COVID-19 vaccine mRNA-1273 elicits a protective immune profile in mice that is not associated with vaccine-enhanced disease upon SARS-CoV-2 challenge.

Vaccine-associated enhanced respiratory disease (VAERD) was previously observed in some preclinical models of severe acute respiratory syndrome (SARS) and MERS coronavirus vaccines. We used the SARS coronavirus 2 (SARS-CoV-2) mouse-adapted, passage 10, lethal challenge virus (MA10) mouse model of acute lung injury to evaluate the immune response and potential for immunopathology in animals vaccinated with research-grade mRNA-1273. Whole-inactivated virus or heat-denatured spike protein subunit vaccines with alum designed to elicit low-potency antibodies and Th2-skewed CD4+ T cells resulted in reduced viral titers and weight loss post challenge but more severe pathological changes in the lung compared to saline-immunized animals. In contrast, a protective dose of mRNA-1273 induced favorable humoral and cellular immune responses that protected from viral replication in the upper and lower respiratory tract upon challenge. A subprotective dose of mRNA-1273 reduced viral replication and limited histopathological manifestations compared to animals given saline. Overall, our findings demonstrate an immunological signature associated with antiviral protection without disease enhancement following vaccination with mRNA-1273.

Accelerated COVID-19 vaccine development: milestones, lessons, and prospects.

The development of effective vaccines to combat infectious diseases is a complex multi-year and multi-stakeholder process. To accelerate the development of vaccines for coronavirus disease 2019 (COVID-19), a novel pathogen emerging in late 2019 and spreading globally by early 2020, the United States government (USG) mounted an operation bridging public and private sector expertise and infrastructure. The success of the endeavor can be seen in the rapid advanced development of multiple vaccine candidates, with several demonstrating efficacy and now being administered around the globe. Here, we review the milestones enabling the USG-led effort, the methods utilized, and ensuing outcomes. We discuss the current status of COVID-19 vaccine development and provide a perspective for how partnership and preparedness can be better utilized in response to future public-health pandemic emergencies.

Nonspecific effects of neonatal and infant vaccination: public-health, immunological and conceptual challenges.

Vaccines can have nonspecific effects through their modulation of responses to infections not specifically targeted by the vaccine. However, lack of knowledge about the underlying immunological mechanisms and molecular cause-and-effect relationships prevent use of this potentially powerful early-life intervention to its greatest benefit. The World Health Organization has identified investigations into the molecular basis of nonspecific vaccine effects as a research priority.

MKMR: a multi-kernel machine regression model to predict health outcomes using human microbiome data.

Studies have found that human microbiome is associated with and predictive of human health and diseases. Many statistical methods developed for microbiome data focus on different distance metrics that can capture various information in microbiomes. Prediction models were also developed for microbiome data, including deep learning methods with convolutional neural networks that consider both taxa abundance profiles and taxonomic relationships among microbial taxa from a phylogenetic tree. Studies have also suggested that a health outcome could associate with multiple forms of microbiome profiles. In addition to the abundance of some taxa that are associated with a health outcome, the presence/absence of some taxa is also associated with and predictive of the same health outcome. Moreover, associated taxa may be close to each other on a phylogenetic tree or spread apart on a phylogenetic tree. No prediction models currently exist that use multiple forms of microbiome-outcome associations. To address this, we propose a multi-kernel machine regression (MKMR) method that is able to capture various types of microbiome signals when doing predictions. MKMR utilizes multiple forms of microbiome signals through multiple kernels being transformed from multiple distance metrics for microbiomes and learn an optimal conic combination of these kernels, with kernel weights helping us understand contributions of individual microbiome signal types. Simulation studies suggest a much-improved prediction performance over competing methods with mixture of microbiome signals. Real data applicants to predict multiple health outcomes using throat and gut microbiome data also suggest a better prediction of MKMR than that of competing methods.

