteplase.

These analyses were underpowered and hypothesis-generating, Lou warned ISC attendees. Additionally, the trial results as a whole may have limited generalizability to non-Chinese populations.

Finally, Lou emphasized that HOPE was not a study applicable to LVO patients presenting directly to thrombectomy-capable stroke centers.

• 

  Nicole Lou is a reporter for MedPage Today, where she covers cardiology news and other developments in medicine. Follow

Disclosures

HOPE was funded by the Second Affiliated Hospital of Zhejiang University, China.

Lou had no disclosures.

Primary Source

International Stroke Conference

Source Reference: Zhou Y, et al "Alteplase for ischemic stroke at 4.5-24 hours with perfusion-imaging selection: HOPE trial" ISC 2025.

Brain-computer interface tool improves motor function of stroke patients: study

 Nothing here tells me the EXACT DAMAGE DIAGNOSIS that this would be good for. I assume not mine since most of my motor and pre-motor cortex is dead and I highly doubt they are listening in on the frontal cortex commands.

Brain-computer interface tool improves motor function of stroke patients: study

BEIJING, April 22 (Xinhua) -- A team of Chinese scientists have found during a clinical trial that brain-computer interface (BCI) rehabilitation can improve upper limb motor function in patients with stroke.

BCI is a kind of communication system that converts the "ideas" in the brain into instructions and has been used in stroke rehabilitation.

The researchers from the Beijing Tiantan Hospital under Capital Medical University led an investigator-initiated, 17-center clinical trial in China, in which 296 patients with ischemic stroke were randomized to receive BCI or traditional rehabilitation training for one month.

The primary efficacy outcomes showed that the score change from baseline of BCI group was noticeably higher than that of control group, according to a study recently published in the journal Cell Med.

There are nearly 200 medical brain-computer interface enterprises in China, with 25 percent of those enterprises working with implantable technology and 75 percent working with non-implantable technology, according to the China Academy of Information and Communications Technology's report on the development and application of brain-computer interface technology (2023). ■

Enhancing Value and Well-Being The Basket of Motivators Framework for Aligning Neurology Clinical Practices With Performance Outcomes

You can easily have your neurologists produce quality outcomes if you create EXACT DAMAGE DIAGNOSES and then follow that up with EXACT REHAB PROTOCOLS! Your neurologists won't be second guessing themselves all the time and wondering how their work will be measured.

Enhancing Value and Well-Being The Basket of Motivators Framework for Aligning Neurology Clinical Practices With Performance Outcomes

Peter N. Hadar, MD, MS https://orcid.org/0000-0002-1681-4717, Susanna Gallani, PhD, MBA https://orcid.org/0000-0001-6242-3031, and Lidia Moura, MD, PhD, MPH https://orcid.org/0000-0002-1191-1315Authors Info & Affiliations

June 2024 issue

14 (3)

https://doi.org/10.1212/CPJ.0000000000200280

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Abstract

Purpose of Review

Physician burnout, which is prevalent in neurology, has accelerated in recent years. While multifactorial, a major contributing factor to burnout is a payment model that rewards volume over quality, leaving physicians overburdened and unfulfilled. The aim of this review was to investigate ways of reducing burnout while improving quality-based outcomes in a value-based health care model.

Recent Findings

Burnout affects researchers, educators, clinicians, and administrators in all fields and tracks, but neurologists experience some of the worst burnout rates among specialties. Transitioning to a value-based health care model, which rewards quality and outcomes(Yeah, you reward 100% recovery! That would be quality!) over volume, may contribute to reversing the burnout trend. However, this requires that physicians feel valued in the workplace in ways corresponding to their preferences. We propose to stratify neurologists using the “basket of motivators” framework, which operates multiple individual-based and team-based motivators including balance among work responsibilities, work-life balance, institutional pride, self-actualization at work, work environment, and finances. By tailoring individual-based and team-based financial and nonfinancial incentives, neurologists are empowered to work at the top of their license to provide high-impact clinical care while combating the most prominent causes of burnout.

Summary

To address the neurologist burnout epidemic, a transition to value-based health care is needed that rewards quality-based performance outcomes through both individual-based and team-based approaches that apply financial and nonfinancial incentives. Understanding the underlying motivations behind neurologists' drives to work can inform tailored incentives that allow neurologists to provide value to their patients and feel valued by their organizations.

 

 

 

 

 

 

 

 

 

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Motor recovery after stroke: Lessons from functional brain imaging

 The lesson I got from this is that NOTHING HERE is going to get you recovered, the only goal in stroke! Survivors don't care about your imaging, it does nothing for recovery. Send me hate mail on this: oc1dean@gmail.com. I'll print your complete statement with name and my response in my blog.

