Scientific Research

Abstract

Introduction:

Chronic pain is associated with frailty. We hypothesised that painful comorbidities would be more strongly associated with frailty than non-painful comorbidities.

Method:

Data were from Investigating Musculoskeletal Health and Wellbeing, a UK-based cohort of people with or at risk of musculoskeletal problems or frailty. Average pain over the previous month was assessed using an 11-point numerical rating scale (NRS). The original FRAIL questionnaire comprises five self-report items: Fatigue, Resistance, Ambulation, Illnesses and Loss of weight. In this study, risk of frailty was operationalised using a modified FRAIL questionnaire, omitting the “illnesses” item which related to comorbidities. Comorbidities were classified as either ‘painful’ or ‘non-painful’ based on the International Association for the Study of Pain chronic pain classification criteria. Ordinal logistic regression models explored associations of comorbidity counts with frailty.

Results:

Cross-sectional data were from 2473 participants, 57% female, median age 72 (range 40 to 96) years. 518 (21%) participants were classified as frail. Mean (SD) pain score was 5.5 (2.5). Median (IQR) painful comorbidities was 2 (1 to 3) and non-painful 1 (0 to 2). Highest comorbidity frequency: arthritis (66%) and hypertension (38%). Pain was associated with frailty (OR 1.52 (1.45 to 1.58)). Painful comorbidities (aOR 1.64 (1.54 to 1.75) and non-painful comorbidities (aOR 1.31 (1.21 to 1.41)) were both associated with frailty when included in the same multivariable model adjusted for age, sex and BMI.

Conclusions:

Painful comorbidities were most strongly associated with frailty, although non-painful comorbidities also contributed. Pain and frailty are interconnected, and this might, in part, be due to comorbidities or their treatments. These findings provide justification for further research to identify the mechanisms through which pain is involved in frailty and to include pain management in interventions to ameliorate frailty.

Introduction: Resilient ageing is conceptualised as strive towards achieving satisfactory quality of life (QoL) at old age by embracing positive adaptation and coping mechanisms against adversities regardless of health conditions. Preventive Home Visit (PHV) including various types of home-care interventions were introduced to delay health deterioration and improved QoL. However, research related to resilience as an outcome measured for PHV is scarce. Therefore, this systematic review aims to evaluate the effectiveness of PHV in improving resilience among community dwelling older adults and the association with health and other QoL related outcomes.

Method: Database search was conducted by using five databases (PubMed, PsycINFO, CINAHL, Web of Science and Scopus) up to 31 March 2022 involving community dwelling older adults who received PHV. Three authors reviewed the articles for inclusion and performed methodological quality assessment.

Results: Out of 1,568 records, 14 articles involving 7,254 participants met the inclusion criteria with age range between 79 to 85 years old. Quality assessment by using Joanna Briggs Institute (JBI) Critical Appraisal Tools indicated that all articles were assessed as moderate to high quality and were included in the review. More than two third of the studies focused on health or combination of health and QoL and only three studies revealed positive effect of PHV. The remainder were either produced mixed results or had no effect following the intervention. There was only one study examined resilience. However, no significant effect of PHV was reported based on this study.

Conclusion: Based on this current review, there were mixed results of PHV effectiveness. Due to the paucity of research in this area, there is no conclusive evidence of the effectiveness of PHV in enhancing resilience in older adults. Since there has not been any research on PHV and resilience done in Low-middle Income Countries (LMICs), it is necessary to fulfil this gap. Future research should concentrate on developing more robust and holistic PHV interventions that involve resilience in addition to QoL and multi-domain health-related outcomes.

Introduction

In 2017 NHS England introduced proactive identification of frailty into the General Practitioners (GPs) Contract. There is currently little information as to how this policy has been operationalised by front-line clinicians, their working understanding of frailty, or perceptions of impact on patient care. Evidence from international settings suggests primary care clinicians may have mixed interpretations of frailty, with important implications for their willingness to support different frailty interventions. We aimed to explore the conceptualisation of frailty, and how community-dwelling frail older adults are identified in primary care.

Methods

Semi-structured interviews were conducted with primary care staff across England, including GPs, physician associates, nurse practitioners, paramedics and pharmacists. Thematic analysis was facilitated through NVivo (Version 12).

