Association between temporal changes in C-reactive protein levels and prognosis in patients with previous myocardial

Takuya Oikawa1, Yasuhiko Sakata2, Kotaro Nochioka2

  • 1Department of Cardiovascular Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.

Insights

Elevated C-reactive protein (CRP) levels after myocardial infarction (MI) predict worse outcomes. Temporal increases in CRP are linked to higher risks of death, emphasizing CRP

Area of Science:

  • Cardiology
  • Biomarkers
  • Inflammation

Background:

  • C-reactive protein (CRP) is an inflammatory biomarker known to predict cardiovascular events.
  • Previous research established CRP's predictive value independently of low-density lipoprotein cholesterol.
  • The association between temporal changes in CRP levels and clinical events in patients with prior myocardial infarction (MI) remained unexamined.

Purpose of the Study:

  • To investigate the relationship between temporal changes in C-reactive protein (CRP) levels and clinical outcomes in patients with a history of myocardial infarction (MI).
  • To determine if sustained or increased CRP levels post-MI are associated with adverse cardiovascular and all-cause mortality.

Main Methods:

  • Analysis of 2184 patients with previous MI from the Chronic Heart Failure Registry and Analysis in the Tohoku district-2 (CHART-2) Study.
  • Assessment of C-reactive protein (CRP) levels at baseline and 1-year follow-up.
  • Evaluation of all-cause, cardiovascular, and non-cardiovascular deaths during a median 6.4-year follow-up period.
  • Statistical analysis using hazard ratios (HR) and inverse probability of treatment weighting (IPTW) models.

Main Results:

  • Patients with baseline CRP ≥ 2.0 mg/L had significantly increased risks of all-cause and non-cardiovascular death compared to those with CRP < 2.0 mg/L.
  • Temporal increases in CRP levels were strongly associated with prognosis; patients with CRP ≥ 2.0 mg/L at both baseline and 1-year showed significantly higher risks of all-cause, cardiovascular, and non-cardiovascular death.
  • Even patients with initially low CRP (< 2.0 mg/L) who showed an increase to ≥ 2.0 mg/L at 1-year had elevated risks of all-cause and cardiovascular death.

Conclusions:

  • Temporal increases in C-reactive protein (CRP) levels are significantly associated with an increased incidence of clinical events, including all-cause, cardiovascular, and non-cardiovascular death, in patients with previous myocardial infarction (MI).
  • Sustained or rising CRP levels serve as a critical prognostic indicator in post-MI patients, highlighting the importance of monitoring inflammatory markers.
Abstract

Related Concept Videos

Run Charts01:12

Run Charts

Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For...
276
The R Chart01:02

The R Chart

In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
382
Interpreting R Charts01:22

Interpreting R Charts

R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
343
Pareto Chart00:52

Pareto Chart

A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
7.6K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
15.4K
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...
3.0K