scholarly journals Clinical Measurement of Sit-to-Stand Performance in People With Balance Disorders: Validity of Data for the Five-Times-Sit-to-Stand Test

2005 ◽  
Vol 85 (10) ◽  
pp. 1034-1045 ◽  
Author(s):  
Susan L Whitney ◽  
Diane M Wrisley ◽  
Gregory F Marchetti ◽  
Michael A Gee ◽  
Mark S Redfern ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Balance Disorders ◽  
Stand Test ◽  
Balance Confidence ◽  
Sit To Stand ◽  
Dynamic Gait Index ◽  
Dynamic Gait ◽  
Confidence Scale ◽  
Better Than

Abstract Background and Purpose. People with balance disorders are characterized as having difficulty with transitional movements, such as the sit-to-stand movement. A valid and feasible tool is needed to help clinicians quantify the ability of people with balance disorders to perform transitional movements. The purpose of this study was to describe the concurrent and discriminative validity of data obtained with the Five-Times-Sit-to-Stand Test (FTSST). The FTSST was compared with the Activities-specific Balance Confidence Scale (ABC) and the Dynamic Gait Index (DGI). Subjects and Methods. Eighty-one subjects without balance disorders and 93 subjects with balance disorders were recruited for the study. Each subject was asked to stand from a 43-cm-high chair 5 times as quickly as possible. The ABC and DGI scores were recorded. Results. Subjects with balance disorders performed the FTSST more slowly than subjects without balance disorders. Discriminant analysis demonstrated that the FTSST correctly identified 65% of subjects with balance dysfunction, the ABC identified 80%, and the DGI identified 78%. The ability of the FTSST to identify subjects with balance dysfunction was better for subjects younger than 60 years of age (81%). Discussion and Conclusion. The FTSST displays discriminative and concurrent validity properties that make this test potentially useful in clinical decision making, although overall the ABC and the DGI are better than the FTSST at discriminating between subjects with and subjects without balance disorders.

scholarly journals [ID 38878] AVALIAÇÃO DO MEDO DE QUEDA, CONFIANÇA NO EQUILÍBRIO, MARCHA E EQUILÍBRIO CORPORAL DE IDOSAS PRATICANTES REGULARES DO MÉTODO PILATES

2020 ◽  
Vol 24 (Supl.2) ◽  
Author(s):  
Marcelo De maio Nascimento ◽  
Cássia Poliana Príncipe Nunes ◽  
Eddie Nara Dantas Passos Rosa ◽  
Deborah Silva de Menezes ◽  
Ana Carolina Pereira Eugênio ◽  
...  
Keyword(s):  
Balance Confidence ◽  
Dynamic Gait Index ◽  
Dynamic Gait ◽  
Confidence Scale ◽  
Gait Index

Objetivo: Avaliar o desempenho de mulheres idosas praticantes regulares do método Pilates em testes de marcha e equilíbrio corporal, assim como, a percepção do medo de queda e da confiança no equilíbrio, além de estimar o risco de queda da população avaliada. Metodologia: Trata-se de um estudo do tipo transversal observacional descritivo, desenvolvido com 254 mulheres (67,35±5,20 anos), praticantes regulares do método Pilates, com e sem histórico de quedas. Foram utilizados os seguintes instrumentos: Questionário (sociodemográfico, comorbidades, medicamentos e histórico de quedas), Mini-exame do estado mental de saúde (MEEM), Falls efficacy scale (FES), Balance confidence scale (ABC), Teste de equilíbrio corporal (TEC), Dynamic gait index (DGI), Time up and go (TUG), incluindo sua versão motora (TUGm) e cognitiva (TUGc). Resultados: Sexagenárias e septuagenárias mostraram desempenho satisfatório na avaliação da marcha na condição simples TUG (p

Abstract 1882: Use of Speckle Tracking to Quantify Global LV Function: A Comparison with 2D and 3D Echo and Magnetic Resonance Imaging

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Joseph K Brown ◽  
Thomas H Marwick
Keyword(s):  
Ejection Fraction ◽  
Speckle Tracking ◽  
Clinical Decision Making ◽  
Global Longitudinal Strain ◽  
Clinical Decision ◽  
Lv Function ◽  
Endocardial Border ◽  
3D Echo ◽  
2D And 3D ◽  
Better Than