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

 

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(If this really helped the statement would be: This imaging gives us an exact damage diagnosis so we now can choose the correct rehab protocols that deliver recovery from such damage.) in the selection of rehabilitation methods that best foster recovery. [Neurol Res 2002; 24: 453-458]

AI Can Assist With Brain Lesion Localisation Following Stroke

 Once we know the EXACT LOCATION; our researchers can determine the EXACT RECOVERY PROTOCOLS that fix such damage. And we can forever remove the stupid saying; 'All strokes are different, all stroke recoveries are different'.

AI Can Assist With Brain Lesion Localisation Following Stroke

Artificial intelligence (AI) may serve as a future tool for neurologists to locate where in the brain a stroke has occurred, according to a study published in Neurology Clinical Practice.

For the study, a large language model, generative pre-trained transformer 4 (GPT-4), was trained on history and neurologic physical examination from published cases

click to scroll down to continue reading the article

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of acute stroke followed by questions for clinical reasoning.

“Not everyone with stroke has access to brain scans or neurologists, so we wanted to determine whether GPT-4 could accurately locate brain lesions after stroke based on a person’s health history and a neurologic exam,” said Jung-Hyun Lee, MD, State University of New York Downstate Health Sciences University, Brooklyn, New York.

To evaluate the efficacy of GPT-4 for locating lesions in the brain, Dr. Lee and colleagues used 46 published cases of patients with stroke. The researchers fed raw text from patients’ health histories and neurologic exams into GPT-4. They asked the AI to answer 3 questions: whether a patient had 1 or more lesions; on which side of the brain lesions were located; and in which region of the brain the lesions were found. They repeated these questions for each patient 3 times. Results from GPT-4 were then compared with brain scans for each patient.

Researchers found that GPT-4 processed the text from the health histories and neurologic exams to locate lesions in many patients’ brains, identifying which side of the brain the lesion was on, as well as the specific brain region, with the exception of lesions in the cerebellum and spinal cord.

GPT-4 was able to identify the side of the brain where lesions were found with a sensitivity of 74% and a specificity of 87%. It also identified the brain region with a sensitivity of 85% and a specificity of 94%.

When looking at how often the 3 tests had the same result for each patient, GPT-4 was consistent for 76% of patients regarding the number of brain lesions. It was consistent for 83% of patients for the side of the brain, and for 87% of patients regarding the brain regions.

However, when combining its responses to all 3 questions across all 3 times, GPT-4 provided accurate answers for only 41% of patients.

“While not yet ready for use in the clinic, large language models such as generative pre-trained transformers have the potential not only to assist in locating lesions after stroke, they may also reduce healthcare disparities because they can function across different languages,” concluded Dr. Lee. “The potential for use is encouraging, especially due to the great need for improved healthcare in underserved areas across multiple countries where access to neurologic care is limited.”

Reference: https://www.neurology.org/doi/10.1212/CPJ.0000000000200293

SOURCE: American Academy of Neurology

Dose Response to Upper Extremity Stroke Rehabilitation Varies by Individual: Early Indicators of Treatment Response

 Competent researchers would correlate an exact damage diagnosis to the EXACT rehab protocol used and thus make rehab interventions repeatable on demand! Then we could get rid of this crapola excuse used by all stroke medical 'professionals' to justify why they failed to get their patients recovered! 'All strokes are different, all stroke recoveries are different.'

Dose Response to Upper Extremity Stroke Rehabilitation Varies by Individual: Early Indicators of Treatment Response

Lynne V. Gauthier,

Roshan Ravi,

David DeLuca and

Wenjin Zhou

Originally published26 Feb 2024https://doi.org/10.1161/STROKEAHA.123.045039Stroke. 2024;55:696–704

Abstract

BACKGROUND:

Dose response has remained a priority area in motor rehabilitation research for decades, prompting several large randomized trials and meta-analyses. These between-subjects comparisons have revealed equivocal relationships between the duration of motor practice and rehabilitation response. Prior reliance on time-consuming clinical assessments made it infeasible to capture within-subjects dose response, as tracking the dose-response trajectory of an individual requires dozens of repeated administrations.

METHODS:

This secondary observational cohort analysis of existing data from the gaming arms of the VIGoROUS multisite trial (Video Game Rehabilitation for Outpatient Stroke) describes the rehabilitation dose response of 80 participants with mild-moderate chronic stroke. The 3-dimensional joint position data were captured via the Kinect v2 optical sensor as participants completed a prescribed 15 hours of in-home unsupervised game-based motor practice. Kinematic dose response trajectories were fitted from hundreds to thousands of in-game repetitions for 4 separate upper extremity movements for each participant.

