Concurrent and predictive validity of the Mini Nutritional Assessment Short‐Form and the Geriatric Nutritional Risk Index in older stroke rehabilitation patients

The solution is AN EXACT DIET PROTOCOL! WHOM EXACTLY IS WORKING ON THAT? 

Or is your hospital so FUCKING INCOMPETENT they have never written up a diet protocol for all these conditions?

For dementia prevention; for cognitive improvement; for cholesterol reduction; for plaque removal; for Parkinsons prevention; for inflammation reduction; etc.

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

Concurrent and predictive validity of the Mini Nutritional Assessment Short‐Form and the Geriatric Nutritional Risk Index in older stroke rehabilitation patients

Title

Concurrent and predictive validity of the Mini Nutritional Assessment Short‐Form and the Geriatric Nutritional Risk Index in older stroke rehabilitation patients

Other Title

• 高齢脳卒中リハビリテーション患者におけるMini Nutritional Assessment Short-FormとGeriatric Nutritional Risk Indexの併存的および予測的妥当性

Author

Nishioka, Shinta

Alias Name

• 西岡, 心大
• ニシオカ, シンタ

Author

Omagari, Katsuhisa

Alias Name

• オオマガリ, カツヒサ
• オオマガリ, カツヒサ

Author

Nishioka, Emi

Alias Name

• ニシオカ, エミ
• ニシオカ, エミ

Author

Mori, Natsumi

Alias Name

• モリ, ナツミ
• モリ, ナツミ

Author

竹谷, 豊

Author

Kayashita, Jun

Alias Name

• カヤシタ, ジュン
• カヤシタ, ジュン

University

徳島大学

Types of degree

博士（栄養学）

Grant ID

甲栄第279号

Degree year

2019-08-21

Description

Background: 

Malnutrition might worsen the clinical outcomes in stroke patients, although few nutritional screening tools have assessed their validity. 

Methods: 

We assessed clinical data of consecutive stroke patients aged ≥65 years in rehabilitation hospital from 2015 to 2017 using the Mini Nutritional Assessment Short-Form (MNA-SF) and the Geriatric Nutritional Risk Index (GNRI) for index testing. The European Society for Parenteral and Enteral Nutrition diagnostic criteria for malnutrition (ESPEN-DCM) was used as a reference standard. The receiver-operating characteristics curve was illustrated by the sensitivity (Se) and specificity (Sp). The Youden index was used to define the cut-off value for malnutrition detection or screening. The Functional Independence Measure (FIM) and discharge destination were compared for verifying predictive validity. 

Results: 

We enrolled 420 patients for the analysis. Of them, 125 patients were included in malnutrition group (mean age: 80 years) and 295 in non-malnutrition group (mean age: 77 years) by the ESPEN-DCM. The area under the curve of the MNA-SF and the GNRI were 0.890 and 0.865, respectively. Se and Sp cut-off values to detect or screen malnutrition were 5 (Se: 0.78; Sp: 0.85) and 7 (Se: 0.96; Sp: 0.57) for the MNA-SF and 92 (Se: 0.74; Sp: 0.84) and 98 (Se: 0.93; Sp: 0.50) for the GNRI, respectively. The GNRI were associated with discharge destination, whereas no correlation was observed between the MNA-SF and outcomes by multivariable analysis. 

Conclusions: 

The MNA-SF and GNRI have fair concurrent validity if appropriate cut-off values were used. The GNRI exhibits good predictive validity in stroke patients.                 

Effects of dynamic body weight support on functional independence measures in acute ischemic stroke: a retrospective cohort study

For me body weight supported treadmill training was worthless. I needed the weight of my body to counteract the spasticity of my legs. And since spasticity never goes away, even now as I'm chronic this would do no good. Overground training is much better in my opinion since it normally gives you perturbations you need to deal with, giving you better balance and preventing falls.

 

Effects of dynamic body weight support on functional independence measures in acute ischemic stroke: a retrospective cohort study

• Justin Huber,
• Nicholas Elwert,
• Elizabeth Salmon Powell,
• Philip M. Westgate,
• Emily Hines &
• Lumy Sawaki 

Journal of NeuroEngineering and Rehabilitation volume 20, Article number: 6 (2023) Cite this article

• 154 Accesses

• 2 Altmetric

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Abstract

Background

Stroke remains a major public health concern in the United States and a leading cause of long-term disability in adults. Dynamic body weight support (DBWS) systems are popular technology available for use in clinical settings such inpatient rehabilitation. However, there remains limited studies in such inpatient settings that compare DBWS to standard of care (SOC) using real world outcome measures. For survivors of acute ischemic stroke, we determine if incorporating a dynamic body weight support (DBWS) system into inpatient therapy offers greater improvement than standard of care (SOC).

