Prehospital screening of acute stroke with the National Institutes of Health Stroke Scale (ParaNASPP): a stepped-wedge, cluster-randomised controlled trial

Why aren't you testing these much earlier ideas out? Incompetently don't know about them?  Your NIHSS has no objectivity.

Hats off to Helmet of Hope - stroke diagnosis in 30 seconds; February 2017 

New Device Quickly Assesses Brain Bleeding in Head Injuries - 5-10 minutes April 2017

Prehospital screening of acute stroke with the National Institutes of Health Stroke Scale (ParaNASPP): a stepped-wedge, cluster-randomised controlled trial

• Mona Guterud, MSc *
• Helge Fagerheim Bugge, MD *
• Prof Jo R⊘islien, PhD
• Prof Jo Kramer-Johansen, PhD
• Prof Mathias Toft, PhD
• Hege Ihle-Hansen, PhD
• et al.
• Show all authors
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Published:September, 2023DOI:https://doi.org/10.1016/S1474-4422(23)00237-5

Summary

Background

Timely treatment of acute stroke depends on early identification and triage. Improved methods for recognition of stroke in the prehospital setting are needed. We aimed to assess whether use of the National Institutes of Health Stroke Scale (NIHSS) by paramedics in the ambulance could improve communication with the hospital, augment triage, and enhance diagnostic accuracy of acute stroke.

Methods

The Paramedic Norwegian Acute Stroke Prehospital Project (ParaNASPP) was a stepped-wedge, single-blind, cluster-randomised controlled trial. Patients with suspected acute stroke, who were evaluated by paramedics from five ambulance stations in Oslo, Norway, were eligible for inclusion. The five ambulance stations (defined as clusters) all initially managed patients according to a standard stroke protocol (control group), with randomised sequential crossover of each station to the intervention group. The intervention consisted of supervised training on NIHSS scoring, a mobile application to aid scoring, and standardised communication with stroke physicians. Random allocation was done via a simple lottery draw by administrators at Oslo University Hospital, who were independent of the research team. Allocation concealment was not possible due to the nature of the intervention. The primary outcome was the positive predictive value (PPV) for prehospital identification of patients with a final discharge diagnosis of acute stroke, analysed by intention to treat. Prespecified secondary safety outcomes were median prehospital on-scene time and median door-to-needle time. This trial is registered with ClinicalTrials.gov, NCT04137874, and is completed.

Findings

Between June 3, 2019, and July 1, 2021, 935 patients were evaluated by paramedics for suspected acute stroke. 134 patients met exclusion criteria or did not consent to participate. The primary analysis included 447 patients in the intervention group and 354 in the control group. There was no difference in PPV for prehospital identification of patients with a final discharge diagnosis of acute stroke between the intervention group (48·1%, 95% CI 43·4–52·8) and control group (45·8%, 40·5–51·1), with an estimated percentage points difference between groups of 2·3 (95% CI –4·6 to 9·3; p=0·51). Median prehospital on-scene time increased by 5 min in the intervention group (29 min [IQR 23–36] vs 24 min [19–31]; p<0·0001), whereas median door-to-needle time was similar between groups (26 min [21–36] vs 27 min [20–36]; p=0·90). No prehospital deaths were reported in either group.

Interpretation

The intervention did not improve diagnostic accuracy in patients with suspected stroke. A general increase in prehospital time during the pandemic and the identification of smaller strokes that require more deliberation are possible explanations for the increased on-scene time. The ParaNASPP model is to be implemented in Norway from 2023, and will provide real-life data for further research.

Funding

Norwegian Air Ambulance Foundation and Oslo University Hospital.

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Happiness

 Well I'm happy. I'm retired and divorced.

Tried to read 'Neurodharma; New Science, Ancient Wisdom, and Seven Practices of the Highest Happiness'. But it was tough going and never figured out what the seven practices were until I read a review.

