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Non-communicable diseases (NCDs) have been highlighted as important risk factors for COVID-19 mortality. However, insufficient data exist on the wider context of infectious diseases in people with NCDs. We aimed to investigate the association between NCDs and the risk of death from any infection before the COVID-19 pandemic (up to Dec 31, 2019). For this observational study, we used data from the UK Biobank observational cohort study to explore factors associated with infection death. We excluded participants if data were missing for comorbidities, body-mass index, smoking status, ethnicity, and socioeconomic deprivation, and if they were lost to follow-up or withdrew consent. Deaths were censored up to Dec 31, 2019. We used Poisson regression models including NCDs present at recruitment to the UK Biobank (obesity [defined by use of body-mass index] and self-reported hypertension, chronic heart disease, chronic respiratory disease, diabetes, cancer, chronic liver disease, chronic kidney disease, previous stroke or transient ischaemic attack, other neurological disease, psychiatric disorder, and chronic inflammatory and autoimmune rheumatological disease), age, sex, ethnicity, smoking status, and socioeconomic deprivation. Separate models were constructed with individual NCDs replaced by the total number of prevalent NCDs to define associations with multimorbidity. All analyses were repeated with non-infection-related death as an alternate outcome measure to establish differential associations of infection death and non-infection death. Associations are reported as incidence rate ratios (IRR) accompanied by 95% CIs. After exclusion of 9210 (1·8%) of the 502 505 participants in the UK Biobank cohort, our study sample comprised 493 295 individuals. During 5 273 731 person-years of follow-up (median 10·9 years [IQR 10·1–11·6] per participant), 27 729 deaths occurred, of which 1385 (5%) were related to infection. Advancing age, male sex, smoking, socioeconomic deprivation, and all studied NCDs were independently associated with the rate of both infection death and non-infection death. Compared with White ethnicity, a pooled Black, Asian, and minority ethnicity group was associated with a reduced risk of infection death (IRR 0·64, 95% CI 0·46–0·87) and non-infection death (0·80, 0·75–0·86). Stronger associations with infection death than with non-infection death were observed for advancing age (age 65 years vs 45 years: 7·59, 95% CI 5·92–9·73, for infection death vs 5·21, 4·97–5·48, for non-infection death), current smoking (vs never smoking: 3·69, 3·19–4·26, vs 2·52, 2·44–2·61), socioeconomic deprivation (most vs least deprived quintile: 2·13, 1·78–2·56, vs 1·38, 1·33–1·43), class 3 obesity (vs non-obese: 2·21, 1·74–2·82, vs 1·55, 1·44–1·66), hypertension (1·36, 1·22–1·53, vs 1·15, 1·12–1·18), respiratory disease (2·21, 1·96–2·50, vs 1·28, 1·24–1·32), chronic kidney disease (5·04, 4·28–7·31, vs 2·50, 2·20–2·84), psychiatric disease (1·56, 1·30–1·86, vs 1·23, 1·18–1·29), and chronic inflammatory and autoimmune rheumatological disease (2·45, 1·99–3·02, vs 1·41, 1·32–1·51). Accrual of multimorbidity was also more strongly associated with risk of infection death (five or more comorbidities vs none: 9·53, 6·97–13·03) than of non-infection death (5·26, 4·84–5·72). Several NCDs are associated with an increased risk of infection death, suggesting that some of the reported associations with COVID-19 mortality might be non-specific. Only a subset of NCDs, together with the accrual of multimorbidity, advancing age, smoking, and socioeconomic deprivation, were associated with a greater IRR for infection death than for other causes of death. Further research is needed to define why these risk factors are more strongly associated with infection death, so that more effective preventive strategies can be targeted to high-risk groups. British Heart Foundation.

