Cardiovascular risk prediction in type 2 diabetes before and after widespread screening: a derivation and validation study.

BACKGROUND: Until recently, most patients with diabetes worldwide have been diagnosed when symptomatic and have high cardiovascular risk, meaning most should be prescribed cardiovascular preventive medications. However, in New Zealand, a world-first national programme led to approximately 90% of eligible adults being screened for diabetes by 2016, up from 50% in 2012, identifying many asymptomatic patients with recent-onset diabetes. We hypothesised that cardiovascular risk prediction equations derived before widespread screening would now significantly overestimate risk in screen-detected patients. METHODS: New Zealanders aged 30-74 years with type 2 diabetes and without known cardiovascular disease, heart failure, or substantial renal impairment were identified from the 400 000-person PREDICT primary care cohort study between Oct 27, 2004, and Dec 30, 2016, covering the period before and after widespread screening. Sex-specific equations estimating 5-year risk of cardiovascular disease were developed using Cox regression models, with 18 prespecified predictors, including diabetes-related and renal function measures. Equation performance was compared with an equivalent equation derived in the New Zealand Diabetes Cohort Study (NZDCS), which recruited between 2000 and 2006, before widespread screening. FINDINGS: 46 652 participants were included in the PREDICT-1° Diabetes subcohort, of whom 4114 experienced first cardiovascular events during follow-up (median 5·2 years, IQR 3·3-7·4). 14 829 (31·8%) were not taking oral hypoglycaemic medications or insulin at baseline. Median 5-year cardiovascular risk estimated by the new equations was 4·0% (IQR 2·3-6·8) in women and 7·1% (4·5-11·2) in men. The older NZDCS equation overestimated median cardiovascular risk by three times in women (median 14·2% [9·7-20·0]) and two times in men (17·1% [4·5-20·0]). Model and discrimination performance measures for PREDICT-1° Diabetse equations were also significantly better than for the NZDCS equation (eg, for women: R2=32% [95% CI 29-34], Harrell's C=0·73 [0·72-0·74], Royston's D=1·410 [1·330-1·490] vs R2=24% [21-26], C=0·69 [0·67-0·70], and D=1·147 [1·107-1·187]). INTERPRETATION: International treatment guidelines still consider most people with diabetes to be at high cardiovascular risk; however, we show that recent widespread diabetes screening has radically changed the cardiovascular risk profile of people with diabetes in New Zealand. Many of these patients have normal renal function, are not dispensed glucose-lowering medications, and have low cardiovascular risk. These findings have clear international implications as increased diabetes screening is inevitable due to increasing obesity, simpler screening tests, and the introduction of new-generation glucose-lowering medications that prevent cardiovascular events. Cardiovascular risk prediction equations derived from contemporary diabetes populations, with multiple diabetes-related and renal function predictors, will be required to better differentiate between low-risk and high-risk patients in this increasingly heterogeneous population and to inform appropriate non-pharmacological management and cost-effective targeting of expensive new medications. FUNDING: Health Research Council of New Zealand, Heart Foundation of New Zealand, and Healthier Lives National Science Challenge.

Lithium-ion battery degradation: how to model it.

Predicting lithium-ion battery degradation is worth billions to the global automotive, aviation and energy storage industries, to improve performance and safety and reduce warranty liabilities. However, very few published models of battery degradation explicitly consider the interactions between more than two degradation mechanisms, and none do so within a single electrode. In this paper, the first published attempt to directly couple more than two degradation mechanisms in the negative electrode is reported. The results are used to map different pathways through the complicated path dependent and non-linear degradation space. Four degradation mechanisms are coupled in PyBaMM, an open source modelling environment uniquely developed to allow new physics to be implemented and explored quickly and easily. Crucially it is possible to see 'inside the model and observe the consequences of the different patterns of degradation, such as loss of lithium inventory and loss of active material. For the same cell, five different pathways that can result in end-of-life have already been found, depending on how the cell is used. Such information would enable a product designer to either extend life or predict life based upon the usage pattern. However, parameterization of the degradation models remains as a major challenge, and requires the attention of the international battery community.