Consensus proposal for revised International Working Group 2023 response criteria for higher-risk myelodysplastic syndromes.

Myelodysplastic syndromes/myelodysplastic neoplasms (MDS) are associated with variable clinical presentations and outcomes. The initial response criteria developed by the International Working Group (IWG) in 2000 have been used in clinical practice, clinical trials, regulatory reviews, and drug labels. Although the IWG criteria were revised in 2006 and 2018 (the latter focusing on lower-risk disease), limitations persist in their application to higher-risk MDS (HR-MDS) and their ability to fully capture the clinical benefits of novel investigational drugs or serve as valid surrogates for longer-term clinical end points (eg, overall survival). Further, issues related to the ambiguity and practicality of some criteria lead to variability in interpretation and interobserver inconsistency in reporting results from the same sets of data. Thus, we convened an international panel of 36 MDS experts and used an established modified Delphi process to develop consensus recommendations for updated response criteria that would be more reflective of patient-centered and clinically relevant outcomes in HR-MDS. Among others, the IWG 2023 criteria include changes in the hemoglobin threshold for complete remission (CR), the introduction of CR with limited count recovery and CR with partial hematologic recovery as provisional response criteria, the elimination of marrow CR, and specific recommendations for the standardization of time-to-event end points and the derivation and reporting of responses. The updated criteria should lead to a better correlation between patient-centered outcomes and clinical trial results in an era of multiple emerging new agents with novel mechanisms of action.

The challenge of clinical end points in sickle cell disease.

As most patients with sickle cell disease (SCD) do not have access to curative therapies, the availability of drug therapies that can modify disease severity remains highly desirable. Despite an increased understanding of the pathophysiology of SCD, only 4 drugs are approved by the US Food and Drugs Administration. Most drug trials in SCD have involved the use of acute pain episodes as the primary clinical end point. These studies have typically been to prevent or shorten the duration of such episodes. To date, no drug has received regulatory approval for shortening the duration of acute vaso-occlusive complications, likely highlighting the complex pathophysiology of acute pain episodes. Trials to prevent acute pain episodes have largely evaluated those episodes requiring health care use as a surrogate end point. However, with differences in culture and health care practices among countries, health care use may not reliably predict clinically important effects on acute pain episodes. This article discusses issues related to the use of health care use as the primary end point for prevention trials of acute pain episodes and highlights the importance of evaluating patient-reported outcomes as well as other SCD-related complications as outcome measures.

Chronic conditions, late mortality, and health status after childhood AML: a Childhood Cancer Survivor Study report.

Five-year survival following childhood acute myeloid leukemia (AML) has increased following improvements in treatment and supportive care. Long-term health outcomes are unknown. To address this, cumulative incidence of late mortality and grades 3 to 5 chronic health condition (CHC) were estimated among 5-year AML survivors diagnosed between 1970 and 1999. Survivors were compared by treatment group (hematopoietic cell transplantation [HCT], chemotherapy with cranial radiation [chemo + CRT], chemotherapy only [chemo-only]), and diagnosis decade. Self-reported health status was compared across treatments, diagnosis decade, and with siblings. Among 856 survivors (median diagnosis age, 7.1 years; median age at last follow-up, 29.4 years), 20-year late mortality cumulative incidence was highest after HCT (13.9%; 95% confidence interval [CI], 10.0%-17.8%; chemo + CRT, 7.6%; 95% CI, 2.2%-13.1%; chemo-only, 5.1%; 95% CI, 2.8%-7.4%). Cumulative incidence of mortality for HCT survivors diagnosed in the 1990s (8.5%; 95% CI, 4.1%-12.8%) was lower vs those diagnosed in the 1970s (38.9%; 95% CI, 16.4%-61.4%). Most survivors did not experience any grade 3 to 5 CHC after 20 years (HCT, 45.8%; chemo + CRT, 23.7%; chemo-only, 27.0%). Furthermore, a temporal reduction in CHC cumulative incidence was seen after HCT (1970s, 76.1%; 1990s, 38.3%; P = .02), mirroring reduced use of total body irradiation. Self-reported health status was good to excellent for 88.2% of survivors; however, this was lower than that for siblings (94.8%; P < .0001). Although HCT is associated with greater long-term morbidity and mortality than chemotherapy-based treatment, gaps have narrowed, and all treatment groups report favorable health status.