Results 31 practitioners participated (12 GPs, 19 non-GPs). Frailty was seen as difficult to define, with uncertainty in its value as a medical diagnosis. The most common working model was the frailty phenotype, associated with deterioration at end of life. There were a mixture of formal and informal processes for identifying frailty. A few practices had embedded population screening and structured reviews. Informal processes included use of ‘housebound’ as a proxy for frailty, identification through chronic disease and medication reviews, and holistic assessment through good continuity of care. Many clinicians described poor accuracy of the electronic Frailty Index, yet it was commonly used to grade frailty during protocolised chronic disease reviews. The Clinical Frailty Score, in contrast, was felt to be easy to use and interpret, but inconsistently recorded within electronic health records. Most clinicians favoured better tools for identifying frailty, alongside resources to support these individuals.

Conclusions

Concepts of frailty in primary care differ. Identification is predominantly ad-hoc, opportunistic and associated with terminal illness. A more cohesive approach to frailty, relevant to primary care, together with better diagnostic tools, may encourage wider recognition.

Introduction:

Major trauma including Traumatic Brain Injury (TBI) is an increasingly common cause of hospitalisation in older adults. We studied post-discharge recovery from TBI using a remote healthcare monitoring system that captures data on activity and sleep. We aim to assess the feasibility and acceptability of this technology to monitor recovery at home following a significant acute clinical event in Older adults.

Methods:

We installed Minder, a remote healthcare monitoring system, in recently discharged patients >60 years with moderate-severe TBI. We present descriptive analyses of post-discharge recovery for two males, corroborating data from Minder against verified activities and events. We recorded semi-structured interviews assessing acceptability.

Results:

We present 6 months of sleep and activity data from Minder and feedback from interviews. Data observed from Participant 1 revealed habitual patterns of activity and sleep. These remained stable, despite discrete clinical events. Conversely, Participant 2's data revealed irregular sleep patterns that became increasingly fragmented. Activity was detected in multiple rooms throughout the house at night, consistent with carer reports of night-time wandering. Increased overnight activity coincided with multiple falls, prompting increased care provision. Initial feedback from interviews was the technology helped participants and those involved in their care feel supported.

Conclusions:

As pressure on services mounts, novel approaches to post-discharge care are of increasing importance. Remote healthcare monitoring can provide high temporal resolution data offering ‘real world’ insights into the effects of significant health events in Older adults. Our provisional results support our hypothesis that use of this technology is feasible and acceptable for frail, multi-morbid participants and highlights the substantial potential of this technology to help clinicians improve community-based care and more effectively monitor interventions and chronic conditions.

Introduction:

Co-morbidities and frailty are common in older heart failure patients. The aim of this study is to explore the relationship between co-morbidity, frailty and ejection fraction (EF) in older heart failure inpatients.

Methods:

A cross-sectional, observational, retrospective analysis of consecutive patients aged 60 years and over who were admitted with heart failure in a UK hospital. Patients with incomplete data were excluded. Carlson’s comorbidity index (CCI) was used to compute comorbidity, and the Rockwood Clinical Frailty Scale (CFS) was used to measure frailty. The EF was calculated as the midpoint of the ranges measured by echocardiography. IBM SPSS 28 software was used for statistical analysis. Descriptive statistics were used to measure baseline characteristics, and Pearson’s correlation coefficient and linear regression were used to calculate the correlation.

Results and discussion:

101 patients were analysed; 48 males and 53 females. The mean age was 81.2 years (SD 9.98). The mean CCI was 6.97 (SD 1.63), and the mean CFS was 5.09 (SD 1.14).

There was a statistically significant positive correlation between CCI and CFS (r= 0.232; p= .01).

There was a statistically significant inverse correlation between CCI and EF (r= -.277; p=. 005).

When taking into account the level of frailty, the correlation between CCI and EF was much stronger in non-frail than in frail patients (r= -.612; p=. 035 and r= -.216; p= .047, respectively).

There was no correlation between CFS and EF (r= .095; p=.26).

Conclusion:

There was a positive correlation between multi-morbidity and frailty in older inpatients admitted with heart failure. There was a statistically significant inverse correlation between CCI and ejection fraction, but there was no correlation between frailty and ejection fraction.