In our experience, while patients often feel better, they rarely become asymptomatic (NYHA (New York Heart Association) class 1),12 an observation supported by real-world data even in those receiving ARNI.13 14 Moreover, we should consider whether a highly subjective and poorly reproducible assessment is appropriate to determine our allocation of life-saving treatments.15 Hence, criteria requiring repeat assessment act as a barrier to initiating additional therapies such as MRA or ARNI,7 which are regarded as ‘second-line’ due to the hierarchical framework which places greater emphasis on therapies based on the chronological sequence in which the trials were performed. There is no logical basis to assume that drug classes trialled earliest would be the most beneficial, yet this is what guidelines imply. [...]if we are to make progress, future guidelines must address these limitations and incorporate the Four Pillars of Heart Failure into a comprehensive disease modifying programme for all people living with HFrEF. Furthermore, the comparator was a submaximal dose of enalapril compounded by lower blood pressure in those allocated ARNI suggesting undertreatment in the control arm.16 It has also been suggested that the trial was additionally biased in favour of the novel agent due to a double drug run-in period of unequal times, in which those randomised to ARNI had already received an ACEi and were therefore pre-selected (20% of patients were lost during the run-in period).17 Drug doses are related to outcomes in HFrEF18–20 and the HR for the composite outcome in PARADIGM-HF between sacubitril-valsartan and enalapril was similar to the comparison of high and low dosing of lisinopril in the ATLAS trial.21 However, post-hoc analysis has shown that the point estimates for the benefit of low dose ARNI compared with low dose ACEi were identical to the point estimate of the overall trial,22 and real-world data have shown clear improvements in outcomes, symptoms and quality of life compared with standard of care ACEi.23 Another difficulty employing ARNI across the board includes the wash-out period required following cessation of ACEi due to risks of angioedema. [...]if the benefits of the activity are perceived (whether correctly or incorrectly) to be minimal, physician inertia may prevail.

Aims Left ventricular (LV) thrombus is increasingly detected in patients with and without ischaemic heart disease due to the increased availability of cardiac magnetic resonance imaging. Risk factors include anterior ST elevation myocardial infarction, delayed reperfusion therapy, and non‐ischaemic cardiomyopathy with severe LV systolic dysfunction. We aimed to report the characteristics and outcomes of patients with LV thrombus treated with either vitamin K antagonist (VKA) or direct oral anticoagulants (DOAC) with a view to describing differences in efficacy, specifically, subsequent thromboembolic events, thrombus resolution, and also side effects of therapy including clinically significant bleeding. Methods and results We conducted a retrospective, observational cohort study of patients diagnosed with LV thrombus between 1 December 2012 and 30 June 2018 and treated with either DOAC or VKA. We recorded patient demographics, past medical history, prescribed medications, and baseline investigations. The primary outcomes were rates of thromboembolism and clinically significant bleeding, with secondary outcomes of thrombus resolution on repeat cardiac imaging, repeat hospitalization, and all‐cause mortality. During the study period, 84 patients were diagnosed with and managed for LV thrombus. Of these, 62 received VKA and 22 DOAC including 13 prescribed rivaroxaban, eight apixaban, and one dabigatran. Most patients 75 (89%) were male with an average age of 62 ± 14 years. Ischaemic heart disease was the cause of LV impairment in 73 (87%) patients. Baseline characteristics were similar between groups at baseline. Most n = 55 (65%) were co‐prescribed a single antiplatelet agent and 32 (38%) received dual‐antiplatelet therapy. During an average follow‐up of 3.0 ± 1.4 years, there were no statistically significant differences between VKA and DOAC in rates of stroke (2% vs. 0%, P = 0.55), other thromboemboli (2% vs. 0%, P = 0.55), or clinically significant bleeding (10% vs. 0%, P = 0.13). The average interval to cardiac imaging follow‐up was 233 ± 251 days and was not different between groups (P = 0.83), and there was no difference in the rate of resolution of thrombus (76% vs. 65% P = 0.33). Rehospitalization (50% vs. 45%: P = 0.53) and all‐cause mortality (10% vs. 14%; P = 0.61) were also similar. Conclusions Our data suggest that DOACs are likely to be at least as effective and safe as VKA for stroke prevention in patients with LV thrombus and, despite their lack of a licence for this indication, are therefore likely to represent a reasonable and more convenient option for this setting. The optimal timing and type of anticoagulation for LV thrombus, as well as the role of screening for high‐risk patients, should be tested in prospective, randomized trials.

