Stroke Rehabilitation: A Function-Based Approach - book

 Notice the COMPLETE FAILURE of this book; 'management' NOT RECOVERY!

When your therapist references this book; DEMAND 100% RECOVERY PROTOCOLS! Not this 'management' crapola!

Stroke Rehabilitation: A Function-Based Approach

by Glen Gillen EdD OTR FAOTA (Author), Dawn M. Nilsen EdD OTR/L FAOTA (Author)

Learn to confidently manage the growing number of stroke rehabilitation clients with Gillen’s Stroke Rehabilitation: A Function-Based Approach, 5th Edition. Using a holistic and multidisciplinary approach, this unique text remains the only comprehensive, evidence-based stroke rehabilitation resource for occupational therapists. This new fifth edition has been extensively updated to include the research, trends, and best practices in the field. As with previous editions, this comprehensive reference uses an application-based method that integrates background medical information, samples of functionally based evaluations, and current treatment techniques and intervention strategies.

• Case studies challenge you to apply rehabilitation concepts to realistic scenarios.
• Evidence-based clinical trials and outcome studies clearly outline the basis for stroke interventions.
• A survivor's perspective is included in one chapterto give you a better understanding of the stroke rehabilitation process from the client point-of-view.
  • Multidisciplinary approach highlights discipline-specific distinctions in stroke rehabilitation among occupation and physical therapists, physicians, and speech-language pathologists.
  • Review questions in each chapter help you assess your understanding of rehabilitation concepts.
  • Key terms and chapter objectives at the beginning of each chapter help you study more efficiently.
  • NEW! Revised and expanded content keeps you up to date on the latest information in all areas of stroke rehabilitation.
  • NEW! Updated references reflect the changes that have been made in the field.
  • NEW! Assessment Appendix and Pharmacological Appendix
  • UPDATED! Resources for Educators and Students on Evolve  

Neurocomputational models of stroke: a systematic review and perspectives for rehabilitation

 With NO protocols created or identified; ABSOLUTELY FUCKING USELESS CRAPOLA! Doesn't anyone in stroke know that survivors need EXACT RECOVERY PROTOCOLS? My opinion is that everyone in stroke must be blitheringly stupid. They'll be screaming for help when they become the 1 in 4 per WHO that has a stroke.  

Neurocomputational models of stroke: a systematic review and perspectives for rehabilitation

• Anna Hoyle,
• Leen Jabban,
• Adrian R. Rivadulla,
• Balázs Nyírő,
• Eamonn O’Neill,
• Benjamin Metcalfe &
• Damien Coyle 

We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.

Abstract

Background

Stroke recovery depends on complex, multi-scale neural mechanisms that remain poorly understood despite major advances in neuroimaging and rehabilitation science. Computational modelling has begun to bridge the gap between descriptive observations from neuroimaging and behavioural studies and mechanistic understanding by simulating how lesions disrupt neural dynamics and how the brain reorganises to restore function.

Objective

To systematically identify and analyse existing computational models of stroke across different scales; to examine which aspects of stroke-related impairment and recovery have been modelled, how different model types are used, and how stroke effects are incorporated; and to evaluate their current contributions, strengths, and limitations for understanding stroke and informing rehabilitation research.

Methods

A systematic search following PRISMA guidelines was conducted across PubMed, Embase, IEEE Xplore and Web of Science to identify peer-reviewed studies computationally modelling neural aspects of stroke. A structured scoring framework assessed each study across four dimensions: biological plausibility, empirical validation, data integration and personalisation. Studies were thematically grouped to identify methodological trends, limitations and opportunities for future model development.

Results

From 4749 studies screened, 36 met the inclusion criteria. The included models addressed a range of stroke-related processes, including cortical plasticity, lesion effects, functional recovery, pathoelectrophysiology and informing rehabilitation. Model types were used differently across these aims: neural network models were most common in studies of cortical plasticity, lesion effects, and functional recovery, whereas neural mass and whole-brain models were more often used for pathoelectrophysiology and rehabilitation-related questions. Stroke effects were incorporated in diverse ways, ranging from abstract lesioning to patient-specific neuroimaging-based approaches. Although some studies incorporated patient-specific brain imaging data (9/36) and empirical validation (23/36), many remained largely theoretical.