Dual versus single long-acting bronchodilator use could raise acute coronary syndrome risk by over 50%: A population-based nested case-control study.

BACKGROUND: Coronary heart disease occurs more frequently among patients with chronic obstructive pulmonary disease (COPD) compared to those without COPD. While some research suggests that long-acting bronchodilators might confer an additional risk of acute coronary syndrome (ACS), information from real-world clinical practice about the cardiovascular impact of using two versus one long-acting bronchodilator for COPD is limited. We undertook a population-based nested case-control study to estimate the risk of ACS in users of both a long-acting muscarinic antagonist (LAMA) and a long-acting beta2-agonist (LABA) relative to users of a LAMA. METHODS: The study was based on the primary care PREDICT Cardiovascular Disease Cohort and linked data from regional laboratories and the New Zealand Ministry of Health's national data collections. The underlying cohort (n = 29,993) comprised patients aged 45-84 years, who initiated treatment with a LAMA and/or LABA for COPD between 1 February 2006 and 11 October 2016. 1490 ACS cases were matched to 13,550 controls by date of birth, sex, date of cohort entry (first long-acting bronchodilator dispensing), and COPD severity. RESULTS: Relative to current use of LAMA therapy, current use of LAMA and LABA dual therapy was associated with a significantly higher risk of ACS (adjusted OR = 1.72; [95% CI: 1.28-2.31]). CONCLUSION: Dual long-acting bronchodilator therapy, rather than LAMA mono-therapy, could increase the risk of ACS by more than 50%. This has important implications for decisions about the potential benefit/harm ratio of COPD treatment intensification, given the modest benefits of dual therapy.

Lithium ion battery degradation: what you need to know.

The expansion of lithium-ion batteries from consumer electronics to larger-scale transport and energy storage applications has made understanding the many mechanisms responsible for battery degradation increasingly important. The literature in this complex topic has grown considerably; this perspective aims to distil current knowledge into a succinct form, as a reference and a guide to understanding battery degradation. Unlike other reviews, this work emphasises the coupling between the different mechanisms and the different physical and chemical approaches used to trigger, identify and monitor various mechanisms, as well as the various computational models that attempt to simulate these interactions. Degradation is separated into three levels: the actual mechanisms themselves, the observable consequences at cell level called modes and the operational effects such as capacity or power fade. Five principal and thirteen secondary mechanisms were found that are generally considered to be the cause of degradation during normal operation, which all give rise to five observable modes. A flowchart illustrates the different feedback loops that couple the various forms of degradation, whilst a table is presented to highlight the experimental conditions that are most likely to trigger specific degradation mechanisms. Together, they provide a powerful guide to designing experiments or models for investigating battery degradation.

Predicting Bleeding Risk to Guide Aspirin Use for the Primary Prevention of Cardiovascular Disease: A Cohort Study.

Background: Many prognostic models for cardiovascular risk can be used to estimate aspirin's absolute benefits, but few bleeding risk models are available to estimate its likely harms. Objective: To develop prognostic bleeding risk models among persons in whom aspirin might be considered for the primary prevention of cardiovascular disease (CVD). Design: Prospective cohort study. Setting: New Zealand primary care. Participants: The study cohort comprised 385 191 persons aged 30 to 79 years whose CVD risk was assessed between 2007 and 2016. Those with indications for or contraindications to aspirin and those who were already receiving antiplatelet or anticoagulant therapy were excluded. Measurements: For each sex, Cox proportional hazards models were developed to predict major bleeding risk; participants were censored at the earliest of the date on which they first met an exclusion criterion, date of death, or study end date (30 June 2017). The main models included the following predictors: demographic characteristics (age, ethnicity, and socioeconomic deprivation), clinical measurements (systolic blood pressure and ratio of total-high-density lipoprotein cholesterol), family history of premature CVD, medical history (smoking, diabetes, bleeding, peptic ulcer disease, cancer, chronic liver disease, chronic pancreatitis, or alcohol-related conditions), and medication use (nonsteroidal anti-inflammatory agents, corticosteroids, and selective serotonin reuptake inhibitors). Results: During 1 619 846 person-years of follow-up, 4442 persons had major bleeding events (of which 313 [7%] were fatal). The main models predicted a median 5-year bleeding risk of 1.0% (interquartile range, 0.8% to 1.5%) in women and 1.1% (interquartile range, 0.7% to 1.6%) in men. Plots of predicted-against-observed event rates showed good calibration throughout the risk range. Limitation: Hemoglobin level, platelet count, and body mass index were excluded from the main models because of high numbers of missing values, and the models were not externally validated in non-New Zealand populations. Conclusion: Prognostic bleeding risk models were developed that can be used to estimate the absolute bleeding harms of aspirin among persons in whom aspirin is being considered for the primary prevention of CVD. Primary Funding Source: The Health Research Council of New Zealand.

