Scientific Research

Aim: Several scores have been developed to identify SDEC patients from Emergency Department (ED) triage and acute medical intakes. Scores are designed to improve system efficiency, overcrowding and patient experience but none have been developed for older adults. Previous work has shown that existing scores e.g. Glasgow Admission Prediction Score, Sydney Triage to Admission Risk Tool and the Ambulatory Score were not able to predict admission in our population(1). We have developed a novel, frailty-focused score. Methods: The Older Person’s Assessment service (OPAS) is ED based, accepting patients with frailty syndromes aged >70 years to provide a comprehensive geriatric assessment (CGA) and is extended into medical SDEC. The databases were retrospectively analysed and interactions with age, Charlson Co-morbidity index (CCI) and Clinical Frailty Score (CFS) were evaluated alongside NEWS, 4AT, including who with and where the patient resides. Results 1011 attendances, 414 (40.9%) Male, mean age 82.3(±8.4) years, CFS 5.3(±1.2) and CCI 8.0(±1.8), 701(69.3%) discharged same-day and 629(62.2%) fallers. OPAS: 776 attendances, 306 (39.4%) Male, age 82.4(±8.7) years, CFS 5.3(±1.1) and CCI 7.9(±1.9), 540 (69.5%) discharged same-day, 557(71.8%) fallers. SDEC: 234 attendances, 108(46.2%) Male, age 81.8(±8.0) years, CFS 5.2(±1.3) and CCI 8.2(±1.7),162(69.2%) discharged same-day, 72(30.1%) fallers. There was significant difference between groups with NEWS (p<0.02), mortality (P<0.001) and presenting complaint(p<0.001). We used a cut-off Score >6.5 indicating admission(p<0.0001). Each variable’s weighing was determined using T-tests and Chi-squared analysis. Overall score Sensitivity 0.75, Specificity 0.63, Positive Predictive Value 0.65, Negative Predictive value 0.57, Area under Curve 0.65. Conclusion Frailty is an important determinant in identifying whether ambulatory care is appropriate. The efficacy of the score is comparable to the results derived in validation cohorts of existing and recommended scores. We are currently prospectively testing the score but clinical judgement, alongside a MDT providing a CGA is gold standard care.

Introduction 

The National Hip Fracture Database (NHFD) is the mandatory national clinical audit for patients presenting with hip fracture. Since 2007, the NHFD has made admission cognitive assessment using the Abbreviated Mental Test Score (AMTS) routine for people presenting with this injury. In 2024, the NHFD plans to replace the AMTS with the 4A test (4AT), so all patients are additionally assessed for delirium on presentation. This study aims to compare the AMTS and 4AT for this patient group, so the NHFD and our local team can anticipate the consequences of this change in patient assessment.

Methods

The clerking house officer completed both AMTS and 4AT for patients admitted consecutively under the ‘femur fracture pathway’ to University Hospital Wales between August-October 2023. We classified an AMTS < 8 and 4AT = 1-3 as suggestive of cognitive impairment. A 4AT ≥ 4 also indicated possible delirium.

Results

A total of 100 patients were included, 65 female and 35 male. 4AT was normal (0) in 67/75 patients with normal AMTS (8+). 4AT was abnormal (1+) in 24/25 patients with abnormal AMTS (<8). Screening with 4AT highlighted possible delirium in 15 patients (15%) which may not have been identified by AMTS. Four questions from AMTS form the ‘AMT-4’ sub-domain of 4AT. AMT-4 was normal (0) in 73/75 patients with a normal AMTS, and abnormal (1+) in 22/25 patients with an abnormal AMTS (sensitivity 0.88, specificity 0.97).

Conclusion

The 4AT provides invaluable training in delirium recognition for junior doctors, and highlights aspects of cognition (such as delirium) missed by the AMTS whilst being a quick, user-friendly tool. The AMT-4 subdomain of 4AT proved remarkably consistent with full AMTS results. Our findings are being integrated into local clerking protocols and used by the NHFD in its redesign of cognitive screening nationally.

