Detalhes bibliográficos
| Ano de defesa: |
2018 |
| Autor(a) principal: |
Oliveira, Gabriela Guimarães
 |
| Orientador(a): |
Bós, Ângelo José Gonçalves
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Pontifícia Universidade Católica do Rio Grande do Sul
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| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Gerontologia Biomédica
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| Departamento: |
Escola de Medicina
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tede2.pucrs.br/tede2/handle/tede/8192
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Resumo: |
Performance of oldest-old fallers and do non fallers in the evaluation of Timed Up and Go (TUG) using a smartphone application The falling is a serious event in the elderly population. Oldest-old (80 years or more) are more susceptible to their occurrence. Mobile technologies are shown as a facilitative and preventive alternative in actions in the field of public health. It is a cross-sectional observational and analytical study, with the objective to observe the performance of oldest-old fallers and non-fallers during the Timed Up and Go (TUG) test using a smartphone application. Participants were oldest-old (≥90 years old), from Porto Alegre (RS), accompanied by the Care for the Oldest-Old Multiprofessional Project. We included in the study oldest-old that walked independently (without caregiver, family member or health professional) and safely, with or without the aid of gait devices (walking stick, crutch and walker) were included in the study; as well as those who understood verbal commands. Oldest-old patients who reported significant lower limb or spine pain on the day of the test were excluded from the study. In the analysis we use the sociodemographic variables (sex, age, schooling and monthly income), clinical variables (Mini Mental State Examination (MMSE), Geriatric Depression Scale (GDS), presence of multimorbities( ) and polypharmacy 5≥ medications) and variables related to falls (history of falling in the last six months and fear of falling). As well as, parameters tracked by the application, which are temporal (Total TUG Duration, Transition Length from Seating to Standing (s) and Duration of Transition from Standing to Seating) and Angular (Maximum Trunk Angle Variation (g) and Maximum angular velocity during the forward lean phase (g / s) of the application). Significance levels of less than 5% were considered to be statistically significant and those between 5 and 10% were indicative of significance. The data were analyzed in the Epi InfoTM 7.2 program. From the 98 volunteers that participated at the study, 26.5% reported fall in the last six months. Women (25.76%) reported more frequent falls than men (p=0.492). Oldest-old fallers had mean age (92±3.14 years) higher than non-fallers (p=0.636), as well as more depressive symptoms (p<0.001). In the complete TUG, 97% of the non-fallers presented a medium or high risk of falling, compared to 92% of the fallers, showing an inadequacy of this classification for oldest-old. Fallers presented worse performance in each of the phases of the TUG, demonstrating to be more able to find differences between the groups than the complete test. Cut-off points for risk of falls were >1.68 seconds, in the sitting to standing phase, <1.91 seconds, in the standing to sitting phase, >42.2 degrees in the angle variation, and >84 degrees/second at the speed angle. The UAH Mobility Suite® smartphone application was able to evaluate the performance of oldest-old fallers and do non fallers through TUG time and its parameters, although any parameters were significant when compared to groups. Depression proved to be the only statistically significant variable, indicating that oldest-old depressive symptoms are more likely to fall. This was the first report of the use of UAHMobilitySuite® in oldest-old ones. The application has proved to be useful for being used in the home environment, and can be used in future researches. |
