85 research outputs found
Acceptability of mindfulness from the perspective of stroke survivors and caregivers: a qualitative study
Background:
Depression is very common among stroke survivors with estimated prevalence rates of approximately 33% among stroke survivors, but treatment options are limited. Mindfulness-Based Stress Reduction (MBSR) is an effective treatment for depression generally, but benefits in stroke patients are unclear. The aim of this study was to determine the feasibility of delivering MBSR to stroke survivors and their caregivers in the community. We conducted a study to gain views of MBSR as a potential treatment option among stroke survivors and their caregivers in the community.
Methods:
Participants were recruited from an urban community in Scotland (UK) using newspaper adverts, social media and support groups run by health charities. A 2-h MBSR taster session was delivered by two experienced mindfulness instructors, followed by focus group sessions with all participants on their user experience and suggestions for MBSR modifications for stroke survivors. The focus group sessions were audio recorded and transcribed verbatim. Transcript data were analysed thematically using the framework approach.
Results:
The study sample consisted of 28 participants (16 females); there were 21 stroke survivors (11 females) and 7 caregivers (5 females). The median age for participants was 60 years.
Most participants described the MBSR taster session as a positive experience. The main challenge reported was trying to maintain focus and concentration throughout the MBSR session. Some participants expressed reservations about the duration of standard mindfulness course sessions, suggesting a preference for shorter sessions. The potential for achieving better control over negative thoughts and emotions was viewed as a potential facilitator for future MBSR participation. Participants suggested having an orientation session prior to starting an 8-week course as a means of developing familiarity with the MBSR instructor and other participants.
Conclusion:
It was feasible to recruit 21 stroke survivors and 7 caregivers for MBSR taster sessions in the community. A shorter MBSR session and an orientation session prior to the full course are suggestions for potential MBSR modifications for stroke survivors, which needs further research and evaluation
Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms
Background:
Depression is a major health problem worldwide and the majority of patients
presenting with depressive symptoms are managed in primary care. Current
approaches for assessing depressive symptoms in primary care are not accurate
in predicting future clinical outcomes, which may potentially lead to over or
under treatment. The Allostatic Load (AL) theory suggests that by measuring
multi-system biomarker levels as a proxy of measuring multi-system physiological
dysregulation, it is possible to identify individuals at risk of having adverse
health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by
applying statistical formulations to different multi-system biomarkers, have
been associated with depressive symptoms.
Aims and Objectives:
To test the hypothesis, that a combination of allostatic load (AL) biomarkers will
form a predictive algorithm in defining clinically meaningful outcomes in a
population of patients presenting with depressive symptoms.
The key objectives were:
1. To explore the relationship between various allostatic load biomarkers and
prevalence of depressive symptoms in patients, especially in patients diagnosed
with three common cardiometabolic diseases (Coronary Heart Disease (CHD),
Diabetes and Stroke).
2 To explore whether allostatic load biomarkers predict clinical outcomes in
patients with depressive symptoms, especially in patients with three common
cardiometabolic diseases (CHD, Diabetes and Stroke).
3 To develop a predictive tool to identify individuals with depressive symptoms
at highest risk of adverse clinical outcomes.
Methods:
Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing
cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’
was a research data source containing health related information from 666
participants recruited from the general population. The clinical outcomes for
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both datasets were studied using electronic data linkage to hospital and
mortality health records, undertaken by Information Services Division, Scotland.
Cross-sectional associations between allostatic load biomarkers calculated at
baseline, with clinical severity of depression assessed by a symptom score, were
assessed using logistic and linear regression models in both datasets. Cox’s
proportional hazards survival analysis models were used to assess the
relationship of allostatic load biomarkers at baseline and the risk of adverse
physical health outcomes at follow-up, in patients with depressive symptoms.
The possibility of interaction between depressive symptoms and allostatic load
biomarkers in risk prediction of adverse clinical outcomes was studied using the
analysis of variance (ANOVA) test. Finally, the value of constructing a risk
scoring scale using patient demographics and allostatic load biomarkers for
predicting adverse outcomes in depressed patients was investigated using
clinical risk prediction modelling and Area Under Curve (AUC) statistics.
Key Results:
Literature Review Findings.
The literature review showed that twelve blood based peripheral biomarkers
were statistically significant in predicting six different clinical outcomes in
participants with depressive symptoms. Outcomes related to both mental health
(depressive symptoms) and physical health were statistically associated with
pre-treatment levels of peripheral biomarkers; however only two studies
investigated outcomes related to physical health.
Cross-sectional Analysis Findings:
In DepChron, dysregulation of individual allostatic biomarkers (mainly
cardiometabolic) were found to have a non-linear association with increased
probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety
and Depression Score HADS-D≥8). A composite AI score constructed using five
biomarkers did not lead to any improvement in the observed strength of the
association. In Psobid, BMI was found to have a significant cross-sectional
association with the probability of depressive symptoms (assessed by General
Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive
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protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a
significant cross-sectional relationship with the continuous measure of GHQ-28.