RESULTS:

Of 75 participants with sufficient data for dose-response analysis, 85% showed improved motor capacity for at least 1 movement. Dose response was bimodal; 42% required <5 hours of motor practice before reaching a plateau in movement kinematics, whereas 55% required >10 and 34% required >30 hours. We could predict with 93% accuracy whether or not an individual would ultimately respond to game-based motor practice within 5 hours of gameplay.

CONCLUSIONS:

Dose response varies considerably between individuals. About half of chronic stroke patients benefit from higher doses of motor practice than the current standard of care. Individualized dose-response data from motion capture rehabilitation gaming can guide clinical decision-making early on in treatment.

REGISTRATION:

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02631850.

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Does gait analysis change clinical decision-making in post-stroke patients? Results from a pragmatic prospective observational study

Why was this done?  Isn't it completely obvious that if you don't do objective damage diagnosis you can never create protocols for recovery? Not doing gait analysis means your therapist and doctor are just guessing on what to do. ARE YOU OK WITH THAT CRAPOLA MEDICAL TREATMENT?

Does gait analysis change clinical decision-making in post-stroke patients? Results from a pragmatic prospective observational study

 

 
chronic poststroke patients. Further work should be done to better translate GA results into indications for specific physiotherapy.
Clinical Rehabilitation Impact.
 The use of GA as a  tool to better define the rehabilitation planning in post-stroke patients should be fostered, particularly  when surgery or botulinum toxin are considered and/ or the prescription of orthoses is hypothesised.
K
EY
 
 WORDS
:
Gait - Stroke - Decision making - Rehabilitation - Technology assessment, biomedical.
Computerized gait analysis (GA), performed in a laboratory equipped with instruments for kin-ematic, kinetic and EMG data collection, is unanimously recognized as the most effective approach for an objective and comprehensive analysis of human locomotion.¹Conversely, the role of GA in clinical decision-making is still controversial,^{2, 3}except for the application in the pre-surgical planning of children  with cerebral palsy (CP), where it was ascertained that the percentage of CP patients whose surgical plan was changed after GA ranges between 52% ⁴ to 89%,⁵ with a more recent study reporting a value of 70%.⁶ A systematic review of Wren et al ⁷found 11 articles related to “diagnostic thinking and treatment” of GA, among a total of 240 articles about the clinical efficacy of GA, and concluded that there is strong evidence of an effect of GA on treatment decision-

 Background.
 Gait analysis (GA) was demonstrated  to change presurgical planning and improve gait outcomes in children with Cerebral Palsy. GA is often used also to assess walking capability of post stroke subjects, although its influence in the clinical management of these patients has not yet been established.
Objective.
 To assess the impact of GA on clinical deci-assess the impact of GA on clinical decision-making in adult chronic post stroke patients.
 Design.
 Pragmatic prospective observational study.
Setting.
 Rehabilitation hospital, both outpatients and inpatients.
 Population.
 Forty-nine patients (age: 53.3±14.5 years)  who had had a cerebrovascular accident 35.2±26.4 months before and were referred to the gait analysis service.
 Methods.
 Recommendations of therapeutic treatments  before and after the analysis of GA data were com-pared, together with the confidence level of recommendations on a 10-point scale. Frequency of changes of post-GA vs pre-GA recommendations were computed for each recommendation type: surgery, botulinum  toxin (BT), orthotic management and physiotherapy.
 Results.
 Based on the analysis of GA data, 71% of post-stroke subjects had their treatment planning changed in some components. Indeed, 73% of patients with indications for surgery had their surgical planning changed; 81%, 37% and 32% had, respectively, their BT, orthotic and physiotherapy planning changed. Confidence level of recommendations increased significantly after GA, in both the whole group of patients (from 6.7±1.4 to 8.7±0.6, P<0.01) and the subgroup  whose recommendations had not changed (7.0±1.5vs.  8.8±0.4, P<0.01).
Conclusion.
 GA significantly influences the therapeutic planning and reinforces decision-making for
Corresponding author: M. Ferrarin, IRCCS S. Maria Nascente, Fondazione Don Carlo Gnocchi Onlus, Via Capecelatro 66, 20148 Milan, Italy. E-mail: mferrarin@dongnocchi.it
 

Evolution of FMRI activation in the perilesional primary motor cortex and cerebellum with rehabilitation training-related motor gains after stroke: a pilot study

