The LAST word on coaching as a stroke intervention?

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An exploration of treatment burden and patient capacity in people with stroke

Background and aims: Advances in modern medicine have led to improved outcomes after stroke, yet an increased treatment burden has been placed on patients. Treatment burden is the workload of health care for people with chronic illness and the impact that this has on functioning and well-being. Those with comorbidities are likely to be particularly burdened. Excessive treatment burden can negatively affect outcomes. Individuals are likely to differ in their ability to manage health problems and follow treatments, defined as patient capacity. The aim of this thesis was to explore the experience of treatment burden for people who have had a stroke and the factors that influence patient capacity. Methods: There were four phases of research. 1) A systematic review of the qualitative literature that explored the experience of treatment burden for those with stroke. Data were analysed using framework synthesis, underpinned by Normalisation Process Theory (NPT). 2) A cross-sectional study of 1,424,378 participants >18 years, demographically representative of the Scottish population. Binary logistic regression was used to analyse the relationship between stroke and the presence of comorbidities and prescribed medications. 3) Interviews with twenty-nine individuals with stroke, fifteen analysed by framework analysis underpinned by NPT and fourteen by thematic analysis. The experience of treatment burden was explored in depth along with factors that influence patient capacity. 4) Integration of findings in order to create a conceptual model of treatment burden and patient capacity in stroke. Results: Phase 1) A taxonomy of treatment burden in stroke was created. The following broad areas of treatment burden were identified: making sense of stroke management and planning care; interacting with others including health professionals, family and other stroke patients; enacting management strategies; and reflecting on management. Phase 2) 35,690 people (2.5%) had a diagnosis of stroke and of the 39 co-morbidities examined, 35 were significantly more common in those with stroke. The proportion of those with stroke that had >1 additional morbidities present (94.2%) was almost twice that of controls (48%) (odds ratio (OR) adjusted for age, gender and socioeconomic deprivation; 95% confidence interval: 5.18; 4.95-5.43) and 34.5% had 4-6 comorbidities compared to 7.2% of controls (8.59; 8.17-9.04). In the stroke group, 12.6% of people had a record of >11 repeat prescriptions compared to only 1.5% of the control group (OR adjusted for age, gender, deprivation and morbidity count: 15.84; 14.86-16.88). Phase 3) The taxonomy of treatment burden from Phase 1 was verified and expanded. Additionally, treatment burdens were identified as arising from either: the workload of healthcare; or the endurance of care deficiencies. A taxonomy of patient capacity was created. Six factors were identified that influence patient capacity: personal attributes and skills; physical and cognitive abilities; support network; financial status; life workload, and environment. A conceptual model of treatment burden was created. Healthcare workload and the presence of care deficiencies can influence and be influenced by patient capacity. The quality and configuration of health and social care services influences healthcare workload, care deficiencies and patient capacity. Conclusions: This thesis provides important insights into the considerable treatment burden experienced by people who have had a stroke and the factors that affect their capacity to manage health. Multimorbidity and polypharmacy are common in those with stroke and levels of these are high. Findings have important implications for the design of clinical guidelines and healthcare delivery, for example co-ordination of care should be improved, shared decision-making enhanced, and patients better supported following discharge from hospital

Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants

Background: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. Objective: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). Design: Data were obtained from an anonymized community cohort aged 40–72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. Results: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. Conclusions: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke

What helps and hinders the provision of healthcare that minimises treatment burden and maximises patient capacity? A qualitative study of stroke health professional perspectives

OBJECTIVES: Treatment burden is the healthcare workload experienced by individuals with long-term conditions and the impact on well-being. Excessive treatment burden can negatively affect quality-of-life and adherence to treatments. Patient capacity is the ability of an individual to manage their life and health problems and is dependent on a variety of physical, psychological and social factors. Previous work has suggested that stroke survivors experience considerable treatment burden and limitations on their capacity to manage their health. We aimed to examine the potential barriers and enablers to minimising treatment burden and maximising patient capacity faced by health professionals and managers providing care to those affected by stroke. SETTING: Primary and secondary care stroke services in a single health board area in Scotland. PARTICIPANTS: Face-to-face qualitative interviews with 21 participants including stroke consultants, nurses, physiotherapists, occupational therapists, speech and language therapists, psychologists, general practitioners and health-service managers. OUTCOME MEASURES: Data were analysed using thematic analysis to ascertain any factors that influence the provision of low-burden healthcare. RESULTS: Barriers and facilitators to the provision of healthcare that minimises treatment burden and maximises patient capacity were reported under five themes: healthcare system structure (e.g. care coordination and autonomous working); resources (e.g. availability of ward nurses and community psychologists); knowledge and awareness (e.g. adequate time and materials for optimal information delivery); availability of social care (e.g. waiting times for home adaptations or extra social support) and patient complexity (e.g. multimorbidity). CONCLUSIONS: Our findings have important implications for the design and implementation of stroke care pathways, emphasising the importance of removing barriers to health professional provision of person-centred care. This work can inform the design of interventions aimed at nurturing autonomous working by health professionals, improving communication and care coordination or ensuring availability of a named person throughout the patient journey