The subtitle of the book indicates there are seven practices of highest happiness. They are:

• Steadying the mind

• Warming the heart

• Resting in fullness

• Being wholeness

• Receiving nowness

• Opening into allness

• Finding timelessness 

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I preferred the book;

'8 mindful steps to Happiness: Walking the Buddha's Path' there is this point. 'Desire causes suffering'; page 52.

You'll have to figure out the conundrum yourself. Desiring happiness causes suffering.

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I haven't finished reading the book: 'The Practical Neuroscience of Buddha's Brain; Happiness, love & wisdom'. So no clue if this is going to help. 

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 And the reason I am so happy is this:

I don't know where my resiliency came from, stroke at 50, fired at 55, divorced at 57.

 I still walk funny and the left arm and hand are useless and I see nothing out there that is going to get those recovered because no one in the world is working on CURING SPASTICITY, not the useless manage spasticity.  

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Yet I'm the happiest I've ever been. 

Mine is here:

Why my stroke was the best thing to ever happen to me

 

Then there is this:

Happiness: A Novel Outcome Measure in Stroke?

Going to Bhutan in August for two weeks with Road Scholar. They measure Gross National Happiness.

The Birthplace Of 'Gross National Happiness' Is Growing A Bit Cynical

I'll do Norway next year to climb to the top of Preikestolen

Distance: 7.6 km (4.7 miles)
Elevation Gain: 350 meters (1150 feet)
Difficulty: Moderate
Length of Time: 4 to 5 hours

Does implementation of a standardized pathway of stroke care affect functional outcome after stroke?

Well it is incredibly obvious that stroke survivors don't need 'care'; they need 100% recovery protocols! GET THERE! Solve the correct problem; 100% recovery protocols, 'care' is useless.

Does implementation of a standardized pathway of stroke care affect functional outcome after stroke?

Elin Bergh https://orcid.org/0000-0001-6947-9011 Elin.Josefina.Bergh@ahus.no, Torunn Askim, […], Ole Morten Rønning https://orcid.org/0000-0001-5080-5788, Jurate Saltyte Benth, Hild Fjærtoft, and Bente Thommessen https://orcid.org/0000-0002-8665-1108, +3 -3View all authors and affiliations

Express Articles

https://doi.org/10.1177/17474930221126592

Abstract

Background: 

 

A stroke care pathway (SCP) was introduced in Norway in 2018. The goal of the pathway was to avoid delay in treatment and diagnostics of acute stroke and to secure treatment according to national guidelines. In this study, we aimed to evaluate how the implementation of the SCP affects outcome after stroke.

Methods:  

 

We performed a register-based study using data from the Norwegian Stroke Register that covers 87% of acute stroke patients in Norway.

Patients included one year before and one year after the introduction of the care pathway were compared (2017 versus 2019). Change in functional outcome, the proportion of independent patients 90 days post-stroke, discharge destination, proportions admitted to stroke units and 90 days mortality were compared. Functional outcome was measured using modified Rankin Scale (mRS) and functional independence was defined as mRS 0-2.

Results: 

 

In total 11 009 patients with 90 days follow-up data were analysed. Comparing the cohorts from 2017 and 2019 there was no change in demographics or stroke characteristics. No statistically significant differences in mRS, admission to thrombolysis time or 90 days mortality were found. However, the proportion of patients discharged directly home and treated in a stroke unit increased from 2017 to 2019.

Conclusion: 

 

The implementation of a standardized pathway of stroke care in Norway, did not lead to improvement in functional outcome or a reduction in 90 days mortality. However, the proportion of patients discharged directly home increased, and more patients were treated in stroke units in 2019 compared to 2017.

Does implementation of a standardized pathway of stroke care affect functional outcome after stroke?

The whole problem here is they are trying to standardize 'care', NOT recovery protocols.  They don't have a fucking clue on how to solve stroke.

Does implementation of a standardized pathway of stroke care affect functional outcome after stroke?