A composite AI score constructed using 12 biomarkers did not show a significant
association with depressive symptoms among Psobid participants.
Longitudinal Analysis Findings:
In DepChron, three clinical outcomes were studied over four years: all-cause
death, all-cause hospital admissions and composite major adverse cardiovascular
outcome-MACE (cardiovascular death or admission due to MI/stroke/HF).
Presence of depressive symptoms and composite AI score calculated using mainly
peripheral cardiometabolic biomarkers was found to have a significant
association with all three clinical outcomes over the following four years in
DepChron patients. There was no evidence of an interaction between AI score
and presence of depressive symptoms in risk prediction of any of the three
clinical outcomes. There was a statistically significant interaction noted
between SBP and depressive symptoms in risk prediction of major adverse
cardiovascular outcome, and also between HbA1c and depressive symptoms in
risk prediction of all-cause mortality for patients with diabetes. In Psobid,
depressive symptoms (assessed by GHQ-28≥5) did not have a statistically
significant association with any of the four outcomes under study at seven years:
all cause death, all cause hospital admission, MACE and incidence of new cancer.
A composite AI score at baseline had a significant association with the risk of
MACE at seven years, after adjusting for confounders. A continuous measure of
IL-6 observed at baseline had a significant association with the risk of three
clinical outcomes- all-cause mortality, all-cause hospital admissions and major
adverse cardiovascular event. Raised total cholesterol at baseline was associated
with lower risk of all-cause death at seven years while raised waist hip ratio-
WHR at baseline was associated with higher risk of MACE at seven years among
Psobid participants. There was no significant interaction between depressive
symptoms and peripheral biomarkers (individual or combined) in risk prediction
of any of the four clinical outcomes under consideration.
Risk Scoring System Development:
In the DepChron cohort, a scoring system was constructed based on eight
baseline demographic and clinical variables to predict the risk of MACE over four
years. The AUC value for the risk scoring system was modest at 56.7% (95% CI
55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the
low event rate observed for the clinical outcomes.
Conclusion:
Individual peripheral biomarkers were found to have a cross-sectional association
with depressive symptoms both in patients with cardiometabolic disease and
middle-aged participants recruited from the general population. AI score
calculated with different statistical formulations was of no greater benefit in
predicting concurrent depressive symptoms or clinical outcomes at follow-up,
over and above its individual constituent biomarkers, in either patient cohort.
SBP had a significant interaction with depressive symptoms in predicting
cardiovascular events in patients with cardiometabolic disease; HbA1c had a
significant interaction with depressive symptoms in predicting all-cause
mortality in patients with diabetes. Peripheral biomarkers may have a role in
predicting clinical outcomes in patients with depressive symptoms, especially for
those with existing cardiometabolic disease, and this merits further
investigation
Relationship between blood pressure values, depressive symptoms and cardiovascular outcomes in patients with cardiometabolic disease
We studied joint effect of blood pressure-BP and depression on risk of major adverse cardiovascular outcome in patients with existing cardiometabolic disease. A cohort of 35537 patients with coronary heart disease, diabetes or stroke underwent depression screening and BP was recorded concurrently. We used Cox’s proportional hazards to calculate risk of major adverse cardiovascular event-MACE (myocardial infarction/heart failure/stroke or cardiovascular death) over 4 years associated with baseline BP and depression.
11% (3939) had experienced MACE within 4 years. Patients with very high systolic BP-SBP (160-240) hazard ratio-HR 1.28 and with depression (HR 1.22) at baseline had significantly higher adjusted risk. Depression had significant interaction with SBP in risk prediction (p=0.03). Patients with combination of SBP and depression at baseline had 83% higher adjusted risk of MACE, as compared to patients with reference SBP and without depression. Patients with cardiometabolic disease and comorbid depression may benefit from closer monitoring of SBP
Relationship of depression screening in cardiometabolic disease with vascular events and mortality: findings from a large primary care cohort with 4 years follow-up
Aims:
Benefits of routine depression screening for cardiometabolic disease patients remain unclear. We examined the association between depression screening and all-cause mortality and vascular events in cardiometabolic disease patients.
Methods and results:
125 143 patients with cardiometabolic diseases (coronary heart disease, diabetes or previous stroke) in the UK participated in primary care chronic disease management in 2008/09, which included depression screening using the Hospital Anxiety and Depression Score. 10 670 receiving depression treatment exempted, 35 537 screened, while 78 936 not screened. We studied all-cause mortality and vascular events at 4 years, by electronic data linkage of 124 414 patients (99.4%) on primary care registers to hospital discharge and mortality records and used Cox proportional hazards on matched data using propensity score. Mean age for the screened and not screened population was 69 years (standard deviation—SD 11.9) and 67 years (SD 14.3), respectively; 58% (20 658) of the screened population were men and 65.3% (22 726) were socioeconomically deprived, compared with 54.2% (42 727) and 67.4% (51 686), respectively, in the not screened population. The screened population had lower all-cause mortality (Hazard Ratio—HR 0.89) and vascular events (HR 0.85) in the matched data of N = 21 893 patients each in the screened and the unscreened groups.