Introduction  Converting oral Parksinon’s disease (PD) medications to transdermal Rotigotine is sometimes required when patients have swallowing difficulties. Correct dosing is important to avoid under-treatment and deterioration of PD symptoms. Conversely, excessive dopamine agonist can cause hallucinations and confusion. In the UK, 2 main dose conversion calculators exist: PD Med Calc1 and OPTIMAL2, both utilising different formulae. We compared both to identify any dose discrepancies in their recommendations, and select one for use within revised trust guidelines.  Methods  We conducted a retrospective analysis of 22 cases from pharmacy data of 1400 prescriptions issued between January 2021 - July 2022 for patients switched from oral PD medications to a Rotigotine Patch whilst admitted to a UK teaching hospital. We calculated the recommended Rotigotine patch dose from each patient’s usual oral medication regimen using both the PD Med Calc1 and OPTIMAL2 calculators to identify discrepancies.  Results  In 86% of cases (19/22) there was a difference between doses suggested by both calculators. Of these, 95% (18/19) showed OPTIMAL recommended doses 20-200% higher than PD Med Calc. In 5% (1/19) OPTIMAL recommended a marginally lower dose than PD Med Calc.   Conclusions  In dopamine agonist naive patients, PD Med Calc recommended a lower starting Rotigotine dose than OPTIMAL. Most admitted PD patients on patch conversion were older adults, and this population is particularly vulnerable to the side effects of excessive dopamine agonist exposure. The authors recommended using PD Med Calc within revised trust guidelines to minimise negative sequelae and ensure dosing consistency.  1 PD 'Nil by Mouth' Medication Dose Calculator http://pdmedcalc.co.uk/ 2 OPTIMAL Calculator - A Guideline for the OPTIMAL management of inpatients with Parkinson's Disease. http://www.parkinsonscalculator.com/index.html  

The UK Parkinson's Disease Clinical Studies Group

The UK has a successful trial scene for Parkinson’s Disease, Multiple System Atrophy and Progressive Supranuclear Palsy neuroprotective studies, but with the growing number of trials, a formal, national structure is required to ensure the successful delivery of the studies. With funding from Cure Parkinson’s, the UK-PD-CSG launched in April-2022. The UK-PD-CSG’s goal is to further develop and support Parkinson’s clinical research across the UK and ensure more people with Parkinson’s (PwP) have the opportunity to participate in clinical trials.

The group has 65+ members, including neurologists, geriatricians, specialist nurses and Allied Health Professionals, stakeholder representatives (Cure Parkinson's, Parkinson's UK, BGS Movement Disorders SIG, ABN Movement Disorders SIG, PD Nursing Specialist Association) and PwP, all with a particular interest and expertise in PD, MSA and PSP clinical research. The group is operated by chair Professor Oliver Bandmann, Coordinator Emma Davies and co-deputy chairs Professors Camille Carroll and Tom Foltynie.

The UK-PD-CSG regular, virtual meetings provide a forum to disseminate research information, opportunities, and resources to enhance the information flow throughout research studies by establishing effective communication streams. The meetings facilitate meaningful discussion and collaboration between researchers, PwP and research organisations.

A strength of the group is the geographical spread of members, with all 18 NIHR Clinical Research Network Regions represented by at least one member. In addition to experienced researchers, the group supports individuals who are new to research to grow the number of research active sites across the UK.

The UK-PD-CSG continues to grow and works to engage more individuals interested in PD, MSA and PSP clinical research. To enable the sustained growth of the clinical trial scene, the UK-PD-CSG plays an integral, strategic role in ensuring the UK maintains and develops a trial-ready workforce and infrastructure to successfully deliver clinical research and provide more research opportunities to PwP.

