Stakeholder collaboration in long-term care of older people in Lithuania

Demographic situation, changes in the role of women in society and growing demand for long-term care (LTC) of older people have challenged the ability to meet the growing LTC needs in most developed countries. In countries where responsibility for LTC is still largely laid on families, it is, however, even more critical and calls for improvements in formal LTC systems. More intensive stakeholder collaboration in LTC policy development, organising and delivery are of primary importance in improving LTC systems. Such collaboration, however, is not always successful; thus, it is critical to understand what makes it effective and efficient. In this paper, we specifically look into multistakeholder collaboration in LTC in Lithuania, one of the fastest ageing countries in the EU, with the demand for LTC services growing fast and exceeding the supply despite rising business and NGO engagement. To determine facilitators of such collaboration, we build on the data obtained through eight focus group discussions with all key stakeholder representatives (LTC policymakers, organisers and service providers [public, private and NGOs], 54 participants in total). Our findings indicate that in addition to national and organisational level facilitators studied in prior research, there are important individual level factors, such as meaningfulness at work, concern and care for others, possibility for personal growth and development, satisfaction with supervision, a sense of belonging and role clarity. On the other hand, our results show that collaboration is constrained by a shortage of human resources, increased workload caused by growing LTC demand, bureaucratic requirements, legal restrictions, lack of awareness of LTC service availability among elder persons, and prevailing social norms and attitudes to institutionalised care. Interestingly, a lack of financial resources is not perceived as a major constraint.     

A comparison of the efficacy of textured insoles on balance performance in older people with versus without plantar callosities

BackgroundTextured insoles have been suggested to enhance foot sensation, which contributes to controlling upright balance. However, the interaction between plantar callosity and the textured surface has not been studied.Research questionFirstly, to compare the efficacy of textured insoles on balance performance and foot position sense between two groups of older people: one group had plantar callosity, and the other did not. Secondly, to investigate the efficacy of textured insoles within each study group.MethodsThirty older people with a history of falls (15 with plantar callosity and 15 without callosity) participated in this study. All participants underwent assessments of postural sway on a force plate, joint position sensation of the ankle with a slope box, and mobility using the "Timed Up and Go" test under three insole surface conditions: 1) smooth (control), 2) placebo and 3) textured surface. Two-way analyses of variance were used to compare the outcomes of the two groups and three conditions.ResultsOlder people with plantar callosity had worse ankle joint position sense and slower antero-posterior and mediolateral postural sway velocity than their peers who did not have plantar callosity. The textured insoles improved ankle joint position sense and mobility regardless of callus status in the plantar surface of older peoples’ feet. The insole-callosity interaction was not significant for any study outcome.SignificanceTextured insoles could be beneficial to older people with and without callosity as they have shown immediate improvements in ankle joint position sense and mobility.     

Evidence-based strategies to reduce the incidence of postoperative delirium: a narrative review

Delirium is one of the most commonly occurring postoperative complications in older adults. It occurs due to the vulnerability of cerebral functioning to pathophysiological stressors. Identification of those at increased risk of developing delirium early in the surgical pathway provides an opportunity for modification of predisposing and precipitating risk factors and effective shared decision-making. No single delirium prediction tool is used widely in surgical settings. Multi-component interventions to prevent delirium involve structured risk factor modification supported by geriatrician input; these are clinically efficacious and cost effective. Barriers to the widespread implementation of such complex interventions exist, resulting in an ‘implementation gap’. There is a lack of evidence for pharmacological prophylaxis for the prevention of delirium. Current evidence suggests that avoidance of peri-operative benzodiazepines, careful titration of anaesthetic depth guided by processed electroencephalogram monitoring and treatment of pain are the most effective strategies to minimise the risk of delirium. Addressing postoperative delirium requires a collaborative, whole pathway approach, beginning with the early identification of those patients who are at risk. The research agenda should continue to examine the potential for pharmacological prophylaxis to prevent delirium while also addressing how successful models of delirium prevention can be translated from one setting to another, underpinned by implementation science methodology.     

