Introdução: As quedas hospitalares interferem na funcionalidade do paciente durante e após a hospitalização. Nosso objetivo foi verificar se uma escala de identificação do risco de quedas (Morse Fall Scale) e um teste de avaliação de equilíbrio dinâmico (Mini-BESTest) identificam os idosos caidores durante e após hospitalização. Método: Trata-se de um estudo coorte prospectivo com análise retrospectiva. Participaram 154 idosos (>=65 anos) internados em duas enfermarias não cirúrgicas de Clínica Médica e Geriatria de um Hospital Universitário de porte extra. Foram realizadas avaliações do Mini-BESTest e da Morse Fall Scale (MFS) na admissão e na alta hospitalar. O acompanhamento das quedas foi feito por telefone em 1, 3 e 6 meses após alta hospitalar. Resultados: Os idosos foram divididos em: caidores (Grupo Q, n=5) e não caidores (Grupo NQ, n=149) na hospitalização. Na admissão não houve diferença significativa entre os Grupos Q e NQ nas ferramentas avaliadas (Mini-BESTest Q=23, NQ=20, p=0.85; MFS Q=25, NQ=15, p=0,87) e na alta hospitalar apenas na MFS (Mini-BESTest Q=20, NQ=22, p=0,22; MFS Q=50, NQ=25, p=0,01). Nos domínios \"Respostas Posturais\" do Mini- BESTest e nos domínios \"Histórico de Quedas\" e \"Tipo de Marcha\" da MFS houve diferença entre Q e NQ na alta (respectivamente, =0,02; p=0,01; p=0,02). Foi realizada uma subanálise com pareamento de dados por gênero, idade e comorbidades e também não foram encontradas diferenças clínicas, demográficas e nos escores das escalas entre os grupos Q (n=5) e NQp (n=10) (p > 0,05). Na predição de quedas pós-alta o Mini-BESTest apresentou AUC=0,53, p=0,50, sensibilidade 48,8% e especificidade 59,5%, já a MFS apresentou AUC=0,56, p=0,20, sensibilidade 44,2% e especificidade 72%. Houve um aumento de caidores nos 6 meses de Follow-up (11,2%, 15,6% e 17,1%;), e os pacientes com baixo risco de queda pela MFS tiveram mais quedas no Follow-up do que os pacientes de alto risco. Conclusão: Mini-BESTest e a Morse Fall Scale não identificaram os idosos caidores durante e após a hospitalização, apesar de alterações nos domínios na alta hospitalar e do aumento de quedas no Follow-up / Introduction: Hospital falls interfere with the patient\'s functionality during and after hospitalization. This study aimed to identify whether the Morse Fall Scale and Mini-BESTest can identify fall risk in elderly patients during and after hospitalization. Method: This is a prospective cohort study with retrospective analysis. A total of 154 consecutive elderly patients (>=65 years old) who were hospitalized at two clinical wards in a tertiary Hospital were included in the study. Mini-BESTest and Morse Fall Scale (MFS) assessments were carried out at hospital admission and discharge. The occurrence of falls was evaluated by phone calls 1, 3 and 6 months after hospital discharge. Results: Patients were divided in two groups, those who had falls (F group, n=5) and those who did not fall (NF group, n=149) during hospitalization. At hospital admission, no differences were observed between the F and NF groups in the Mini-BESTest (F=23 vs. NF=20; p=0.85) and MFS (F=25 vs. NF=15; p=0.87) scores. At hospital discharge, the F and NF groups had similar scores in the Mini-BESTest (F=20 vs. NF=22; p=0.22) but differences in the MFS (F=50 vs. NF=25; p=0.01). The domain assessments for \"postural responses\" of the Mini-BESTest and \"history of falls\" and \"type of gait\" of the MFS were different between the F and NF groups at hospital discharge (p=0.02, p=0.01 and p=0.02, respectively). A sub analysis was performed with data matching by gender, age and comorbidities and no clinical, demographic and scales differences were observed between the group F (n=5) and group NFm (n=10) (p > 0.05). In the prediction of post-discharge falls, the Mini-BESTest presented AUC = 0.53, p = 0.50, sensitivity 48.8% and specificity 59.5%, the MFS presented AUC=0.56, p=0. 20, sensitivity 44.2% and specificity 72%. There was an increase in the number of patients who fell from the 1st to the 6th month of follow-up (from 11.2% to 17.1%), and the patients with low and medium fall risk determined by the MFS had more falls in the follow-up period than those classified as high risk. Conclusion: Our results suggest that neither the Mini-BESTest nor the MFS identified elderly fall risk during and after hospitalization. In addition, we observed the need to supervise elderly patients after hospitalization