Analysis of 567,758 randomized controlled trials published over 30 years reveals trends in phrases used to discuss results that do not reach statistical significance.

The power of language to modify the reader's perception of interpreting biomedical results cannot be underestimated. Misreporting and misinterpretation are pressing problems in randomized controlled trials (RCT) output. This may be partially related to the statistical significance paradigm used in clinical trials centered around a P value below 0.05 cutoff. Strict use of this P value may lead to strategies of clinical researchers to describe their clinical results with P values approaching but not reaching the threshold to be "almost significant." The question is how phrases expressing nonsignificant results have been reported in RCTs over the past 30 years. To this end, we conducted a quantitative analysis of English full texts containing 567,758 RCTs recorded in PubMed between 1990 and 2020 (81.5% of all published RCTs in PubMed). We determined the exact presence of 505 predefined phrases denoting results that approach but do not cross the line of formal statistical significance (P < 0.05). We modeled temporal trends in phrase data with Bayesian linear regression. Evidence for temporal change was obtained through Bayes factor (BF) analysis. In a randomly sampled subset, the associated P values were manually extracted. We identified 61,741 phrases in 49,134 RCTs indicating almost significant results (8.65%; 95% confidence interval (CI): 8.58% to 8.73%). The overall prevalence of these phrases remained stable over time, with the most prevalent phrases being "marginally significant" (in 7,735 RCTs), "all but significant" (7,015), "a nonsignificant trend" (3,442), "failed to reach statistical significance" (2,578), and "a strong trend" (1,700). The strongest evidence for an increased temporal prevalence was found for "a numerical trend," "a positive trend," "an increasing trend," and "nominally significant." In contrast, the phrases "all but significant," "approaches statistical significance," "did not quite reach statistical significance," "difference was apparent," "failed to reach statistical significance," and "not quite significant" decreased over time. In a random sampled subset of 29,000 phrases, the manually identified and corresponding 11,926 P values, 68,1% ranged between 0.05 and 0.15 (CI: 67. to 69.0; median 0.06). Our results show that RCT reports regularly contain specific phrases describing marginally nonsignificant results to report P values close to but above the dominant 0.05 cutoff. The fact that the prevalence of the phrases remained stable over time indicates that this practice of broadly interpreting P values close to a predefined threshold remains prevalent. To enhance responsible and transparent interpretation of RCT results, researchers, clinicians, reviewers, and editors may reduce the focus on formal statistical significance thresholds and stimulate reporting of P values with corresponding effect sizes and CIs and focus on the clinical relevance of the statistical difference found in RCTs.

Use of the Win Ratio Analysis in Critical Care Trials.

Composite outcomes are commonly used in critical care trials to estimate the treatment effect of an intervention. A significant limitation of classical analytic approaches is that they assign equal statistical importance to each component in a composite, even if these do not have the same clinical importance (i.e., in a composite of death and organ failure, death is clearly more important). The win ratio (WR) method has been proposed as an alternative for trial outcomes evaluation, as it effectively assesses events based on their clinical relevance (i.e., hierarchical order) by comparing each patient in the intervention group with their counterparts in the control group. This statistical approach is increasingly used in cardiovascular outcome trials. However, WR may be useful to unveil treatment effects also in the critical care setting, because these trials are typically moderately sized, thus limiting the statistical power to detect small differences between groups, and often rely on composite outcomes that include several components of different clinical importance. Notably, the advantages of this approach may be offset by several drawbacks (such as ignoring ties and difficulties in selecting and ranking endpoints) and challenges in appropriate clinical interpretation (i.e., establishing clinical meaningfulness of the observed effect size). In this perspective article, we present some key elements to implementing WR statistics in critical care trials, providing an overview of strengths, drawbacks, and potential applications of this method. To illustrate, we conduct a reevaluation of the HYPO-ECMO (Hypothermia during Venoarterial Extracorporeal Membrane Oxygenation) trial using the WR framework as a case example.