Background: Ejection fraction (EF) plays a prominent role in clinical decision making but this calculation is time-consuming and dependent on load and geometry. A simple and quick technique for assessing global LV function would be useful. We sought to evaluate the robustness of global longitudinal strain (GLS) for assessment of LV function in comparison to Simpsons biplane ejection-fraction (2D-EF), 3D ejection fraction (3D-EF) and MRI ejection fraction (MRI-EF). We further investigated the automated measures of EF (auto-EF) from wall tracking. Methods: 2D and 3D echo and MRI measurement of EF were performed in 53 pts with previous infarction. GLS was measured by offline speckle-tracking in the apical 4C and 2C views. Abnormal curves were excluded on the basis of visual assessment. Auto-EF was calculated using the method of discs, using the traced endocardial border to establish end-diastolic and end-systolic volumes. Results: Average global TQ (tracking quality) was 1.14±0.22, permitting reliable derivation of strain from all segments. GLS showed a significant linear correlation with MRI-EF, similar to that between 3D-EF and MRI and better than that between 2D-EF and MRI and automated EF and MRI (Table ). Of 26 pts with a normal MRI-EF (≥50%), 85% had GLS within normal limits and 81% had normal 3D-EF, but significantly fewer were recognized as normal by 2D-EF (Table ). In pts with ≤5 abnormal segments, 3D-EF was the most accurate modality for assessing global LV function, while GLS was better than 2D-EF and auto-EF. In pts with >5 abnormal segments, GLS was the most accurate modality of quantifying global LV function against MRI-EF (r = −0.83, p <0.0001), comparatively better than 3D-EF against MRI-EF (r = 0.75, p <0.0001). Conclusion: GLS is an effective method of quantifying global LV function. In pts with >5 abnormal segments, GLS offered the best correlation with MRI-EF, reflecting the benefit of a geometry independent and site-specific parameter.

scholarly journals Differentiation of Patients with Balance Insufficiency (Vestibular Hypofunction) versus Normal Subjects Using a Low-Cost Small Wireless Wearable Gait Sensor

Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 29 ◽  
Author(s):  
Tam Nguyen ◽  
Jonathan Young ◽  
Amanda Rodriguez ◽  
Steven Zupancic ◽  
Donald Lie
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Normal Subjects ◽  
The Elderly ◽  
Measurement Unit ◽  
Balance Disorders ◽  
Remote Sensor ◽  
Data Collection And Analysis ◽  
Dynamic Gait Index ◽  
Dynamic Gait

Balance disorders present a significant healthcare burden due to the potential for hospitalization or complications for the patient, especially among the elderly population when considering intangible losses such as quality of life, morbidities, and mortalities. This work is a continuation of our earlier works where we now examine feature extraction methodology on Dynamic Gait Index (DGI) tests and machine learning classifiers to differentiate patients with balance problems versus normal subjects on an expanded cohort of 60 patients. All data was obtained using our custom designed low-cost wireless gait analysis sensor (WGAS) containing a basic inertial measurement unit (IMU) worn by each subject during the DGI tests. The raw gait data is wirelessly transmitted from the WGAS for real-time gait data collection and analysis. Here we demonstrate predictive classifiers that achieve high accuracy, sensitivity, and specificity in distinguishing abnormal from normal gaits. These results show that gait data collected from our very low-cost wearable wireless gait sensor can effectively differentiate patients with balance disorders from normal subjects in real-time using various classifiers. Our ultimate goal is to be able to use a remote sensor such as the WGAS to accurately stratify an individual’s risk for falls.

Factors Associated With Rehabilitation Outcomes in Patients With Unilateral Vestibular Hypofunction: A Prospective Cohort Study

2020 ◽  
Vol 100 (11) ◽  
pp. 2009-2022
Author(s):  
Susan J Herdman ◽  
Courtney D Hall ◽  
Lisa Heusel-Gillig
Keyword(s):  
Gait Speed ◽  
Outcome Measure ◽  
Patient Characteristics ◽  
Meaningful Change ◽  
Balance Confidence ◽  
Factors Associated ◽  
Rehabilitation Outcomes ◽  
Vestibular Hypofunction ◽  
Dynamic Gait Index ◽  
Dynamic Gait

