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.

Wednesday, March 16, 2022

Optimizing falls risk prediction for inpatient stroke rehabilitation: A secondary data analysis

Instead of predicting falls why not do something useful and come up with EXACT FALL PREVENTION PROTOCOLS?

Optimizing falls risk prediction for inpatient stroke rehabilitation: A secondary data analysis

, MSc, PT, , MSc, PT, , MSc, PT, , MSc, PT, , MSc, PT, , MScCH, PT, show all
Received 31 May 2021, Accepted 26 Jan 2022, Published online: 09 Mar 2022
 

Background

Identifying individuals at risk for falls during inpatient stroke rehabilitation can ensure timely implementation of falls prevention strategies to minimize the negative personal and health system consequences of falls.

Objectives

To compare sociodemographic and clinical characteristics of fallers and non-fallers; and evaluate the ability of the Berg Balance Scale (BBS) and Morse Falls Scale (MFS) to predict falls in an inpatient stroke rehabilitation setting.

Methods

A longitudinal study involving a secondary analysis of health record data from 818 patients with stroke admitted to an urban, rehabilitation hospital was conducted. A fall was defined as having ≥1 fall during the hospital stay. Cut-points on the BBS and MFS, alone and in combination, that optimized sensitivity and specificity for predicting falls, were identified.

Results

Low admission BBS score and admission to a low-intensity rehabilitation program were associated with falling (p < .05). Optimal cut-points were 29 for the BBS (sensitivity: 82.4%; specificity: 57.4%) and 30 for the MFS (sensitivity: 73.2%; specificity: 31.4%) when used alone. Cut-points of 45 (BBS) and 30 (MFS) in combination optimized sensitivity (74.1%) and specificity (42.7%).

Conclusions

A BBS cut-point of 29 alone appears superior to using the MFS alone or combined with the BBS to predict falls.

 

No comments:

Post a Comment