Elin Bergh https://orcid.org/0000-0001-6947-9011 Elin.Josefina.Bergh@ahus.no, Torunn Askim, […], Ole Morten Rønning https://orcid.org/0000-0001-5080-5788, Jurate Saltyte Benth, Hild Fjærtoft, and Bente Thommessen https://orcid.org/0000-0002-8665-1108, +3 -3View all authors and affiliations

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https://doi.org/10.1177/17474930221126592

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Abstract

Background: 

A stroke care pathway (SCP) was introduced in Norway in 2018. The goal of the pathway was to avoid delay in treatment and diagnostics of acute stroke and to secure treatment according to national guidelines. In this study, we aimed to evaluate how the implementation of the SCP affects outcome after stroke.

Methods: 

We performed a register-based study using data from the Norwegian Stroke Register that covers 87% of acute stroke patients in Norway.

Patients included one year before and one year after the introduction of the care pathway were compared (2017 versus 2019). Change in functional outcome, the proportion of independent patients 90 days post-stroke, discharge destination, proportions admitted to stroke units and 90 days mortality were compared. Functional outcome was measured using modified Rankin Scale (mRS) and functional independence was defined as mRS 0-2.

Results: 

In total 11 009 patients with 90 days follow-up data were analysed. Comparing the cohorts from 2017 and 2019 there was no change in demographics or stroke characteristics. No statistically significant differences in mRS, admission to thrombolysis time or 90 days mortality were found. However, the proportion of patients discharged directly home and treated in a stroke unit increased from 2017 to 2019.

Conclusion: 

The implementation of a standardized pathway of stroke care in Norway, did not lead to improvement in functional outcome or a reduction in 90 days mortality. However, the proportion of patients discharged directly home increased, and more patients were treated in stroke units in 2019 compared to 2017.

Coassessment framework to identify person-centred unmet needs in stroke rehabilitation: a case report in Norway

One question assessment is all you need. Did you get 100% recovered? Yes/No? Based on that you provide EXACT STROKE PROTOCOLS to get 100% recovered.

Coassessment framework to identify person-centred unmet needs in stroke rehabilitation: a case report in Norway

1. http://orcid.org/0000-0003-2268-3191Kari Jorunn Kværner1,2,
2. Linn Nathalie Støme1,
3. Jonathan Romm3,
4. Karianne Rygh3,
5. Frida Almquist3,
6. Sveinung Tornaas4,
7. Marianne Storen Berg3
   

Abstract

Objective To describe unmet needs and values in stroke rehabilitation using the Health Value Framework and the associated coassessment tool Health Value Spider, a framework designed to identify and prioritise unmet needs based on health technology assessment (HTA).

Setting The study took place at Oslo University Hospital, Norway, from February to April 2019. Participants in three consecutive workshops were recruited from Sunnaas Rehabilitation Hospital, Oslo Municipality, Hospital Procurement Trust and Oslo University Hospital. Twenty-four hospital workers (medical and allied health staff and administrative staff) participated in workshop 1 and 29 patients, user representatives and hospital workers in workshop 2. Twenty-one patients and hospital workers participated in workshop 3.

Interventions Stakeholder analysis and scenario building was performed in a coassessment setting where unmet needs were identified applying the Health Value Framework. Two of the authors are also the developers of the Health Value Framework (KJK and LNS).

Results In the two first workshops where health workers, patients and next of kin perspectives were elicited, three needs were identified: patient insecurity in patient journey transitions, lack of stroke rehabilitation expertise in primary care and invisible patient problems, such as fatigue and cognitive impairment. In workshop 3, 12 opportunity areas were identified. Four opportunity areas were selected by the stakeholders based on a prioritisation process: early discovery of cognitive impairment, rehabilitation continuity, empowered patients and next of kin and remote monitoring and digital touchpoints.

Conclusion Health Value Spider successfully identified and prioritised unmet needs and described associated values.

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http://dx.doi.org/10.1136/bmjinnov-2020-000432

 

Leisure-Time Physical Activity Is Associated With Reduced Risk of Dementia-Related Mortality in Adults With and Without Psychological Distress: The Cohort of Norway

My main leisure time activity was whitewater canoeing. My doctors did nothing to get me back to that activity so I was under lots of psychological distress. Your doctors are supposed to do no harm, mine left me with continuing disability and a higher risk for dementia.