Personalized Prediction of Cardiovascular Benefits and Bleeding Harms From Aspirin for Primary Prevention: A Benefit-Harm Analysis.

Background: Whether the benefits of aspirin for the primary prevention of cardiovascular disease (CVD) outweigh its bleeding harms in some patients is unclear. Objective: To identify persons without CVD for whom aspirin would probably result in a net benefit. Design: Individualized benefit-harm analysis based on sex-specific risk scores and estimates of the proportional effect of aspirin on CVD and major bleeding from a 2019 meta-analysis. Setting: New Zealand primary care. Participants: 245 028 persons (43.6% women) aged 30 to 79 years without established CVD who had their CVD risk assessed between 2012 and 2016. Measurements: The net effect of aspirin was calculated for each participant by subtracting the number of CVD events likely to be prevented (CVD risk score × proportional effect of aspirin on CVD risk) from the number of major bleeds likely to be caused (major bleed risk score × proportional effect of aspirin on major bleeding risk) over 5 years. Results: 2.5% of women and 12.1% of men were likely to have a net benefit from aspirin treatment for 5 years if 1 CVD event was assumed to be equivalent in severity to 1 major bleed, increasing to 21.4% of women and 40.7% of men if 1 CVD event was assumed to be equivalent to 2 major bleeds. Net benefit subgroups had higher baseline CVD risk, higher levels of most established CVD risk factors, and lower levels of bleeding-specific risk factors than net harm subgroups. Limitations: Risk scores and effect estimates were uncertain. Effects of aspirin on cancer outcomes were not considered. Applicability to non-New Zealand populations was not assessed. Conclusion: For some persons without CVD, aspirin is likely to result in net benefit. Primary Funding Source: Health Research Council of New Zealand.

Cardiovascular disease risk prediction equations in 400 000 primary care patients in New Zealand: a derivation and validation study.

BACKGROUND: Most cardiovascular disease risk prediction equations in use today were derived from cohorts established last century and with participants at higher risk but less socioeconomically and ethnically diverse than patients they are now applied to. We recruited a nationally representative cohort in New Zealand to develop equations relevant to patients in contemporary primary care and compared the performance of these new equations to equations that are recommended in the USA. METHODS: The PREDICT study automatically recruits participants in routine primary care when general practitioners in New Zealand use PREDICT software to assess their patients' risk profiles for cardiovascular disease, which are prospectively linked to national ICD-coded hospitalisation and mortality databases. The study population included male and female patients in primary care who had no prior cardiovascular disease, renal disease, or congestive heart failure. New equations predicting total cardiovascular disease risk were developed using Cox regression models, which included clinical predictors plus an area-based deprivation index and self-identified ethnicity. Calibration and discrimination performance of the equations were assessed and compared with 2013 American College of Cardiology/American Heart Association Pooled Cohort Equations (PCEs). The additional predictors included in new PREDICT equations were also appended to the PCEs to determine whether they were independent predictors in the equations from the USA. FINDINGS: Outcome events were derived for 401 752 people aged 30-74 years at the time of their first PREDICT risk assessment between Aug 27, 2002, and Oct 12, 2015, representing about 90% of the eligible population. The mean follow-up was 4·2 years, and a third of participants were followed for 5 years or more. 15 386 (4%) people had cardiovascular disease events (1507 [10%] were fatal, and 8549 [56%] met the PCEs definition of hard atherosclerotic cardiovascular disease) during 1 685 521 person-years follow-up. The median 5-year risk of total cardiovascular disease events predicted by the new equations was 2·3% in women and 3·2% in men. Multivariable adjusted risk increased by about 10% per quintile of socioeconomic deprivation. Maori, Pacific, and Indian patients were at 13-48% higher risk of cardiovascular disease than Europeans, and Chinese or other Asians were at 25-33% lower risk of cardiovascular disease than Europeans. The PCEs overestimated of hard atherosclerotic cardiovascular disease by about 40% in men and by 60% in women, and the additional predictors in the new equations were also independent predictors in the PCEs. The new equations were significantly better than PCEs on all performance metrics. INTERPRETATION: We constructed a large prospective cohort study representing typical patients in primary care in New Zealand who were recommended for cardiovascular disease risk assessment. Most patients are now at low risk of cardiovascular disease, which explains why the PCEs based mainly on old cohorts substantially overestimate risk. Although the PCEs and many other equations will need to be recalibrated to mitigate overtreatment of the healthy majority, they also need new predictors that include measures of socioeconomic deprivation and multiple ethnicities to identify vulnerable high-risk subpopulations that might otherwise be undertreated. FUNDING: Health Research Council of New Zealand, Heart Foundation of New Zealand, and Healthier Lives National Science Challenge.

