Scientific Research

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.

Introduction

Older people living with frailty are at high risk of adverse clinical outcomes following emergency laparotomy, including early death, hospital readmission and functional decline. Despite this, there is a paucity of literature exploring patient experience of surgery in this group, particularly following hospital discharge. As a result, there is limited information to guide the development of service delivery models that support optimal post-operative recovery and improve overall experience

Methods Twenty older people, aged ≥65 years, with a Clinical Frailty Scale score of ≥ 4 and who had undergone emergency laparotomy were recruited from eight participating hospital sites. Participants were interviewed at 3 weeks following their surgery, or the earliest convenient date. Semi-structured interviews were undertaken either face to face or via telephone and explored the peri-operative and early recovery experience. Data were analysed using reflexive thematic analysis

Results Participants described physical, psychological, and social implications following emergency laparotomy which extended further than hospital discharge. Recovery was perceived to be an ongoing and slow process of returning to ‘normal self’ however participants displayed resilience towards achieving this by ‘knuckling down’ and ‘pushing forward’. The experience of hospital care was generally positive, but lack of access to discharge advice and community follow up left some participants feeling ‘abandoned’ and uncertain once they returned home. Many were reliant on family support during this period

Conclusions Older people living with frailty experience multifaceted consequences of emergency laparotomy that result in a prolonged recovery period. Multi-disciplinary post-operative care pathways are essential in addressing the holistic care needs of this group following surgery. The provision of robust discharge information and enhanced access to support in the community could improve patient experience and facilitate ongoing recovery at home.

Author names: M Mintun1; C Ritchie2; P Solomon3; JR Sims1; S Salloway4; O Hansson5; LG Apostolova6; JA Zimmer1; CD Evans1; M Lu1; P Ardayfio1; JD Sparks1; AM Wessels1; S Shcherbinin1; H Wang1; ESM Nery1; EC Collins1; EB Dennehy1; DA Brooks1; DM Skovronsky1; TRAILBLAZER-ALZ 2 Investigators; A Farquharson (Non-author presenter)1

Author provenances: 1. Eli Lilly and Company, USA; 2. Scottish Brain Sciences, UK; 3. Boston Center for Memory and Boston University Alzheimer's Disease Center, USA; 4. Departments of Neurology and Psychiatry, Alpert Medical School of Brown University, USA; Butler Hospital, USA; 5. Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden; Memory Clinic, Skåne University Hospital, Sweden; 6. Department of Neurology, Indiana University School of Medicine, USA

Introduction: In TRAILBLAZER-ALZ donanemab (DONA) cleared brain amyloid plaques, significantly slowing disease progression in early symptomatic Alzheimer’s disease (ESAD).

Methods: TRAILBLAZER-ALZ2 enrolled participants with ESAD and amyloid and tau pathology by positron-emission tomography, randomizing (multicenter) those with low/medium-tau (n=1182) and high-tau (n=552) (missing tau n=2). Participants (randomized double-blind,1:1) received DONA (n=860)/placebo (n=876) IV every 4w for 72w. DONA participants meeting amyloid clearance treatment completion criteria at 24/52w had blinded switched to placebo. Primary outcomes: Integrated AD Rating Scale(iADRS) change from baseline at 76w in low/medium-tau or combined (low/medium- and high-tau) populations. Statistical testing allocated most power (80% α spend) to low/medium-tau population outcomes, with the remainder for combined population outcomes, including clinical and biomarker assessments.

Results: In the low/medium-tau population iADRS change at 76w: −6.02 (DONA) and −9.27 (placebo) (difference 3.25; 95%CI, 1.88-4.62; P<.001), 35.1% slowing of disease progression. change in clinical dementia rating scale (cdr)–sum boxes: 1.20 (dona) and 1.88 (placebo) (difference −0.67; 95% ci −0.95 to −0.40; p<0.001), 36.0% slowing. participants receiving dona experienced 38.6% less risk progressing next stage vs placebo over 76w (cdr-global score, hr="0.61;" p<0.001). amyloid clearance at 24 />52/76w: achieved in 34.2%/71.3%/80.1% DONA-treated participants. Significant, positive results were observed in the combined population. Serious AEs: 17.4% (DONA), and 15.8% (placebo), with 3 deaths among DONA patients who experienced serious amyloid-related imaging abnormalities (ARIA). AEs with DONA included ARIA-E (24.0%, 6.1% symptomatic); ARIA-H (31.4%); infusion-related reactions (8.7%).

Conclusion: DONA treatment significantly slowed clinical progression at 76w with a safety profile consistent with earlier studies.

Presented: AAIC2023.

Background

Older people have complex health needs, with the inter-play between physical and mental health being a prominent issue. The ageing population has resulted in a large proportion of older people living with co-occurring physical and mental health disorders, which can prove challenging to manage simultaneously, particularly for serious mental illness. The aim of this systematic review was to explore models of integrated physical-mental health care available for older people, and whether these result in improved health outcomes. Sources of heterogeneity in the current evidence base alongside limitations were also explored.

Methods

Medline, Embase, CINAHL, PsycINFO and Scopus were searched with a predefined search strategy, generating 5257 articles. Studies were suitable for inclusion where an integrated physical-mental health care service model was utilised in a population of older people (aged >60 years) with a mental health diagnosis and at least one concomitant physical health condition requiring physical health care input. All studies were quality assessed for risk of bias and results were synthesised narratively.