Website: https://sites.google.com/sheffield.ac.uk/uk-pd-csg

X (Twitter): @UK_PD_CSG

LinkedIn:  UK Parkinson's Disease Clinical Studies Group

Instagram: @UK_PD_CSG

“I would imagine it needed a review…” A qualitative study exploring the experiences of people with dementia and their informal carers of long-term condition reviews in primary care

Introduction

Multimorbidity is common for people with dementia (PWD) and is associated with increased healthcare utilisation and poorer outcomes. Part of the management of long-term conditions (LTCs) occurs through annual LTC reviews conducted in primary care. Little is known about the experiences or needs of people with dementia and informal carers in regard to LTC reviews.

Aim

To explore the experiences of PWD and their informal carers of the review and management of LTCs in primary care.

Method

Qualitative research study, protocol informed by discussion with people with lived experience as an informal carer. Institutional ethical approval (ref ETH2122-1035, University of East Anglia) was granted 25/3/2022. Semi-structured interviews were conducted with PWD and informal carers recruited through Join Dementia Research and local (to Norfolk, UK) charities. Thematic analysis was undertaken with reference to Braun and Clarke (2006).

Results

16 participants were interviewed: two PWD, 10 informal carers and two informal care/PWD dyads. Our findings fall into four main themes: 1) What matters to people; medication optimisation and holistic care 2) What is a review; the diversity of experiences 3) The importance of communication and 4) Preference for shared decision making.

Conclusion

Consideration should be given to ensuring patients and carers are aware when a LTC review will take place and providing an opportunity to be involved, thus allowing shared decision making and patient centred care. Further research into the clinician experience and their views on patients’ needs and how to meet them is required to inform how LTC reviews for people with dementia can be optimised.

Background:

Type 2 Diabetes mellitus (T2DM) is the most common long-term metabolic condition in older people. In the UK, half of all diabetic patients are over 65 and prevalence reaches 10% in over 75s. Lifestyle interventions reduce diabetic complications and can achieve remission, however, there are concerns over the generalisability of these findings to the diabetic population, particularly elderly, complex patients, and those from ethnic minorities. This systematic review quantifies the disparity between diabetes clinical trial cohorts and the UK diabetic population.

Method:

This is a systematic review of UK-based randomised control trials (RCTs) of non-pharmaceutical interventions in adults with T2DM. Data was collected on characteristics of participants included in these studies, including age, sex, ethnicity, socioeconomic status and education of participants.

Results:

Our search strategy identified 5437 results, of which 161 met the criteria for full-text screening. After full-text screening and de-duplication, 80 RCTs were included in our analysis. Of 80 studies, 60% (48/80) reported a mean participant age under 60. Only 40 (50%) reported participant age range; of these the maximum participant age was under 65 in 20% and under 75 in 60%. Where the mean age of participants was over 60, 56% (18/32) restricted participation by comorbidities. Almost all of these precluded anyone with pre-existing CVD (17/18), one third precluded any comorbidities, and 5/18 precluded hypertensive patients. Only 26% of studies reported the ethnicity of participants. These cohorts were not representative of the UK diabetic population, with underrepresentation of Asian ethnic groups in 90% of trials.

Conclusions:

Representation of elderly patients with comorbidities and those belonging to ethnic minority groups is severely limited in UK based T2DM RCTs of lifestyle interventions. Failure to include a representative population in clinical trial cohorts risks guidance that is not generalisable to the UK diabetic population, potentially exacerbating existing health inequities.

Introduction: Digital technologies can play a significant role in addressing care needs of older people. The process of establishing an effective and efficient digital engagement with older people demands multi-sectoral collaboration from various stakeholders including non-governmental organizations. The role non-governmental organizations play in such digital programs, their process of engagement with older people and factors which influence such multi-sectoral collaboration is an under researched area.