Annual Risk of Major Bleeding Among Persons Without Cardiovascular Disease Not Receiving Antiplatelet Therapy.

Importance: A decision to initiate aspirin therapy for primary prevention of cardiovascular disease (CVD) requires consideration of both treatment benefits and harms. The most significant harm associated with aspirin is major bleeding, yet there is a paucity of data on bleeding risk in suitable community populations. Objective: To determine the risk of major bleeding among people without CVD who are not receiving antiplatelet therapy. Design, Setting, and Participants: Prospective cohort study of 359 166 individuals aged 30 to 79 years receiving primary care in New Zealand who had CVD risk assessment between 2002 and 2015. Participants were censored at the earliest date on which they had a first major bleeding event, died, or met any baseline cohort exclusion criteria or the study end date of December 31, 2015. Analyses were repeated after excluding people with medical conditions associated with increased bleeding risk (non-high-risk cohort; n=305 057) and after further excluding people receiving other medications associated with increased bleeding risk (nonmedication cohort; n=240 254). Exposures: Sex and age group in 10-year bands from 30 to 79 years. Main Outcomes and Measures: Risk of a major bleeding event (hospitalization or death associated with bleeding); nonfatal gastrointestinal tract bleeding; and gastrointestinal tract bleeding-related case fatality. Results: Mean participant age was 54 years (SD, 10 years), 44% were women, and 57% were European. Among the 359 166 individuals in the baseline cohort, 3976 had a major bleeding event during 1 281 896 person-years of follow-up. Most had gastrointestinal (GI) bleeding (n=2910 [73%]). There were 274 fatal bleeding events (7%), of which 153 were intracerebral. The risk of a nonfatal GI bleeding event per 1000 person-years was 2.19 (95% CI, 2.11-2.27), 1.77 (95% CI, 1.69-1.85) and 1.61 (95% CI, 1.52-1.69), in the baseline, non-high-risk, and nonmedication cohorts, respectively. Case fatality associated with GI bleeding was 3.4% (95% CI, 2.2%-4.1%), 4.0% (95% CI, 3.2%-5.1%), and 4.6% (95% CI, 3.6%-6.0%) in the baseline, non-high-risk, and nonmedication cohorts, respectively. Conclusions and Relevance: In a population not receiving antiplatelet therapy, the annual risk of major bleeding events and nonfatal major bleeding was estimated. These findings could inform population-level guidelines for primary prevention of CVD.

Lightweight Carbon-Metal-Based Fabric Anode for Lithium-Ion Batteries.