Conclusion:
Depression screening was associated with a reduction in all-cause mortality and vascular events in patients with cardiometabolic diseases. The uptake of screening was poor for unknown reasons. Reverse causality and confounding by disease severity and quality of care are important possible limitations. Further research to determine reproducibility and explore underlying mechanisms is merited
Effect of left atrial compliance on pulmonary artery pressure: a case report
BACKGROUND: Left ventricular diastolic dysfunction, with secondary atrial pressure elevation, is a well-known concept. On the contrary, effect of left atrial compliance on pulmonary pressure is rarely considered. CASE PRESENTATION: We report the echocardiographic case of a 9-year-old child who presented severe rheumatic mitral valve regurgitation with a giant left atrium, in contrast to a normal artery pulmonary pressure, testifying of the high left atrial compliance. CONCLUSION: Left atrial compliance is an important determinant of symptoms and pulmonary artery pressure in mitral valve disease
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
Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493,737 UK Biobank participants
Background:
Frailty is associated with older age and multimorbidity (two or more long-term conditions); however, little is known about its prevalence or effects on mortality in younger populations. This paper aims to examine the association between frailty, multimorbidity, specific long-term conditions, and mortality in a middle-aged and older aged population.
Methods:
Data were sourced from the UK Biobank. Frailty phenotype was based on five criteria (weight loss, exhaustion, grip strength, low physical activity, slow walking pace). Participants were deemed frail if they met at least three criteria, pre-frail if they fulfilled one or two criteria, and not frail if no criteria were met. Sociodemographic characteristics and long-term conditions were examined. The outcome was all-cause mortality, which was measured at a median of 7 years follow-up. Multinomial logistic regression compared sociodemographic characteristics and long-term conditions of frail or pre-frail participants with non-frail participants. Cox proportional hazards models examined associations between frailty or pre-frailty and mortality. Results were stratified by age group (37–45, 45–55, 55–65, 65–73 years) and sex, and were adjusted for multimorbidity count, socioeconomic status, body-mass index, smoking status, and alcohol use.
Findings:
493 737 participants aged 37–73 years were included in the study, of whom 16 538 (3%) were considered frail, 185 360 (38%) pre-frail, and 291 839 (59%) not frail. Frailty was significantly associated with multimorbidity (prevalence 18% [4435/25 338] in those with four or more long-term conditions; odds ratio [OR] 27·1, 95% CI 25·3–29·1) socioeconomic deprivation, smoking, obesity, and infrequent alcohol consumption. The top five long-term conditions associated with frailty were multiple sclerosis (OR 15·3; 99·75% CI 12·8–18·2); chronic fatigue syndrome (12·9; 11·1–15·0); chronic obstructive pulmonary disease (5·6; 5·2–6·1); connective tissue disease (5·4; 5·0–5·8); and diabetes (5·0; 4·7–5·2). Pre-frailty and frailty were significantly associated with mortality for all age strata in men and women (except in women aged 37–45 years) after adjustment for confounders.
Interpretation:
Efforts to identify, manage, and prevent frailty should include middle-aged individuals with multimorbidity, in whom frailty is significantly associated with mortality, even after adjustment for number of long-term conditions, sociodemographics, and lifestyle. Research, clinical guidelines, and health-care services must shift focus from single conditions to the requirements of increasingly complex patient populations
Impact of multimorbidity count on all-cause mortality and glycaemic outcomes in people with type 2 diabetes: a systematic review protocol
Introduction: Type 2 diabetes (T2D) is a leading health priority worldwide. Multimorbidity (MM) is a term describing the co-occurrence of two or more chronic diseases or conditions. The majority of people living with T2D have MM. The relationship between MM and mortality and glycaemia in people with T2D is not clear.
Methods and analysis: Medline, Embase, Cumulative Index of Nursing and Allied Health Complete, The Cochrane Library, and SCOPUS will be searched with a prespecified search strategy. The searches will be limited to quantitative empirical studies in English with no restriction on publication date. One reviewer will perform title screening and two review authors will independently screen the abstract and full texts using Covidence software, with disagreements adjudicated by a third reviewer. Data will be extracted using a using a Population, Exposure, Comparator and Outcomes framework. Two reviewers will independently extract data and undertake the risk of bias (quality) assessment. Disagreements will be resolved by consensus. A narrative synthesis of the results will be conducted and meta-analysis considered if appropriate. Quality appraisal will be undertaken using the Newcastle-Ottawa quality assessment scale and the quality of the cumulative evidence of the included studies will be assessed using the Grading of Recommendations, Assessment, Development and Evaluation approach. This protocol was prepared in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines to ensure the quality of our review.
Ethics and dissemination: This review will synthesise the existing evidence about the impact of MM on mortality and glycaemic outcomes in people living with T2D and increase our understanding of this subject and will inform future practice and policy. Findings will be disseminated via conference presentations, social media and peer-reviewed publication
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
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
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