Using genetic variation to disentangle the complex relationship between food intake and health outcomes.

Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

A recombinant VSV-vectored vaccine rapidly protects nonhuman primates against lethal Nipah virus disease.

SignificanceConcern has increased about the pandemic potential of Nipah virus (NiV). Similar to SARS-CoV-2, NiV is an RNA virus that is transmitted by respiratory droplets. There are currently no NiV vaccines licensed for human use. While several preventive vaccines have shown promise in protecting animals against lethal NiV disease, most studies have assessed protection 1 mo after vaccination. However, in order to contain and control outbreaks, vaccines that can rapidly confer protection in days rather than months are needed. Here, we show that a recombinant vesicular stomatitis virus vector expressing the NiV glycoprotein can completely protect monkeys vaccinated 7 d prior to NiV exposure and 67% of animals vaccinated 3 d before NiV challenge.

Estimation of the Time-Varying Effective Reproductive Number of COVID-19 Based on Multivariate Time Series of Severe Health Outcomes.

The time-varying effective reproduction number (Rt at time t) measures the transmissibility of SARS-CoV-2 and is conventionally based on daily case counts, which may suffer from time-varying ascertainment. We analyzed Rt estimates from case counts and severe COVID-19 (intensive care unit admissions, severe or critical cases, and mortality) across 2022 in Hong Kong's fifth and sixth waves of infection. Within the fifth wave, the severe disease-based Rt (3.5) was significantly higher than the case-based Rt (2.4) but not in the sixth wave. During periods with fluctuating underreporting, data based on severe diseases may provide more reliable Rt estimates.

Who Gets Sick From COVID-19? Sociodemographic Correlates of Severe Adult Health Outcomes During Alpha- and Delta-Variant Predominant Periods: September 2020-November 2021.

BACKGROUND: Because COVID-19 case data do not capture most SARS-CoV-2 infections, the actual risk of severe disease and death per infection is unknown. Integrating sociodemographic data into analysis can show consequential health disparities. METHODS: Data were merged from September 2020 to November 2021 from 6 national surveillance systems in matched geographic areas and analyzed to estimate numbers of COVID-19-associated cases, emergency department visits, and deaths per 100 000 infections. Relative risks of outcomes per infection were compared by sociodemographic factors in a data set including 1490 counties from 50 states and the District of Columbia, covering 71% of the US population. RESULTS: Per infection with SARS-CoV-2, COVID-19-related morbidity and mortality were higher among non-Hispanic American Indian and Alaska Native persons, non-Hispanic Black persons, and Hispanic or Latino persons vs non-Hispanic White persons; males vs females; older people vs younger; residents in more socially vulnerable counties vs less; those in large central metro areas vs rural; and people in the South vs the Northeast. DISCUSSION: Meaningful disparities in COVID-19 morbidity and mortality per infection were associated with sociodemography and geography. Addressing these disparities could have helped prevent the loss of tens of thousands of lives.

A minimum data set-Core outcome set, core data elements, and core measurement set-For degenerative cervical myelopathy research (AO Spine RECODE DCM): A consensus study.