Lithium-ion battery electrodes are typically manufactured via slurry casting, which involves mixing active material particles, conductive carbon, and a polymeric binder in a solvent, followed by casting and drying the coating on current collectors (Al or Cu). These electrodes are functional but still limited in terms of pore network percolation, electronic connectivity, and mechanical stability, leading to poor electron/ion conductivities and mechanical integrity upon cycling, which result in battery degradation. To address this, we fabricate trichome-like carbon-iron fabrics via a combination of electrospinning and pyrolysis. Compared with slurry cast Fe2O3 and graphite-based electrodes, the carbon-iron fabric (CMF) electrode provides enhanced high-rate capacity (10C and above) and stability, for both half cell and full cell testing (the latter with a standard lithium nickel manganese oxide (LNMO) cathode). Further, the CMFs are free-standing and lightweight; therefore, future investigation may include scaling this as an anode material for pouch cells and 18,650 cylindrical batteries.

Towards interactional management for power batteries of electric vehicles.

With the ever-growing digitalization and mobility of electric transportation, lithium-ion batteries are facing performance and safety issues with the appearance of new materials and the advance of manufacturing techniques. This paper presents a systematic review of burgeoning multi-scale modelling and design for battery efficiency and safety management. The rise of cloud computing provides a tactical solution on how to efficiently achieve the interactional management and control of power batteries based on the battery system and traffic big data. The potential of selecting adaptive strategies in emerging digital management is covered systematically from principles and modelling, to machine learning. Specifically, multi-scale optimization is expounded in terms of materials, structures, manufacturing and grouping. The progress on modelling, state estimation and management methods is summarized and discussed in detail. Moreover, this review demonstrates the innovative progress of machine learning based data analysis in battery research so far, laying the foundation for future cloud and digital battery management to develop reliable onboard applications.

Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach.

BACKGROUND: Machine learning-based risk prediction models may outperform traditional statistical models in large datasets with many variables, by identifying both novel predictors and the complex interactions between them. This study compared deep learning extensions of survival analysis models with Cox proportional hazards models for predicting cardiovascular disease (CVD) risk in national health administrative datasets. METHODS: Using individual person linkage of administrative datasets, we constructed a cohort of all New Zealanders aged 30-74 who interacted with public health services during 2012. After excluding people with prior CVD, we developed sex-specific deep learning and Cox proportional hazards models to estimate the risk of CVD events within 5 years. Models were compared based on the proportion of explained variance, model calibration and discrimination, and hazard ratios for predictor variables. RESULTS: First CVD events occurred in 61 927 of 2 164 872 people. Within the reference group, the largest hazard ratios estimated by the deep learning models were for tobacco use in women (2.04, 95% CI: 1.99, 2.10) and chronic obstructive pulmonary disease with acute lower respiratory infection in men (1.56, 95% CI: 1.50, 1.62). Other identified predictors (e.g. hypertension, chest pain, diabetes) aligned with current knowledge about CVD risk factors. Deep learning outperformed Cox proportional hazards models on the basis of proportion of explained variance (R2: 0.468 vs 0.425 in women and 0.383 vs 0.348 in men), calibration and discrimination (all P <0.0001). CONCLUSIONS: Deep learning extensions of survival analysis models can be applied to large health administrative datasets to derive interpretable CVD risk prediction equations that are more accurate than traditional Cox proportional hazards models.

Both incidence and prevalence of ischaemic heart disease are declining in parallel: a national data-linkage study in New Zealand (ANZACS-QI 52).

AIMS: To examine trends in ischaemic heart disease (IHD) incidence and prevalence in New Zealand from 2005 to 2016, using comprehensive linked national hospitalization and mortality data as proxy measures of all significant events. METHODS AND RESULTS: Incident and prevalent cases of IHD in people aged ≥25 years were identified using individual patient-linkage of routinely collected ICD-10-coded hospitalization and mortality data. Incidence rates and prevalence proportions were calculated by sex and age group and then age-standardized to the 2016 New Zealand population. Ischaemic heart disease incidence and prevalence declined in men and women in all age groups. The average annual rate of decline in age-standardized IHD incidence was 3.3% for women and 2.7% for men, and the rate of decline in age-standardized IHD prevalence was 3.2% for women and 2.2% for men. Despite a 17% increase in the New Zealand population aged 25 years and over during the study period, the total number of people living with IHD also decreased, particularly in those aged 65 years and older. CONCLUSION: In contrast to observations from other countries, where IHD incidence but not IHD prevalence has been falling, declining IHD incidence in New Zealand in recent decades is now mirrored by declining IHD prevalence.

