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BackgroundSocial prescribing assists patients to engage insocial activities and connect to community supports as part of a holistic approach to primary care. Rx: Community was a social prescribing project, implemented within 11 community health centres situated across Ontario, Canada.AimsTo explore how social prescribing as a process facilitates positive outcomes for patients.Design and settingWe used qualitative methods, conducting 18 focus groups involving 88 patients and 8 additional in-depth interviews.MethodsInterviews and focus groups were transcribed verbatim and analyzed thematically using a theoretical framework based onself-determination theory.ResultsParticipants who had received social prescriptions described social prescribing as an empathetic process that respects their needs and interests. Social prescribing facilitated the patient’s voice in their care, helped patient’s develop skills in addressing needs important to them, and fostered trusting relationships with staff and other participants. Patients reported their social support networks were expanded, and they had improved mental health and ability in self-management of chronic conditions. Patients who became involved in social prescribing as voluntary “health champions” reported this was a positive experience and they gained a sense of purpose by giving back to their communities in ways that felt meaningful for them.ConclusionSocial prescribing produced positive outcomes for patients, and fit well within the community health centre model of primarycare. Future research should examine the impact on health outcomes and examine the return on investment of developing and implementing social prescribing programs.

Background: Transient pulmonary congestion during exercise is emerging as an important determinant of reduced exercise capacity in heart failure with preserved ejection fraction (HFpEF). We sought to determine whether an abnormal cardiac energetic state underpins this process. Methods: We recruited patients across the spectrum of diastolic dysfunction and HFpEF (controls, n=11; type 2 diabetes, n=9; HFpEF, n=14; and severe diastolic dysfunction attributable to cardiac amyloidosis, n=9). Cardiac energetics were measured using phosphorus spectroscopy to define the myocardial phosphocreatine to ATP ratio. Cardiac function was assessed by cardiovascular magnetic resonance cine imaging and echocardiography and lung water using magnetic resonance proton density mapping. Studies were performed at rest and during submaximal exercise using a magnetic resonance imaging ergometer. Results: Paralleling the stepwise decline in diastolic function across the groups (E/e′ ratio; P <0.001) was an increase in NT-proBNP (N-terminal pro-brain natriuretic peptide; P <0.001) and a reduction in phosphocreatine/ATP ratio (control, 2.15 [2.09, 2.29]; type 2 diabetes, 1.71 [1.61, 1.91]; HFpEF, 1.66 [1.44, 1.89]; cardiac amyloidosis, 1.30 [1.16, 1.53]; P <0.001). During 20-W exercise, lower left ventricular diastolic filling rates (r=0.58; P <0.001), lower left ventricular diastolic reserve (r=0.55; P <0.001), left atrial dilatation (r=–0.52; P <0.001), lower right ventricular contractile reserve (right ventricular ejection fraction change, r=0.57; P <0.001), and right atrial dilation (r=–0.71; P <0.001) were all linked to lower phosphocreatine/ATP ratio. Along with these changes, pulmonary proton density mapping revealed transient pulmonary congestion in patients with HFpEF (+4.4% [0.5, 6.4]; P =0.002) and cardiac amyloidosis (+6.4% [3.3, 10.0]; P =0.004), which was not seen in healthy controls (–0.1% [–1.9, 2.1]; P =0.89) or type 2 diabetes without HFpEF (+0.8% [–1.7, 1.9]; P =0.82). The development of exercise-induced pulmonary congestion was associated with lower phosphocreatine/ATP ratio (r=–0.43; P =0.004). Conclusions: A gradient of myocardial energetic deficit exists across the spectrum of HFpEF. Even at low workload, this energetic deficit is related to markedly abnormal exercise responses in all 4 cardiac chambers, which is associated with detectable pulmonary congestion. The findings support an energetic basis for transient pulmonary congestion in HFpEF.

