ROADMAP and ORIENTAL Trials: the Re-emergence of J-Curve Ghost?

Yoshiyuki Hamamoto1, Hiroyuki Koshiyama

  • 1Center for Diabetes and Endocrinology, The Tazuke Kofukai Foundation Medical Institute Kitano Hospital, Osaka, Japan.

Insights

The cardioprotective effects of angiotensin-receptor blockers (ARBs) in type 2 diabetes patients remain unclear. Some trials suggest higher cardiovascular risks with aggressive blood pressure lowering, possibly indicating a J-curve phenomenon in high-risk individuals.

Area of Science:

  • Cardiology
  • Endocrinology
  • Pharmacology

Background:

  • Cardioprotection by angiotensin-receptor blockers (ARBs) in type 2 diabetes is not well-established.
  • Type 2 diabetes is a significant risk factor for cardiovascular disease.

Purpose of the Study:

  • To investigate the cardioprotective potential of ARBs in patients with type 2 diabetes.
  • To analyze cardiovascular event rates in ARB treatment groups.

Main Methods:

  • Review of recent clinical trials, specifically the ROADMAP and ORIENT studies.
  • Analysis of cardiovascular outcomes, including fatal events and deaths, in patients treated with olmesartan.

Main Results:

  • Unexpectedly higher rates of fatal cardiovascular events and cardiovascular deaths were observed in the olmesartan group.
  • These findings suggest a potential increased risk associated with aggressive blood pressure lowering in certain patient subgroups.

Conclusions:

  • Aggressive blood pressure lowering with ARBs may increase cardiovascular risk in high-risk patients, particularly those with coronary heart disease.
  • The J-curve phenomenon, where very low blood pressure is associated with increased risk, may be relevant in this population.

Related Concept Videos

Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Horizontal Curve: Problem Solving01:03

Horizontal Curve: Problem Solving

A horizontal curve is characterized by its radius, intersection angle, and stationing of key points. In this case, the radius is 400 meters, and the angle of intersection is 30 degrees, with the station of the point of curvature (P.C.) at 0 + 150 meters. The goal is to determine the station values at the point of intersection (P.I.), point of tangency (P.T.), and midpoint of the curve, as well as the length of the long chord.The process begins with calculating the tangent distance (T) and the...
Vertical Curve: Problem Solving01:23

Vertical Curve: Problem Solving

Vertical curves provide the transition between two roadway grades, ensuring safety, comfort, and functionality. Calculating elevations at specific stations along the curve involves several systematic steps based on the curve's geometry and provided design parameters.The vertical curve is defined by its length, grades, Point of Vertical Intersection (P.V.I.) location, and P.V.I. elevation. The stations of the Point of Vertical Curvature (P.V.C.), where the curve begins, and the Point of Vertical...
Orthogonal Trajectories01:26

Orthogonal Trajectories

Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Interpreting Run Charts01:25

Interpreting Run Charts

Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...