Abstract Objective The purpose of this study was to determine factors associated with rehabilitation outcomes following vestibular rehabilitation (VR). Methods In this prospective cohort study, 116 patients who completed at least 2 supervised sessions participated. Patient characteristics and comorbidities were recorded. Initial and discharge measures included symptom intensity, balance confidence, quality of life, percent of time symptoms interfere with life, perceived benefits of VR, gait speed, fall risk, visual acuity during head movement, and anxiety/depression. Intention-to-treat analyses were performed to determine outcomes at discharge. Bivariate correlations between independent (group characteristics and baseline measures) and dependent (discharge measures) variables were determined. Logistic regressions were performed to identify factors associated with whether a patient would have a normal score or meaningful change at discharge. Results There was a large effect of VR with significant improvement for the group as a whole on each outcome measure. For each outcome measure, most patients improved. Based on preliminary logistic regression, 2 patient characteristics were associated with outcome: number of therapy visits predicted meaningful improvement in gait speed, and falls after the onset of the unilateral vestibular hypofunction (UVH) predicted meaningful change in the percent of time symptoms interfered with life. Initial Activities-Specific Balance Confidence Scale (ABC) and Dynamic Gait Index scores predicted normal ABC scores at discharge, and initial ABC scores predicted recovery of Dynamic Gait Index scores. Preliminary prediction models were generated for balance confidence, impact of dizziness on life, dynamic visual acuity, gait speed, and fall risk. Conclusions Therapists may use these findings for patient education or to determine the need for adjunct therapy, such as counseling. Impact Not all people with UVH improve following VR, but there is little research examining why. This study looked at multiple factors and identified number of visits and falls after onset of UVH as patient characteristics associated with outcomes following VR; these findings will help therapists create better predictive models.

scholarly journals 1312. Division Divided: Using Debate as an Educational Tool to Teach Evidence-Based Clinical Decision-Making

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S401-S401
Author(s):  
Jennifer O Spicer ◽  
Varun K Phadke
Keyword(s):  
Critical Thinking ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Faculty Members ◽  
Case Conference ◽  
Multiple Choice Questions ◽  
Innovative Teaching ◽  
Attitudes And Practices ◽  
The Impact ◽  
Better Than

Abstract Background In medical education, there has been a push to implement innovative teaching techniques that encourage critical thinking rather than just knowledge dissemination. Debate promotes critical thinking by challenging individuals to consider alternate viewpoints, which could make it an ideal format to review the evidence relevant to common clinical dilemmas in infectious diseases (ID). We describe a pilot of one such debate format in our ID fellowship program. Methods We reviewed literature regarding the effectiveness of ceftriaxone for outpatient antibiotic therapy (OPAT) in methicillin-susceptible Staphylococcus aureus (MSSA) osteoarticular infections. The evidence was presented as a structured debate in place of our weekly case conference. Pre- and post-session surveys containing multiple choice questions and Likert items were administered to assess the impact of the debate on attendees’ knowledge, attitudes, and practices on this topic along with their attitudes toward the debate format. Differences between pre- and post-session surveys were analyzed using paired t-tests and McNemar’s test. Results At the first debate 33 residents, fellows, and faculty members were present, and 24 (73%) completed both the pre- and post-session surveys. Attendees demonstrated significant improvement between the pre- and post-session knowledge questions, which covered the following topics: study design of articles supporting ceftriaxone use (31% vs. 62%, P = 0.008), appropriate method to assess ceftriaxone susceptibility (64% vs. 100%, P = 0.004), and whether the inoculum effect applies to ceftriaxone (35% vs. 77%, P = 0.003). After the debate, attendees were more willing to use ceftriaxone (P = 0.001) and felt more familiar with the literature (P &lt; 0.001). The post-session survey showed that individuals both enjoyed the format and found it effective (Figure 1). Most individuals stated that they were either extremely likely (85%) or likely (8%) to attend if this format was used again. Written comments included “strongly recommend continuing this format” and “much better than regular case conference with more discussion and critical thinking.” Conclusion Debate appears to be an effective and enjoyable format to teach clinical controversies in ID. Disclosures All authors: No reported disclosures.

Use of an Artificial Neural Network for Data Analysis in Clinical Decision-Making: The Diagnosis of Acute Coronary Occlusion

1990 ◽  
Vol 2 (4) ◽  
pp. 480-489 ◽  
Author(s):  
William G. Baxt
Keyword(s):  
Neural Network ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Artificial Neural Network ◽  
Coronary Occlusion ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Acute Coronary Occlusion ◽  
Artificial Neural ◽  
Better Than

A nonlinear artificial neural network trained by backpropagation was applied to the diagnosis of acute myocardial infarction (coronary occlusion) in patients presenting to the emergency department with acute anterior chest pain. Three-hundred and fifty-six patients were retrospectively studied, of which 236 did not have acute myocardial infarction and 120 did have infarction. The network was trained on a randomly chosen set of half of the patients who had not sustained acute myocardial infarction and half of the patients who had sustained infarction. It was then tested on a set consisting of the remaining patients to which it had not been exposed. The network correctly identified 92% of the patients with acute myocardial infarction and 96% of the patients without infarction. When all patients with the electrocardiographic evidence of infarction were removed from the cohort, the network correctly identified 80% of the patients with infarction. This is substantially better than the performance reported for either physicians or any other analytical approach.