Association between gout and cardiovascular outcomes in adults with no history of cardiovascular disease: large data linkage study in New Zealand.

Objective: To examine the association of gout with cardiovascular outcomes using linked administrative health data in Aotearoa New Zealand. Design: Data linkage study. Setting: National registries of pharmaceutical dispensing, hospital admission, and deaths linked to the Auckland/Northland regional repository of laboratory results to create a regional health contact population as of 31 December 2011. Participants: 942 416 residents of the Auckland/Northland region, aged 20-79 years with no history of cardiovascular disease. Main outcome measures: Time to first fatal or non-fatal cardiovascular event, identified from national datasets on hospital admissions and mortality, between 1 January 2012 and 31 December 2016. Cardiovascular disease was broadly defined as comprising ischaemic heart disease, ischaemic or haemorrhagic stroke, transient ischaemic attack, peripheral vascular disease, and heart failure. Interventions: A history of gout identified from a discharge diagnosis of gout from a public hospital admission or previous dispensing of gout specific drug treatments. The cohort was then linked to national hospital admissions and deaths through to 31 December 2016 (ie, 5 years' follow-up). Multivariable Cox proportional hazard models were constructed to assess the associations between gout, other risk factors, and cardiovascular outcomes. Results: Of 942 416 people included in the study, 31 907 (3.4%) had gout (6261 women and 25 646 men). After adjustment for multiple risk factors for cardiovascular disease, gout was associated with increased cardiovascular events (adjusted hazard ratio 1.34 (95% confidence interval 1.23 to 1.45) in women; 1.18 (1.12 to 1.24) in men). For men with gout, there was an increased risk of cardiovascular disease in those who were not dispensed regular allopurinol (1.15 (1.05 to 1.25)) and those with a serum urate above the treatment target of 0.36 mmol/L (1.16 (1.04 to 1.30)). Risk of cardiovascular events was lower for men with gout who were not dispensed colchicine compared with those who were (0.84 (0.77 to 0.92)). These findings were not observed in women. Conclusion: These results indicate that gout is associated with an increased risk of cardiovascular events. In men with gout without history of cardiovascular disease, the cardiovascular risk was lower in those regularly dispensed allopurinol and those with serum urate levels at the recommended treatment target. By contrast, colchicine dispensing was associated with an increased risk of cardiovascular events in men with gout without a cardiovascular history. The potential causal mechanisms of these associations require further exploration, including casual inference modelling in future studies.

Mass spectrometry-based proteomics of human cannabinoid receptor 2: covalent cysteine 6.47(257)-ligand interaction affording megagonist receptor activation.

The lack of experimental characterization of the structures and ligand-binding motifs of therapeutic G-protein coupled receptors (GPCRs) hampers rational drug discovery. The human cannabinoid receptor 2 (hCB2R) is a class-A GPCR and promising therapeutic target for small-molecule cannabinergic agonists as medicines. Prior mutational and modeling data constitute provisional evidence that AM-841, a high-affinity classical cannabinoid, interacts with cysteine C6.47(257) in hCB2R transmembrane helix 6 (TMH6) to afford improved hCB2R selectivity and unprecedented agonist potency. We now apply bottom-up mass spectrometry (MS)-based proteomics to define directly the hCB2R-AM-841 interaction at the amino-acid level. Recombinant hCB2R, overexpressed as an N-terminal FLAG-tagged/C-terminal 6His-tagged protein (FLAG-hCB2R-6His) with a baculovirus system, was solubilized and purified by immunochromatography as functional receptor. A multiplex multiple reaction monitoring (MRM)-MS method was developed that allowed us to observe unambiguously all seven discrete TMH peptides in the tryptic digest of purified FLAG-hCB2R-6His and demonstrate that AM-841 modifies hCB2R TMH6 exclusively. High-resolution mass spectra of the TMH6 tryptic peptide obtained by Q-TOF MS/MS analysis demonstrated that AM-841 covalently and selectively modifies hCB2R at TMH6 cysteine C6.47(257). These data demonstrate how integration of MS-based proteomics into a ligand-assisted protein structure (LAPS) experimental paradigm can offer guidance to structure-enabled GPCR agonist design.