精简易筋经四式治疗肩周炎临床观察

目的观察精简"易筋经四式"治疗肩周炎的临床疗效。方法选取2017年9月—2018年9月期间在北京市丰台区蒲黄榆社区卫生服务中心中医科就诊的40~65岁肩周炎患者60例,随机分为2组,每组30例。观察组习练精简"易筋经四式",对照组采用针刺治疗。结果研究后2组观察对象肩关节疼痛程度评分观察组显著低于对照组(P<0.05)。研究后肩关节功能活动评分观察组显著高于对照组(P<0.05)。研究后观察组患者满意度显著高于对照组(P<0.05)。结论通过该研究证实,习练精简"易筋经四式"对肩周炎患者具有显著的疗效,且患者易于接受,值得在社区广泛推广应用。     

青年人群近距离工作后眼部参数的变化及恢复时间

目的：观察青年人群近距离用眼后眼部生理及功能性参数的变化及恢复时间。

方法：前瞻性研究。随机选取2019-12/2020-06在我院进行医学验光的患者69例138眼，根据主觉验光结果分为正视组(+0.75D≤等效球镜度≤-0.50D，18例36眼)、低度近视组(-0.75D≤等效球镜度≤-3.00D，25例50眼)和中度近视组(-3.25D≤等效球镜度≤-6.00D，26例52眼)。所有受试者近距离阅读20min后远眺放松20min，分别于近距离用眼前、近距离用眼20min后、远眺5、10、15、20min时测量受试者眼部生理性参数\〖前房深度(ACD)、眼轴长度(AL)\〗和功能性参数\〖正相对调节(PRA)、调节反应(BCC)\〗，分析各参数的达极时间和恢复时间。

结果：近距离用眼后眼轴变长，前房变浅，PRA绝对值变大，BCC无明显变化，75%(52/69)的受试者AL在近距离用眼20min后达极，87%(60/69)的受试者ACD在远眺5min时达极，96%(66/69)的受试者PRA在近距离用眼20min后达极，且以上参数均在远眺10min后逐渐恢复至初始状态。

结论：近距离用眼后眼部参数发生改变，眼轴变长，前房变浅，PRA绝对值增大，但均在远眺放松过程中逐渐回退，且均需要10min以上才能恢复至初始状态。     

Preventing Adverse Drug Reactions After Hospital Discharge (PADR-AD): Protocol for a randomised-controlled trial in older people

BackgroundAdverse drug reactions (ADRs) and adverse drug events (ADEs) in older people contribute to a significant proportion of hospital admissions and are common following discharge. Effective interventions are therefore required to combat the growing burden of preventable ADRs. The Prediction of Hospitalisation due to Adverse Drug Reactions in Elderly Community Dwelling Patients (PADR-EC) score is a validated risk score developed to assess the risk of ADRs in people aged 65 years and older and has the potential to be utilised as part of an intervention to reduce ADRs.ObjectivesThis trial was designed to investigate the effectiveness of an intervention to reduce ADR incidence in older people and to obtain further information about ADRs and ADEs in the 12–24 months following hospital discharge.MethodsThe study is an open-label randomised-controlled trial to be conducted at the Royal Hobart Hospital, a 500-bed public hospital in Tasmania, Australia. Community-dwelling patients aged 65 years and older with an unplanned overnight admission to a general medical ward will be recruited. Following admission, the PADR-EC ADR score will be calculated by a research pharmacist, with the risk communicated to clinicians and discussed with participants. Following discharge, nominated general practitioners and community pharmacists will receive the risk score and related medication management advice to guide their ongoing care of the patient. Follow-up with participants will occur at 3 and 12 and 18 and 24 months to identify ADRs and ADEs. The primary outcome is moderate-severe ADRs at 12 months post-discharge, and will be analysed using the cumulative incidence proportion, survival analysis and Poisson regression.SummaryIt is hypothesised that the trial will reduce ADRs and ADEs in the intervention population. The study will also provide valuable data on post-discharge ADRs and ADEs up to 24 months post-discharge.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.