British Heart Foundation

Climate extremes exact a heavy and differential toll on society. Reported economic losses are primarily concentrated in developed economies, whereas reported fatalities occur overwhelmingly in developing economies. Moreover, even at single locations the adverse impacts of extreme climate events are often unequally distributed across the population. Understanding such impacts holds enormous societal and economic value, and is a key step towards climate resilience and adaptation. Recent research advances include improved impact forecasting and enhanced understanding of how the interaction between human and natural systems shapes the impacts of climate extremes. Nonetheless, there are some key challenges that have hindered progress. We focus on three: Limited availability and quality of impact data, difficulties in understanding the processes leading to impacts and lack of reliable impact projections. We argue that newly released datasets and recent methodological and technical advances open a window of opportunity to address several dimensions of these challenges. Notable examples include extracting impact information from textual sources using large language models and developing impact projections using data-driven approaches. Moreover, interdisciplinary collaborations between the social and natural sciences can elucidate processes underlying past climate impacts and enable building storylines of future societal impacts. We call for building momentum in seizing these opportunities for a breakthrough in the study of impacts of climate extremes. Achieving meaningful progress will require interdisciplinary and intersectoral research, and strong collaboration across academic, policy and practitioner communities.

ABSTRACT BACKGROUND Peak oxygen uptake (pVO 2 ) is a strong, independent predictor of adverse cardiovascular outcomes, supporting cardiopulmonary exercise testing as a primary end point assessing efficacy of novel drug therapies in obstructive hypertrophic cardiomyopathy (oHCM) clinical trials. However, characterizing changes in pVO 2 that patients perceive as beneficial or meaningful (ie, minimal important difference [MID]) has not been determined. METHODS Data from patients with symptomatic oHCM enrolled in SEQUOIA-HCM and MAPLE-HCM were pooled. A total of 282 patients were randomized 1:1 to aficamten (5–20 mg daily) or matching placebo in SEQUOIA-HCM, and 175 patients were randomized 1:1 to aficamten (5-20mg daily) or to metoprolol (50–200 mg) in MAPLE-HCM; follow-up in both trials was 24 weeks. Primary outcome was change from baseline to week 24 (Δ) in pVO 2 using Patient Global Impression of Change with anchor-based analysis to define MID. RESULTS At week 24, ΔpVO 2 (mL/kg/min) that corresponded to no change, one-category improvement, and one-category worsening were –0.05 (95% CI, –0.58 to 0.48), +0.35 (95% CI, –0.22 to 0.91), and –0.61 (95% CI, –1.36 to 0.13), respectively. Similarly, minute ventilation to carbon dioxide production ratio (VE/VCO 2 ) slope that corresponded to no change, one-category improvement, and one-category worsening were 0.16 (95% CI, –0.59 to 0.90), –1.15 (95% CI, – 1.89 to –0.42), and 0.88 (95% CI, –0.42 to 2.19), respectively. In a responder analysis using this new threshold for pVO 2 , 60% of patients receiving aficamten achieved a ΔpVO 2 ≥0.35 versus 31% of patients on placebo or metoprolol (odds ratio, 3.4 [95% CI, 2.3–4.9], P <0.001). Consistent findings were seen with VE/VCO 2 responder analysis. CONCLUSIONS Changes in pVO 2 of +0.35 and –0.61 mL/kg/min were associated with a small but perceptible clinical improvement and worsening, respectively, in patients with oHCM. Applying this newly defined threshold resulted in excellent differentiation of treatment effect in a clinical trial. These novel data provide a measure of clarity to patients and clinicians regarding the interpretation of changes in pVO 2 following therapeutic interventions, with potential impact on HCM management strategies and future clinical trials. Clinical Trial Registration SEQUOIA-HCM ( NCT05186818 ; https://clinicaltrials.gov/study/NCT05186818?term=sequoia-hcm&rank=1 ); MAPLE-HCM ( NCT05767346 ; https://clinicaltrials.gov/study/NCT05767346?term=maple-hcm&rank=1 ) Clinical Perspective What Is New? Using pooled data from over 440 patients with symptomatic obstructive hypertrophic cardiomyopathy enrolled in two phase 3 clinical trials, we define, for the first time, the minimally important difference for peak oxygen uptake (pVO 2 ) and ventilatory efficiency (VE/VCO 2 ) using patient-anchored and distribution-based methodologies. A change in pVO 2 of +0.35 mL/kg/min and a change in VE/VCO 2 of –1.15 represent the minimal thresholds associated with patient-perceived clinical improvement. Responder analyses using these thresholds demonstrated robust differentiation between aficamten and placebo/metoprolol, with an odds ratio exceeding 3 for achieving a meaningful improvement in pVO 2 . What Are the Clinical Implications? These newly defined thresholds bridge the gap between statistically significant changes in cardiopulmonary exercise testing measures and clinically meaningful benefit as perceived by patients with obstructive hypertrophic cardiomyopathy. Clinicians can use these benchmarks to contextualize individual patient responses to medical therapy, informing shared decision-making regarding treatment continuation or modification. These data provide a standardized, patient-centered framework for designing and interpreting primary end points in future hypertrophic cardiomyopathy clinical trials.