Bakgrund: Personer som opererats för godartad lillhjärnstumör när de var barn upplever sig ha balansproblem och förekomst av lätt balansnedsättning har rapporterats. I en pågående uppföljningsstudie vid Akademiska sjukhuset undersöks bl.a. balansen i denna patientgrupp. Syfte: … att i en delstudie med kontrollpersoner beskriva och jämföra balansförmågan vid genomförande av Mini-BESTest med fokus på Timed-Up-and-Go (TUG) och TUG_kognitiv. Metod: Tvärsnittsstudie. Elva personer 19-33 år rekryterades. Deltagarna utförde Mini-BESTest med rörelseanalyssystemet MoLab. Beroende variabler var poäng på MiniBESTest, absolut och relativ tid för TUG-faser samt balansvariabeln trunk sway velocity. Resultat: Medianvärdet för Mini-BESTest var 31 (Q1-Q3=29-31). En skillnad på 17,3%  framkom för den totala tiden mellan TUG och TUG_kognitiv. Signifikanta skillnader mellan balansuppgifterna påvisades för total absolut tid (p = 0,003), fas 2 (p = 0,013) och fas 3 (p = 0,021). För balansvariabeln trunk sway velocity i antero-/posterior riktning framkom signifikanta skillnader för fas 2 (p=0,008), fas 3 (p=0,010) och fas 4 (p = 0,05), medio-/lateralt en signifikant skillnad för fas 2 (p = 0,03). Konklusion: Denna studie visade att friska unga vuxna får en påverkan på balansen när de samtidigt utför en kognitiv uppgift. Resultatet går inte att generalisera till en större population utan gäller för de undersökta deltagarna / Background: People treated for benign cerebellar tumor during childhood experience balance problems and studies report presence of mild balance impairment. In an ongoing follow-up study at the University Hospital in Uppsala balance in this patient group is being investigated. Objective: ... in a sub-study with control persons describe and compare balance performance of Mini-BESTest focusing on Timed-Up-and-Go (TUG) and TUG_cognitive. Methods: Cross-sectional study. Eleven people 19-33 years were recruited. The participants performed the Mini-BESTest with the MoLab motion analysis system. Dependent variables were points on MiniBESTest, absolute and relative time for TUG-phases, and the balance variable trunk sway velocity. Results: Median value for Mini-BESTest was 31 (Q1-Q3 = 29-31). A difference of 17.3% was shown for total time between TUG and TUG_cognitive. Significant differences between the balance tests were shown for total absolute time (p = 0.003), phase 2 (p = 0.013) and phase 3 (p = 0.021). For trunk sway velocity in the antero-/posterior direction, significant differences were shown for phase 2 (p = 0.008), phase 3 (p = 0.010) and phase 4 (p = 0.05), medio-/laterally  significant difference for phase 2 (p = 0.03). Conclusion: This study demonstrated that healthy young adults have an impact on balance when they simultaneously perform a cognitive task. The result cannot be generalized to a larger population, but applies to the participants investigated.

PURPOSE: The aims of this study were to: 1) determine the concurrent validity of the mini-Balance Evaluations Systems Test (BESTest) and the instrumented test of postural sway (iSWAY) to quantify sensory orientation impairments in adults with known postural control deficits; and 2) determine the predictive validity of iSWAY to differentiate between fallers and non-fallers in adults with known postural control deficits. The Sensory Organization Test (SOT) served as the gold standard measure. METHODS: An exploratory methodological design using secondary analysis was used. The sample consisted of 45 subjects with Parkinson¡¦s disease (PD). Subjects were concurrently tested on SOT, mini-BEST, and iSWAY. DATA ANALYSIS: Frequency distributions, central tendencies, variability, and outliers were used to analyze goodness-of-fit to the normal distribution. Mean was used for age while mode was used for fall group, fall status, and gender. The following statistical tests were used: 1) Spearman rank correlation (rs) to measure the relationship between the the mini-BEST and SOT outcome scores; 2) parametric Pearson product-moment correlation (r) was used to measure the relationship between the iSWAY and SOT outcome scores; and 3) multiple regression to analyze the association between several independent variables (iSWAY scores) and dependent variable (number falls). A receiving operator curve was constructed to determine the iSWAY score that best discriminates fallers from non-fallers. RESULTS: There was a significant and fair correlation between mini-BESTest and SOT: Composite and Total rs = 0.380 (p = 0.010); Composite and Sensory rs = 0.343 (p = 0.021), Individual Items Eyes Open, Foam Surface (EOF) and Condition five rs = 0.399 (p = 0.007). There was insignificant and little-to-no relationship between mini-BESTest and SOT Condition one. There was a moderate-to-good inverse correlation between iSWAY and SOT: Composite r = - 0.634 (p = f¬0.01); Individual items ECF and Condition five r = -0.543 (p = f¬0.01). There was significant and fair inverse correlation between iSWAY and SOT Condition one r = -0.432 (p = 0.028). There was a predictive relationship between iSWAY RANGE Composite (p = 0.040) and RMS Composite (p = 0.021) and history of falls. A multiple regression equation including three iSWAY Composite scores explained 38% variability in reported falls. The ROC curve identified an iSWAY RMS Score of less than 0.249 as demonstrating the highest likelihood of differentiating between fallers and non-fallers. DISCUSSION: Mini-BESTest and iSWAY are clinically meaningful measures of sensory orientation in persons with PD. iSWAY can help better quantify sensory orientation impairments and inform other examination findings about history of falls. Future research is needed to investigate validity of these tests with other populations and expand validation of other test components.