BACKGROUND: Degenerative cervical myelopathy (DCM) is a progressive chronic spinal cord injury estimated to affect 1 in 50 adults. Without standardised guidance, clinical research studies have selected outcomes at their discretion, often underrepresenting the disease and limiting comparability between studies. Utilising a standard minimum data set formed via multi-stakeholder consensus can address these issues. This combines processes to define a core outcome set (COS)-a list of key outcomes-and core data elements (CDEs), a list of key sampling characteristics required to interpret the outcomes. Further "how" these outcomes should be measured and/or reported is then defined in a core measurement set (CMS). This can include a recommendation of a standardised time point at which outcome data should be reported. This study defines a COS, CDE, and CMS for DCM research. METHODS AND FINDINGS: A minimum data set was developed using a series of modified Delphi processes. Phase 1 involved the setup of an international DCM stakeholder group. Phase 2 involved the development of a longlist of outcomes, data elements, and formation into domains. Phase 3 prioritised the outcomes and CDEs using a two-stage Delphi process. Phase 4 determined the final DCM minimal data set using a consensus meeting. Using the COS, Phase 5 finalised definitions of the measurement construct for each outcome. In Phase 6, a systematic review of the literature was performed, to scope and define the psychometric properties of measurement tools. Phase 7 used a modified Delphi process to inform the short-listing of candidate measurement tools. The final measurement set was then formed through a consensus meeting (Phase 8). To support implementation, the data set was then integrated into template clinical research forms (CRFs) for use in future clinical trials (Phase 9). In total, 28 outcomes and 6 domains (Pain, Neurological Function, Life Impact, Radiology, Economic Impact, and Adverse Events) were entered into the final COS. Thirty two outcomes and 4 domains (Individual, Disease, Investigation, and Intervention) were entered into the final CDE. Finally, 4 outcome instruments (mJOA, NDI, SF-36v2, and SAVES2) were identified for the CMS, with a recommendation for trials evaluating outcomes after surgery, to include baseline measurement and at 6 months from surgery. CONCLUSIONS: The AO Spine RECODE-DCM has produced a minimum data set for use in DCM clinical trials today. These are available at https://myelopathy.org/minimum-dataset/. While it is anticipated the CDE and COS have strong and durable relevance, it is acknowledged that new measurement tools, alongside an increasing transition to study patients not undergoing surgery, may necessitate updates and adaptation, particularly with respect to the CMS.

Health outcomes after myocardial infarction: A population study of 56 million people in England.

BACKGROUND: The occurrence of a range of health outcomes following myocardial infarction (MI) is unknown. Therefore, this study aimed to determine the long-term risk of major health outcomes following MI and generate sociodemographic stratified risk charts in order to inform care recommendations in the post-MI period and underpin shared decision making. METHODS AND FINDINGS: This nationwide cohort study includes all individuals aged ≥18 years admitted to one of 229 National Health Service (NHS) Trusts in England between 1 January 2008 and 31 January 2017 (final follow-up 27 March 2017). We analysed 11 non-fatal health outcomes (subsequent MI and first hospitalisation for heart failure, atrial fibrillation, cerebrovascular disease, peripheral arterial disease, severe bleeding, renal failure, diabetes mellitus, dementia, depression, and cancer) and all-cause mortality. Of the 55,619,430 population of England, 34,116,257 individuals contributing to 145,912,852 hospitalisations were included (mean age 41.7 years (standard deviation [SD 26.1]); n = 14,747,198 (44.2%) male). There were 433,361 individuals with MI (mean age 67.4 years [SD 14.4)]; n = 283,742 (65.5%) male). Following MI, all-cause mortality was the most frequent event (adjusted cumulative incidence at 9 years 37.8% (95% confidence interval [CI] [37.6,37.9]), followed by heart failure (29.6%; 95% CI [29.4,29.7]), renal failure (27.2%; 95% CI [27.0,27.4]), atrial fibrillation (22.3%; 95% CI [22.2,22.5]), severe bleeding (19.0%; 95% CI [18.8,19.1]), diabetes (17.0%; 95% CI [16.9,17.1]), cancer (13.5%; 95% CI [13.3,13.6]), cerebrovascular disease (12.5%; 95% CI [12.4,12.7]), depression (8.9%; 95% CI [8.7,9.0]), dementia (7.8%; 95% CI [7.7,7.9]), subsequent MI (7.1%; 95% CI [7.0,7.2]), and peripheral arterial disease (6.5%; 95% CI [6.4,6.6]). Compared with a risk-set matched population of 2,001,310 individuals, first hospitalisation of all non-fatal health outcomes were increased after MI, except for dementia (adjusted hazard ratio [aHR] 1.01; 95% CI [0.99,1.02];p = 0.468) and cancer (aHR 0.56; 95% CI [0.56,0.57];p < 0.001). The study includes data from secondary care only-as such diagnoses made outside of secondary care may have been missed leading to the potential underestimation of the total burden of disease following MI. CONCLUSIONS: In this study, up to a third of patients with MI developed heart failure or renal failure, 7% had another MI, and 38% died within 9 years (compared with 35% deaths among matched individuals). The incidence of all health outcomes, except dementia and cancer, was higher than expected during the normal life course without MI following adjustment for age, sex, year, and socioeconomic deprivation. Efforts targeted to prevent or limit the accrual of chronic, multisystem disease states following MI are needed and should be guided by the demographic-specific risk charts derived in this study.