 But with no specific protocols listed and no objective damage starting point this is still almost completely useless

Evolution of FMRI activation in the perilesional primary motor cortex and cerebellum with rehabilitation training-related motor gains after stroke: a pilot study

 Yun Dong,MD,PhD,Carolee J.Winstein,PhD,Richard Albistegui-DuBois,PhD,and Bruce H.Dobkin,MD
Background
Previous studies report that motor recovery after partial destruction of the primary motor cortex (M1) may be(weasel words are useless to survivors.) associated with adaptive functional reorganization within spared M1.
Objective
To test feasible methodologies for evaluating relationships between behavioral gains facilitated by rehabilitative training and functional adaptations in perilesional M1 and the cerebellum.
Methods
Four patients with hemiparesis for more than 3 months after a cortical lesion partially within M1 and 12 healthy volunteers participated.Functional magnetic resonance imaging (fMRI) using a finger-tapping task and concurrent behavioral assessments, including the Fugl-Meyer Motor Assessment of the upper extremity and the Wolf Motor Function Test,were conducted before and after 2 weeks of arm focused training;2 patients were further examined 6 and 12 months later to evaluate long-term persistence of brain behavior adaptations.
Results
All patients showed higher activation magnitude in perilesional M1 than healthy controls before and after therapy.Further long-term functional gains paralleled the decrease of activation magnitude in perilesional M1 in the 2 more impaired cases.
Conclusion  

The evolution of suggestive correlations between serial scans of fMRI adaptive activity within the primary motor cortex and the cerebellum in relation to relevant behavioral changes over the course of 2 weeks of task specific therapy and then no formal therapy suggests that repeated assessments may be best for monitoring therapy induced neuroplasticity.This approach may help develop optimal rehabilitation strategies to maximize post stroke motor recovery as well as improve the search for brain behavior correlations in functional neuroimaging research.

Key Words:
Stroke rehabilitation—fMRI—Wol fMotor Function Test—Primary motor cortex—Constraint-induced movement therapy—Adaptive reorganization.
Post stroke recovery of motor function with and without specific rehabilitation training has been attributed in part to adaptive functional reorganization within the central nervous system.^1,2The under-lying neurophysiological mechanisms may include changes in neuronal membrane excitability,synaptic strengthening, synaptogenesis, dendritic arborization,fiber sprouting from surviving neurons,and recruitment of nearby and remote neuronal ensembles after focal brain injury.^3,4Functional reorganization within the intact area surrounding an infarct restricted to the primary motor cortex (M1) was observed over the temporal course of recovery from stroke using functional magnetic resonance imaging (fMRI). The studies supported the notion that human M1 is capable of functional adaptation comparable to that seen in primate experiments.^5,6Growing evidence from both animal and human studies suggests the importance of perilesional adaptive reorganization and the potential modulative effects of focused,intensive rehabilitative training in facilitating this use-dependent reorganization.^7,8With the use of advanced neuroimaging technologies,rehabilitation therapy-induced adaptive reorganization within putative motor networks has been investigated in chronic stroke patients who received constraint induced movement therapy (CIMT).^9-12The correlates between motor functional gains and changes in physiological signals have differed across studies,however.To best elucidate the mechanisms mediating cerebral adaptations after stroke,studies must account for inter subject variability in initial impairment level(Yeah, like an objective damage diagnosis?),lesion location and size,trajectory of behavioral gains associated with time and motor learning experience,and dose of rehabilitation therapy.¹³ between intensive training-related motor functional improvement and adaptive reorganization in perilesionalM1 in patients with partial M1 damage.We performed consecutive fMRI scans with concurrent behavioral assessments in 4 patients who had a single stroke involving a portion ofM1 before,immediately after 2 weeks of CIMT,and,in 2 willing subjects,6 and 12 months later.The aims of the study were 2-fold:1) to test the hypothesis that rehabilitative training-related behavioral gains are associated with specific functional adaptations within the intact perilesional M1 and the remotely connected cerebellum and 2) to test methods for evaluating direct brain-behavior correlates and generate preliminary data for larger scale studies.

The Art and Science of Stroke Outcome Prognostication

There is literally no science involved, no objective damage diagnosis. All guesswork like this:

Mercury astronaut Scott Carpenter suffers stroke; full recovery expected

Oops! 