Methods

A retrospective chart review included 52 individuals with an acute ischemic stroke admitted to an inpatient rehabilitation facility. Functional Independence Measure (FIM) data, specifically changes in FIM at discharge, served as the primary outcome measure. Patient cohorts received either therapies per SOC or therapies incorporating DBWS. Regardless of cohort group, all patients underwent therapies for 3 h per day for 5 days a week.

Results

For both groups, a statistically and clinically significant increase in total FIM (P < 0.0001) was observed at discharge compared to at admission. Improvements for the DBWS group were significantly greater than the SOC group as evidenced by higher gains in total FIM (p = 0.04) and this corresponded to a medium effect size (Cohen’s d = 0.58). Among FIM subscores, the DBWS group achieved a significant increase in sphincter control while all other subscore changes remained non-significant.

Conclusions

This preliminary evidence supports the benefit of using DBWS during inpatient rehabilitation in individuals who have experienced an acute ischemic stroke. This may be due to the greater intensity and repetitions of tasks allowed by DBWS. These preliminary findings warrant further investigations on the use of DBWS in inpatient settings.

Introduction

Stroke continues to be a major public health concern in the United States and one of the leading causes of long-term disability in adults with approximately 795,000 new cases every year [1]. Unfortunately, as evidenced by ischemic stroke incidence and stroke mortality, the stroke burden is unfortunately increasing in some regions of the country and particularly areas with socioeconomic and healthcare disparities [2, 3]. While significant advancement in recent medical care has increased survival post-stroke, approximately 5 million Americans are still living with residual deficits with an estimated healthcare cost of $46 billion each year. Stroke-related healthcare costs are projected to reach more than $94 billion per year by 2035 in the United States [1]. Therefore, it is of paramount importance to find new ways to improve rehabilitation outcomes and quality of life for people with stroke.

The concept of neuroplasticity plays a crucial role in rehabilitation outcomes [4]. Remarkable neuroplastic changes in corticospinal systems have been demonstrated during and/or after the intense performance of motor activities [5]. Generally speaking, neuroplastic change occurs more readily as activities become more intensive and repetitive with progressive challenges and salience [6]. Such activities have a greater likelihood of leading to lasting change in functional performance if the activities require active participation, problem-solving, and attention to task. It has also been known for a while now that the potential for functional recovery after stroke is greatest during the first 3–6 months following a stroke [7, 8]. Therefore, inpatient rehabilitation occurs during a pivotal time frame from a neuroplasticity perspective.

However, for patients with considerable motor and balance impairments, it is very difficult even in an inpatient setting to implement therapy repetitions with the aforementioned intensity, salience, and progressive challenge [9]. These patients have a justified fear of falling. Moreover, the fall risk is difficult to manage solely with therapy personnel as the current rehabilitation setting in the United States features an already high patient-therapist ratio [10]. Conceivably, the fall risk and the fear of falling are detrimental for neuroplasticity: (a) the attention of the patient and therapist can be more focused on safety measures and distracted from the motor task itself; (b) therapists may select tasks that are safer in lieu of challenging tasks that are more conducive to neuroplastic changes; and (c) repetition goals may be too conservative due to concerns of patient fatigue and the increased fall risk associated with fatigue [11]. These conservative repetition goals in current standards of care are evidenced by a recent study reporting very limited daily step counts for patients undergoing inpatient stroke rehabilitation [12].