IntroductionLeft ventricular ejection fraction (LVEF) has well-known limitations including modest reproducibility, load dependence, and representation of the percentage change in left ventricular (LV) volume rather than myocardial contractility. Although diastolic dysfunction has been proposed as a key mechanism underpinning the pathophysiology of heart failure with a preserved ejection fraction (HFpEF) the presence of subtle or concomitant systolic dysfunction has previously been suggested. We aimed to assess the prognostic value of systolic blood pressure: indexed left ventricular end-systolic volume ratio, or ‘cardiac contractility index’ (CCI).MethodsIn a prospective, observational cohort study LVEF and CCI were measured in 728 unselected individuals with newly diagnosed chronic heart failure. We divided patients into tertiles of LVEF and CCI, and also divided those with heart failure with reduced ejection fraction (HFrEF) or HFpEF by the median value of CCI (4.43mmHg/ml/m2) into four groups. Unadjusted and adjusted Poisson regression models were used to determine mortality rates for CCI and LVEF as continuous variables.ResultsThere was a modest, positive correlation between LVEF and CCI (r=0.70 [0.66-0.74], R2 0.49; p<0.0001), although the latter was distributed widely for any given value of LVEF, especially for those with HFpEF (Figure 1). We observed distinct clinical characteristics across tertiles of both LVEF and CCI, with an inverse relationship with conventional markers of risk including N-terminal B-type natriuretic peptide (p<0.001 in both comparisons) (Table 1). During 5.9 (2.9-9.0) years of follow up 491 (67.4%) patients died. There was a clear relationship between tertiles of CCI and all-cause mortality risk (p<0.001), which was less evident when patients were divided by LVEF. When modelled as continuous variables there was a curvi-linear relationship between all-cause mortality rates and CCI, but the relationship between LVEF and mortality risk was more complex, with no clear association across a wide range from 25-55%. In models including relevant covariates, the association between LVEF and mortality was no longer evident except for those with LVEF 60% (relative to 50%) but remained evident for all specified values of CCI (Table 1). Patients with HFpEF and CCI below the median value had distinct clinical characteristics (Table 2), and all-cause mortality risk ~40% higher than those with CCI above median (p<0.001), similar to those with HFrEF (Figure 2).ConclusionsCCI is a non-invasive, relatively afterload independent measure left ventricular contractility which provided additional prognostic information beyond conventional assessment by LVEF. These data could help refine the inclusion criteria of future randomised controlled trials, and its simplicity means CCI could be easily applied to existing datasets in order to identify who may have derived benefits from pharmacological therapies.Abstract 132 Table 1Unadjusted and adjusted poisson regression analyses Cardiac contractility index LVEF Unadjusted IRR (95% CI) Adjusted IRR (95% CI ) Adjusted IRR (95% CI ) Age (per year)1.06 (1.05-1.07)1.06 (1.04-1.07)1.06 (1.04-1.07)Male1.19 (0.99-1.42)1.08 (0.87-1.35)1.15 (0.93-1.43)Ischaemic heart disease1.05 (0.87-1.28)0.94 (0.76-1.17)0.96 (0.77-1.19)Diabetes mellitus1.09 (0.89-1.32)1.21 (0.98-1.50)1.22 (1.00-1.51)Hypertension1.00 (0.83-1.21)1.07 (0.87-1.32)1.05 (0.85-1.30)SBP (per mmHg)1.00 (0.99-1.00)1.00 (1.00-1.00)1.00 (0.99-1.00)HR (per beat/min)1.01 (1.00-1.01)1.01 (1.00-1.01)1.01 (1.00-1.01)log10 haemoglobin (per g/L)0.32 (0.17-0.61)0.87 (0.35-2.19)0.62 (0.25-1.51)Log10 creatinine (per