 Scott Carpenter - Obituary

 

 

The Art and Science of Stroke Outcome Prognostication

Meah MingYang Gao

,

Jeffrey Wang

,

Gustavo Saposnik

Originally published25 Mar 2020https://doi.org/10.1161/STROKEAHA.120.028980Stroke. 2020;51:1358–1360

• This article is a commentary on the following

See related article, p 1477

Tell me and I forget. Teach me and I remember. Involve me and I learn.

—Benjamin Franklin (1706–1790), statesman, scientist, and inventor¹

As stroke clinicians, we are routinely asked by patients and families regarding prognosis. The cognitive process underlying prognostication is complex, poorly understood, and thus can be subjected to cognitive biases colored by our personal experiences. Previous studies suggest that clinicians, even those with expertise in stroke, perform poorly in predicting clinical outcomes. For example, the JURaSSiC study (Clinician Judgment vs Risk Score to Predict Stroke Outcomes) reported that clinicians’ overall accuracy for predicting death or disability at discharge was a staggeringly low (16.9%), and none of the 111 participating clinicians with expertise in stroke care correctly predicted all 5 case outcomes.^1a Similarly, Ntaios et al² found that >50% of all estimates made by physicians with an interest in stroke care were inaccurate, and their predictions became even less precise in those patients who received thrombolytic therapy. Interestingly, meteorologists provide more accurate predictions for rain (r: 95%)³ and poker players for chances of winning a hand (r: 96%).⁴ Contrarily, patients and families rely on our lower rated predictions to make critical decisions. As a result, evidence-based prognostic models are necessary to better inform clinicians.

To address this need, several prognostic models have been developed to aid prognostication after ischemic stroke (Table). Comparative studies have shown that these prognostic models outperform clinician judgment in predicting stroke outcomes.^1,2 These prognostic scores were derived from rigorous mathematical modeling based on data from large cohorts of acute stroke patients. While there have been some external validation studies, they were largely conducted in a Western population and in patients recruited before the widespread utilization of reperfusion therapies.⁵ Furthermore, new advances are occurring at an unprecedented pace across the continuum of stroke care, from the development of neuroprotective agents, application of extended window reperfusion therapies, to modern stroke rehabilitation technologies. These prognostic models require regular validation and calibration using updated data to retain their usefulness.

Table. Comparison of 6 Stroke Prognostic Scores as Tested by Matsumoto et al⁶

Prognostic Score	Applicable Population	Variables	Outcomes	Patient-Centered Outcomes Included?
PLAN7	Patients treated with intravenous thrombolysis were excluded	Age, level of consciousness, arm weakness, leg weakness, neglect or aphasia, history of atrial fibrillation, history of congestive heart failure, cancer, prestroke functioning	mRS score of 5–6 and death at 30 d and 1 y	No
IScore8	Derived from an ischemic stroke cohort. Validated in NINDS tPA trials, VISTA	3 mo: age, sex, stroke severity (CNS), stroke subtype (TOAST), history of atrial fibrillation, history of congestive heart failure, cancer, renal dialysis, prestroke functioning, acute glucose	mRS score of 3–6 and death at 30 d and 1 y	No
		1 y: in addition, history of myocardial infarction, smoking status
ASTRAL9	Patients with prestroke dependency were excluded	Age, stroke severity (NIHSS), level of consciousness, presence of visual field defect, symptoms onset to treatment time, acute glucose	mRS score of 3–6 and death at 3 mo	No
HIAT10	Derived from patients treated with intra-arterial thrombolysis	Age, stroke severity (NIHSS), acute glucose	mRS score of 4–6 at discharge	No
THRIVE11	Derived from patients treated with endovascular therapy. Validated also in patients treated with intravenous thrombolysis or no acute treatment	Age, stroke severity (NIHSS), history of atrial fibrillation, history of hypertension, diabetes mellitus	Functional outcome (mRS, 0–2 vs 3–6) and mortality at 3 mo	No
SPAN-10012	Derived from patients treated with intravenous thrombolysis	Age, stroke severity (NIHSS)	Composite favorable outcome (mRS, 0–1; NIHSS, ≤1; Barthel index, ≥95; and Glasgow Outcome Scale score, 1), catastrophic outcome (mRS, 4–6) and death at 3 mo	No

ASTRAL indicates Acute Stroke Registry and Analysis of Lausanne; CNS, Canadian Neurological Scale; HIAT, Houston Intra-Arterial Recanalization Therapy; Iscore, Ischemic Stroke Predictive Risk Score; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; NINDS, National Institute of Neurological Disorders and Stroke; PLAN, Preadmission Comorbidities, Level of Consciousness, Age, and Neurological Deficit; SPAN, Stroke Prognostication Using Age and National Institutes of Health Stroke Scale; THRIVE, Totaled Health Risks in Vascular Events; TOAST, Trial of ORG 10172 in Acute Stroke Treatment; tPA, tissue-type plasminogen activator; and VISTA, Virtual International Stroke Trials Archive.

