Dataset Information

Elderly fall risk prediction using static posturography.

ABSTRACT: Maintaining and controlling postural balance is important for activities of daily living, with poor postural balance being predictive of future falls. This study investigated eyes open and eyes closed standing posturography with elderly adults to identify differences and determine appropriate outcome measure cut-off scores for prospective faller, single-faller, multi-faller, and non-faller classifications. 100 older adults (75.5 ± 6.7 years) stood quietly with eyes open and then eyes closed while Wii Balance Board data were collected. Range in anterior-posterior (AP) and medial-lateral (ML) center of pressure (CoP) motion; AP and ML CoP root mean square distance from mean (RMS); and AP, ML, and vector sum magnitude (VSM) CoP velocity were calculated. Romberg Quotients (RQ) were calculated for all parameters. Participants reported six-month fall history and six-month post-assessment fall occurrence. Groups were retrospective fallers (24), prospective all fallers (42), prospective fallers (22 single, 6 multiple), and prospective non-fallers (47). Non-faller RQ AP range and RQ AP RMS differed from prospective all fallers, fallers, and single fallers. Non-faller eyes closed AP velocity, eyes closed VSM velocity, RQ AP velocity, and RQ VSM velocity differed from multi-fallers. RQ calculations were particularly relevant for elderly fall risk assessments. Cut-off scores from Clinical Cut-off Score, ROC curves, and discriminant functions were clinically viable for multi-faller classification and provided better accuracy than single-faller classification. RQ AP range with cut-off score 1.64 could be used to screen for older people who may fall once. Prospective multi-faller classification with a discriminant function (-1.481 + 0.146 x Eyes Closed AP Velocity-0.114 x Eyes Closed Vector Sum Magnitude Velocity-2.027 x RQ AP Velocity + 2.877 x RQ Vector Sum Magnitude Velocity) and cut-off score 0.541 achieved an accuracy of 84.9% and is viable as a screening tool for older people at risk of multiple falls.

SUBMITTER: Howcroft J

PROVIDER: S-EPMC5319679 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Elderly fall risk prediction using static posturography.

Howcroft Jennifer J Lemaire Edward D ED Kofman Jonathan J McIlroy William E WE

PloS one 20170221 2

Maintaining and controlling postural balance is important for activities of daily living, with poor postural balance being predictive of future falls. This study investigated eyes open and eyes closed standing posturography with elderly adults to identify differences and determine appropriate outcome measure cut-off scores for prospective faller, single-faller, multi-faller, and non-faller classifications. 100 older adults (75.5 ± 6.7 years) stood quietly with eyes open and then eyes closed whil ...[more]

PMID: 28222191

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Project description:Balance impairment is common in people with multiple sclerosis (PwMS) and frequently impacts quality of life by decreasing mobility and increasing the risk of falling. However, there are only scarce data examining the contribution of specific neurological functional systems on balance measures in MS. Therefore, the primary aim of our study was to examine the differences in posturography parameters and fall incidence according to the pyramidal, cerebellar and sensory systems functional systems in PwMS. The study included 342 PwMS, 211 women and mean disease duration of 8.2 (S.D = 8.3) years. The study sample was divided into six groups according to the pyramidal, cerebellar and sensory functional system scores, derived from the Expanded Disability Status Scale (EDSS) data. Static postural control parameters were obtained from the Zebris FDM-T Treadmill (zebris® Medical GmbH, Germany). Participants were defined as "fallers" and "non-fallers" based on their fall history. Our findings revealed a trend that PwMS affected solely in the pyramidal system, have reduced stability compared to patients with cerebellar and sensory dysfunctions. Moreover, the addition of sensory impairments to pyramidal dysfunction does not exacerbate postural control. The patients in the pure sensory group demonstrated increased stability compared to each of the three combined groups; pyramidal-cerebellar, pyramidal-sensory and pyramidal-cerebellar-sensory groups. As for fall status, the percentage of fallers in the pure pyramidal, cerebellar and sensory groups were 44.3%, 33.3% and 19.5%, respectively. As for the combined functional system groups, the percentage of fallers in the pyramidal-cerebellar, pyramidal-sensory and pyramidal-cerebellar-sensory groups were 59.7%, 40.7% and 65%, respectively. This study confirms that disorders in neurological functional systems generate different effects on postural control and incidence of falls in the MS population. From a clinical standpoint, the present information can benefit all those engaged in physical rehabilitation of PwMS.

Project description:BackgroundFalls in acute care settings threaten patients' safety. Researchers have been developing fall risk prediction models and exploring risk factors to provide evidence-based fall prevention practices; however, such efforts are hindered by insufficient samples, limited covariates, and a lack of standardized methodologies that aid study replication.ObjectiveThe objectives of this study were to (1) convert fall-related electronic health record data into the standardized Observational Medical Outcome Partnership's (OMOP) common data model format and (2) develop models that predict fall risk during 2 time periods.MethodsAs a pilot feasibility test, we converted fall-related electronic health record data (nursing notes, fall risk assessment sheet, patient acuity assessment sheet, and clinical observation sheet) into standardized OMOP common data model format using an extraction, transformation, and load process. We developed fall risk prediction models for 2 time periods (within 7 days of admission and during the entire hospital stay) using 2 algorithms (least absolute shrinkage and selection operator logistic regression and random forest).ResultsIn total, 6277 nursing statements, 747,049,486 clinical observation sheet records, 1,554,775 fall risk scores, and 5,685,011 patient acuity scores were converted into OMOP common data model format. All our models (area under the receiver operating characteristic curve 0.692-0.726) performed better than the Hendrich II Fall Risk Model. Patient acuity score, fall history, age ≥60 years, movement disorder, and central nervous system agents were the most important predictors in the logistic regression models.ConclusionsTo enhance model performance further, we are currently converting all nursing records into the OMOP common data model data format, which will then be included in the models. Thus, in the near future, the performance of fall risk prediction models could be improved through the application of abundant nursing records and external validation.

Dataset Information

Elderly fall risk prediction using static posturography.

Publications

Elderly fall risk prediction using static posturography.

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