Diabetes and CVD risk during angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker treatment in hypertension: a study of 15,990 patients

Assessing Covariate Balance with Small Sample Sizes

Propensity score adjustment addresses confounding by balancing covariates in subject treatment groups through matching, stratification, inverse probability weighting, etc. Diagnostics ensure that the adjustment has been effective. A common technique is to check whether the standardized mean difference for each relevant covariate is less than a threshold like 0.1. For small sample sizes, the probability of falsely rejecting the validity of a study because of chance imbalance when no underlying balance exists approaches 1. We propose an alternative diagnostic that checks whether the standardized mean difference statistically significantly exceeds the threshold. Through simulation and real-world data, we find that this diagnostic achieves a better trade-off of type 1 error rate and power than standard nominal threshold tests and not testing for sample sizes from 250 to 4000 and for 20 to 100,000 covariates. In network studies, meta-analysis of effect estimates must be accompanied by meta-analysis of the diagnostics or else systematic confounding may overwhelm the estimated effect. Our procedure for statistically testing balance at both the database level and the meta-analysis level achieves the best balance of type-1 error rate and power. Our procedure supports the review of large numbers of covariates, enabling more rigorous diagnostics.

Adjusting for indirectly measured confounding using large-scale propensity score

Confounding remains one of the major challenges to causal inference with observational data. This problem is paramount in medicine, where we would like to answer causal questions from large observational datasets like electronic health records (EHRs) and administrative claims. Modern medical data typically contain tens of thousands of covariates. Such a large set carries hope that many of the confounders are directly measured, and further hope that others are indirectly measured through their correlation with measured covariates. How can we exploit these large sets of covariates for causal inference? To help answer this question, this paper examines the performance of the large-scale propensity score (LSPS) approach on causal analysis of medical data. We demonstrate that LSPS may adjust for indirectly measured confounders by including tens of thousands of covariates that may be correlated with them. We present conditions under which LSPS removes bias due to indirectly measured confounders, and we show that LSPS may avoid bias when inadvertently adjusting for variables (like colliders) that otherwise can induce bias. We demonstrate the performance of LSPS with both simulated medical data and real medical data.

Combating the Coronavirus Pandemic: Early Detection, Medical Treatment, and a Concerted Effort by the Global Community

The World Health Organization (WHO) has declared the outbreak of 2019 novel coronavirus, known as 2019-nCoV, a pandemic, as the coronavirus has now infected over 2.6 million people globally and caused more than 185,000 fatalities as of April 23, 2020. Coronavirus disease 2019 (COVID-19) causes a respiratory illness with symptoms such as dry cough, fever, sudden loss of smell, and, in more severe cases, difficulty breathing. To date, there is no specific vaccine or treatment proven effective against this viral disease. Early and accurate diagnosis of COVID-19 is thus critical to curbing its spread and improving health outcomes. Reverse transcription-polymerase chain reaction (RT-PCR) is commonly used to detect the presence of COVID-19. Other techniques, such as recombinase polymerase amplification (RPA), loop-mediated isothermal amplification (LAMP), clustered regularly interspaced short palindromic repeats (CRISPR), and microfluidics, have allowed better disease diagnosis. Here, as part of the effort to expand screening capacity, we review advances and challenges in the rapid detection of COVID-19 by targeting nucleic acids, antigens, or antibodies. We also summarize potential treatments and vaccines against COVID-19 and discuss ongoing clinical trials of interventions to reduce viral progression.

Impact of ischaemic heart disease severity and age on risk of cardiovascular outcome in diabetes patients in Sweden: a nationwide observational study

OBJECTIVES

To compare short-term cardiovascular (CV) outcome in type 2 diabetes (T2D) patients without ischaemic heart disease (IHD), with IHD but no prior myocardial infarction (MI), and those with prior MI; and assess the impact on risk of age when initiating first-time glucose-lowering drug (GLD).

DESIGN

Cohort study linking morbidity, mortality and medication data from Swedish national registries.

PARTICIPANTS

First-time users of GLD during 2007-2016.

OUTCOMES

Predicted cumulative incidence for the CV outcome (MI, stroke and CV mortality) was estimated. A Cox model was developed where age at GLD start and CV risk was modelled.

RESULTS

260 070 first-time GLD users were included, 221 226 (85%) had no IHD, 16 294 (6%) had stable IHD-prior MI and 22 550 (9%) had IHD+MI. T2D patients without IHD had a lower risk of CV outcome compared with the IHD populations (±prior MI), (3-year incidence 4.78% vs 5.85% and 8.04%). The difference in CV outcome was primarily driven by a relative greater MI risk among the IHD patients. For T2D patients without IHD, an almost linear association between age at start of GLD and relative risk was observed, whereas in IHD patients, the younger (<60 years) patients had a relative greater risk compared with older patients.

