“Enjoy your baby” Internet-based CBT for mothers with babies: a feasibility randomised control trial

Background: Postnatal depression is a global health problem with lasting effects on the family. Government policy is focussed on early intervention and increasing access to psychological therapies. There is a growing evidence base for the use of computerised CBT packages and this study investigated the feasibility of a CBT-based self-help internet intervention for new mothers. Objective: To assess the ability to recruit mothers, deliver an internet course, obtain follow-up data and evaluate what mothers think of the course. Design: A feasibility randomised control design was used to compare a waiting list control group (delayed access= DA) to the Enjoy Your Baby course (immediate access= IA). Measures were administered at baseline and 8 week follow-up. Methods: Adverts were placed in the Metro freesheet, on charity web pages, on social media, posters were put up in the community, and leaflets were handed out at mother and baby groups. Participants had to be 18 years old or over with a child less than 18 months old. The IA arm was given access to the course straight away. After 8 weeks all participants were asked to recomplete the original measures and those in the IA arm also gave feedback on the course. Participants in the DA arm were given access after recompleting the questionnaires. Due to a lack of follow-up data a small discussion group was conducted. Intervention: The course contains 4 core modules including helping mothers understand why they feel the way they do and helping them build closeness to their babies. Additional modules, worksheets and homework tasks were available. The DA group were given a list of additional support resources and services, and encouraged to seek additional help if required. All participants received weekly automated emails for 12 weeks as they worked through the course. It was not possible to deliver individualised support. 34 Results: Despite using a number of recruitment strategies, recruitment was lower and slower than anticipated, and attrition was high. 41 women, primarily recruited via the internet, were randomised (IA n=21, DA n=20). No significant differences were observed between participants in either arm at baseline and no statistically significant differences were identified when the demographics and baseline measures of participants who logged-on to the course were compared to those who did not, or when participants who completed follow-up measures were compared to those who did not. Pre and post intervention scores on the EPDS approached statistical significance (P=.059, r=.444) favouring the intervention arm. The discussion group suggested strengths of the course and recommended areas for improvement, including making the course more mobile friendly. Conclusion: Internet interventions show promise; however it is difficult to recruit mothers, engagement is low and attrition high. A number of recommendations are made and a further pilot or an internal pilot of a larger substantive study should be conducted to confirm recruitment and retention. Trial ID: ISRCTN90927910.

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 3 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 4 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.

Cognitive impairment in heart failure

The clinical syndrome of heart failure is one of the leading causes of hospitalisation and mortality in older adults. Due to ageing of the general population and improved survival from cardiac disease the prevalence of heart failure is rising. Despite the fact that the majority of patients with heart failure are aged over 65 years old, many with multiple co-morbidities, the association between cognitive impairment and heart failure has received relatively little research interest compared to other aspects of cardiac disease. The presence of concomitant cognitive impairment has implications for the management of patients with heart failure in the community. There are many evidence based pharmacological therapies used in heart failure management which obviously rely on patient education regarding compliance. Also central to the treatment of heart failure is patient self-monitoring for signs indicative of clinical deterioration which may prompt them to seek medical assistance or initiate a therapeutic intervention e.g. taking additional diuretic. Adherence and self-management may be jeopardised by cognitive impairment. Formal diagnosis of cognitive impairment requires evidence of abnormalities on neuropsychological testing (typically a result ≥1.5 standard deviation below the age-standardised mean) in at least one cognitive domain. Cognitive impairment is associated with an increased risk of dementia and people with mild cognitive impairment develop dementia at a rate of 10-15% per year, compared with a rate of 1-2% per year in healthy controls.1 Cognitive impairment has been reported in a variety of cardiovascular disorders. It is well documented among patients with hypertension, atrial fibrillation and coronary artery disease, especially after coronary artery bypass grafting. This background is relevant to the study of patients with heart failure as many, if not most, have a history of one or more of these co-morbidities. A systematic review of the literature to date has shown a wide variation in the reported prevalence of cognitive impairment in heart failure. This range in variation probably reflects small study sample sizes, differences in the heart failure populations studied (inpatients versus outpatients), neuropsychological tests employed and threshold values used to define cognitive impairment. The main aim of this study was to identify the prevalence of cognitive impairment in a representative sample of heart failure patients and to examine whether this association was due to heart failure per se rather than the common cardiovascular co-morbidities that often accompany it such as atherosclerosis and atrial fibrillation. Of the 817 potential participants screened, 344 were included in this study. The study cohort included 196 patients with HF, 61 patients with ischaemic heart disease and no HF and 87 healthy control participants. The HF cohort consisted of 70 patients with HF and coronary artery disease in sinus rhythm, 51 patients with no coronary artery disease in sinus rhythm and 75 patients with HF and atrial fibrillation. All patients with HF had evidence of HF-REF with a LVEF <45% on transthoracic echocardiography. The majority of the cohort was male and elderly. HF patients with AF were more likely to have multiple co-morbidities. Patients recruited from cardiac rehabilitation clinics had proven coronary artery disease, no clinical HF and a LVEF >55%. The ischaemic heart disease group were relatively well matched to healthy controls who had no previous diagnosis of any chronic illness, prescribed no regular medication and also had a LVEF >55%. All participants underwent the same baseline investigations and there were no obvious differences in baseline demographics between each of the cohorts. All 344 participants attended for 2 study visits. Baseline investigations including physiological measurements, electrocardiography, echocardiography and laboratory testing were all completed at the initial screening visit. Participants were then invited to attend their second study visit within 10 days of the screening visit. 342 participants completed all neuropsychological assessments (2 participants failed to complete 1 questionnaire). A full comprehensive battery of neuropsychological assessment tools were administered in the 90 minute study visit. These included three global cognitive screening assessment tools (mini mental state examination, Montreal cognitive assessment tool and the repeatable battery for the assessment of neuropsychological status) and additional measures of executive function (an area we believe has been understudied to date). In total there were 9 cognitive tests performed. These were generally well tolerated. Data were also collected using quality of life questionnaires and health status measures. In addition to this, carers of the study participant were asked to complete a measure of caregiver strain and an informant questionnaire on cognitive decline. The prevalence of cognitive impairment varied significantly depending on the neuropsychological assessment tool used and cut-off value used to define cognitive impairment. Despite this, all assessment tools showed the same pattern of results with those patients with heart failure and atrial fibrillation having poorer cognitive performance than those with heart failure in sinus rhythm. Cognitive impairment was also more common in patients with cardiac disease (either coronary artery disease or heart failure) than age-, sex- and education-matched healthy controls, even after adjustment for common vascular risk factors.