Methods for estimating costs in patients with hyperlipidemia experiencing their first cardiovascular event in the United Kingdom

The Impact of Obesity in Saudi Arabia: Healthcare Resource Use and Costs Associated with Obesity-Related Complications

INTRODUCTION

Saudi Arabia has a high prevalence of obesity, which increases the risk of individuals experiencing multiple chronic complications. Only a few publications highlight the healthcare costs of obesity-related complications (ORCs) in Saudi Arabia.

METHODS

A micro-costing approach was used to estimate the healthcare costs associated with 10 ORCs. Experienced clinicians in public and private practice across different geographical regions in Saudi Arabia were asked to estimate healthcare resource use associated with each ORC, and estimated unit costs were obtained from hospital administrators. Estimated overall annual costs per patient were calculated as a weighted average of separate public and private sector costs.

RESULTS

Individuals in Saudi Arabia with any single ORC incurred overall average annual healthcare costs of 2165-7558 US dollars (USD). Heart failure, chronic kidney disease, dyslipidemia, and type 2 diabetes (T2D) were the most costly complications, mainly driven by monitoring and/or pharmacological treatment costs. In contrast, asthma, hypertension, and angina were the least costly complications. Costs in private healthcare were higher than in public healthcare; the largest differences (2359-2793 USD) were noted for dyslipidemia, T2D, and osteoarthritis, mainly explained by differences in pharmacological treatment costs.

CONCLUSIONS

These data suggest that ORCs result in a considerable financial burden to the healthcare system, and highlight the substantial cost savings that could be achieved by preventing or delaying the occurrence of ORCs in Saudi Arabia.

Treatment and low-density lipoprotein cholesterol levels in patients with hypercholesterolaemia or mixed dyslipidaemia at high or very high cardiovascular risk: a population-based cross-sectional study in the Netherlands

OBJECTIVE

To describe treatment patterns, low-density lipoprotein cholesterol (LDL-C) levels and healthcare resource utilization (HCRU) in the Netherlands in 2018 of patients with hypercholesterolaemia or mixed dyslipidaemia at high or very high cardiovascular (CV) risk.

METHODS

From the PHARMO Database Network adult patients with a diagnosis or receiving lipid lowering therapy (LLT) between 2009 and 2018 were selected. Patients at high or very high CV risk according to 2016 ESC/EAS guidelines with recorded LDL-C levels who were treated with LLT or were characterized as statin intolerant in 2018 were included. LLT treatment patterns, LDL-C levels and HCRU (General Practitioner [GP] consultations and hospitalizations) were assessed.

RESULTS

The study population included 54,346 patients, of which 70% were at very high CV risk and 30% at high CV risk. The majority (93%) received statin monotherapy, mostly of moderate (73%) or high (15%) intensity. Only 3% received a combination of statin and ezetimibe. Statin intolerance, based on a treatment algorithm, was estimated at 3%. Average LDL-C decreased with LLT intensity. Overall, 74% reached LDL-C < 2.5 mmol/l and 34% <1.8 mmol/l with their current treatment, and 46% reached their LDL-C goal according to 2016 ESC/EAS guidelines. The highest rates of hospitalizations and GP consultations, including home visits, were recorded in patients with peripheral artery disease or polyvascular disease.

CONCLUSION

The treatment of hypercholesterolaemia and mixed dyslipidaemia in patients at high or very high CV risk in the Netherlands was suboptimal in 2018. To further lower CV risk alternative treatment strategies using add-on therapies are needed.

Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar

OBJECTIVE

To assess the consistency of machine learning and statistical techniques in predicting individual level and population level risks of cardiovascular disease and the effects of censoring on risk predictions.

DESIGN

Longitudinal cohort study from 1 January 1998 to 31 December 2018.

SETTING AND PARTICIPANTS

3.6 million patients from the Clinical Practice Research Datalink registered at 391 general practices in England with linked hospital admission and mortality records.

MAIN OUTCOME MEASURES

Model performance including discrimination, calibration, and consistency of individual risk prediction for the same patients among models with comparable model performance. 19 different prediction techniques were applied, including 12 families of machine learning models (grid searched for best models), three Cox proportional hazards models (local fitted, QRISK3, and Framingham), three parametric survival models, and one logistic model.

RESULTS

The various models had similar population level performance (C statistics of about 0.87 and similar calibration). However, the predictions for individual risks of cardiovascular disease varied widely between and within different types of machine learning and statistical models, especially in patients with higher risks. A patient with a risk of 9.5-10.5% predicted by QRISK3 had a risk of 2.9-9.2% in a random forest and 2.4-7.2% in a neural network. The differences in predicted risks between QRISK3 and a neural network ranged between -23.2% and 0.1% (95% range). Models that ignored censoring (that is, assumed censored patients to be event free) substantially underestimated risk of cardiovascular disease. Of the 223 815 patients with a cardiovascular disease risk above 7.5% with QRISK3, 57.8% would be reclassified below 7.5% when using another model.

CONCLUSIONS

A variety of models predicted risks for the same patients very differently despite similar model performances. The logistic models and commonly used machine learning models should not be directly applied to the prediction of long term risks without considering censoring. Survival models that consider censoring and that are explainable, such as QRISK3, are preferable. The level of consistency within and between models should be routinely assessed before they are used for clinical decision making.