Introduction

Frailty is a syndrome associated with increasing numbers of elderly hospital admissions and prolonged inpatient stays (Archibald et al, Geriatrics, 2020, 20, 17). In 2015, an estimated 14% of inpatients in the UK were considered to have a degree of frailty, representing an approximate annual cost to the NHS of £5.8 billion (Soong et al, BMJ Open, 2015, 5, e008456; Han et al, Age and Aging, 2019, 48, 665-671). Frailty is poorly defined; there are discrepancies in existing literature on how to best quantify frailty. It is recognised there is a higher risk of adverse outcomes in this vulnerable population due to lack of physiological reserve (Clegg et al, The Lancet, 2013, 381, 752-762). The Hospital Frailty Risk Score (HFRS) is a recent development to measure frailty and identify patients at risk (Gilbert et al, The Lancet, 2018, 391, 1775-1782). This study sought to establish whether the HFRS could be used in patients with degenerative spinal disease, undergoing decompression surgery, to predict post-operative outcomes. 

Methods

A retrospective service evaluation of eligible patients in Leeds Teaching Hospitals Trust between March 2018 - March 2020. The exposure was the patients’ HFRS; the outcome was the length of stay (LOS) until physiotherapy discharge. Data was sourced from electronic records.

Results

214 patients were identified with an available HFRS value. Patients were categorised as low, intermediate or high frailty. Kruskal-Wallis test for LOS and categorical HFRS: X² =8.673, p<0.05. The median HFRS value was 1.25 (interquartile range 0.00 to 3.35). Mann-Whitney U test for LOS and numerical HFRS: W=29297, p<0.05. 

Conclusions

The results of this study complement pre-existing studies of similar natures, evaluating frailty scoring and post-operative outcomes. Thus supporting the potential for standardised use of HFRS alongside holistic patient examination to streamline pre-assessment, improve outcomes and reduce the NHS frailty burden. 

Introduction

Diagnosis of Transient Ischaemic Attack [TIA] is important to minimise risk of future strokes. This retrospective descriptive study aimed to describe frequency of alternative diagnoses in a busy inner-city neurovascular clinic and evaluate processes of assessment and investigations of ‘true’ TIA patients.

Methods

Data was obtained over a 2-year period [2019-2020] for all new patients assessed in a busy consultant-provided daily week-day neurovascular service that serves a million multi-ethnic, population. Data collected included socio-demographic details, final clinical diagnoses, and process measures including speed of assessment and rate of neurological and cardiological investigations.

Results

Of 1764 patients, 39.3% [694] were diagnosed as TIA; 60.7% [1070] had 40 distinct differential diagnoses. Top ten diagnoses included migraine including ocular migraine [9.5%], Syncope [5.5%], Local Eye conditions (non-neurological)[5.3%], non-cervical radiculopathy [4.0%], Benign Paroxysmal Positional Vertigo [4.0%], Previous/Incidental Stroke [3.7%], Transient Global Amnesia [2.4%], Orthostatic Hypotension [1.8%], Non-migraine Headache syndromes [1.6%], Cervical Neuropathy [1.3%]. 10.9%[193] had no organic pathological diagnosis. For 694 TIA patients, 100% had neuroimaging [CT/MRI] and 98% had carotid dopplers on or before day of clinic. Non-urgent cardiovascular investigations performed included echocardiogram [83%], Holter monitoring [75%] and bubble echocardiogram [5%].

Discussion

This large survey has described the frequency of TIA and alternative diagnoses in a dedicated neurovascular service. The study highlights the importance of accurate diagnosis of TIA by experienced clinicians for appropriate secondary prevention. We also described the efficiency, and speed of assessment and proportion of investigations undertaken in these patients. This study provides valuable information to clinicians, researchers and commissioners of stroke services in future.

Introduction: Poor muscle health is associated with a series of chronic and metabolic conditions that are prevalent in individuals who chronically experience poor-quality sleep. But there is no study deciphering the role of sleep deprivation on muscle ageing. Therefore, in the present study we have measured the ultrastructure, histopathology, and oxidative stressors in soleus muscle of wistar rat after sleep deprivation and recovery sleep.

Material and Methods: The experiments were conducted in18 rats of three groups. Group I rats had normal sleep wake cycle, Group II rats were subjected to 24 h sleep deprivation (SD) by gentle handling method1 and Group III rats had recovery sleep after 24 h SD. At the end of the sleep, sleep deprivation and recovery period, soleus muscle tissue was collected for ultrastructural, histological and oxidative stress markers. Oxidative damage was assessed by lipid peroxidation, catalase activity, reduced glutathione and nuclear labelling of 8-OHdG. The study was conducted as per the guidelines of the Institutional Animal Ethics Committee (960/IAEC/16).