Methods: A scoping review was performed to map existing literature on older people’s engagement with digital health technologies delivered through NGOs. The focus was on exploring the factors influencing the process of digital engagement, delineating modes of digital engagement and exploring the caring needs of older people. Multiple databases and grey literature sources were searched to retrieve articles from 2000 till 2023. JBI methodology for scoping reviews was adopted for this review.

Results: Out of 8970 citations, 50 articles (27 original articles, 9 reports, 12 website sources, 1 handbook and 1 research summary) were included in the final review. NGOs engage with older people either directly by delivering the program or indirectly through other program stakeholders through various inter-organizational processes (collaboration, co-ordination, partnership, delegation, sector-wide participation and association). Different types of NGOs (national, regional, provincial and local) were involved in this process of delivering care. Majority of the studies implemented programs through smartphone or tablet based digital applications. Individual factors, organizational factors, technological factors and system-wide factors influence the process of digital engagement between older people and NGOs.

Conclusion: The number of studies included in this scoping review, concerning older people’s engagement with digital health technologies, through NGOs were informative, but limited information was present on the process of engagement. Acknowledgement of NGOs work, and the societal role they play do also indicate that our developing digital societies more or less depend on these organizations.

Introduction: Any Frailty Index (FI) measures overall health. The FI-Lab employs common laboratory data and clinical measures to do so.  

Objective: To examine how an FI-lab constructed from vital signs, laboratory tests, and electrocardiographic data is associated with in-patient admission and time to death. FI-Lab performance was compared with an FI from a Comprehensive Geriatric Assessment (FI-CGA), the Clinical Frailty Scale (CFS), and the Canadian Triage Acuity Scale (CTAS).

Methods: Participants were Emergency Department (ED) patients aged 65+ years referred to Internal Medicine, staffed by a geriatrician (KR). Fifty-seven FI-Lab variables were binarized (0 = no deficit; 1 = deficit) using standard normal ranges. Each FI was calculated as the fraction of items present as deficits. Age- and sex-adjusted Cox proportional hazard and logistic regression models were used to assess relationships with all-cause mortality, and in-patient admission, respectively.  

Results: Of 928 patients, an FI-Lab was calculable in 780. Median age was 81 years (IQR:13); 53.9% were female. FI-Lab values ranged from 0.02–0.78 (mean: 0.42; standard deviation (SD) ±0.10). No significant sex differences were found [females (mean: 0.41±0.11) vs males (0.42±0.09; p=0.067)]. At 30 days, each 0.01 FI-Lab unit increase showed higher mortality hazard rate (HR) (95% confidence interval (CI):1.05 (1.03–1.07) and inpatient admission risk: Odds ratio (OR) 1.02 (1.00–1.04), as did the FI-CGA (1.02; 1.00-1.04) and CTAS (1.20; 0.83-1.75). Similar results held for inpatient admission, same for CTAS (1.18; 0.82-1.72). At one year, only the FI-lab and CFS significantly predicted mortality risk.

Conclusions: FI-Lab scores were associated with higher mortality rates and in-patient admission risk in older ED patients referred to Medicine. In acute care, the FI-Lab appears to integrate baseline frailty with illness severity. As such data often are routinely available, the FI-Lab might be an additional measure of frailty-related risk, potentially available in real time.

Objective

Ageing is associated with reduced vaccine efficacy due to immunosenescence. Severe COVID-19 outcomes are associated with comorbidities prevalent in older people. We report results from the INFORM study on severe COVID-19 outcomes in vaccinated older individuals with varying numbers of comorbidities.

Methods

A retrospective observational cohort study was conducted in England using a 25% random sample from NHS databases. COVID-19-related outcomes (hospitalisations and mortality) in fully vaccinated (≥3 doses) older individuals from 1 Jan to 31 Dec 2022 are reported.

