BACKGROUND The cardiovascular and mortality benefits of achieving guideline-recommended concentrations of low-density lipoprotein (LDL) and non-high-density lipoprotein (non-HDL) cholesterol with statins in primary prevention remain uncertain. METHODS AND FINDINGS In this new-user cohort study, we used electronic healthcare databases from Hong Kong (HK), New Zealand (NZ) and the United Kingdom (UK) to identify 185,237 patients initiating statins between 1 January 2007 and 31 December 2012 (with follow-up to 31 December 2017) without atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease. Associations between LDL and non-HDL cholesterol measured within 2 years post-initiation with the outcomes of major adverse cardiovascular events (MACE) or all-cause mortality were assessed in landmark analyses using multivariable Cox regression adjusted for age, sex, hypertension, atrial fibrillation, diabetes mellitus, dyslipidaemia, obesity, smoking, alcohol misuse, rheumatoid arthritis, systemic lupus erythematosus and connective tissue disorders, severe mental illness, antihypertensive drugs, antidiabetic drugs, antiplatelet drugs, and anticoagulant drugs. Estimates were pooled using random-effects meta-analysis. At 2 years, LDL cholesterol was <1.4 mmol/L in 7,084 (3.8%), 1.4-1.7 mmol/L in 21,893 (11.8%), 1.8-2.5 mmol/L in 81,941 (44.2%) and ≥2.6 mmol/L in 74,294 (40.1%) patients. Mean duration of follow-up for the primary outcome of MACE was 6.5 years in HK, 5.6 years in NZ and 5.4 years in UK. versus an LDL cholesterol ≥2.6 mmol/L, adjusted hazard ratios (HR) for MACE were 0.80 (95% CI [0.77,0.83]) for 1.8-2.5 mmol/L, 0.79 (0.66,0.94) for 1.4-1.7 mmol/L and 0.82 (0.60,1.12) for <1.4 mmol/L. Non-HDL cholesterol showed similar estimates for MACE (e.g., HR 0.75, [0.72,0.79] for 2.6-3.3 mmol/L versus ≥3.4 mmol/L). In continuous analysis, the association with MACE was approximately log-linear across achieved LDL and non-HDL cholesterol in HK and the UK, whereas in NZ estimates were less consistent and imprecise at the lowest concentrations. After adjustment for confounding factors, very low LDL (HR 1.06, [0.96,1.16]) and non-HDL cholesterol (HR 0.98, [0.84,1.14]) were not associated with all-cause mortality. Limitations include heterogeneity across cohorts, which may reflect confounding by indication where treatment intensity was guided by cardiovascular risk, and residual confounding from comorbidities, lifestyle interventions and disease severity. Estimates are also conditional on patients having initiated statins, survived to the landmark, and undergone follow-up lipid testing. CONCLUSIONS Lower achieved LDL and non-HDL cholesterol after statin initiation was associated with a reduction in MACE, with limited evidence of an increase in all-cause mortality at very low concentrations after adjustment for confounding. Additional reductions in cardiovascular events could be obtained by achieving guideline-recommended non-HDL cholesterol levels of at least <3.4 mmol/L after statin initiation for primary prevention.
BackgroundCOVID-19 vaccines played a critical role in reducing global health burden during the COVID-19 pandemic, but their rapid development required extraordinary effort. This study aims to evaluate their global return-on-investment (ROI) during the first year of the vaccination programme (8 December 2020-8 December 2021) to provide insights into the economic benefits relative to the costs of vaccine development, manufacturing, and delivery.Methods and findingsPublic health outcomes of COVID-19 vaccination, including life years and quality-adjusted life years (QALYs) gained from averted deaths, infections, and hospitalizations, were estimated. Health benefits were valued using two approaches: i) cost-benefit analysis and ii) cost-effectiveness analysis. These benefits were compared to the costs of vaccine development, manufacturing, and delivery to estimate the ROI under both approaches. Probabilistic sensitivity analyses were conducted to assess the impact of parameter uncertainty on ROI estimates. Vaccine development and delivery cost $79.4 billion, but the health and economic benefits of vaccination were valued between $6.43 and $64.3 trillion. High-income countries saw the greatest health benefits per-person vaccinated, and low-income countries gained the greatest nonhealth benefits per-person vaccinated, when expressed as a proportion of gross domestic product per capita. This estimated ROIs of $59.7-$809 per dollar invested in the base case analysis. ROIs ranged between $60.3-$753 across probabilistic sensitivity analyses for both approaches. Limitations include reliance on previous analyses of COVID-19 vaccination impact and a time horizon limited to the first year of COVID-19 vaccination.ConclusionsRapid COVID-19 vaccine development and delivery were an excellent investment. Vaccine development and equitable vaccine distribution globally should be prioritized before and during global health crises.