The economic burden of infections following intramedullary nailing for a tibial shaft fracture in England

OBJECTIVES

Determine the impact of infections on direct costs and healthcare resource use in England for patients undergoing intramedullary nailing (IMN) for tibial shaft fractures.

DESIGN

Non-concurrent cohort based on retrospectively collected data with 2-year follow-up.

SETTING

England.

PARTICIPANTS

The study population included adult patients (≥18 years) in England with a diagnosis of tibial shaft fracture (International Classification of Diseases-10, S822) in the inpatient setting between May 2003 and June 2017 followed by a procedure for IMN for tibial shaft fracture within 30 days. Patient data were derived from the Clinical Practice Research Datalink linked to National Health Service Hospital Episode Statistics datasets.

PRIMARY INDEPENDENT VARIABLE

Infection.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was total inpatient costs from index stay admission through 1 year of follow-up. Secondary outcome included cumulative total healthcare costs, and resource utilisation at 30 days, 90 days, 1 year and 2 years.

RESULTS

Overall, 805 patients met the inclusion criteria. At index inpatient stay, 3.7% had a post-IMN infection, rising to 11.7% at 1 year. One-year inpatient costs were 80% higher for patients with infection (p<0.001). Total costs were estimated to be £14 756 (95% CI £13 123 to £16 593) for patients with infection versus £8279 (95% CI £7946 to £8626). Length of stay (LOS), readmission and reoperation were the key drivers of healthcare costs (all p<0.001). After adjustment, LOS was higher by 109% (95% CI 62% to 169%), from 10.5 days to 21.9 days, for patients with infection. The odds of being readmitted or requiring reoperation were higher by 5.18 times (95% CI 3.01 to 9.13) and 2.47 times (95% CI 1.48 to 4.09), respectively, for patients with infection versus those without infection.

CONCLUSIONS

Post-IMN infection significantly increases inpatient costs, LOS, readmissions and reoperations associated with tibial fracture fixation. Healthcare burden could be reduced through novel surgical site infection prevention strategies.

Effect of Ephedrae Herba methanol extract on high-fat diet-induced hyperlipidaemic mice

Context: Ephedrae Herba (EH), the dried stems and leaves of Ephedra sinica Stapf., E. intermedia Schrenk et C. A. Mey., or E. equisetina Bge. (Ephedraceae [Ephedra]) is used to treat respiratory diseases. Recently, especially in the Republic of Korea, EH has also been used for weight reduction. Objective: We evaluated the effects and molecular targets of methanol EH extract (EHM) on high-fat diet (HFD)-induced hyperlipidemic ICR mice. Materials and methods: EHM was orally administered (100 mg/kg body weight/day) for 3 weeks. We observed changes in body weight (BW), total cholesterol (TC), high-density lipoprotein-cholesterol, and triglycerides to evaluate the physiological changes induced by HFD or EHM administration. To evaluate lipid peroxidation and liver toxicity, malondialdehyde and blood alanine aminotransferase levels were measured. In addition to analyzing liver gene expression profiles, EHM target proteins were identified using a protein interaction database. Results: EHM administration for 3 weeks significantly (p < 0.05) decreased TC and triglyceride levels without altering BW in mice, and gene expression levels in the livers of EHM-treated mice were restored at 34.0% and 48.4% of those up- or down-regulated by hyperlipidaemia, respectively. Proteins related to DNA repair and energy metabolism were identified via protein interaction network analysis as molecular targets of EHM that play key roles in ameliorating hyperlipidaemia. Discussion and conclusions: EHM regulated hyperlipidaemia by decreasing total blood lipid and triglyceride levels in hyperlipidaemic mice. EHM showed preventive effects against hyperlipidaemia in mice, possibly via the regulation of DNA repair and the expression of energy metabolism-related genes and proteins.

Effect of methanol extract of Salviae miltiorrhizae Radix in high-fat diet-induced hyperlipidemic mice

Background

The dried root of Salvia miltiorrhiza, Salviae miltiorrhizae Radix (SR), is one of the most popular medicinal herbs in Asian countries such as China and Korea. In Asian traditional medicine, SR is considered to have a bitter flavor, be slightly cold in nature, and exert therapeutic actions in the heart and liver meridians. Thus, SR has been used to control symptoms related to cardiovascular diseases. Hyperlipidemia is recognized as the main cause of cerebrovascular and heart diseases; consequently, therapeutic strategies for hyperlipidemia have been widely studied. In this study, the effects and molecular targets of methanol extract of SR (SRme) in hyperlipidemic mice were investigated.

Methods

High-fat diet was fed to mice to induce hyperlipidemia, and measurement of blood cholesterol and triglycerides were conducted to evaluate the effect of SRme on hyperlipidemic mice, and gene expression in mice liver was analyzed to identify key molecules which could be potential targets for developing anti-hyperlipidemic herbal medicines.

Results

There was no significant effect on the body weight gain of hyperlipidemic mice, but the triglyceride content in blood was significantly reduced by the administration of SRme to hyperlipidemic mice. Proteins such as minichromosome maintenance (Mcm) family which play a key role in DNA replication were identified as molecular targets in the amelioration of hyperlipidemia.

Conclusions

SRme ameliorated hyperlipidemia in high-fat diet fed mice by inhibiting increase of blood serum level of triglycerides. And several proteins such as Mcm proteins were deduced to be molecular targets in treating hyperlipidemia.

Electronic supplementary material

The online version of this article (doi:10.1186/s13020-017-0150-0) contains supplementary material, which is available to authorized users.