Original Research ARTICLE

Front. Aging Neurosci., 25 May 2018 | https://doi.org/10.3389/fnagi.2018.00151

 

Ekaterina Zotcheva^1*, Geir Selbæk^2,3,4, Espen Bjertness⁴, Linda Ernstsen¹ and Bjørn H. Strand^2,4,5

• ¹Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
• ²Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
• ³Center for Old Age Psychiatric Research, Innlandet Hospital Trust, Ottestad, Norway
• ⁴Faculty of Medicine, University of Oslo, Oslo, Norway
• ⁵Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway

Background: Leisure-time physical activity (PA) has been proposed as a protective factor against dementia, whereas psychological distress is associated with an increased risk of dementia. We investigated the associations of leisure-time PA and psychological distress with dementia-related mortality, and whether the association between leisure-time PA and dementia-related mortality differs according to level of psychological distress.

Methods: 36,945 individuals from the Cohort of Norway aged 50-74 years at baseline (1994–2002) were included and followed up until January 1st 2015. Leisure-time PA and psychological distress were assessed through questionnaires, whereas dementia-related mortality was obtained through the Norwegian Cause of Death Registry. Adjusted Cox regression analyses were used to estimate hazard ratios (HR) and 95% confidence intervals (95%CI).

Results: Compared to inactivity, leisure-time PA was associated with a decreased risk of dementia-related mortality; low intensity leisure-time PA (HR = 0.73, 95% CI 0.59–0.89); high intensity leisure-time PA (HR = 0.61, 95%CI 0.49-0.77). A statistically significant difference in dementia-related mortality risk was observed between low and high intensity leisure-time PA (p < 0.05). Psychological distress was associated with an increased risk of dementia-related mortality (HR = 1.45, 95% CI 1.16–1.81). Among non-distressed, leisure-time PA was associated with a decreased dementia-related mortality risk; low intensity leisure-time PA (HR = 0.77, 95% CI 0.61–0.97); high intensity leisure-time PA (HR = 0.65, 95% CI 0.51–0.84). The same applied for those with psychological distress; low intensity leisure-time PA (HR = 0.57, 95% CI 0.35–0.94); high intensity leisure-time PA (HR = 0.42, 95% CI 0.22–0.82). The interaction between leisure-time PA and psychological distress on dementia-related mortality was not statistically significant (p = 0.38).

Conclusions: Participating in leisure-time PA was associated with a reduced risk of dementia-related mortality, whereas psychological distress was associated with an increased risk of dementia-related mortality. Leisure-time PA appears to be equally strongly related with dementia-related mortality among those with and without psychological distress, underlining the importance of leisure-time PA for various groups of middle-aged and older adults.

Introduction

Physical activity (PA) is widely considered one of the key lifestyle factors associated with reduced risk of mortality (Arem et al., 2015) and a number of non-communicable diseases (Reiner et al., 2013). Furthermore, a large body of research indicates that participating in regular PA may reduce the risk of cognitive decline (Blondell et al., 2014) and dementia (Rosness et al., 2014; Guure et al., 2017). A recently published meta-analysis of prospective studies demonstrated a dose-response relationship between volume and intensity of PA and risk of dementia (Xu et al., 2017). For every 10 metabolic equivalent of task hours (MET-h) increase per week, there was a 10% decrease in the risk of all-cause dementia (Xu et al., 2017). As populations across the globe age, the prevalence of dementia is predicted to increase substantially, from approximately 47 million in 2015, to 132 million by 2050 (Prince et al., 2015). Hence, measures to prevent or delay new cases of dementia are required, and research on protective and risk factors for dementia has intensified during the last decade (Livingston et al., 2017).