Integrative multiomics analysis highlights immune-cell regulatory mechanisms and shared genetic architecture for 14 immune-associated diseases and cancer outcomes.

Developing functional insight into the causal molecular drivers of immunological disease is a critical challenge in genomic medicine. Here, we systematically apply Mendelian randomization (MR), genetic colocalization, immune-cell-type enrichment, and phenome-wide association methods to investigate the effects of genetically predicted gene expression on ten immune-associated diseases and four cancer outcomes. Using whole blood-derived estimates for regulatory variants from the eQTLGen consortium (n = 31,684), we constructed genetic risk scores for 10,104 genes. Applying the inverse-variance-weighted MR method transcriptome wide while accounting for linkage disequilibrium structure identified 664 unique genes with evidence of a genetically predicted effect on at least one disease outcome (p < 4.81 × 10-5). We next undertook genetic colocalization to investigate cell-type-specific effects at these loci by using gene expression data derived from 18 types of immune cells. This highlighted many cell-type-dependent effects, such as PRKCQ expression and asthma risk (posterior probability = 0.998), which was T cell specific. Phenome-wide analyses on 311 complex traits and endpoints allowed us to explore shared genetic architecture and prioritize key drivers of disease risk, such as CASP10, which provided evidence of an effect on seven cancer-related outcomes. Our atlas of results can be used to characterize known and novel loci in immune-associated disease and cancer susceptibility, both in terms of elucidating cell-type-dependent effects as well as dissecting shared disease pathways and pervasive pleiotropy. As an exemplar, we have highlighted several key findings in this study, although similar evaluations can be conducted via our interactive web platform.

Surgical Outcome Reporting. Moving From a Comic to a Tragic Opera?

OBJECTIVES: To assess the current quality of surgical outcome reporting in the medical literature and to provide recommendations for improvement. BACKGROUND: In 1996, The Lancet labeled surgery as a "comic opera" mostly referring to the poor quality of outcome reporting in the literature impeding improvement in surgical quality and patient care. METHODS: We screened 3 first-tier and 2 second-tier surgical journals, as well as 3 leading medical journals for original articles reporting on results of surgical procedures published over a recent 18-month period. The quality of outcome reporting was assessed using a prespecified 12-item checklist. RESULTS: Six hundred twenty-seven articles reporting surgical outcomes were analyzed, including 125 randomized controlled trials. Only 1 (0.2%) article met all 12 criteria of the checklist, whereas 356 articles (57%) fulfilled less than half of the criteria. The poorest reporting was on cumulative morbidity burden, which was missing in 94% of articles (n=591) as well as patient-reported outcomes missing in 83% of publications (n=518). Comparing journal groups for the individual criterion, we found moderate to very strong statistical evidence for better quality of reporting in high versus lower impact journals for 7 of 12 criteria and strong statistical evidence for better reporting of patient-reported outcomes in medical versus surgical journals ( P <0·001). CONCLUSIONS: The quality of outcomes reporting in the medical literature remains poor, lacking improvement over the past 20 years on most key end points. The implementation of standardized outcome reporting is urgently needed to minimize biased interpretation of data thereby enabling improved patient care and the elaboration of meaningful guidelines.