In the current issue, Matsumoto et al¹³ assessed the performance of 6 stroke prognostic scores in 4237 acute ischemic stroke patients hospitalized at a Japanese stroke center between 2012 and 2017. This study adds value to existing literature given its large sample size and relatively modern enrollment period allowing patients who received reperfusion therapies to be included in the cohort. Authors directly compared the performances of 6 point-based stroke prognostic scores against each other and showed that they all performed reasonably well in this real-world population; areas under the receiver operating characteristic curve ranged from 0.69 (Houston Intra-Arterial Recanalization Therapy [HIAT] score) to 0.92 (Preadmission Comorbidities, Level of Consciousness, Age, and Neurological Deficit [PLAN] score) in predicting poor functional outcomes and 0.87 (PLAN) to 0.88 (Ischemic Stroke Predictive Risk Score [Iscore] and Acute Stroke Registry and Analysis of Lausanne [ASTRAL] score) in predicting in-hospital mortality. This current study also explored the promising field of machine learning in the current era of big data. In all data-driven modeling methods, the National Institutes of Health Stroke Scale score, preadmission modified Rankin Scale (mRS), and age emerged as the top 3 factors predicting functional outcomes, validating what clinicians have long known intuitively to be important clinical prognostic indicators.

However, the findings by Matsumoto et al may not generalize readily to other stroke populations. The participants were all treated in a single center in Japan, and only 1.5% underwent endovascular therapy. Nonetheless, this study provides valuable external validation of several prognostic scores in an East Asian cohort. Furthermore, stroke patients who do not undergo reperfusion therapy remain the vast majority globally. Another important caveat to consider is that the functional outcomes in this study were recorded at the time of discharge, while original publications of the ASTRAL, Totaled Health Risks in Vascular Events (THRIVE), and Stroke Prognostication Using Age and National Institutes of Health Stroke Scale (SPAN)-100 scores used 90-day outcomes. This discrepancy may underlie the relatively lower performance of these three scores in this cohort as compared with PLAN and IScore, both of which were originally derived using functional data at discharge.

There is a growing body of literature examining the utility of machine learning for both diagnosis and prognosis in a multitude of medical subspecialties.¹⁴ In the present study, the authors assessed the utility of newer machine learning algorithms in prognostication for ischemic stroke. Unsurprisingly, these models performed well in predicting poor functional outcome at time of discharge. Specifically, the 2 ensemble decision tree models tested outperformed the more traditional logistic regression models for predicting mRS scores of 3 to 6 and 4 to 6, allowing improved precision at the midpoint of the functional outcome spectrum. However, decision tree models were limited by the problem of overfitting, which occurs with low-frequency outcomes (eg, in-hospital mortality) or smaller sample sizes. Furthermore, the 5 machine learning algorithms tested in this study offered at best a marginally higher degree of accuracy over the highest performing clinical prognostic scores. Overall, while stroke prognosis using machine learning is an exciting concept, more work is needed to fully realize its predictive potential and support clinical application.⁶

Another question remains: if prognostic scores for ischemic stroke have been externally validated, why are they not being used routinely in clinical practice? Are we still "eyeballing" when asked about the prognosis of our stroke patients? There are many potential reasons. Is it a matter of overconfidence in our ability to prognosticate based on clinical experience alone? Or are most frontline clinicians simply not aware of the existence of these scores? A higher number of variables not readily available without detailed chart review make routine use of a predictive model cumbersome. Lastly, perhaps an easy-to-measure outcome such as the mRS, though well suited for testing therapeutic interventions, falls short when it comes to the complex task of prognostication after stroke. Each individual patient we encounter on the stroke unit may have a different idea of what is important to his or her quality of life, and, therefore, prediction of specific patient-centered outcomes, such as swallowing or social participation, is likely more meaningful than dichotomized mRS ranges of 0 to 2 versus 3 to 6.¹⁵ Five of the 6 scores cited by Matsumoto et al were validated for prediction of a dichotomized mRS range or death, and the remaining score (SPAN-100) used a dichotomized composite of mRS, National Institutes of Health Stroke Scale, Barthel Index, and Glasgow Outcome Scale (Table).