Background Obesity is a major risk factor for a broad spectrum of diseases, yet the molecular pathways underlying this risk remains poorly understood. Individual analytical approaches—interventional trials, observational data, and genetic methods—are each susceptible to distinct sources of bias. We aimed to identify a common metabolic perturbation signature of adiposity by triangulating evidence across multiple sources of body mass index (BMI) variation, and to characterise associations between this signature and contrasting adiposity-linked disease outcomes. Methods and findings We integrated mass spectrometry and nuclear magnetic resonance metabolomic profiling from two weight-loss interventions—a structured diet programme (DiRECT trial, ISRCTN03267836) and metabolic and bariatric surgery (By-Band-Sleeve trial, ISRCTN00786323)—with mendelian randomisation (MR) estimates of the effect of lifetime BMI exposure on metabolite levels, in order to identify a consistent BMI-associated metabolite signature across sources with distinct error structures. Weight loss-associated metabolites were then instrumented using genetic variants and their associations with heart failure (HF), osteoarthritis, and kidney cancer estimated in a two-sample MR framework, with instruments grouped into clusters based on genetic similarity to aid biological interpretation. 242 metabolites were consistently altered across weight loss interventions, predominantly comprising lipids, lipoproteins, and amino acids. The majority of these showed concordant associations with lifetime BMI in MR, consistent with regulation by adiposity. Differential components of this signature were associated with disease-specific outcomes. For HF, low-density lipoprotein (LDL) measures were strongly associated with increased risk, consistent with ischaemic aetiology enrichment, whilst high-density lipoprotein (HDL) cholesterol-enrichment traits were protective, and markers of dysfunctional HDL remodelling were associated with increased risk. For osteoarthritis, lipoprotein associations were again associated with disease risk but in the opposite direction to that seen with HF; additional signals were observed in glycine metabolism pathways. For kidney cancer, the adiposity metabolite signature translated poorly into disease associations, with only 5-methyluridine and ursodeoxycholate associations identified. The main limitations of our study include the potential for residual horizontal pleiotropy with metabolite instruments despite multiple sensitivity analyses and the rank-normalised scale of metabolite measures, which limits direct physiological interpretability. Conclusions Triangulating evidence across dietary intervention, metabolic and bariatric surgery, and MR of lifetime BMI identified a robust metabolic signature of adiposity. The association of components of this signature with obesity-related outcomes was disease-specific, supporting the notion that not all adiposity-associated metabolic perturbations are uniformly relevant across the spectrum of obesity-related diseases.
BackgroundPandemic influenza preparedness in high-resource nations has traditionally relied on large antiviral stockpiles, typically targeting coverage for 25% of the population. This inventory-based benchmark focuses on cumulative disease burden but often overlooks the inelastic capacity of healthcare systems to manage acute surges. As multi-billion-dollar inventories reach expiration, we evaluated whether static stockpiles remain a viable strategy for preventing healthcare system collapse during future pandemics.Methods and findingsWe projected daily hospital bed demand using three complementary frameworks: a static lower-bound estimation, a dynamic deterministic Susceptible-Infectious-Hospitalized-Recovered transmission model, and historical reconstructions of the 1918, 1957, and 1968 pandemics using mortality data. We evaluated official planning scenarios for the United Kingdom, Japan, and the United States, comparing projected demand against national surge capacities (i.e., staffed beds). To test the theoretical limits of the stockpile strategy, we applied best-case assumptions, including perfect distribution of antivirals to 100% of symptomatic cases and high clinical effectiveness (30% to 60% reduction in hospitalization). Our models identified a critical feasibility gap. While stockpiles successfully suppressed demand to manageable levels in moderate scenarios (analogous to 1957/1968), they were structurally insufficient for severe events. In high-severity scenarios (analogous to 1918 or CDC Very Severe parameters), the daily surge of patients exceeded available hospital capacity by a factor of 5-9. This inundation occurred even under the assumption of 100% treatment coverage, rendering antivirals incapable of preventing transition to crisis standards of care. Although this analysis is subject to the inherent uncertainties of future pandemics, our use of optimistic best-case assumptions suggests that the identified structural failures are a lower-bound estimate. Realistic operational hurdles would only widen the disparity between stockpile targets and system capacity. The main limitations of this study's methodology are its inherent optimistic bias, specifically the use of a conservative 4-day hospital length of stay that underestimates prolonged intensive care needs, the reliance on general hospital beds as a proxy that abstracts away from critical sub-system bottlenecks, and the assumption of guaranteed antiviral efficacy against novel strains.ConclusionsThis study demonstrates that large reserves cannot overcome the rigid physical constraints of healthcare systems, even under the optimistic assumption of perfect distribution. Consequently, the conventional 25% coverage target for antiviral stockpiles, a hallmark of legacy planning, presents a critical opportunity for re-evaluation. As global stocks near expiration, policymakers are uniquely positioned to leverage this inflection point by exploring a capacity-based framework. This adaptive paradigm suggests incorporating a synergistic mix of targeted reserves, temporary non-pharmaceutical interventions, and flexible delivery options, such as decentralized home-first care. Together, these integrated measures could serve as a vital temporal bridge, preserving system integrity until vaccine deployment.
Traditional antenatal care consists of an accelerating frequency of visits with advancing gestational age, as the bulk of pregnancy complications occur in late pregnancy.The 'inverted pyramid of care' concept describes a focus on structured risk assessment in early pregnancy, to facilitate prevention and enhanced surveillance of those at increased risk of maternal, intrinsic fetal, and uteroplacental problems.Since publication of this concept in 2011, it has become clear that early pregnancy screening may be contingent, with a sub-population identified for re-screening in mid- or late pregnancy.Maternal conditions (such as pre-eclampsia), intrinsic fetal conditions (such as chromosomal abnormalities) and uteroplacental problems (such as placenta accreta spectrum) can now be predicted or identified at earlier stages.This Policy Forum advocates for building risk-stratified care pathways around early prediction, prevention, and personalised surveillance. We provide updated guidance for 'inverted' antenatal care, including optimal screening timepoints and the most accurate methods of screening.We also highlight recent advances in diagnostics and treatment that we anticipate will further improve antenatal care in the future, including development and integration of artificial intelligence-assisted technologies.