scholarly journals Epidemiologia da Vertigem na Urgência Hospitalar

2016 ◽  
Vol 29 (5) ◽  
pp. 326 ◽  
Author(s):  
Luis Roque Reis ◽  
Rita Lameiras ◽  
Pedro Cavilhas ◽  
Pedro Escada
Keyword(s):  
Health Care ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Medical Attention ◽  
Annual Number ◽  
Health Care Planning ◽  
Balance Disorders ◽  
Population Type ◽  
Epidemiological Characteristics ◽  
Annual Proportion

<p><strong>Introduction:</strong> Vertigo is one of the most frequent motives in seeking specialized medical care in an emergency. The aim of this study was to evaluate the relevance of balance disorders in the Otorhinolaryngology urgency, the epidemiological characteristics and the possible seasonality. It was used a sample of patients who were assisted in a health care emergency department of this specialty, of a universitary hospital and during a period of four years.<br /><strong>Material and Methods:</strong> The project was conceived as a descriptive epidemiological study of population type, retrospective, during the period from 2010 to 2013. A total population of 40.173 attendances of patients during this period used the emergency eepartment of Otolaryngology. The parameters studied included age, gender, annual number of cases (total and percentage), date of crisis of vertigo, seasonal distribution by seasons and annual proportion of hospitalized cases.<br /><strong>Results:</strong> A total of 4.347 patients (10.8%) sought medical attention due to dizziness/balance disorders over the four years of the study. There has been an annual increase in the number of cases between 7.6% (in 2010) and 17% (in 2013). Women were more often affected (68.3%) and crises occurred more often in individuals between 60 and 79 years of age (40%). The cases were distributed heterogeneous between the seasons, having more episodes of dizziness in summer and autumn and with an increasing trend between 2010 and 2013. The number of hospitalizations has increased annually over this period.<br /><strong>Discussion:</strong> The epidemiology of vertigo and vestibular disorders is still a specific field to study, because it may be useful for clinical decision-making and health care planning.<br /><strong>Conclusion:</strong> The study revealed that cases of vertigo in urgency increased annually and are more frequent in women, in elderly population and in Summer and Autumn.</p>

scholarly journals An Evaluation and Dissemination Model for the Machine Learning Embedded System Lifecycle in Clinical Practice Settings

2021 ◽  
Author(s):  
melanie besculides ◽  
Ksenia Gorbenko ◽  
Cardinale Smith ◽  
Robert Freeman ◽  
David Reich ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Practice ◽  
Embedded System ◽  
Quantitative Methods ◽  
Clinical Decision Making ◽  
Comprehensive Evaluation ◽  
Healthcare Setting ◽  
Clinical Decision ◽  
Qualitative And Quantitative Methods ◽  
Better Than

Machine learning (ML) algorithms are gaining popularity in clinical practice settings due to their ability to process information in ways that augment human reasoning. While tools that rely on output from ML algorithms in the healthcare setting are appealing for their ability to aid in clinical decision making and streamline workflows, their implementation and effectiveness are not well documented. There is an abundance of published ML literature that focuses on whether algorithms can predict an outcome or predict it better than previous algorithms, but a dearth of effort evaluating their implementation or impact on patient outcomes. While developing and validating algorithms is an important first step in research, comprehensive evaluation is needed before application of ML algorithms in new settings is considered. Evaluation should examine both the process of implementation and the outcomes using a mix of qualitative and quantitative methods. This commentary describes a model we developed to guide our institutional ML evaluation efforts.

scholarly journals Comparing Machine Learning Algorithms for Predicting ICU Admission and Mortality in COVID-19

2020 ◽  
Author(s):  
Sonu Subudhi ◽  
Ashish Verma ◽  
Ankit B. Patel ◽  
C. Corey Hardin ◽  
Melin J. Khandekar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Clinical Decision Making ◽  
Learning Algorithms ◽  
Disease Outbreaks ◽  
Clinical Decision ◽  
Machine Learning Algorithms ◽  
Healthcare Database ◽  
Icu Admission ◽  
Infectious Disease Outbreaks ◽  
Better Than

AbstractAs predicting the trajectory of COVID-19 disease is challenging, machine learning models could assist physicians determine high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) healthcare database, we developed and internally validated models using patients presenting to Emergency Department (ED) between March-April 2020 (n = 1144) and externally validated them using those individuals who encountered ED between May-August 2020 (n = 334). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and procalcitonin levels were important for ICU admission models whereas eGFR <60 ml/min/1.73m2, ventilator use, and potassium levels were the most important variables for predicting mortality. Implementing such models would help in clinical decision-making for future COVID-19 and other infectious disease outbreaks.

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