μmol/L)6.61 (3.74-11.67)1.59 (0.78-3.23)1.58 (0.77-3.24)Log10 albumin0.00 (0.00-0.01)0.01 (0.00-0.16)0.01 (0.00-0.14)Log10 NTpro-BNP2.19 (1.85-2.59)1.29 (1.02-1.62)1.37 (1.09-1.72)Cardiac contractility index (mmHg/ml/m2) 21.56 (1.26-1.93)1.34 (1.03-1.75)- 41.07 (1.01-1.13)1.06 (1.00-1.13)- 4.431.001.00- 60.78 (0.67-0.92)0.78 (0.66-0.93)- 80.54 (0.39-0.74)0.61 (0.43-0.85)-LVEF (%) 201.69 (1.24-2.29)-1.27 (0.89-1.80) 301.19 (0.98-1.45)-1.01 (0.80-1.28) 400.95 (0.79-1.13)-0.89 (0.73-1.09) 501.00-1.00 600.66 (0.52-0.84)-0.69 (0.54-0.88)Abstract 132 Table 2Clinical characteristics of patients with HFrEF and HFpEF divided by median cardiac contractility index All patients (n=728) HFrEF HFpEF Low CCI (n=232) High CCI (n=61) Low CCI (n=132) High CCI (n=303) Age (years)82.6 ± 9.281.1 ± 10.3# 83.2 ± 8.583.9 ± 8.4# 83.1 ± 8.4Male sex [n(%)]330 (45.3)151 (65.1)*# 23 (37.7)*64 (48.5)*# 92 (30.4)*NYHA Class III/IV [n(%)]328 (45.1)95 (40.9)18 (29.5)55 (41.7)160 (52.8)IHD [n(%)]210 (28.8)87 (37.5)# 25 (41.0)# 33 (25.0)# 65 (21.5)# Hypertension [n(%)]490 (67.3)123 (53.0)*# 42 (68.9)*94 (71.2)# 231 (76.2)Atrial fibrillation [n(%)]263 (36.1)81 (34.9)20 (32.8)57 (43.2)105 (34.7)SBP (mmHg)140.3 ± 22.9131.6 ± 22.8*149.0 ± 20.5*133.8 ± 20.0*148.0 ± 21.4*Heart rate (beats/min)76.0 ± 16.978.7 ± 19.7# 79.5 ± 19.3# 74.4 ± 15.5# 73.8 ± 14.3# LVEF (%)48.2 ± 11.634.6 ± 9.6*# 45.0 ± 4.1*# 54.2 ± 3.5*# 56.6 ± 3.8*# CCI (mmHg/ml/m2)4.55 ± 1.922.64 ± 0.88*# 5.31 ± 0.77*# 3.69 ± 0.56*# 6.24 ± 1.37*# NT-proBNP (pg/mL)1066 (503.5-2570)2235 (788-5052)*# 813 (450-1810)*1153 (503-2353)*# 761 (401-1409)* *represents p<0.05 between cardiac contractility index categories within HFrEF and HFpEF groups. #represents p<0.05 between HFrEF and HFpEF within cardiac contractility index groups.Abstract 132 Figure 1Abstract 132 Figure 2Conflict of InterestSpeaker's fees, Honoraria and non-financial support from AstraZeneca.

Pacemakers are widely utilised to treat bradycardia, but right ventricular (RV) pacing is associated with heightened risk of left ventricular (LV) systolic dysfunction and heart failure. We aimed to compare personalised pacemaker reprogramming to avoid RV pacing with usual care on echocardiographic and patient-orientated outcomes. A prospective phase II randomised, double-blind, parallel-group trial in 100 patients with a pacemaker implanted for indications other than third degree heart block for ≥2 years. Personalised pacemaker reprogramming was guided by a published protocol. Primary outcome was change in LV ejection fraction on echocardiography after 6 months. Secondary outcomes included LV remodeling, quality of life, and battery longevity. Clinical and pacemaker variables were similar between groups. The mean age (SD) of participants was 76 (+/-9) years and 71% were male. Nine patients withdrew due to concurrent illness, leaving 91 patients in the intention-to-treat analysis. At 6 months, personalised programming compared to usual care, reduced RV pacing (-6.5±1.8% versus -0.21±1.7%; p<0.01), improved LV function (LV ejection fraction +3.09% [95% confidence interval (CI) 0.48 to 5.70%; p = 0.02]) and LV dimensions (LV end systolic volume indexed to body surface area -2.99mL/m2 [95% CI -5.69 to -0.29; p = 0.03]). Intervention also preserved battery longevity by approximately 5 months (+0.38 years [95% CI 0.14 to 0.62; p<0.01)) with no evidence of an effect on quality of life (+0.19, [95% CI -0.25 to 0.62; p = 0.402]). Personalised programming in patients with pacemakers for bradycardia can improve LV function and size, extend battery longevity, and is safe and acceptable to patients. ClinicalTrials.gov identifier: NCT03627585.