Results

Nine studies met the inclusion criteria. All studies incorporated service models involving integrated and/or multidisciplinary care. These included joint medical-mental health wards as well as the implementation of multidisciplinary teams in hospital and care facilities. Overall, this enhanced the quality of care for elderly patients with benefits including but not limited to, enhanced patient experience, the expansion of multidisciplinary team practice, improved management of illness, and timely intervention.

Conclusions

Multidisciplinary and integrated care resulted in improvement of a range of health outcomes for older people with combined physical and mental health needs. Larger and more robust studies are needed to explore the development of these service models further, with cost-effectiveness analyses.

Introduction: Optimal intrinsic capacity (IC) is crucial for preserving the functional abilities of older adults. The presence of multimorbidity is closely associated with IC impairments. Various multimorbidity indices have been developed for diverse health outcomes. This study aimed to compare the performance of six commonly used multimorbidity indices to discriminate IC impairments among community-dwelling older adults.

Method: We used data from a multidimensional geriatric assessment program including 627 community-dwelling older adults in five cities of Hunan, China. Six multimorbidity indices were extracted from the data, including disease counts, Functional Comorbidity Index (FCI), the Deyo Charlson comorbidity index, two indices (total score and comorbidity index) derived from the Cumulative Illness Rating Scale-Geriatric (CIRS-G), and medication counts. The IC was measured with five individual domains, i.e., locomotion, vitality, sensory, cognition, and psychological capacity. Individuals were regarded as having IC impairments if they had impairments in one or more domains. Associations between multimorbidity indices and IC impairments were examined using logistic regression analyses. The discriminative ability of multimorbidity indices for IC impairments was compared using the c-statistics.

Results: A total of 374 (59.6%) participants had IC impairments. All multimorbidity indices were significantly associated with IC impairments after adjusting for confounding factors. All indices showed acceptable discriminative power (c-statistic ranged from 0.711 to 0.759) for IC impairments. The comorbidity index derived from CIRS-G resulted in the highest c-statistic, followed by the total score of CIRS-G and FCI.

Conclusions: Our study results suggest that multimorbidity indices differed in their ability to discriminate IC impairments. The comorbidity index derived from CIRS-G performed better than other multimorbidity indices included in this study. The comorbidity index has the potential as a simple proxy measure of indicating the need for interventions to optimise IC for older adults in community settings.

Background: Care home residents form a large number of admissions to Emergency Departments (ED) across the UK. Over an 8-month period we reviewed care home admissions to ED to provide further insight on these admission types and identify ways to improve care.

Method: All patients with a frailty score of 6 or more admitted from care homes to Chelsea and Westminster Hospital ED between 1^st June 2022 and to 31^st January 2023 were included. Data was collected from the hospital computer system and London Ambulance Service (LAS) attendance sheets. Information collected included; care home the patient resided at, LAS attendance times at scene, if discussion with a Health Care Professional (HCP) prior to attendance had occurred, Presenting Complaint (PC) and Length Of Stay (LOS). We then sub-categorised data accordingly.

Results: There were 180 patient admissions from 34 care homes. 34% (N=61) of LAS attendances occurred during normal working hours (9am-5pm Monday- Friday) with only 43% (N=26) of patients being discussed with an HCP prior to admission. Of these, 30% (N=18) were discharged <24hrs and subjectively 39% (N=7) did not require ED admission. Out of hours (OOH) attendances formed 66% of admissions, with most common PC being fall (33%, N=59) followed by respiratory issues (22%, N=38). Overall admissions accounted for 454 bed stay days.

Conclusion: Discussing patient’s with an HCP prior to contacting LAS would reduce ED admissions alongside accessing rapid response team more frequently. Expanding an HCP accessible service OOH would be necessary to facilitate this and implementing a frailty telephone service from Chelsea and Westminster may be one solution. Focusing on individual care homes and working with community teams form the next steps in this review.  

Introduction

Verbal autopsy (VA) is a tool used to determine cause of death (COD) in regions lacking routine medical certification. Automated algorithms are widely used to interpret VA data. This study aimed to investigate potential differences in COD between frail and non-frail older people in northern Tanzania.

Method

This work forms part of a longitudinal study investigating the clinical outcomes of 308 consecutive adults aged ≥60 years following admission to four hospitals in northern Tanzania. Frailty status was established on admission using the Clinical Frailty Scale (CFS) and dichotomised with CFS ≥5 indicating frailty. For participants who passed away in the 10-12 months following admission, VA data were collected through telephone interview using the 2022 World Health Organization (WHO) VA instrument. COD estimates were established using the SmartVA-Analyze program, implementing the Tariff 2.0 Method.

Results

After a mean follow-up period of 10.8 (±0.9) months, VA data were available for 69 participants. At admission screening, 51 (73.9%) were frail, while 18 (26.1%) were non-frail. SmartVA produced COD estimates for 42 (60.9%) participants, while 27 (39.1%) remained undetermined. Cause Specific Mortality Fractions (CSMFs) for non-communicable disease were higher for those with frailty than the non-frail group (70.6% vs. 54.0%, respectively). An undetermined COD was more likely in those with frailty. Of the 27 undetermined COD, 22 (81.5%) were attributed to frail individuals and 5 (18.5%) to non-frail. These undetermined COD represent 43.1% of frailty-related deaths and 27.8% of non-frailty-related deaths.

Conclusions

Older people with frailty living in Tanzania are more likely to die from non-communicable diseases compared to non-frail older people. Although employing SmartVA to analyse VA data from this population was feasible, it faced challenges ascribing COD to all participants. This limitation may be due to the multi-morbidity often present in older populations where multiple factors combine to cause mortality.