Acute care assessment of older adults living with frailty

No abstract available

Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort

Aims: To examine the number and type of co-morbid long-term health conditions (LTCs) and their associations with all-cause mortality in an atrial fibrillation (AF) population. Methods and results: Community cohort participants (UK Biobank n = 502 637) aged 37–73 years were recruited between 2006 and 2010. Self-reported LTCs (n = 42) identified in people with AF at baseline. All-cause mortality was available for a median follow-up of 7 years (interquartile range 76–93 months). Hazard ratios (HRs) examined associations between number and type of co-morbid LTC and all-cause mortality, adjusting for age, sex, socio-economic status, smoking, and anticoagulation status. Three thousand six hundred fifty-one participants (0.7% of the study population) reported AF; mean age was 61.9 years. The all-cause mortality rate was 6.7% (248 participants) at 7 years. Atrial fibrillation participants with ≥4 co-morbidities had a six-fold higher risk of mortality compared to participants without any LTC. Co-morbid heart failure was associated with higher risk of mortality [HR 2.96, 95% confidence interval (CI) 1.83–4.80], whereas the presence of co-morbid stroke did not have a significant association. Among non-cardiometabolic conditions, presence of chronic obstructive pulmonary disease (HR 3.31, 95% CI 2.14–5.11) and osteoporosis (HR 3.13, 95% CI 1.63–6.01) was associated with a higher risk of mortality. Conclusion: Survival in middle-aged to older individuals with self-reported AF is strongly correlated with level of multimorbidity. This group should be targeted for interventions to optimize their management, which in turn may potentially reduce the impact of their co-morbidities on survival. Future AF clinical guidelines need to place greater emphasis on the issue of co-morbidity

Multimorbidity in stroke

No abstract available

Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants

Background: Multimorbidity is common in stroke, but the risk factors and effects on mortality remain poorly understood. Objective: To examine multimorbidity and its associations with sociodemographic/lifestyle risk factors and all-cause mortality in UK Biobank participants with stroke or transient ischaemic attack (TIA). Design: Data were obtained from an anonymized community cohort aged 40–72 years. Overall, 42 comorbidities were self-reported by those with stroke or TIA. Relative risk ratios demonstrated associations between participant characteristics and number of comorbidities. Hazard ratios demonstrated associations between the number and type of comorbidities and all-cause mortality. Results were adjusted for age, sex, socioeconomic status, smoking, and alcohol intake. Data were linked to national mortality data. Median follow-up was 7 years. Results: Of 8,751 participants (mean age 60.9±6.7 years) with stroke or TIA, the all-cause mortality rate over 7 years was 8.4%. Over 85% reported ≥1 comorbidities. Age, socioeconomic deprivation, smoking and less frequent alcohol intake were associated with higher levels of multimorbidity. Increasing multimorbidity was associated with higher all-cause mortality. Mortality risk was double for those with ≥5 comorbidities compared to those with none. Having cancer, coronary heart disease, diabetes, or chronic obstructive pulmonary disease significantly increased mortality risk. Presence of any cardiometabolic comorbidity significantly increased mortality risk, as did any non-cardiometabolic comorbidity. Conclusions: In stroke survivors, the number of comorbidities may be a more helpful predictor of mortality than type of condition. Stroke guidelines should take greater account of comorbidities, and interventions are needed that improve outcomes for people with multimorbidity and stroke

Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank Cohort

Background: Multimorbidity is associated with higher mortality, but the relationship with cancer and cardiovascular mortality is unclear. The influence of demographics and type of condition on the relationship of multimorbidity with mortality remains unknown. We examine the relationship between multimorbidity (number/type) and cause of mortality and the impact of demographic factors on this relationship. Methods: Data source: the UK Biobank; 500,769 participants; 37-73 years; 53.7% female. Exposure variables: number and type of long-term conditions (LTCs) (N = 43) at baseline, modelled separately. Cox regression models were used to study the impact of LTCs on all-cause/vascular/cancer mortality during median 7-year follow-up. All-cause mortality regression models were stratified by age/sex/socioeconomic status. Results: All-cause mortality is 2.9% (14,348 participants). Of all deaths, 8350 (58.2%) were cancer deaths and 2985 (20.8%) vascular deaths. Dose-response relationship is observed between the increasing number of LTCs and all-cause/cancer/vascular mortality. A strong association is observed between cardiometabolic multimorbidity and all three clinical outcomes; non-cardiometabolic multimorbidity (excluding cancer) is associated with all-cause/vascular mortality. All-cause mortality risk for those with ≥ 4 LTCs was nearly 3 times higher than those with no LTCs (HR 2.79, CI 2.61–2.98); for ≥ 4 cardiometabolic conditions, it was > 3 times higher (HR 3.20, CI 2.56–4.00); and for ≥ 4 non-cardiometabolic conditions (excluding cancer), it was 50% more (HR 1.50, CI 1.36–1.67). For those with ≥ 4 LTCs, morbidity combinations that included cardiometabolic conditions, chronic kidney disease, cancer, epilepsy, chronic obstructive pulmonary disease, depression, osteoporosis and connective tissue disorders had the greatest impact on all-cause mortality. In the stratified model by age/sex, absolute all-cause mortality was higher among the 60–73 age group with an increasing number of LTCs; however, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those 37–49 years, especially men. While socioeconomic status was a significant predictor of all-cause mortality, mortality risk with increasing number of LTCs remained constant across different socioeconomic gradients. Conclusions: Multimorbidity is associated with higher all-cause/cancer/vascular mortality. Type, as opposed to number, of LTCs may have an important role in understanding the relationship between multimorbidity and mortality. Multimorbidity had a greater relative impact on all-cause mortality in middle-aged as opposed to older populations, particularly males, which deserves exploration

Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study

Objective: This study aims: (1) to describe the pattern and extent of multimorbidity and polypharmacy in UK Biobank participants with chronic obstructive pulmonary disease (COPD) and (2) to identify which comorbidities are associated with increased risk of adverse drug reactions (ADRs) resulting from polypharmacy. Design: Cross-sectional. Setting: Community cohort. Participants: UK Biobank participants comparing self-reported COPD (n=8317) with no COPD (n=494 323). Outcomes: Multimorbidity (≥4 conditions) and polypharmacy (≥5 medications) in participants with COPD versus those without. Risk of ADRs (taking ≥3 medications associated with falls, constipation, urinary retention, central nervous system (CNS) depression, bleeding or renal injury) in relation to the presence of COPD and individual comorbidities. Results: Multimorbidity was more common in participants with COPD than those without (17% vs 4%). Polypharmacy was highly prevalent (52% with COPD taking ≥5 medications vs 18% in those without COPD). Adjusting for age, sex and socioeconomic status, those with COPD were significantly more likely than those without to be prescribed ≥3 medications contributing to falls (OR 2.27, 95% CI 2.13 to 2.42), constipation (OR 3.42, 95% CI 3.10 to 3.77), urinary retention (OR 3.38, 95% CI 2.94 to 3.87), CNS depression (OR 3.75, 95% CI 3.31 to 4.25), bleeding (OR 4.61, 95% CI 3.35 to 6.19) and renal injury (OR 2.22, 95% CI 1.86 to 2.62). Concomitant cardiovascular disease was associated with the greatest risk of taking ≥3 medications associated with falls/renal injury. Concomitant mental health conditions were most strongly associated with medications linked with CNS depression/urinary retention/bleeding. Conclusions: Multimorbidity is common in COPD and associated with high levels of polypharmacy. Co-prescription of drugs with various ADRs is common. Future research should examine the effects on healthcare outcomes of co-prescribing multiple drugs with similar potential ADRs. Clinical guidelines should emphasise assessment of multimorbidity and ADR risk