Conclusions

While current models capture different key aspects related to stroke, these phenomena are typically investigated in isolation, with little integration either functionally or across spatial scales. The review suggests that bringing together strengths that are currently distributed across different modelling approaches, such as multi-scale structure, patient-specific modelling, empirical validation and biologically plausible plasticity, could help advance the field.

Development and validation of a machine learning model based on multi-source clinical data for predicting the risk of early neurological deterioration in patients with ischemic stroke

 

Totally wrong objective; Survivors actually want early neurological deterioration prevented! Predictions DO NOTHING TOWARDS RECOVERY! 

What prevents early neurological deterioration is the needed research, not this crapola! You've known of the need for almost a decade but INCOMPETENTLY did this instead! You're fired!

• Early neurological deterioration (36 posts to January 2017)

Development and validation of a machine learning model based on multi-source clinical data for predicting the risk of early neurological deterioration in patients with ischemic stroke

• 

  Yue Li

• W

  Wei Wang

• Y

  Yilan Wei

• J

  Jing Han

• Y

  Yuan Shi

• Q

  Quping Ouyang *

• Neurological Disease Center, Beijing Shunyi District Hospital, Beijing, China

Abstract

Background and objective: 

Early neurological deterioration (END) is a critical clinical event associated with poor patient outcomes after acute ischemic stroke. Early identification of high-risk patients is crucial for timely clinical management. This study aimed to develop and validate a model for predicting END risk for acute ischemic stroke patients using machine learning algorithms.

Methods: 

This study retrospectively and consecutively enrolled 1,151 patients with acute ischemic stroke from the Stroke Center of Beijing Shunyi District Hospital between January 2021 and December 2024. END was defined as progressive worsening of neurological deficit symptoms after onset. Predictive variables were screened using univariate analysis and multiple feature selection methods (Treebag, Boruta, Bayesian). Nine machine learning algorithms (Decision Tree, Efficient Neural Network, K-Nearest Neighbors, Light Gradient Boosting Machine, Logistic Regression, Multilayer Perceptron, Random Forest, Simplified Support Vector Machine, Extreme Gradient Boosting) were employed to construct prediction models. Hyperparameters were optimized via 10-fold cross-validation, and model performance was evaluated in an internal validation cohort (30% of the sample). Primary evaluation metrics included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, F1 score, and net benefit from decision curve analysis (DCA). The SHAP method was used to interpret the optimal model.

Results: 

A total of 161 patients (14.0%) developed END. Feature selection ultimately identified five key predictors: ischemic stroke etiological subtype, Oxford Community Stroke Project (OCSP) classification, age, atrial fibrillation history, and prior stroke history. In both the development and internal validation cohorts, the logistic regression model demonstrated favorable and stable performance (development cohort AUC: 0.787, 95% CI: 0.735–0.839; internal validation cohort AUC: 0.751, 95% CI: 0.668–0.834), with a low log-loss value. DCA suggested potential clinical utility of the logistic regression model. SHAP analysis revealed that the etiological subtype of ischemic stroke and age were the features contributing most to the model’s predictions.

Conclusion: 

This study successfully developed and validated a logistic regression model for predicting END risk. The model incorporates five routinely available clinical variables and demonstrates satisfactory predictive performance and interpretability. The developed online tool may assist clinicians in early risk stratification, providing a reference for personalized intervention.

Serial immune-inflammatory recovery trajectories after acute ischemic stroke: associations with early neurological deterioration and 90-day functional outcome in a retrospective cohort

 

'Associations' don't get you recovered, or are you too fucking stupid to see that? What prevents early neurological deterioration is the needed research, not this crapola! You've known of the need for almost a decade but INCOMPETENTLY did this instead! You're fired!

• Early neurological deterioration (36 posts to January 2017)

Serial immune-inflammatory recovery trajectories after acute ischemic stroke: associations with early neurological deterioration and 90-day functional outcome in a retrospective cohort

• 

  Ruihan Ni 1

• 

  Lan Chu 1,2*

• 1. Suzhou Medical College, Soochow University, Suzhou, Jiangsu, China

• 2. Department of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China

Abstract

Background: 

Systemic inflammation after acute ischemic stroke is usually assessed using admission biomarkers, which may not distinguish transient stress from sustained immune-inflammatory activation. We examined whether serial immune-inflammatory recovery trajectories were associated with early neurological deterioration (END) and 90-day functional outcome.