The heterogeneous effects of China's hierarchical medical system reforms on health service utilisation and health outcomes among elderly populations: a longitudinal quasi-experimental study.

BACKGROUND: System-wide, comprehensive, primary health care (PHC)-oriented health reforms are infrequently introduced in low-income and middle-income countries and often poorly studied. China initiated a large-scale reform in 2015 that included multiple policies: partial gatekeeping, a family physician scheme, and increased system integration. These policies aimed to build a PHC-oriented health system and improve primary care utilisation. This study assessed the heterogeneous effects of the reforms on health service utilisation and health outcomes across regions and over time. METHODS: In this longitudinal quasi-experimental study, we used longitudinal data (2011-18) from a national survey on elderly populations and governmental yearbooks. This study exploits the staggered rollout of the reforms at the city level identified using web-scrapping. We employed an event study design to assess reform effects on (1) visits to PHC facilities, (2) admissions to hospital, (3) out-of-pocket expenditures (OOPEs), and (4) self-reported health. Models were adjusted for city and time fixed effects, along with demographic and socioeconomic characteristics at individual and provincial levels. Analysis was separated into rural and urban populations. FINDINGS: 18 988 Chinese individuals aged 45 and older (mean age 60·4 years [SD 10·3], 9990 [52·6%] women, 8998 [47·4%] men) were included in the analysis. The reform was associated with increasing odds of visiting PHC facilities among rural populations, which became stronger in the 2 years after the reform (adjusted odd ratio [aOR] 1·35, 95% CI 1·02-1·84, p=0·0374; absolute effect sizes [probability] 3%) before it faded. Meanwhile, urban populations were unaffected (from aOR 1·22, 0·82-1·81 to 0·89, 0·50-1·57). The reform did not have a significant effect on admission to hospital (rural: from 0·97, 0·72-1·31 to 1·47, 0·85-2·55; urban: from 1·00, 0·69-1·43 to 1·59, 0·76-3·30) or OOPEs (rural: from 260·32 Chinese Yuan, 95% CI -6·34 to 526·97, to 693·07 Chinese Yuan, -102·96 to 1489·09; urban: from 235·37 Chinese Yuan, -405·10 to 875·83, to 859·93 Chinese Yuan, -199·02 to 1918·88). Urban populations reported higher self-reported health after the reforms than the year before the reforms (1·50, 1·12-2·01, p=0·0002; 5%). INTERPRETATION: System-wide PHC-oriented reforms might contribute to short-term increases in primary care utilisation in elderly populations with implications for urban-rural inequalities. Effects on financial protection and health inequality were limited. Efforts in improving the accessibility and quality of primary care in deprived areas are indispensable to addressing the persistent inverse care law and to achieving Universal Health Coverage for all countries. FUNDING: None.

How does the environment in and around the home affect social care and health outcomes for older people? A national longitudinal dynamic cohort study.