Dynamic body weight support (DBWS) systems are a popular set of technologies that facilitate over-ground therapy and are designed to unload body weight more consistently during dynamic conditions such as movement-based therapy (Fig. 1). This consistent unloading is achieved by means of a sensor, an actuator, and an onboard computer controller. The controller is crucial to creating a feedback control loop, which constantly compares measured load versus the desired load and adjusts rope tension accordingly by means of the actuator. The onboard computer controller inherent to these systems allows novel safety features to reduce fall risk—automatic fall detection and an injury prevention mode. In addition, these systems allow real-time feedback for participants owing to the visual displays of real-time sensor data. By facilitating safe therapy and real-time feedback, DBWS has the potential to foster principles of neuroplasticity. That is, participants may better focus their attention and they may be more motivated for therapeutic activities. Our group has reported beneficial effects of DBWS on inpatient discharge outcomes compared to standard of care in patient populations such as traumatic brain injury and spinal cord injuries [13, 14]. However, it is not known if DBWS can also lead to greater functional recovery during inpatient rehabilitation in a population with an acute ischemic stroke, which is the motivation for this study. In the present study, we evaluate whether over-ground gait and balance training incorporating DBWS leads to greater functional recovery after an acute ischemic stroke compared to standard of care (SOC) as assessed by the Functional Independence Measure (FIM).

Fig. 1

Conceptual illustration of a dynamic body weight support system compared to a static body weight support system

Full size image

Predictive ability of hand-grip strength and muscle mass on functional prognosis in stroke rehabilitation patients

 

But you're not predicting recovery, you're predicting failure to recover. SOLVE THE FUCKING 100% RECOVERY PROBLEM. SURVIVORS WANT NOTHING LESS.

Predictive ability of hand-grip strength and muscle mass on functional prognosis in stroke rehabilitation patients

Author links open overlay panelTatsuyaMatsushita

ShintaNishiokaPh.D.AnnaYamanouchiYukaOkazakiKanaOishiRyuseiNakashimaYoshiharuTokunagaM.D., Ph. D.ShinyaOnizukaM.D., Ph. D.

https://doi.org/10.1016/j.nut.2022.111724Get rights and content

Highlights

•

Hand-grip strength independently predicted functional outcomes in stroke patients.

•

Adjusted skeletal muscle mass index did not show the relationship with the outcome.

•

The cutoff value of hand-grip strength for returning home was 15.1 kg for males.

•

For females, 9.5 kg was the cutoff value of hand-grip strength for returning home.

Abstract

Objective

: To investigate the association of muscle strength and adjusted appendicular skeletal muscle mass (ASM) with the Functional Independence Measure (FIM) and the probability of returning home in stroke patients.

Research Methods & Procedure

: A retrospective cohort study was conducted for older stroke patients admitted to convalescent rehabilitation wards between January 2017 and October 2020. Hand-grip strength (HGS) was used to assess muscle strength. ASM was measured by bioelectrical impedance analysis and then divided by height-squared, body weight, body mass index, body fat mass, and body fat percentage to calculate the adjusted ASM. The primary outcome was FIM at discharge and the secondary outcome was the probability of returning home. Multivariate analyses were conducted to adjust confounding effects.

Results

: The data of 699 participants (female, 47%; median age, 79 years) were analyzed. HGS was independently associated with FIM at discharge in males (partial regression coefficient [B] = 0.482; 95% confidence interval [CI] = 0.225–0.740) and females (B = 0.664; 95% CI = 0.263–1.065) and with returning home in males (odds ratio [OR] = 1.070; 95% CI = 1.030–1.100) and females (OR = 1.070 [95% CI = 1.000–1.130). Conversely, none of the adjusted ASM indices were associated with the outcomes. The cutoff value of HGS for returning home was 15.1 kg for males and 9.5 kg for females

Conclusions

: HGS independently predicted FIM at discharge and the probability of returning home(Not good enough! Are you even measuring 100% recovery?  No, then you are OK with failure! Survivors aren't!) in stroke patients. The adjusted ASM methods had less predictive value for functional and discharge outcomes.

 

Predicting FIM gain in stroke patients by adding median FIM gain stratified by FIM score at hospital admission to the explanatory variables in multiple regression analysis—An analysis of the Japan Rehabilitation Database

Stroke survivors don't give a crap about what the predictions are except that they are used to not do aggressive treatments. And I bet the patient and family are not told that the treatments are being reduced.
https://www.jstage.jst.go.jp/article/jjcrs/7/0/7_13/_article

http://doi.org/10.11336/jjcrs.7.13

Original Article

Original Article

Makoto Tokunaga¹⁾, Yoshitaka Mori²⁾, Yoshitaka Ogata²⁾, Yasunori Tanaka²⁾, Kouichi Uchino³⁾, Yuki Maeda³⁾, Machiko Kamiyoshi³⁾

1) Department of Rehabilitation, Kumamoto Kinoh Hospital 2) Department of Physical Therapy, Kumamoto Kinoh Hospital 3) Department of Occupational Therapy, Kumamoto Kinoh Hospital