Methods: 

This single-center retrospective cohort included 760 adults with acute ischemic stroke identified from a hospital stroke database. NLR, SII, SIRI, and hs-CRP measured at admission, 24 h, 72 h, and day 7 were log-transformed and standardized, and equally weighted values were averaged at each observed time point. Latent class mixed models with 2–5 classes were compared without using outcome information, and a five-class solution was selected before association and prediction analyses. The primary outcome was 90-day mRS 3–6. END was defined as an NIHSS increase of ≥2 points within 72 h; the landmark END analysis excluded END within 24 h and tested 0–24 h immune change for END from 24 to 72 h.

Results: 

The five LCMM classes comprised 182 low-stable, 223 transient moderate, 161 delayed recovery, 122 persistent high, and 72 extreme persistent high patients. Among 751 patients with 90-day outcome data, the observed rate of mRS 3–6 increased from 21.5 to 30.6%, 44.2, 71.9, and 98.6% across these classes. After adjustment, persistent high (OR 2.46, 95% CI 1.31–4.61; p = 0.005) and extreme persistent high inflammation (OR 20.24, 95% CI 2.48–165.26; p = 0.005) were associated with mRS 3–6; a bias-reduced sensitivity estimate for the extreme class remained large (OR 13.61, 95% CI 2.34–79.26). Ordinal analysis showed progressively worse mRS for delayed recovery (common OR 2.73), persistent high (4.18), and extreme persistent high (6.72). The 0–24 h composite immune-change metric was not associated with landmark END (OR 1.12, 95% CI 0.92–1.36; p = 0.265). Adding LCMM-5 to the clinical model increased AUC from 0.828 to 0.841, but did not clearly outperform adding admission NLR/SII.

Conclusion: 

Longitudinal classification identified five immune-inflammatory recovery trajectories with a marked gradient in 90-day disability. Persistent-high and extreme persistent-high classes retained independent associations with poor functional outcome.

Association between complete blood count-derived hematological inflammatory ratios and nutritional risk in elderly patients with acute ischemic stroke

 

'Associations' don't get you recovered, or are you too fucking stupid to see that? What prevents nutritional risk is the needed research, not this crapola! Like EXACT DIET PROTOCOLS, starting in the hospital!

• 49% malnutrition post-stroke (1 posts to April 2025)

You've known of the risk for over a year! 

SOLVE THE GODDAMN PROBLEM!

Association between complete blood count-derived hematological inflammatory ratios and nutritional risk in elderly patients with acute ischemic stroke

• 

  Liang’e Xu 1

• 

  Wenjing Wu 2

• 

  Chao Chen 3*

• 1. Department of Neurology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

• 2. Department of Neurology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China

Abstract

Background and aims: 

Mounting evidence suggests CBC-derived hematological inflammatory ratios correlate with nutritional status, yet few studies explore their cross-sectional associations with GNRI-defined concurrent nutritional risk in elderly patients with acute ischemic stroke (AIS). This single-center, cross-sectional, observational study was designed to evaluate the correlation between routine admission hematological markers and nutritional risk in elderly patients with AIS. Twelve CBC-derived indices were analyzed: lymphocyte ratio (LR), red blood cell-to-lymphocyte ratio (RLR), hemoglobin-to-lymphocyte ratio (HLR), monocyte-to-lymphocyte ratio (MLR), monocyte-to-neutrophil ratio (MNR), neutrophil-to-lymphocyte ratio (NLR), NLR-to-platelet ratio (NLR/PLT100), MLR-to-platelet ratio (MLR/PLT), platelet-to-neutrophil ratio (PNR), platelet-to-lymphocyte ratio (PLR), mean platelet volume-to-lymphocyte ratio (MPVLR), serum albumin-to-lymphocyte ratio (ALBLR).

Methods: 

Between January 2022 and January 2024, 540 elderly AIS patients (≥60 years) were enrolled. All participants underwent admission GNRI assessment and were split into GNRI-defined nutritional risk group (GNRI≤98, n = 245, 45.4%) and non-nutritional risk group (GNRI>98, n = 295). Venous blood was collected within 24 h on admission. Univariate and multivariate logistic regression were applied to explore cross-sectional correlations, and an exploratory combined statistical model was built. ROC curve, DeLong’s test, likelihood ratio test and AIC were used to evaluate model discrimination and fit.