Both early- and late-life depression has been linked to an increased risk of dementia (Byers and Yaffe, 2011). Likewise, psychological distress, characterized by general symptoms of anxiety and depression, has been associated with a higher risk of dementia (Skogen et al., 2015) and dementia-related mortality (Rosness et al., 2016). However, PA has repeatedly been associated with reduced symptoms of depression and anxiety in non-clinical populations (Rebar et al., 2015). A recent randomized exercise trial revealed that increases in moderate-to-vigorous PA predicted reductions in psychological distress in older adults (Awick et al., 2017), and a meta-analysis of randomized controlled studies showed that exercise has a significant antidepressant effect among individuals with depression (Schuch et al., 2016). Thus, existing research indicates that PA is beneficial for both mental and cognitive health.

Despite the aforementioned associations between PA, psychological distress, and dementia, little is known on how PA is associated with dementia risk among individuals with psychological distress. Khatri et al. (2001) randomized clinically depressed older adults to either an anti-depressive medication group, an aerobic exercise group, or a combined exercise and medication group. After 4 months, the researchers found that aerobic exercise improved cognitive function among depressed older adults, and that these improvements corresponded to decreases in depressive symptoms (Khatri et al., 2001). However, the latter study did not investigate risk of incident dementia. The aim of the present study was to investigate the associations of leisure-time PA and psychological distress with dementia-related mortality in middle-aged and older adults, and to examine whether the association between leisure-time PA and dementia-related mortality differs according to level of psychological distress.

Methods

Study Population

The present study is part of the Gene-Environment Interaction in Dementia (GENIDEM) project, which aims to investigate environmental and genetic factors for dementia. The study population comprised 36,945 individuals free from symptoms or diagnosis of heart disease from the Cohort of Norway (CONOR) aged 50–74 years at baseline (1994–2002) linked with the Norwegian Cause of Death Registry and the National Education Database by means of a unique personal identification number. CONOR is a multipurpose study set up to study aetiological factors for a large variety of diseases, and includes 10 epidemiological cohorts from different geographical areas in Norway (Naess et al., 2008). In the present study, three epidemiological cohorts were excluded, as they did not include the CONOR Mental Health Index (CONOR-MHI) scale used to assess psychological distress.

Baseline data collection in CONOR was carried out from 1994 to 2002, following a standardized procedure, where participants received a letter of invitation containing an information brochure by mail 2 weeks prior to a health examination. The health examination included a physical checkup including measurements of participants' height, weight, and blood pressure, as well as drawing blood samples. After completing the examination, the participants returned a self-report questionnaire assessing health- and lifestyle-related variables by mail (Naess et al., 2008). Study participants were followed from baseline until death, emigration, or January 1st 2015, whichever occurred first, with a maximum follow-up time of 20.4 years (mean 15.3). Mean age at follow-up was 76.5 years (max 94.1 years).

All participants included in CONOR gave their written informed consent. The participants' names and personal ID numbers were omitted before data were made available for research purposes. The study was approved by the Norwegian Data Inspectorate and the Regional Committees for Medical Research Ethics, and was conducted in accordance with the Declaration of Helsinki.

Physical Activity

Participants were asked to define the intensity and duration of their leisure-time PA in an average week during the past year. The leisure-time PA question was divided into intensity categories of “low intensity” (not causing perspiration or panting) and “high intensity” (causing perspiration and/or panting) leisure-time PA, each with four alternatives related to average hours per week: “none,” “ <1 h,” “1–2 h,” and “≥3 h.” To ensure sufficient statistical power, all individuals participating in any low intensity leisure-time PA were placed in one group and all individuals participating in any high intensity leisure-time PA were placed in one group, irrespective of hours of weekly leisure-time PA. Participants who replied “none” to both categories of leisure-time PA were considered inactive. Participants who replied “none” on one category of but did not provide an answer to the other category of leisure-time PA, or who had missing answers on both categories were excluded. In the present study, participants were categorized into the following three categories of leisure-time PA based on intensity: “inactive,” “low intensity leisure-time PA,” and “high intensity leisure-time PA.”