CONCLUSIONS

T2D patients without IHD had a lower risk of the CV outcome compared with the T2D populations with IHD, primarily driven by a greater risk of MI. For T2D patients without IHD, an almost linear association between age at start of GLD and relative risk was observed, whereas in IHD patients, the younger patients had a relative greater risk compared with older patients. Our findings suggest that intense risk prevention should be the key strategy in the management of T2D patients, especially for younger patients.

Validation of electronic medical data: Identifying diabetes prevalence in general practice

BACKGROUND:

Electronic medical records are increasingly used for research with limited external validation of their data.

OBJECTIVE:

This study investigates the validity of electronic medical data (EMD) for estimating diabetes prevalence in general practitioner (GP) patients by comparing EMD with national Bettering the Evaluation and Care of Health (BEACH) data.

METHOD:

A "decision tree" was created using inclusion/exclusion of pre-agreed variables to determine the probability of diabetes in absence of diagnostic label, including diagnoses (coded/free-text diabetes, polycystic ovarian syndrome, impaired glucose tolerance, impaired fasting glucose), diabetic annual cycle of care (DACC), glycated haemoglobin (HbA1c) > 6.5%, and prescription (metformin, other diabetes medications). Via SQL query, cases were identified in EMD of five Illawarra and Southern Practice Network practices (30,007 active patients; from 2 years to January 2015). Patient-based Supplementary Analysis of Nominated Data (SAND) sub-studies from BEACH investigating diabetes prevalence (1172 GPs; 35,162 patients; November 2012 to February 2015) were comparison data. SAND results were adjusted for number of GP encounters per year, per patient, and then age-sex standardised to match age-sex distribution of EMD patients. Cluster-adjusted 95% confidence intervals (CIs) were calculated for both datasets.

RESULTS:

EMD diabetes prevalence (T1 and/or T2) was 6.5% (95% CI: 4.1-8.9). Following age-sex standardisation, SAND prevalence, not significantly different, was 6.7% (95% CI: 6.3-7.1). Extracting only coded diagnosis missed 13.0% of probable cases, subsequently identified through the presence of metformin/other diabetes medications (*without other indicator variables) (6.1%), free-text diabetes label (3.8%), HbA1c result* (1.6%), DACC* (1.3%), and diabetes medications* (0.2%).

DISCUSSION:

While complex, proxy variables can improve usefulness of EMD for research. Without their consideration, EMD results should be interpreted with caution.

CONCLUSION:

Enforceable, transparent data linkages in EMRs would resolve many problems with identification of diagnoses. Ongoing data quality improvement remains essential.

Hepatocyte growth factor exerts beneficial effects on mice with type II diabetes‑induced chronic renal failure via the NF‑κB pathway

Type II diabetes is associated with a low quality of life and inflammation, and is often accompanied by varying degrees of chronic renal failure. Chronic renal failure is considered one of the most important factors that aggravates diabetes and contributes to renal insufficiency in patients with diabetes though cellular fibrosis. It has previously been reported that hepatocyte growth factor (HGF) serves extensive biological roles, and is a multifunctional antifibrotic factor that is involved in kidney development, acute injury and regeneration. The present study aimed to investigate whether HGF exerts beneficial effects on type II diabetes‑induced chronic renal failure in a mouse model. Plasma concentration levels of HGF, tumor necrosis factor (TNF)‑α, monocyte chemoattractant protein (MCP)‑1, interleukin (IL)‑1 and IL‑6 were analyzed prior to and following treatment with HGF. Blood urea nitrogen, plasma creatinine concentrations, and electrolyte, total serum protein, parathyroid hormone and C‑reactive protein levels were analyzed by ELISA. The mechanism underlying the effects of the HGF‑mediated signaling pathway was also investigated in mice with type II diabetes‑induced chronic renal failure. Histological analysis was used to determine the therapeutic effects of HGF on mice with type II diabetes‑induced chronic renal failure. The results indicated that HGF exhibited lower plasma concentrations in mice with type II diabetes‑induced chronic renal failure compared with in healthy mice. In addition, treatment with HGF relieved chronic renal failure via inhibition of inflammation. The results indicated that TNF‑α, MCP‑1 and IL‑1 serum concentration levels were downregulated following treatment with HGF. Conversely, IL‑6 and vascular endothelial growth factor concentration was increased in the HGF‑treated mice compared with in the control mice. The results also demonstrated that HGF treatment downregulated the expression of nuclear factor (NF)‑κB molecules, and target molecules C‑C motif chemokine ligand (Ccl)2, Ccl5, intercellular adhesion molecule 1 and TNF‑α. The present study demonstrated that HGF markedly improved renal failure induced by type II diabetes in a mouse model; histological analyses revealed that renal cell injury was improved following treatment with HGF. In conclusion, these results suggested that HGF may exert beneficial effects on type II diabetes‑induced chronic renal failure via regulation of the NF‑κB signaling pathway.