Two highly prevalent and growing global diseases impacted by skeletal muscle atrophy are chronic heart failure (HF) and type 2 diabetes mellitus (DM). The presence of either condition increases the likelihood of developing the other, with recent studies revealing a large and relatively poorly characterized clinical population of patients with coexistent HF and DM (HFDM). HFDM results in worse symptoms and poorer clinical outcomes compared with DM or HF alone, and cardiovascular‐focused disease‐modifying agents have proven less effective in HFDM indicating a key role of the periphery. This review combines current clinical knowledge and basic biological mechanisms to address the critical emergence of skeletal muscle atrophy in patients with HFDM as a key driver of symptoms. We discuss how the degree of skeletal muscle wasting in patients with HFDM is likely underpinned by a variety of mechanisms that include mitochondrial dysfunction, insulin resistance, inflammation, and lipotoxicity. Given many atrophic triggers (e.g. ubiquitin proteasome/autophagy/calpain activity and supressed IGF1‐Akt‐mTORC1 signalling) are linked to increased production of reactive oxygen species, we speculate that a higher pro‐oxidative state in HFDM could be a unifying mechanism that promotes accelerated fibre atrophy. Overall, our proposal is that patients with HFDM represent a unique clinical population, prompting a review of treatment strategies including further focus on elucidating potential mechanisms and therapeutic targets of muscle atrophy in these distinct patients.

Chronic heart failure (CHF) is a chronic, progressive disease that has detrimental consequences on a patient's quality of life (QoL). In part due to requirements for market access and licensing, the assessment of current and future treatments focuses on reducing mortality and hospitalizations. Few drugs are available principally for their symptomatic effect despite the fact that most patients' symptoms persist or worsen over time and an acceptance that the survival gains of modern therapies are mitigated by poorly controlled symptoms. Additional contributors to the failure to focus on symptoms could be the result of under‐reporting of symptoms by patients and carers and a reliance on insensitive symptomatic categories in which patients frequently remain despite additional therapies. Hence, formal symptom assessment tools, such as questionnaires, can be useful prompts to encourage more fidelity and reproducibility in the assessment of symptoms. This scoping review explores for the first time the assessment options and management of common symptoms in CHF with a focus on patient‐reported outcome tools. The integration of patient‐reported outcomes for symptom assessment into the routine of a CHF clinic could improve the monitoring of disease progression and QoL, especially following changes in treatment or intervention with a targeted symptom approach expected to improve QoL and patient outcomes.

Left ventricular (LV) thrombus is an increasingly recognised complication following anterior myocardial infarction and non-ischaemic cardiomyopathy. Whilst vitamin K antagonists (VKA) remain the only approved therapeutic option to reduce the risk of systemic thromboembolism including stroke, the off-label use of direct oral anticoagulants (DOACs) is becoming an attractive alternative.We aimed to improve the diagnosis and management of LV thrombus at a tertiary cardiology centre using quality improvement methodology. Outcomes included increasing the use of DOACs from 25% to 70% over a period of 1 year and shorten length of time from diagnosis to repeat imaging to within 3–6 months as recommended by guidelines.During the first Plan–Do–Study–Action (PDSA) cycle, we identified 84 patients diagnosed with LV thrombus between 1 December 2012 and 30 June 2018. The majority (74%) were prescribed VKA. Repeat imaging occurred in 89% of patients, but only 55% using the same modality. The mean duration between diagnosis and repeat imaging was 233±251 days. There were no significant differences between VKA and DOAC in terms of thrombus resolution, systemic embolisation or clinically significant bleeding. We published trust-wide guidelines on the management of LV thrombus with recommendations supporting the use of DOACs and appropriate follow-up imaging. A second PDSA cycle undertaken between 1 October 2019 and 31 March 2020 identified a further 20 patients. DOAC use increased to 70% and 70% of patients underwent follow-up imaging following a mean duration of 140±61 days, although in only 36% using the same modality.Using quality improvement methodology, we confirmed safe and efficient use of DOAC in the setting of LV thrombus. We published trust guidelines supporting their use, which was associated with an increase in DOAC use and in earlier follow-up imaging in line with our recommendations.