Results

Of a reference population of 7,180,205 fully vaccinated individuals ≥12 years, 2,232,140 were ≥65 years. The proportion of older people with ≥1 COVID-19 hospitalisation increased with age (≥65, 0.6%; ≥70, 0.7%; ≥75, 0.9%; ≥80, 1.2%) compared to overall population (OP, 0.2%). Incidence rates (IR) (95% CI) per 100 person years also increased with age for hospitalisation (≥65, 0.58 [0.57-0.59]; ≥70, 0.71 [0.69-0.73]; ≥75, 0.90 [0.88-0.92]; ≥80, 1.20 [1.18-1.22] versus OP, 0.22 [0.21-0.23]) and death (≥65, 0.16 [0.15-0.17]; ≥70, 0.20 [0.18-0.22]; ≥75, 0.28 [0.26-0.30]; ≥80, 0.42 [0.39-0.45] versus OP, 0.05 [0.04-0.06]).

In those ≥65, 1,375,470 were not immunocompromised (IC) but had ≥1 high-risk comorbidity (no-IC/+Com), 586,155 had neither IC or comorbidity (noIC/noCom). An increased number of comorbidities was associated with increased hospitalisation and death IRs. In those ≥65 noIC/+Com, IRs (95% CI) were 0.63 (0.61-0.65), 0.88 (0.86-0.90) and 1.25 (1.22-1.28) for hospitalisation vs 0.20 (0.17-0.23) in noIC/noCom; and 0.16 (0.14-0.18), 0.23 (0.21-0.25) and 0.32 (0.29-0.09) vs 0.06 (0.03-0.09) for noIC/noCom for death where individuals had ≥1, ≥2 and ≥3 noIC/+Com, respectively.

Conclusions

Despite vaccination, older people are at increased risk for severe COVID-19 outcomes, with higher risk associated with more comorbidities. Even older patients with no-IC conditions have increased risk, especially those with other high-risk comorbidities. Additional interventions may be required to protect older people against severe COVID-19 outcomes.

Introduction:

Multimorbidity is complex and impacts patients' quality of life, health outcomes, and health care utilisation. This project aims to identify multimorbidity patterns and their impact on long-term care admissions in community-dwelling older adults.

Methods:

Multimorbidity was ascertained using primary care data Tū Ora COMPASS Health. Adults aged 65+ (55+ for Māori and Pasifika) were included in the analysis. Aged residential care (ARC) admission was determined from interRAI. Twelve conditions ascertained were hypertension, ischaemia, congestive heart failure, stroke, diabetes, cancer, chronic obstructive pulmonary disease, depression, hypothyroid, osteoporosis, dementia, and neurological diseases. Latent class analyses were completed to identify multimorbidity patterns by ethnicity, i.e., Māori, Pasifika, and nonMāori/non-Pasifika (nMP). For the latter group, analyses were also completed by age groups (<80 years and ≥80 years. Cox-regression models were used to examine the association between multimorbidity patterns and 5-year ARC admission.

Results:

The sample comprises 45,178 older adults: nMP (88%), Māori (8%), and 1,755 Pasifika (4%). The average age for Māori and Pasifika was 65.1, respectively, and nMP was 74.1. We identified three multimorbidity patterns for Māori and Pasifika, and four for nMP (<80 and ≥80). All twelve conditions clustered differently in these samples. Eleven-per-cent Māori were in a 'complex-cluster', and they had a three times higher risk of ARC admission than 'healthier-cluster' [aHR(95%CI): 2.96 (1.81-4.36)]. We did not observe an association between condition clusters and ARC admission risk in the Pasifika sample. In the nM/nP<80y sample, those in 'complex-cluster' (4%) had a 5.5 times higher risk of ARC admission (5.48, 4.68-6.41) than in the 'healthier-cluster'; a similar association was observed in nM/nP≥80y in 'complex-cluster' (8%) when compared to 'healthier-cluster' (4.08, 3.67-4.53).

Conclusions:

Complex clusters were associated with an increased risk of five-year ARC admission. Multimorbidity patterns are helpful for a more strategic approach to managing multimorbidity better in primary care settings.