Resveratrol provides benefits in mice with type II diabetes-induced chronic renal failure through AMPK signaling pathway

Type II diabetes-induced ischemic injuries are known to lead to the rapid degeneration of the kidneys as a result of chronic renal failure. Chronic renal failure is a condition, which typically manifests with symptoms including cardiovascular system and left ventricular hypertrophy, atherosclerosis as well as arterial and aortic stiffness. Resveratrol is a multifunctional compound that has been reported to produce beneficial outcomes for patients with type-II diabetes due to prevention of oxidative stress and apoptosis. However, the beneficial effects of resveratrol in chronic renal failure and the underlying mechanisms have remained to be fully elucidated. The present study investigated the therapeutic effects of resveratrol in mice with chronic renal failure induced by type-II diabetes and assessed the mechanism of action. Oxidative stress, apoptosis and adenosine monophosphate-activated protein kinase (AMPK) in the renal cells of the model mice were assessed. Changes in inflammatory factors renal cells from experimental mice as well as insulin resistance were also analyzed. Morphological changes and immunocytes in renal cells were determined by immunostaining. The results demonstrated that resveratrol treatment decreased the apoptotic rate of renal cells from experimental mice. Oxidative stress also improved in renal cells, as indicated by inhibition of superoxide dismutase and reduced glutathione and 4-hydroxy-2-nonenal levels. In addition, insulin resistance was improved after an 8-week treatment with resveratrol. Inflammatory factors were decreased and factors promoting kidney function were increased after resveratrol treatment. Furthermore, morphological changes were observed to be ameliorated, indicating the therapeutic efficacy of resveratrol. In addition, immunocyte precipitation in renal cells was markedly decreased in resveratrol-treated mice. Importantly, the AMPK signaling pathway was found to be involved in the beneficial effect of resveratrol on the model mice. In conclusion, the present study suggested that resveratrol may be an ideal agent for the treatment of chronic renal failure induced by type-II diabetes through regulation of the AMPK signaling pathway, which should be further investigated in clinical trials.

Comparative risk of new-onset diabetes mellitus for antihypertensive drugs: A network meta-analysis

New-onset diabetes mellitus (NOD) refers to forms of diabetes mellitus that develop during the therapeutic processes of other diseases such as hypertension. This study has been conducted in a network meta-analysis to compare antihypertensive drugs by identifying both the advantages and disadvantages on NOD by focusing on their respective effect rates. Odd ratios and corresponding 95% confidence intervals or credible intervals were calculated within pairwise and network meta-analysis. A total of 38 articles with 224 140 patients were included to evaluate the preventive effect of hypertension drugs on NOD. From the network meta-analysis it was evident that both angiotensin-converting enzyme inhibitor as well as angiotensin receptor blocker treatments are associated with a lower risk of developing NOD compared with placebo, with ranking probabilities of 79.81% and 72.77%, respectively, while β-blockers and calcium channel blockers may significantly increase the probability of developing NOD (β-blockers: odds ratio, 2.18 [95% credible intervals: 1.36-3.50]; calcium channel blockers: odds ratio, 1.16 [95% credible intervals, 1.05-1.29]). In conclusion, angiotensin receptor blockers have an advantage over the other treatments regarding the NOD.

Comparing the effect of angiotensin-converting enzyme inhibitors and angiotensin receptor blockers on renal function decline in diabetes

AIM

To compare effectiveness of angiotensin-converting enzyme inhibitors (ACEis)/angiotensin receptor blockers (ARBs) for protecting Type 2 diabetes mellitus (DM2) patients from renal function decline in a real-world setting.

METHODS

Retrospective cohort study of new ACEi/ARB users in 2007-2012 in an unselected primary care DM2 population. Outcome is decline in renal function stage (combining estimated glomerular filtration rate and albuminuria). Patients were matched on a propensity score. Extended Cox models with time-varying covariates were used to estimate hazard ratios of outcome.

RESULTS

The time to renal function decline for ARB users was slightly, but not significantly longer than for ACEi users (hazard ratio: 0.80; 95% CI: 0.58-1.10; p = 0.166).