Psychological Distress

Psychological distress was assessed with the CONOR Mental Health Index (CONOR-MHI). CONOR-MHI consists of seven items assessing general symptoms of depression and anxiety, and is based on a modification of the General Health Questionnaire (GHQ) and the Hopkins Symptom Check List (HSCL-10) (Søgaard et al., 2003). The items on the CONOR-MHI are shown below. Each item has four answer categories: “no,” “a little,” “a good amount,” and “very much,” and are given values 1–4. The CONOR-MHI score is calculated by dividing the total score (range 7–28) on all seven items by seven, resulting in a range of 1–4, where 1 represents low level of psychological distress, and 4 represents high level of psychological distress. In records containing one missing value, the value was replaced with the sample mean value for each item, whereas records with two or more missing items were excluded.

CONOR Mental Health Index

Have you, in the course of the last two weeks, felt:

Nervous and unsettled?

Troubled by anxiety?

Secure and calm (inverse score)?

Irritable?

Happy and optimistic (inverse score)?

Sad/depressed?

Lonely?

A study comparing the CONOR-MHI to the HSCL-10 and the Hospital Anxiety and Depression Scale (HADS) showed a strong correlation with both scales, r = 0.70 and r = 0.76, respectively (Søgaard et al., 2003). The same study showed that a cut-off at ≥2.15 on the CONOR-MHI has a sensitivity and specificity of, respectively, 41 and 98% for caseness of HADS-anxiety, 38 and 96% for HADS-depression, and 66 and 95% for HSCL-10 (Søgaard et al., 2003). Based on the cut-off of ≥2.15 on the CONOR-MHI, participants in the present study were categorized into two groups: “no psychological distress” or “psychological distress.”

Dementia-Related Mortality

Dementia-related mortality was used as a proxy for dementia illness, and was obtained from death certificates from the Norwegian Cause of Death Registry (Rosness et al., 2014). Dementia was identified when it served either as the underlying, immediate, or accompanying cause of death, according to the International Statistics Classification of Diseases and Related Health Problems, 10th revision, codes F00-F03 and G30.0-G30.9. In the present study population, a total of 919 dementia-related deaths were registered during the follow-up period. For validity purposes, we re-ran analyses with cases restricted to those with dementia as underlying cause.

Covariates

The following variables that could possibly affect the association between leisure-time PA, psychological distress, and dementia-related mortality were identified based on prior studies: sex, education, diabetes, smoking, body mass index (BMI; weight in kilograms divided by height in meters squared), and hypertension. Demographic and health-related covariates were obtained from the results of the physical checkup and the self-report questionnaire at baseline. Attained educational level was obtained by coupling the participants' unique identification number to the National Education Database. The education variable was then divided into three groups: “high” (university degree/college, corresponding to 13 or more years of schooling), “medium” (secondary qualifications, corresponding to 10 years of schooling), and “low” (elementary school, corresponding to 7 years of schooling) (Strand et al., 2014). Participants who reported currently or previously suffering from diabetes were categorized as diabetic. Smoking habits were dichotomized into daily or non-daily smoker. BMI was divided into four categories: underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), and obesity (BMI ≥30). Participants were categorized as hypertensive at a systolic pressure of ≥160 mm Hg and/or a diastolic pressure of ≥100 mm Hg, according to the National Institutes of Health guidelines (National Institutes of Health, 2015).

Statistical Analyses

Adjusted Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) for the associations of leisure-time PA and psychological distress with dementia-related mortality. Attained age was used as the time variable in the regression models, and thereby all the models were finely adjusted by age. Emigration or non-dementia-related mortality were censored. For leisure-time PA, the “inactive” group served as the reference group, whereas for psychological distress, “no psychological distress” served as the reference group. Leisure-time PA served as the main exposure in the regression models. In the first regression model (model 1), the analyses were adjusted for sex. Next, education, smoking, and psychological distress were added to the model (model 2). The final model (model 3) included the covariates from model 1 and 2, in addition to diabetes, BMI, and hypertension.