Efforts should be made to survey stroke clinicians on why they are not routinely using externally validated prognostic models. Improving both the accuracy and meaningfulness of prognostication scores may foster better communication and lead to improved shared clinical decision-making. Ultimately, predictive models, even those derived from complex data-driven algorithms, are incorrect in some patients. They should not be the sole foundation for clinical decision-making in practice and certainly cannot replace a stroke physician’s comprehensive assessment and clinical acumen.¹⁶ After all, stroke is a complex condition occurring in heterogeneous populations with variety of mechanisms, each having a different prognosis. True stroke expertise lies in not only learning the science of evidence-based models but more importantly, mastering the art of how to apply the available evidence at bedside. Our mandate is to overcome those challenges and ameliorate the existing knowledge-to-action gaps in acute stroke care.

Sources of Funding

Dr Saposnik is supported by the Heart and Stroke Foundation of Canada Career Award following an open peer-review competition.

Disclosures

Dr Saposnik is the Associate Editor for the Emerging Therapies Section at Stroke journal. He is supported by the Heart and Stroke Foundation of Canada Career Award following an open peer-reviewed competition and received research grants from Roche and speaker honoraria from Servier and Celgene. The other authors report no conflicts.

Footnotes

*Drs Gao and Wang contributed equally.

 

Correlations Between Physician and Hospital Stroke Thrombectomy Volumes and Outcomes: A Nationwide Analysis

My conclusion on this is that because you don't have ANY OBJECTIVE DAMAGE DIAGNOSIS LEADING TO EXACT STROKE PROTOCOLS, you will never get the recovery results you want. And since you are measuring 'better outcomes' rather than 100% recovery you will never get to 100% recovery.

Correlations Between Physician and Hospital Stroke Thrombectomy Volumes and Outcomes: A Nationwide Analysis

Laura K. Stein

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J Mocco

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Johanna Fifi

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Nathalie Jette

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Stanley Tuhrim

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Mandip S. Dhamoon

Originally published7 Jun 2021https://doi.org/10.1161/STROKEAHA.120.033312Stroke. ;0:STROKEAHA.120.033312

Abstract

Background and Purpose:

Despite the Joint Commission’s certification requirement of ≥15 stroke thrombectomy (ST) cases per center and proceduralist annually, the relationship between ST case volumes and outcomes is uncertain. We sought to determine whether a proceduralist or hospital volume threshold exists that is associated with better outcomes among Medicare beneficiaries.

Methods:

Retrospective cohort study using validated International Classification of Diseases,Tenth Revision, Clinical Modification codes to identify admissions with acute ischemic stroke and treatment with ST. We used de-identified, national 100% inpatient Medicare data sets from January 1, 2016, to December 31, 2017 for US individuals aged ≥65 years. We calculated total procedures by proceduralist and hospital. We performed adjusted logistic regression of total cases as a predictor of inpatient mortality, good outcome (defined by dichotomized discharge disposition of inpatient rehabilitation or better), and 30-day readmission. We adjusted for sex, age, Charlson Comorbidity Index, availability of neurocritical care, teaching hospital status, socioeconomic status, 2-year stroke volume, and urban versus rural hospital location. We dichotomized case numbers incrementally to determine a volume threshold for better outcomes.

Results:

Thirteen thousand three hundred thirty-five patients were treated with ST by 2754 proceduralists at 641 hospitals. For every 10 more proceduralist cases, patients had 4% lower adjusted odds of inpatient mortality (adjusted odds ratio, 0.96 [95% CI, 0.95–0.98], P<0.0001) and 3% greater adjusted odds of good outcome (adjusted odds ratio, 1.03 [95% CI, 1.02–1.04], P<0.0001). For every 10 more hospital cases, patients had 2% lower odds of inpatient mortality (adjusted odds ratio, 0.98 [95% CI, 0.98–0.99], P=0.0003) and 2% greater odds of good outcome (adjusted odds ratio, 1.02 [95% CI, 1.01–1.02], P<0.0001). With increasing volumes, there were higher odds of better outcomes.

Conclusions:

Nationally, higher proceduralist and hospital ST case volumes were associated with reduced inpatient mortality and better outcome. These data support volume requirements in guidelines for ST training and certification.

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Asymmetry and variability should be included in the assessment of gait function in poststroke hemiplegia with independent ambulation during early rehabilitation

You are referring to objective damage diagnosis, use the correct terminology. With no objective diagnosis you can never match stroke protocols to results. 

 Asymmetry and variability should be included in the assessment of gait function in poststroke hemiplegia with independent ambulation during early rehabilitation

Archives of Physical Medicine and Rehabilitation , Volume 102(4) , Pgs. 611-618.