Heart failure (HF) is a complex clinical syndrome associated with high morbidity and mortality, accounting for approximately 2 % of total healthcare expenditures. Despite advances in pharmacological and device-based therapies, HF continues to affect over 70 million people globally, with an increasing prevalence driven by an aging population. The classification remains imperfect due to the pathophysiological complexity of the syndrome. Recent attention has focused on aetiological characterisation, particularly in non-ischaemic cardiomyopathies, where genetic testing may provide diagnostic, prognostic, and therapeutic insights. Left ventricular reverse remodeling (LVRR) and the recognition of HF with improved ejection fraction (HFimpEF) have highlighted the dynamic nature of HF and the importance of continued therapy despite apparent recovery. Guideline-directed medical therapy (GDMT), based on four foundational drug classes for HFrEF, has demonstrated significant benefit, yet its implementation remains suboptimal. For HFpEF, all effective drugs have however failed to reduce mortality. Device therapy, including implantable cardioverter-defibrillators (ICDs), cardiac resynchronisation therapy (CRT) and valve replacement offers additional benefit in select patients and may facilitate optimisation of medical therapy. New avenues such as multiomic profiling, gene therapy, and artificial intelligence (AI) are expanding our ability to phenotype HF, predict disease progression, and personalize treatment strategies. This viewpoint summarises the current understanding of HF, with an emphasis on the classification, aetiology, phenotypes and evidence-based management including newer therapies and their scope of use across the spectrum of LVEF.

The authors regret that in Figure 1 the name of the drug Sacubitril/ Valsartan was incorrectly reported as sacubutril valsartan.This was a typographical error, and the figure has now been corrected as below.This correction does not affect the scientific conclusions of the article.The authors would like to apologise for any inconvenience caused.

ABSTRACT INTRODUCTION The pathophysiology and risk factors for Alzheimer’s disease (AD) and dementia are insufficiently known. We studied the connections between gut microbiome, overall dementia and AD in a prospective, population-based cohort. METHODS We followed a population based random sample of 4,055 individuals (FINRISK 2022) for 16 years, with 330 cases of incident dementia and 280 AD cases. Gut microbiome community diversity and composition were assessed against future dementia and AD risk. Competing mortality risks were accounted for using Fine–Gray models. RESULTS Community diversity was not associated with dementia or AD. However, a supervised ordination with dbRDA suggested a possible compositional link between gut microbiome and dementia. One putative bacterial genus, Dorea , was associated with a decreased dementia risk. APOE ε4 genotype associated with several taxa; of these, phylum Verrucomicrobiota and species Nocardia carnea were associated with incident dementia. DISCUSSION The gut-brain axis has a modest association on future dementia or AD risk. Microbial composition, rather diversities, may contribute to dementia risk.