Results: The data demonstrated that SD leads to ultrastructural changes in soleus muscle which includes sarcolemmal and mitochondrial alterations. In case of histopathological and histomorphological changes there was signs of tissue degeneration, inflammatory infiltrate in type I fibers and muscle atrophy was observed in soleus muscles. There was significant increase in level of 8-OHdG (p=0.02) and malondialdehyde in 24h SD (p=0.02) than control and recovery sleep groups. Moreover, the catalase activity and reduced glutathione level was significantly decreased in 24h SD group (p≤0.02) than control and recovery sleep.

Conclusion: 24hr sleep deprivation leads to an ageing like state in the skeletal muscle, which was recovered after sleep rebound.

Introduction

Patients with frailty who have emergency admissions are at risk of mortality and may benefit from Anticipatory Care Planning (ACP). Appropriate identification, to target limited resource in an in-patient environment can be challenging. We conducted a prospective study on a cohort of frail in-patients with a hospital admission of ≥ 72 hours duration.  We aimed to evaluate the effectiveness of the SPICT tool alongside Clinical Frailty Score (CFS) as a predictor of mortality to improve our targeting of patients for ACP.

Method.

On a single day a SPICT form was completed prospectively for each inpatient on 3 hospital inpatient wards (Complex Frailty Unit, General/Orthopaedic Rehabilitation, Step-Down Unit).  Patients were deemed SPICT positive if they scored on ≥ 2 General Indicators and ≥ 2 Clinical Indicators. CFS was also recorded. Electronic records of this patient cohort were followed up for 9 months.

Results

Of 66 inpatients, 58 (87.9%) were aged ≥ 65 years and had a CFS ≥ 4. Mode CFS value = 6 (23 patients, 39.7%).  32 (55.2%) were SPICT positive; 26 (44.8%) SPICT negative.  At 3 months follow-up SPICT had Positive Predictive Value (PPV) 40.6% and Negative Predictive Value (NPV) 84.6% for mortality. At 6 months PPV = 56.3%; NPV = 80.8%. At 9 months PPV = 59.4%; NPV = 76.9%.  SPICT negative patients with CFS 6 had mortality risk of 14.3% at 3, 6 and 9 months follow-up respectively.  SPICT positive patients with CFS 6 had mortality risks of 50% at 3 months and 62.5% at 6 and 9 months.

Conclusion

SPICT is a predictor of mortality in patients with frailty during unplanned admissions to hospital of ≥ 72 hours duration.  It is now used alongside CFS for all patients admitted to our Complex Frailty Unit, identifying patients most likely to benefit from inpatient ACP on discharge.

Introduction:

Many commonly prescribed medications have inadvertent anticholinergic effects. People living with Dementia (PLWD) are vulnerable to these effects and at risk of adverse outcomes, the risk being higher with greater anticholinergic exposure. We investigated prescribing patterns and anticholinergic burden (ACB) in a cohort of community-dwelling PLWD and explored the effect of ACB on cognition, neuropsychiatric symptoms, quality of life (QoL), and functional independence.

Method:

The medication and demographic information for 87 (39 female) community-dwelling PLWD were obtained from Electronic Care Summaries. We used the German Anticholinergic Burden Scale (GABS) to measure ACB. Additionally, we investigated associations between ACB and cognitive(ADAS-Cog), functional(BADL), neuropsychiatric (NPI) and QoL(DemQoL) assessments.

Results:

28.7% of participants had a clinically significant score (ACB> 2). The most commonly prescribed medications with ACB were Lansoprazole(18.3%), Mirtazapine(12.6%) and Codeine(12.6%). ACB was higher in males and negatively correlated with age, r(87)=-.21,p=.03. There was no association between ACB and cognition, QoL, functional independence, and neuropsychiatric symptoms. Over six months, PLWD with no ACB had a greater negative change in neuropsychiatric symptoms[t(18)=2.27,p=.04] and functional independence[t(23)=-3.8,p=.001], indicating greater dependence and worsening neuropsychiatric symptoms.

Conclusion:

A third of PLWD in the community had clinically significant ACB. No ACB was associated with worsening neuropsychiatric symptoms and functional dependence over a six-month period. Community prescribers should consider regular medication reviews with PLWD and carers to ensure medications are prescribed safely and appropriately.