To investigate whether psychological distress modified the association between leisure-time PA and dementia-related mortality, an interaction term between leisure-time PA and psychological distress was added to the regression models. In addition, relative excess risk due to interaction (RERI) estimates were calculated to investigate possible additive interaction between leisure-time PA and psychological distress. To obtain psychological distress-specific associations between leisure-time PA and dementia-related mortality, the regression models 1, 2, and 3 were stratified by psychological distress. In these analyses, psychological distress was removed as a covariate from the regression models. Stata version 14 was used for all statistical analyses.

Results

Baseline characteristics of the study sample by leisure-time PA group are presented in Table 1. Participants in the leisure-time PA groups had higher education, less psychological distress, hypertension, and diabetes, and were less likely to smoke compared to inactive participants. The high intensity leisure-time PA group consisted of less women than the low intensity leisure-time PA group and the inactive group.

Leisure-time PA was associated with a decreased risk of dementia-related mortality when compared to inactivity; low intensity leisure-time PA (HR = 0.68, 95% CI 0.56–0.84); high intensity leisure-time PA (HR = 0.54, 95% CI 0.43–0.68) in a model adjusted by sex (Table 2, Model 1). The results were slightly attenuated, but remained statistically significant after additional adjustment for education, smoking and psychological distress; low intensity leisure-time PA (HR = 0.76, 95% CI 0.62–0.93); high intensity leisure-time PA (HR = 0.63, 95% CI 0.50–0.80) (Model 2). Additional adjustment for diabetes, hypertension and BMI did not attenuate the results noteworthy; low intensity leisure-time PA (HR = 0.73, 95% CI 0.59–0.89); high intensity leisure-time PA (HR = 0.61, 95% CI 0.49–0.77) (Model 3). A statistically significant difference in dementia-related mortality hazard ratios was observed between low and high intensity leisure-time PA (P < 0.05). Psychological distress was associated with an increased risk of dementia-related mortality (HR = 1.45, 95% CI 1.16–1.81) in the fully adjusted model 3.

Upright activity within the first week after stroke is associated with better functional outcome and health-related quality of life: A Norwegian multi-site study

Impossible to tell if this is a valid conclusion at all. Nothing mentioned about what the objective damage diagnosis was - location and size.  If you can get patients out of bed early then they probably had a less damaging stroke. Damn these people don't understand cause and effect at all. 

Upright activity within the first week after stroke is associated with better functional outcome and health-related quality of life: A Norwegian multi-site study

Hokstad A¹, Indredavik B, Bernhardt J, Langhammer B, Gunnes M, Lundemo C, Bovim MR, Askim T.

Author information

Abstract

OBJECTIVE:

To assess the amount of early upright activity of patients managed in Norwegian stroke units and its association with functional outcome and health-related quality of life 3 months later.

DESIGN:

A prospective observational multi-centre study.

SUBJECTS:

A total of 390 acute stroke patients, mean age 76.8 years, 48.1% men, less than14 days post-stroke, recruited from 11 Norwegian stroke units.

METHODS:

Time spent in different activity categories (in bed, sitting out of bed, upright) was observed with a standard method. Outcome was assessed by modified Rankin Scale (mRS), and health-related quality of life by EuroQol-5 Dimension 5 level (EQ-5D-5L) 3 months later. Ordinal logistic and linear regression analyses were used to examine the association between activity categories and mRS and EQ-5D-5L, respectively. Age, National Institute of Health Stroke Scale (NIHSS) score, premorbid mRS, sex, and hospital-site were added as covariates.

RESULTS:

The odds ratio (OR) (95% confidence interval (CI)) for poorer functional outcome (higher mRS) decreased as time spent in upright activities increased (OR 0.97 (95% CI 0.94-1.00)). There was also a significant positive association between time in upright activity and higher EQ-5D-5L, Beta 0.184 (95% CI 0.001- 0.008) 3 months later.

CONCLUSION:

This study confirms the beneficial effect of upright activity applied during hospital stay in Norwegian stroke units.