Background Observational studies investigating risk factors in coronavirus disease 2019 (COVID-19) have not considered the confounding effects of advanced care planning, such that a valid picture of risk for elderly, frail and multi-morbid patients is unknown. We aimed to report ceiling of care and cardiopulmonary resuscitation (CPR) decisions and their association with demographic and clinical characteristics as well as outcomes during the COVID-19 pandemic. Methods Retrospective, observational study conducted between 5th March and 7th May 2020 of all hospitalised patients with COVID-19. Ceiling of care and CPR decisions were documented using the Recommended Summary Plan for Emergency Care and Treatment (ReSPECT) process. Unadjusted and multivariable regression analyses were used to determine factors associated with ceiling of care decisions and death during hospitalisation. Results A total of 485 patients were included, of whom 409 (84·3%) had a documented ceiling of care; level one for 208 (50·9%), level two for 75 (18·3%) and level three for 126 (30·8%). CPR decisions were documented for 451 (93·0%) of whom 336 (74·5%) were ‘not for resuscitation’. Advanced age, frailty, White-European ethnicity, a diagnosis of any co-morbidity and receipt of cardiovascular medications were associated with ceiling of care decisions. In a multivariable model only advanced age (odds 0·89, 0·86–0·93 p < 0·001), frailty (odds 0·48, 0·38–0·60, p < 0·001) and the cumulative number of co-morbidities (odds 0·72, 0·52–1·0, p = 0·048) were independently associated. Death during hospitalisation was independently associated with age, frailty and requirement for level two or three care. Conclusion Ceiling of care decisions were made for the majority of patients during the COVID-19 pandemic, broadly in line with known predictors of poor outcomes in COVID-19, but with a focus on co-morbidities suggesting ICU admission might not be a reliable end-point for observational studies where advanced care planning is routine.

The coronavirus disease 2019 (COVID-19) pandemic is an unprecedented challenge. Meeting this has resulted in changes to working practices and the impact on the management of patients with heart failure with reduced ejection fraction (HFrEF) is largely unknown. We performed a retrospective, observational study contrasting patients diagnosed with HFrEF attending specialist heart failure clinics at a UK hospital, whose subsequent period of optimisation of medical therapy was during the COVID-19 pandemic, with patients diagnosed the previous year. The primary outcome was the change in equivalent dosing of ramipril and bisoprolol at 6-months. Secondary outcomes were the number and type of follow-up consultations, hospitalisation for heart failure and all-cause mortality. In total, 60 patients were diagnosed with HFrEF between 1 December 2019 and 30 April 2020, compared to 54 during the same period of the previous year. The absolute number of consultations was higher (390 vs 270; p = 0.69), driven by increases in telephone consultations, with a reduction in appointments with hospital nurse specialists. After 6-months, we observed lower equivalent dosing of ramipril (3.1 ± 3.0 mg vs 4.4 ± 0.5 mg; p = 0.035) and similar dosing of bisoprolol (4.1 ± 0.5 mg vs 4.9 ± 0.5 mg; p = 0.27), which persisted for ramipril (mean difference 1.0 mg, 95% CI 0.018–2.09; p = 0.046) and bisoprolol (mean difference 0.52 mg, 95% CI -0.23–1.28; p = 0.17) after adjustment for baseline dosing. We observed no differences in the proportion of patients who died (5.0% vs 7.4%; p = 0.59) or were hospitalised with heart failure (13.3% vs 9.3%; p = 0.49). Our study suggests the transition to telephone appointments and re-deployment of heart failure nurse specialists was associated with less successful optimisation of medical therapy, especially renin-angiotensin inhibitors, compared with usual care.