Released on J-STAGE 20160513  

Keywords: Functional Independence Measure, FIM gain, multiple regression analysis, explanatory variable, stroke

• Full Text PDF [1101K]

• Abstracts
• References(13)
• Supplementary materials(1)

Tokunaga M, Mori Y, Ogata Y, Tanaka Y, Uchino K, Maeda Y, Kamiyoshi M. Predicting FIM gain in stroke patients by adding median FIM gain stratified by FIM score at hospital admission to the explanatory variables in multiple regression analysis —An analysis of the Japan Rehabilitation Database—. Jpn J Compr Rehabil Sci 2016; 7: 13-18.
Objective: To clarify whether the accuracy of predicting motor Functional Independence Measure (FIM) gain in stroke patients can be improved by calculating median values of motor FIM gain (median mFIM gain) stratified by motor FIM score at hospital admission, then inserting these standard gain values in multiple regression analysis.
Methods: The subjects were 2,542 stroke patients registered in the Japan Rehabilitation Database. Motor FIM score at admission was stratified into 39 groups at 2-point intervals and “median mFIM gain” was calculated for each group. With motor FIM gain as the objective variable, multiple regression analysis was performed with and without median mFIM gain in the explanatory variables. Then, correlations were examined between measured values and predicted values of motor FIM gain.
Results: Adding median mFIM gain to the explanatory variables increased the correlation coefficient of measured values and predicted values of motor FIM gain from 0.507 to 0.638.
Conclusion: Adding median mFIM gain to the explanatory variables can improve the accuracy of multiple regression analyses to predict motor FIM gain.

Measure of Functional Independence Dominates Discharge Outcome Prediction After Inpatient Rehabilitation for Stroke

Once again using totally subjective measurements to predict outcomes rather than objective measures like 3d MRI and PET scans showing the dead and damaged areas. What needs to change to convince them to drop the stupid subjective measures and join the scientific world with objective measures? This a a job for that great stroke association if they accept the job.
http://stroke.ahajournals.org/content/early/2015/02/24/STROKEAHA.114.007392.abstract

1. Allen W. Brown, MD,
2. Terry M. Therneau, PhD,
3. Billie A. Schultz, MD,
4. Paulette M. Niewczyk, PhD, MPH and
5. Carl V. Granger, MD

+ Author Affiliations

1. From the Department of Physical Medicine and Rehabilitation (A.W.B., B.A.S.) and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN (T.M.T.); Uniform Data System for Medical Rehabilitation, Buffalo, NY (P.M.N., C.V.G.); Department of Health Care Studies, Daemen College, Amherst, NY (P.M.N.); and the Department of Neurology, University at Buffalo, Buffalo, NY (C.V.G.).

1. Correspondence to Allen W. Brown, MD, Department of Physical Medicine and Rehabilitation, 200 First St SW, Mayo Clinic, Rochester, MN 55905. E-mail brown.allen@mayo.edu

Abstract

Background and Purpose—Identifying clinical data acquired at inpatient rehabilitation admission for stroke that accurately predict key outcomes at discharge could inform the development of customized plans of care(maybe call these stroke protocols?) to achieve favorable outcomes. The purpose of this analysis was to use a large comprehensive national data set to consider a wide range of clinical elements known at admission to identify those that predict key outcomes at rehabilitation discharge.

Methods—Sample data were obtained from the Uniform Data System for Medical Rehabilitation data set with the diagnosis of stroke for the years 2005 through 2007. This data set includes demographic, administrative, and medical variables collected at admission and discharge and uses the FIM (functional independence measure) instrument to assess functional independence. Primary outcomes of interest were functional independence measure gain, length of stay, and discharge to home.

Results—The sample included 148 367 people (75% white; mean age, 70.6±13.1 years; 97% with ischemic stroke) admitted to inpatient rehabilitation a mean of 8.2±12 days after symptom onset. The total functional independence measure score, the functional independence measure motor subscore, and the case-mix group were equally the strongest predictors for any of the primary outcomes. The most clinically relevant 3-variable model used the functional independence measure motor subscore, age, and walking distance at admission (r²=0.107). No important additional effect for any other variable was detected when added to this model.

Conclusions—This analysis shows that a measure of functional independence in motor performance and age at rehabilitation hospital admission for stroke are predominant predictors of outcome at discharge in a uniquely large US national data set.