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. 2016 Feb;106(2):136-44.
doi: 10.5935/abc.20160011. Epub 2016 Jan 22.

Diagnosis of Rejection by Analyzing Ventricular Late Potentials in Heart Transplant Patients

[Article in English, Portuguese]
Vítor Nogueira Mendes  1 , Telmo Santos Pereira  2 , Vítor Azevedo Matos  3
Affiliations

Diagnosis of Rejection by Analyzing Ventricular Late Potentials in Heart Transplant Patients

[Article in English, Portuguese]
Vítor Nogueira Mendes et al. Arq Bras Cardiol. 2016 Feb.

Abstract

Background: Heart transplant rejection originates slow and fragmented conduction. Signal-averaged ECG (SAECG) is a stratification method in the risk of rejection.

Objective: To develop a risk score for rejection, using SAECG variables.

Methods: We studied 28 transplant patients. First, we divided the sample into two groups based on the occurrence of acute rejection (5 with rejection and 23 without). In a second phase, we divided the sample considering the existence or not of rejection in at least one biopsy performed on the follow-up period (rejection pm1: 18 with rejection and 10 without).

Results: On conventional ECG, the presence of fibrosis was the only criterion associated with acute rejection (OR = 19; 95% CI = 1.65-218.47; p = 0.02). Considering the rejection pm1, an association was found with the SAECG variables, mainly with RMS40 (OR = 0.97; 95% CI = 0.87-0.99; p = 0.03) and LAS40 (OR = 1.06; 95% IC = 1.01-1.11; p = 0.03). We formulated a risk score including those variables, and evaluated its discriminative performance in our sample. The presence of fibrosis with increasing of LAS40 and decreasing of RMS40 showed a good ability to distinguish between patients with and without rejection (AUC = 0.82; p < 0.01), assuming a cutoff point of sensitivity = 83.3% and specificity = 60%.

Conclusion: The SAECG distinguished between patients with and without rejection. The usefulness of the proposed risk score must be demonstrated in larger follow-up studies.

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Conflict of interest statement

Potential Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Figures

Figure 1
Figure 1
ROC Curve for the association between fibrosis and acute rejection.
Figure 2
Figure 2
ROC Curve for the association of SCORE1 with rejection pm1.
Figure 3
Figure 3
ROC curve for the association of SCORE2 with rejection pm1.
Figure 4
Figure 4
ROC curve for the association of SCORE3 with rejection pm1.
See this image and copyright information in PMC

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