Results: 

Multiple indicators including age, hypertension, ALT, UA, TG, LR, RLR, MLR, NLR, NLR/PLT100, MLR/PLT, PLR and MPVLR showed univariate correlations with nutritional risk. Multivariate regression identified MLR and NLR/PLT100 as independent correlates within this cohort; MLR showed the strongest association in this dataset instead of robust correlative ability. Adding MLR alone or combining MLR + NLR/PLT100 to base clinical variables significantly improved C-statistic. The combined model reached an AUC of 0.735, representing only moderate discriminative capacity, and it was merely the superior exploratory model limited to the present sample without external generalizability.

Conclusion: 

Within this single-center cohort, MLR exhibited the strongest cross-sectional correlation with GNRI-defined nutritional risk among all tested CBC-derived hematological inflammatory ratios. The composite model combining baseline clinical indicators, MLR and NLR/PLT*100 demonstrated moderate discriminative ability within the study sample, but is not yet robust enough to serve as an effective tool for routine clinical risk stratification.

The association of high-sensitivity C-reactive protein-triglyceride glucose index with functional outcome in elderly patients with acute ischemic stroke undergoing intravenous thrombolysis

 

 'Associations' don't get you recovered, or are you too fucking stupid to see that? What prevents post stroke cognitive impairment is the needed research, not this crapola!

The association of high-sensitivity C-reactive protein-triglyceride glucose index with functional outcome in elderly patients with acute ischemic stroke undergoing intravenous thrombolysis

• 

  Pengyu Gong 1†

• 

  Gang Chen 2†

• 

  Shuaiyu Chen 3

• Y

  Yaya Fei 1

• Y

  Yuye Jiang 1

• Y

  Yiyang Zhang 1

• J

  Jiajie Lu 1

• J

  Jianhua Song 4

• 

• 

• Y

  Yuechun Wang 1*

• 1. Department of Neurology, Affiliated Hospital of Nantong University, Medical School of Nantong University, Nantong, Jiangsu, China

• 2. Department of Neurology, Haimen Hospital Affiliated to Nantong University, Nantong, Jiangsu, China

Abstract

Background and purpose: 

High-sensitivity C-reactive protein-triglyceride-glucose index (CTI) is an innovative biomarker of insulin resistance and inflammation. The objective of this study was to explore the association of high-sensitivity CTI with functional outcome in elderly patients with acute ischemic stroke (AIS) undergoing intravenous thrombolysis (IVT).

Methods: 

Elderly AIS patients treated with IVT were enrolled in three centers. Unfavorable functional outcome was defined as Modified Rankin Scale score ranging from 3–6. Logistic regression models were used to calculate the odds ratio (OR) and 95% confidence interval (95% CI) for the association between high-sensitivity CTI and 3-month functional outcome. Restricted cubic splines (RCS) were performed to explore the shape of this association. Receiver operating characteristic curve was applied to evaluate the discriminatory capacity of high-sensitivity CTI. Furthermore, subgroup and sensitivity analyses were performed to examine the consistency of the observed association.

Results: 

A total of 708 elderly patients were enrolled, among whom 231 (32.6%) developed unfavorable functional outcome at 3 month follow up. In Model 3, higher continuous high sensitivity CTI levels were independently associated with 3 month unfavorable functional outcome among elderly AIS patients receiving IVT (OR = 1.64; 95% CI, 1.28–2.11). Taking the first quartile of high sensitivity CTI as the reference group, patients in the fourth quartile exhibited the highest risk of unfavorable functional outcome in Model 3 (OR = 2.62, 95% CI, 1.48–4.64). RCS revealed a significant overall association between high sensitivity CTI and unfavorable functional outcome, with no statistically significant nonlinear component (P for overall < 0.001; P for nonlinearity = 0.743). Subgroup and sensitivity analyses demonstrated consistent directions of associations.

Conclusion: 

High-sensitivity CTI was independently associated with functional outcome at 3 months in elderly AIS patients treated with IVT.