BACKGROUND: Reducing the burden of falls and fall-related admissions to hospital and care homes is an important policy area because falls cause significant injury leading to a reduced quality of life. We investigated the effect of the environment around people's homes on the risk of falls for older people in Wales. METHODS: In this longitudinal cohort study, we created a dynamic national e-cohort of individuals aged 60 years or older living in Wales between Jan 1, 2010, and Dec 31, 2019. Using the Secure Anonymised Information Linkage Databank, we linked routinely collected, anonymised health-data on general practitioner (GP) appointments; hospital and emergency admissions; and longitudinal individual-level demographic data to metrics detailing the built environment and deprivation as determined by the Welsh Index of Multiple Deprivation. Using adjusted cox regression models, we assessed how the risk of a fall changed with sex, age, deprivation quintile, urban or rural classification, household occupancy, care status, frailty, dementia diagnosis, and built environment metrics. Built environments of urban and rural areas are very different, so we stratified our analysis by urbanicity to compare these associations in each setting. FINDINGS: We analysed 5 536 444 person-years of data from 931 830 individuals (sex: 51·5% female, 48·5% male; age: 69·2% aged 60-64 years, 12·3% aged 65-69 years, 13·3% aged 70-79 years, 4·4% aged 80-89 years, and 0·7% aged ≥90 years). 154 060 (16·5%) had a fall between joining the cohort and Dec 31, 2019. Men had a lower risk of falling than women (adjusted hazard ratio [aHR] 0·736 [0·729-0·742]), and the risk increased with age compared with individuals aged 60-64 years (1·395 [1·378-1·412] for 65-69 years, 1·892 [1·871-1·913] for 70-79 years, 2·668 [2·623-2·713] for 80-89 years, 3·196 [3·063-3·335] for ≥90 years) and with frailty compared with fit individuals (1·609 [1·593-1·624] for mild frailty, 2·263 [2·234-2·293] for moderate frailty, and 2·833 [2·770-2·897] for severe frailty). Those living in rural areas were less likely to fall than those in urban areas (0·711 [0·702-0·720]). All p values were less than 0·0001. INTERPRETATION: Although preliminary, these results corroborate current knowledge that as we age and become frailer, the risk of falling increases. The effect of urbanicity on risk of fall suggests that the built environment could be associated with fall risk. We only detected falls that caused emergency or hospital admission, leading to potential selection bias. Nevertheless, this research could help guide policy to reduce the incidence of injuries caused by falls in older people. FUNDING: Health and Care Research Wales.

Improving health outcomes of people with diabetes: target setting for the WHO Global Diabetes Compact.

The Global Diabetes Compact is a WHO-driven initiative uniting stakeholders around goals of reducing diabetes risk and ensuring that people with diabetes have equitable access to comprehensive, affordable care and prevention. In this report we describe the development and scientific basis for key health metrics, coverage, and treatment targets accompanying the Compact. We considered metrics across four domains: factors at a structural, system, or policy level; processes of care; behaviours and biomarkers such as glycated haemoglobin (HbA1c); and health events and outcomes; and three risk tiers (diagnosed diabetes, high risk, or whole population), and reviewed and prioritised them according to their health importance, modifiability, data availability, and global inequality. We reviewed the global distribution of each metric to set targets for future attainment. This process led to five core national metrics and target levels for UN member states: (1) of all people with diabetes, at least 80% have been clinically diagnosed; and, for people with diagnosed diabetes, (2) 80% have HbA1c concentrations below 8·0% (63·9 mmol/mol); (3) 80% have blood pressure lower than 140/90 mm Hg; (4) at least 60% of people 40 years or older are receiving therapy with statins; and (5) each person with type 1 diabetes has continuous access to insulin, blood glucose meters, and test strips. We also propose several complementary metrics that currently have limited global coverage, but warrant scale-up in population-based surveillance systems. These include estimation of cause-specific mortality, and incidence of end-stage kidney disease, lower-extremity amputations, and incidence of diabetes. Primary prevention of diabetes and integrated care to prevent long-term complications remain important areas for the development of new metrics and targets. These metrics and targets are intended to drive multisectoral action applied to individuals, health systems, policies, and national health-care access to achieve the goals of the Global Diabetes Compact. Although ambitious, their achievement can result in broad health benefits for people with diabetes.