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1.
BMC Geriatr ; 24(1): 269, 2024 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-38504155

RESUMO

BACKGROUND: Frailty interventions such as Comprehensive Geriatric Assessment (CGA) can provide significant benefits for older adults living with frailty. However, incorporating such proactive interventions into primary care remains a challenge. We developed an IT-assisted CGA (i-CGA) process, which includes advance care planning (ACP). We assessed if, in older care home residents, particularly those with severe frailty, i-CGA could improve access to advance care planning discussions and reduce unplanned hospitalisations. METHOD: As a quality improvement project we progressively incorporated our i-CGA process into routine primary care for older care home residents, and used a quasi-experimental approach to assess its interim impact. Residents were assessed for frailty by General Practitioners. Proactive i-CGAs were completed, including consideration of traditional CGA domains, deprescribing and ACP discussions. Interim analysis was conducted at 1 year: documented completion, preferences and adherence to ACPs, unplanned hospital admissions, and mortality rates were compared for i-CGA and control (usual care) groups, 1-year post-i-CGA or post-frailty diagnosis respectively. Documented ACP preferences and place of death were compared using the Chi-Square Test. Unplanned hospital admissions and bed days were analysed using the Mann-Whitney U test. Survival was estimated using Kaplan-Meier survival curves. RESULTS: At one year, the i-CGA group comprised 196 residents (severe frailty 111, 57%); the control group 100 (severe frailty 56, 56%). ACP was documented in 100% of the i-CGA group, vs. 72% of control group, p < 0.0001. 85% (94/111) of severely frail i-CGA residents preferred not to be hospitalised if they became acutely unwell. For those with severe frailty, mean unplanned admissions in the control (usual care) group increased from 0.87 (95% confidence interval ± 0.25) per person year alive to 2.05 ± 1.37, while in the i-CGA group they fell from 0.86 ± 0.24 to 0.68 ± 0.37, p = 0.22. Preferred place of death was largely adhered to in both groups, where documented. Of those with severe frailty, 55% (62/111) of the i-CGA group died, vs. 77% (43/56) of the control group, p = 0.0013. CONCLUSIONS: Proactive, community-based i-CGA can improve documentation of care home residents' ACP preferences, and may reduce unplanned hospital admissions. In severely frail residents, a mortality reduction was seen in those who received an i-CGA.


Assuntos
Planejamento Antecipado de Cuidados , Fragilidade , Humanos , Idoso , Fragilidade/diagnóstico , Avaliação Geriátrica , Estudos Longitudinais , Hospitalização
2.
Ecol Evol ; 11(11): 6789-6797, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34141256

RESUMO

Scrub vegetation is a valuable habitat and resource for wildlife, but if unmanaged can encroach and dominate adjacent habitats, reducing biodiversity value. A primary task in the management of terrestrial nature reserves in the UK is monitoring and controlling scrub. The methods used to monitor and assess scrub cover are often basic, relying on qualitative assessment. Inaccurate assessments may fail to inform appropriate management of the habitats and lead to loss or degradation of important ecological features. Scrub can be monitored using UAV or satellite-derived imagery, but it can be difficult to distinguish between other vegetation types without using high-cost hyperspectral sensors. An alternative method using high-resolution surface models from photogrammetric point clouds enables the isolation of vegetation types based on height. Scrub can be isolated from woodland, hedgerows, and tall ground vegetation. In this study, we calculate scrub cover using a photogrammetric point cloud modeling approach using UAVs. We illustrate the method with two case studies from the UK. The scrub cover at Daneway Banks, a calcareous grassland site in Gloucestershire, was calculated at 21.8% of the site. The scrub cover at Flat Holm Island, a maritime grassland in the Severn Estuary, was calculated at 7%. This approach enabled the scrub layer to be readily measured and if required, modeled to provide a visual guide of what a projected management objective would look like. This approach provides a new tool in reserve management, enabling habitat management strategies to be informed, and progress toward objectives monitored.

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