CONCLUSION

This study did not show significant differences between the classes in preventing renal function decline in DM2 patients in primary care.

Azilsartan compared to ACE inhibitors in anti-hypertensive therapy: one-year outcomes of the observational EARLY registry

BACKGROUND

Azilsartan medoxomil (AZL-M), has been demonstrated to be more effective than the other sartans currently in use; however, there is insufficient information available comparing it with ACE-inhibitors. Therefore, we aimed to compare the efficacy, safety, and tolerability of AZL-M with that of ACE-inhibitors in a real life clinical setting.

METHODS

The EARLY registry is a prospective, observational, national, multicentre registry with a follow-up period of 12 months. There were two principal objectives: 1) documentation of the achievement of target BP values set according to recent national and international guidelines, and 2) description of the safety profile of AZL-M.

RESULTS

A total of 3 849 patients with essential arterial hypertension were recruited from primary care offices in Germany. Patients who initiated monotherapy at baseline comprising either AZL-M or an ACE-inhibitor were included at a ratio of seven to three. Results demonstrated that a blood pressure target of <140/90 mmHg was achieved by a significantly greater proportion of patients in the AZL-M group (61.1 %) compared with the ACE-inhibitor group (56.4 %; p < 0.05; OR, 1.21; 95 % CI, 1.03-1.42), with this finding maintained after adjusting for differences in baseline characteristics. AZL-M appeared to have an equivalent safety profile to the ACE-inhibitors, with a similar incidence of adverse events in the two patient groups (p = 0.73).

CONCLUSIONS

These data add to the results of previous randomized controlled clinical trials suggesting that, compared with other agents that target the renin-angiotensin system, AZL-M provides statistically significant albeit small improvements in blood pressure control.

Impact of Angiotensin Converting Enzyme Inhibitor versus Angiotensin Receptor Blocker on Incidence of New-Onset Diabetes Mellitus in Asians

PURPOSE

Angiotensin converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB) are associated with a decreased incidence of new-onset diabetes mellitus (NODM). The aim of this study was to compare the protective effect of ACEI versus ARBs on NODM in an Asian population.

MATERIALS AND METHODS

We investigated a total of 2817 patients who did not have diabetes mellitus from January 2004 to September 2009. To adjust for potential confounders, a propensity score matched (PSM) analysis was performed using a logistic regression model. The primary end-point was the cumulative incidence of NODM, which was defined as having a fasting blood glucose ≥126 mg/dL or HbA1c ≥6.5%. Multivariable cox-regression analysis was performed to determine the impact of ACEI versus ARB on the incidence of NODM.

RESULTS

Mean follow-up duration was 1839±1019 days in all groups before baseline adjustment and 1864±1034 days in the PSM group. After PSM (C-statistics=0.731), a total 1024 patients (ACEI group, n=512 and ARB group, n=512) were enrolled for analysis and baseline characteristics were well balanced. After PSM, the cumulative incidence of NODM at 3 years was lower in the ACEI group than the ARB group (2.1% vs. 5.0%, p=0.012). In multivariate analysis, ACEI vs. ARB was an independent predictor of the lower incidence for NODM (odd ratio 0.37, confidence interval 0.17-0.79, p=0.010).

CONCLUSION

In the present study, compared with ARB, chronic ACEI administration appeared to be associated with a lower incidence of NODM in a series of Asian cardiovascular patients.

Opposing tissue-specific roles of angiotensin in the pathogenesis of obesity, and implications for obesity-related hypertension

Metabolic disease, specifically obesity, has now become the greatest challenge to improving cardiovascular health. The renin-angiotensin system (RAS) exists as both a circulating hormone system and as a local paracrine signaling mechanism within various tissues including the brain, kidney, and adipose, and this system is strongly implicated in cardiovascular health and disease. Growing evidence also implicates the RAS in the control of energy balance, supporting the concept that the RAS may be mechanistically involved in the pathogenesis of obesity and obesity hypertension. Here, we review the involvement of the RAS in the entire spectrum of whole organism energy balance mechanisms, including behaviors (food ingestion and spontaneous physical activity) and biological processes (digestive efficiency and both aerobic and nonaerobic resting metabolic rates). We hypothesize that opposing, tissue-specific effects of the RAS to modulate these various components of energy balance can explain the apparently paradoxical results reported by energy-balance studies that involve stimulating, versus disrupting, the RAS. We propose a model in which such opposing and tissue-specific effects of the RAS can explain the failure of simple, global RAS blockade to result in weight loss in humans, and hypothesize that obesity-mediated uncoupling of endogenous metabolic rate control mechanisms can explain the phenomenon of obesity-related hypertension.