Publications by authors named "Connie L Fiems"

3 Publications

  • Page 1 of 1

Reliability of a recumbent stepper submaximal exercise test after traumatic brain injury.

Physiother Theory Pract 2021 Jun 10:1-9. Epub 2021 Jun 10.

University of Indianapolis Krannert School of Physical Therapy, Indianapolis, IN.

: To determine the test-retest reliability of a total body recumbent stepper (TBRS) submaximal exercise test and to examine its relationship with other measures throughout the International Classification of Functioning that are indicative of overall health in individuals with traumatic brain injury (TBI).: Twenty-three ambulatory individuals with severe, chronic (>6 mos) TBI completed a TBRS submaximal exercise test, 6-minute walk test (6MWT), and Mayo Portland Adaptability Inventory (MPAI-4) at initial testing. A repeat TBRS submaximal exercise test was conducted 4-7 days later. Estimated peak oxygen consumption (VO) was calculated from the TBRS submaximal exercise test using the VO prediction equation. Average daily step count was collected by an activity monitor for the 4-7-day period between tests.: Test-retest reliability was good (ICC = 0.79, < .001). The difference between the tests was 0.46 ml・kg・min which was not statistically different. Neither the 6MWT distance nor gait speed are related to the TBRS-estimated peak VO. The MPAI-4 total score and adjustment subscale each had a fair relationship with the TBRS-estimated peak VO ( = -0.41, = .05; s = -0.41, = .05, respectively).: These data suggest that the TBRS submaximal exercise test may be a reliable measure to estimate peak VO in ambulatory adults with chronic severe TBI.
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http://dx.doi.org/10.1080/09593985.2021.1934923DOI Listing
June 2021

Does a Sway-Based Mobile Application Predict Future Falls in People With Parkinson Disease?

Arch Phys Med Rehabil 2020 03 24;101(3):472-478. Epub 2019 Oct 24.

University of Indianapolis College of Health Science, Indianapolis, Indiana, United States.

Objective: To determine whether Sway, a sway-based mobile application, predicts falls and to evaluate its discriminatory sensitivity and specificity relative to other clinical measures in identifying fallers in individuals with Parkinson disease (PD).

Design: Observational cross-sectional study.

Setting: Community.

Participants: A convenience sample of subjects with idiopathic PD in Hoehn and Yahr levels I-III (N=59).

Interventions: Participants completed a balance assessment using Sway, the Movement Disorders Systems-Unified PD Rating Scale motor examination, Mini-BESTest, Activities-specific Balance Confidence (ABC) Scale, and reported 6-month fall history. Participants also reported falls for each of the following 6 months. Binomial logistic regression was used to identify significant predictors of future fall status. Cutoff scores, sensitivity, and specificity were based on receiver operating characteristic plots.

Main Outcome Measures: Sway score.

Results: The most predictive logistic regression model included fall history, ABC Scale, and Sway (P<.001). This model explained 61% (Nagelkerke R) of the variance in fall prediction and correctly classified 85% of fallers. However, only fall history and ABC Scale were statistically significant (P<.02). Participants were 32 times more likely to fall in the future if they fell in the past. The ABC Scale and Mini Balance Evaluation Systems Test (Mini-BESTest) demonstrated greater accuracy than Sway (area under the curve=0.76, 0.72, and 0.65, respectively). Cutoff scores to identify fallers were 85% for the ABC Scale and 21 of 28 for the Mini-BESTest.

Conclusion: Sway did not improve the accuracy of predicting future fallers beyond common clinical measures and fall history.
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http://dx.doi.org/10.1016/j.apmr.2019.09.013DOI Listing
March 2020

Reliability and validity of the Sway Balance mobile application for measurement of postural sway in people with Parkinson disease.

NeuroRehabilitation 2018 ;43(2):147-154

Krannert School of Physical Therapy, University of Indianapolis, Indianapolis, IN, USA.

Background: The emergence of mobile technology allows the examination of balance through direct measures of postural sway in a cost-effective, convenient and portable fashion. However, there is insufficient evidence for use in populations with neurologic conditions.

Objectives: 1) To determine the test-retest reliability of the Sway Balance™ mobile application in measuring postural sway in individuals with Parkinson disease, 2) To examine the concurrent validity of Sway Balance™ with inertial measurement units and 3) To determine if Sway Balance™ scores can predict disease severity.

Methods: Thirty subjects with early stage idiopathic Parkinson disease completed three trials of two Sway Balance™ protocols while postural sway was simultaneously measured by two inertial measurement units and Sway Balance™, then repeated testing one week later.

Results: Sway Balance demonstrated high test-retest reliability for both protocols (ICC = 0.72 and 0.92) and good to excellent inverse correlation with the inertial measurement units across both protocols (ρ= -0.61- -0.92; p < 0.001). Sway Balance™ did not accurately predict disease severity.

Conclusion: Sway Balance™ demonstrates strong test-retest reliability and concurrent validity with measures from inertial measurement units. Questions remain regarding the ability of Sway Balance™ to accurately characterize balance of individuals who demonstrate difficulty maintaining the test condition.
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http://dx.doi.org/10.3233/NRE-182424DOI Listing
November 2018
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