Nationwide dispensing of cardioprotective medications during the first year following acute coronary syndrome (ANZACS-QI 56).

AIM: A number of evidence-based medications are recommended following an acute coronary syndrome (ACS), including statins, antithrombotics (antiplatelet and/or anticoagulants), a beta-blocker and an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker (ACE-I/ARB). This study aimed to describe the dispensing of the cardioprotective medications in the first year following an ACS hospitalisation in New Zealand and how this varies according to age, sex and type of coronary intervention. METHOD: National hospitalisation data was used to identify all New Zealand residents aged 35-79 years who were discharged from hospital in the years 2013/14 with a primary discharge diagnosis of ACS. Using anonymous linkage to national pharmaceutical dispensing and mortality datasets, the dispensing of each group of medications was examined in survivors of quarters one, two and four of the first year post discharge. RESULTS: There were 14,496 patients; mean age was 63.4 years and 68.8% were male. Dispensing of medications in survivors steadily fell across quarters one, two and four: 90.8%, 82.1% and 78.8% of patients were dispensed statins; 90.6%, 79.8% and 78.1% were dispensed aspirin; 82.7%, 72.6% and 70.0% were dispensed beta-blockers; 69.6%, 62.7% and 61.3% were dispensed ACE-I/ARB; 67.7%, 53.6% and 40.4% were dispensed a P2Y12 inhibitor; and 68.6%, 53.0% and 40.7% were dispensed a combination of two or more antithrombotics. CONCLUSION: Cardioprotective medication dispensing was lower than would have been the case if the current ACS guidelines were followed. The greatest decrease in dispensing occurred between quarter one and quarter two, which highlights a potentially important period for targeted interventions to improve adherence.

Acute coronary syndrome registry enrolment status: differences in patient characteristics and outcomes and implications for registry data use (ANZACS-QI 36).

AIMS: Clinical registry-derived data are widely used to represent patient populations. In New Zealand (NZ), a national registry-the All New Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registry-aims to include all patients undergoing coronary angiography; other acute coronary syndrome (ACS) patients are also registered but without complete capture. This study compares national hospitalization data of all first-time ACS admissions in NZ with patients in the ANZACS-QI registry, to investigate the use of clinical registry-derived data in research and in assessing clinical care. METHODS AND RESULTS: Patients admitted with first-time ACS in the NZ National Hospitalisation Dataset between 1 January 2015 and 31 December 2016 were included. Clinical characteristics and time to 12-month clinical outcomes were compared between patients captured and not-captured in the registry. A total of 16 569 patients were admitted with first-time ACS, median age 69 years, 61% male; 60% (n = 9918) were enrolled in ANZACS-QI. Registry-captured patients were younger, more often male, and with a lower comorbidity burden than non-captured patients. Overall, 16% patients died within 12 months, 15% experienced a non-fatal cardiovascular (CV) readmission, and 28% either died or were readmitted. Patients not captured in the registry were more than twice as likely to have experienced death or a non-fatal CV readmission within 12 months as captured patients. CONCLUSIONS: First-time ACS patients captured in the ANZACS-QI registry had very different clinical characteristics and outcomes than those not captured. Cardiovascular registry-derived data are dependent on registry design and may not be representative of the wider patient population; this must be considered when using registry-derived data.

A parameter adaptive method for state of charge estimation of lithium-ion batteries with an improved extended Kalman filter.