Background:Obesity causes diastolic dysfunction, and is one of the leading causes of heart failure with preserved ejection fraction. Myocardial relaxation is determined by both active metabolic processes such as impaired energetic status and steatosis, as well as intrinsic myocardial remodelling. However, the relative contribution of each to diastolic dysfunction in obesity is currently unknown.Methods:Eighty adult subjects (48 male) with no cardiovascular risk factors across a wide range of body mass indices (18.4–53.0 kg m−2) underwent magnetic resonance imaging for abdominal visceral fat, left ventricular geometry (LV mass:volume ratio) and diastolic function (peak diastolic strain rate), and magnetic resonance spectroscopy for PCr/ATP and myocardial triglyceride content.Results:Increasing visceral obesity was related to diastolic dysfunction (peak diastolic strain rate, r=−0.46, P=0.001). Myocardial triglyceride content (β=−0.2, P=0.008), PCr/ATP (β=−0.22, P=0.04) and LV mass:volume ratio (β=−0.61, P=0.04) all independently predicted peak diastolic strain rate (model R2 0.36, P<0.001). Moderated multiple regression confirmed the full mediating roles of PCr/ATP, myocardial triglyceride content and LV mass:volume ratio in the relationship between visceral fat and peak diastolic strain rate. Of the negative effect of visceral fat on diastolic function, 40% was explained by increased myocardial triglycerides, 39% by reduced PCr/ATP and 21% by LV concentric remodelling.Conclusions:Myocardial energetics and steatosis are more important in determining LV diastolic function than concentric hypertrophy, accounting for more of the negative effect of obesity on diastolic function than LV geometric remodelling. Targeting these metabolic processes is an attractive strategy to treat diastolic dysfunction in obesity.

BackgroundHeart failure (HF) is characterized by altered myocardial substrate metabolism which can lead to myocardial triglyceride accumulation (steatosis) and lipotoxicity. However its role in mild HF with preserved ejection fraction (HFpEF) is uncertain. We measured myocardial triglyceride content (MTG) in HFpEF and assessed its relationships with diastolic function and exercise capacity.MethodsTwenty seven HFpEF (clinical features of HF, left ventricular EF >50%, evidence of mild diastolic dysfunction and evidence of exercise limitation as assessed by cardiopulmonary exercise test) and 14 controls underwent 1H-cardiovascular magnetic resonance spectroscopy (1H-CMRS) to measure MTG (lipid/water, %), 31P-CMRS to measure myocardial energetics (phosphocreatine-to-adenosine triphosphate - PCr/ATP) and feature-tracking cardiovascular magnetic resonance (CMR) imaging for diastolic strain rate.ResultsWhen compared to controls, HFpEF had 2.3 fold higher in MTG (1.45 ± 0.25% vs. 0.64 ± 0.16%, p = 0.009) and reduced PCr/ATP (1.60 ± 0.09 vs. 2.00 ± 0.10, p = 0.005). HFpEF had significantly reduced diastolic strain rate and maximal oxygen consumption (VO2 max), which both correlated significantly with elevated MTG and reduced PCr/ATP. On multivariate analyses, MTG was independently associated with diastolic strain rate while diastolic strain rate was independently associated with VO2 max.ConclusionsMyocardial steatosis is pronounced in mild HFpEF, and is independently associated with impaired diastolic strain rate which is itself related to exercise capacity. Steatosis may adversely affect exercise capacity by indirect effect occurring via impairment in diastolic function. As such, myocardial triglyceride may become a potential therapeutic target to treat the increasing number of patients with HFpEF.

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Recent progress in fully-automated image segmentation has enabled efficient extraction of clinical parameters in large-scale clinical imaging studies, reducing laborious manual processing. However, the current state-of-the-art automatic image segmentation may still fail, especially when it comes to atypical cases. Visual inspection of segmentation quality is often required, thus diminishing the improvements in efficiency. This drives an increasing need to enhance the overall data processing pipeline with robust automatic quality scoring, especially for clinical applications. We present a novel quality control-driven (QCD) framework to provide reliable segmentation using a set of different neural networks. In contrast to the prior segmentation and quality scoring methods, the proposed framework automatically selects the optimal segmentation on-the-fly from the multiple candidate segmentations available, directly utilizing the inherent Dice similarity coefficient (DSC) predictions. We trained and evaluated the framework on a large-scale cardiovascular magnetic resonance aortic cine image sequences from the UK Biobank Study. The framework achieved segmentation accuracy of mean DSC at 0.966, mean prediction error of DSC within 0.015, and mean error in estimating lumen area ≤ 17.6 mm 2 for both ascending aorta and proximal descending aorta. This novel QCD framework successfully integrates the automatic image segmentation along with detection of critical errors on a percase basis, paving the way towards reliable fully-automatic extraction of clinical parameters for large-scale imaging studies.

See the response from https://doi.org/10.1111/jgs.16253 et al.