NARIC Accession Number: J86137.  What's this?
ISSN: 0003-9993.
Author(s): Kim, Woo-Sub ; Choi, Hanboram ; Jung, Jung-Woo ; Yoon, Joon S. ; Jeoung, Ju H..
Publication Year: 2021.
Number of Pages: 8.

Abstract: 

Study investigated whether independent features of poststroke spatiotemporal data are dependent on measurement protocol or study sample. Data were obtained from the medical records of patients admitted to the rehabilitation department of the Korea University Guro Hospital, who were in the subacute recovery stage post stroke. Of 98 patients who underwent gait assessment, 69 patients who could walk more than 10 meters without personal assist or assistive devices were included in the data analysis. Spatiotemporal parameters during level walking and their asymmetry and variability were obtained by insole foot pressure measurement system. Of the independent components extracted by principal component analysis, 3 independent components explained 81.9 percent of the total variance of spatiotemporal post stroke gait data. The first component has associations with walking speed and proportion of double support phase and explained 46.6 percent of total variance. The second component has association with temporal asymmetry and explained 21.1 percent of total variance. The third component has association with temporal variability and explained 14.2 percent of total variance. Principal component scores did not show significant differences between stroke types and among stroke lesions. The findings suggest that temporal asymmetry and variability should be included in the assessment of post stroke gait during early rehabilitation. They are independent of each other and provide characteristics of post stroke gait that are independent to the walking speed. They are helpful for rehabilitation planning and developing treatment strategy in post stroke gait rehabilitation.
Descriptor Terms: AMBULATION, EVALUATION, HEMIPLEGIA, INTERNATIONAL REHABILITATION, STROKE.


Can this document be ordered through NARIC's document delivery service*?: Y.

Citation: Kim, Woo-Sub , Choi, Hanboram , Jung, Jung-Woo , Yoon, Joon S. , Jeoung, Ju H.. (2021). Asymmetry and variability should be included in the assessment of gait function in poststroke hemiplegia with independent ambulation during early rehabilitation.  Archives of Physical Medicine and Rehabilitation , 102(4), Pgs. 611-618. Retrieved 5/18/2021, from REHABDATA database.

“Everyone needs rehab, but…”: exploring post-stroke rehabilitation referral and acceptance decisions

 

There should be no questions about decision making at all. You look at the objective damage diagnosis and choose the protocols that will fix that damage.  Until we get to that level of specificity stroke survivors are screwed because your stroke medical 'professionals' are flailing in the dark about how to get survivors 100% recovered. 

“Everyone needs rehab, but…”: exploring post-stroke rehabilitation referral and acceptance decisions

Kerry Marnane, Louise Gustafsson, Sally Bennett, Ingrid Rosbergen & Rohan Grimley

Received 09 Jun 2020, Accepted 14 Apr 2021, Published online: 11 May 2021

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• https://doi.org/10.1080/09638288.2021.1918770
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Abstract

Purpose

To explore the decision-making processes and experiences of acute and rehabilitation clinicians, regarding referral and acceptance of patients to rehabilitation after stroke.

Materials and methods

Multi-site rapid ethnography, involving observation of multidisciplinary case conferences, interviews with acute stroke and rehabilitation clinicians, and review of key documents within five (5) acute stroke units (ASUs) in Queensland, Australia. A cyclical, inductive content analysis was performed.

Results

Seven key themes were identified, revealing the complex nature of post-stroke rehabilitation referral and acceptance decision making. Although the majority of clinicians felt that all patients could benefit from rehabilitation, they acknowledged this could not always be the case. Rehabilitation potential and goals were considered by clinicians, but decision making was impacted by ASU context and team processes, rehabilitation service availability and access procedures, and the relationships between the acute and rehabilitation clinicians. Patients and families were not actively involved in the decision-making processes.(THIS IS TOTALLY WRONG! Doctors and therapists should have NO say in rehab decisions! The only goal in stroke is 100% recovery! NO decision making process needed! GET THERE!)

Conclusions

Post-stroke rehabilitation decision making in Queensland, Australia involves complex processes and compromise. Decisions are not based solely on patients’ rehabilitation needs, and patients and families are not actively involved in the decision-making process. Mechanisms are required to streamline access procedures, and improve shared decision making with patients.

• IMPLICATIONS FOR REHABILITATION

• Referral decision making for post-stroke rehabilitation is complex and not always based solely on patients’ needs.

• Clear and straightforward access procedures and positive relationships between acute and rehabilitation clinicians have a positive impact on referral decision making.

• Stroke services should review their processes to ensure shared decision making is facilitated when patients require access to rehabilitation.