An accurate state of charge (SOC) estimation in battery management systems (BMS) is of crucial importance to guarantee the safe and effective operation of automotive batteries. However, the BMS consistently suffers from inaccuracy of SOC estimation. Herein, we propose a SOC estimation approach with both high accuracy and robustness based on an improved extended Kalman filter (IEKF). An equivalent circuit model is established, and the simulated annealing-particle swarm optimization (SA-PSO) algorithm is used for offline parameter identification. Furthermore, improvements have been made with noise adaptation, a fading filter and a linear-nonlinear filtering based on the traditional EKF method, and rigorous mathematical proof has been carried out accordingly. To deal with model mismatch, online parameter identification is achieved by a dual Kalman filter. Finally, various experiments are performed to validate the proposed IEKF. Experimental results show that the IEKF algorithm can reduce the error to 2.94% under dynamic stress test conditions, and robustness analysis is verified with noise interference, hence demonstrating its practicability for extending to state estimation of battery packs applied in real-world operating conditions.

NiCo Metal-Organic Framework and Porous Carbon Interlayer-Based Supercapacitors Integrated with a Solar Cell for a Stand-Alone Power Supply System.

Nickel cobalt-metal-organic framework (NiCo-MOF), with a semihollow spherical morphology composed of rhombic dodecahedron nanostructures, was synthesized using a scalable and facile wet chemical route. Such a structure endowed the material with open pores, which enabled rapid ion ingress and egress, and the high effective surface area of the MOF allowed the uptake and release of a large number of electrolyte ions during charge-discharge. By combining this NiCo-MOF cathode with a highly porous carbon (PC) anode (derived from the naturally grown and abundantly available bio-waste, namely, palm kernel shells), the resulting PC//NiCo-MOF supercapacitor using an aqueous potassium hydroxide (KOH) electrolyte delivered a capacitance of 134 F g-1, energy and power densities of 24 Wh kg-1 and 0.8 kW kg-1 at 1 A g-1, respectively, over an operational voltage window of 1.6 V. By employing thin interlayers of PC coated over a Whatman filter paper (PC@FP), the modified supercapacitor configuration of PC/PC@FP//PC@FP/NiCo-MOF delivered greatly enhanced performance. This cell delivered a capacitance of 520 F g-1 and an energy density of 92 Wh kg-1, improved by nearly 4-fold, compared to the analogous supercapacitor without the interlayers (at the same power and current densities and voltage window), thus evidencing the role of the cost-effective, electrically conducting porous carbon interlayers in amplifying the supercapacitor's energy storage capabilities. Further, illumination of white light-emitting diodes (LEDs) using a three-series configuration and the photocharging of this supercapacitor with a solution-processed solar cell are also demonstrated. The latter confirms its ability to function as a stand-alone power supply system for electronic/computing devices, which can even operate under medium lighting conditions.

Development and validation of a cardiovascular risk score for patients in the community after acute coronary syndrome.

OBJECTIVE: Following acute coronary syndrome (ACS), patients are managed long-term in the community, yet few tools are available to guide patient-clinician communication about risk management in that setting. We developed a score for predicting cardiovascular disease (CVD) risk among patients managed in the community after ACS. METHODS: Adults aged 30-79 years with prior ACS were identified from a New Zealand primary care CVD risk management database (PREDICT) with linkage to national mortality, hospitalisation, pharmaceutical dispensing and regional laboratory data. A Cox model incorporating clinically relevant factors was developed to estimate the time to a subsequent fatal or non-fatal CVD event and transformed into a 5-year risk score. External validation was performed in patients (Coronary Disease Cohort Study) assessed 4 months post-ACS. RESULTS: The PREDICT-ACS cohort included 13 703 patients with prior hospitalisation for ACS (median 1.9 years prior), 69% men, 58% European, median age 63 years, who experienced 3142 CVD events in the subsequent 5 years. Median estimated 5 year CVD risk was 24% (IQR 17%-35%). The validation cohort consisted of 2014 patients, 72% men, 92% European, median age 67 years, with 712 CVD events in the subsequent 5 years. Median estimated 5-year risk was 33% (IQR 24%-51%). The risk score was well calibrated in the derivation and validation cohorts, and Harrell's c-statistic was 0.69 and 0.68, respectively. CONCLUSIONS: The PREDICT-ACS risk score uses data routinely available in community care to predict the risk of recurrent clinical events. It was derived and validated in real-world contemporary populations and can inform management decisions with patients living in the community after experiencing an ACS.