Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Thursday, October 29, 2020

Predicting length of stay in patients admitted to stroke rehabilitation with severe and moderate levels of functional impairments

WHAT ABSOLUTE FUCKING STUPIDITY. 

Length of stay NOT recovery results! Will you please talk to survivors sometime soon, they don't care about length of stay, they care about RECOVERY YOU BLITHERING IDIOTS.

Predicting length of stay in patients admitted to stroke rehabilitation with severe and moderate levels of functional impairments

García-Rudolph, Alejandro PhDa,b,c,∗; Cegarra, Blanca MSca,b,c,d; Opisso, Eloy PhDa,b,c; Tormos, Josep María PhDa,b,c; Bernabeu, Montserrat MDa,b,c; Saurí, Joan PhDa,b,c

Editor(s): Khasawneh., Fadi T.

Author Information
doi: 10.1097/MD.0000000000022423

Abstract

Severe stroke patients are known to be associated with larger rehabilitation length of stay (LOS) but other factors besides severity may be contributing. We aim to identify LOS predictors within a population of mostly severe patients and analyze the impact of socioeconomic situation in functionality at admission.

A retrospective observational cohort study was conducted including 172 inpatients admitted to a rehabilitation center between 2007 and 2019. Associations with LOS were examined among 30 potential predictor variables using bivariate correlations. Significantly correlated (P < .002, Bonferroni adjustment) variables were entered into 9 different multiple linear regression models.

No mild participants were included, 63.37% severe and 36.63% moderate. Most significant LOS determinants were: 1) total functional independence measure (FIM) (P < .001) and hemiparesis (P = .0108) (adjusted R2 = 0.24), 2) cognitive FIM (P = .002) and severity (P = .001) (adjusted R2 = 0.22), and 3) home accessibility (P = .043) and hemiparesis (P = 0.032) (adjusted R2 = 0.19).

Known LOS predictors (e.g., depression, ataxia) within the full stroke severities were not found significant in our dataset.

Socioeconomic situation was found moderately correlated with total FIM (r = −0.32, P < .0001).

When stratifying the patients’ socioeconomic situation into mild, important, and severe social risk, their respective median total FIM at admission were 61.5, 50, and 41, with significant differences between the mild and important group (P < .001); also significant differences were found between mild and severe groups (P < .001).

A few of the variables identified in the literature as significant predictors of LOS within the full stroke population were also significant for our dataset (National Institutes of Health Stroke Scale, FIM, home accessibility) explaining less than 25% of the LOS variance. Most of the 30 analyzed known predictors were not significant (e.g., depression, age, recurrent stroke, ataxia, orientation, verbal communication, etc) suggesting that factors outside functional, socioeconomic, medical, and demographics not included in this study (e.g., rehabilitation sessions intensity) have important influences on LOS for severe patients.

Patients at mild social risk obtained significantly higher total FIM at admission than patients at important and severe social risk. The importance of socioeconomic situation has been scarcely studied in the literature in relation to functionality at admission; our results suggest that it requires to be considered.

1 Introduction

Stroke rehabilitation length of stay (LOS) is one of the most relevant quantitative indexes that measure health service utilization within a hospital. LOS is the principal predictive factor of medical expenses among variables that affect the total costs during hospitalization.[1] The ability to accurately predict which stroke patients are likely to require longer inpatient care is desirable for both budgetary planning and healthcare providers’ considerations as well as to manage emotional expectations when communicating with patients and families.[2]

Many factors have been shown to influence subacute rehabilitation LOS, including stroke severity measured with the National institute of Health Stroke Scale (NIHSS),[3] ability to perform activities of daily living,[4] or admission Functional Independence Measure (FIM) score.[5] The presence of ataxia may increase LOS,[6] dysphagia,[7] as well as aphasia,[8] diabetes,[9] obesity,[10] and hypertension.[11] Besides, recurrent stroke patients have been previously reported requiring longer LOS.[12]

Furthermore, there is evidence that motor[13] and cognitive[14] rehabilitation after stroke should be started as early as possible. Nevertheless, time since stroke onset to rehabilitation admission has been scarcely included as covariate in LOS predictive models.

Falls are common post-stroke (12%–47%) and may extend inpatient stroke rehabilitation LOS[15] as well as depression.[16] In terms of social factors, there are conflicting reports about whether living alone predicts LOS, for example, Tan et al (longer LOS),[17] Saxena et al (shorter LOS).[18] Besides, inadequate family support[19] and environmental factors (e.g., home modifications) may delay LOS.[20]

A 2015 Lancet review[21] reports that socioeconomic status (SES) is reflected in short-term and long-term outcomes after stroke. Studies have demonstrated an association between lower SES and having more severe deficits after stroke assessed by NIHSS at admission.[22] To our best knowledge there is a lack of similar studies addressing associations between functional independence, for example, total FIM(T-FIM), motor FIM (M-FIM), and cognitive FIM (C-FIM) at admission and SES.

Although several researchers have previously examined the prediction of LOS within the full spectrum of stroke rehabilitation patients (mild, moderate, and severe), different variables may have different impact in LOS when excluding the population with mild functional impairments. For example, while age has previously been identified as a significant contributor of LOS, this variable may not have the same impact for severe and milder patients as the latter group tends to be younger.[5] To classify stroke severity at admission as mild, moderate, or severe, in this work, we apply the RPG benchmark (Rehabilitation Patient Groups), as in similar previous research.[23]

The objectives of the present study are to analyze the associations between functional independence (T-FIM, M-FIM, and C-FIM) at admission and SES within a population of ischemic and hemorrhagic (moderate-RPG and severe-RPG) stroke patients admitted to an inpatient rehabilitation hospital and predict their LOS from a wide range of potential predictors, including the aforementioned demographics, clinical, and social state-of-the-art variables.

It is hypothesized that M-FIM, C-FIM, and T-FIM at admission will have a stronger association (negative correlation) with SES than NIHSS.

It is also hypothesized that, while some of the same variables that have been identified as significant predictors of LOS within the full stroke population will also emerge for this sample, a different composite of predictors will best account for the variance associated with LOS for patients admitted to stroke rehabilitation with severe and moderate functional impairments.

 

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