Predicting efficacy of combined assessment with fragmented QRS and severely depressed heart rate variability on outcome of patients with acute myocardial infarction

The association between fragmented QRS (fQRS) and autonomic nervous dysfunction, and major adverse cardiovascular events (MACE) is not fully clear in patients with acute myocardial infarction (AMI). This study aimed to observe whether combined assessment with fQRS and cardiac autonomic nervous function could enhance the predicting efficacy on outcome in AMI patients. A total of 153 consecutive hospitalized AMI patients were included in this retrospective study. Patients were divided into non-fQRS (nfQRS) group and fQRS group according to 12-lead electrocardiogram, into sHRV [severely depressed heart rate variability (HRV): standard deviation of NN intervals (SDNN) < 100 ms and very low frequency (VLF) < 26.7 ms] group and nsHRV (non-severely depressed HRV) group according to 24 h Holter monitoring, and into non-MACE (nMACE) group and MACE group according to 12 months' follow-up results. The incidence of sHRV was significantly higher in the fQRS group than in the nfQRS group (71.9 vs. 39.3%, p < 0.05). The incidences of MACE were 7.4, 22.2, 25.7 and 56.5%, respectively, in nsHRV + nfQRS group, nsHRV + fQRS group, sHRV + nfQRS group and sHRV + fQRS group (p < 0.05). Multivariable Cox regression analysis showed that patients in the sHRV + fQRS group had a sixfold higher risk of MACE compared to patients in the nsHRV + nfQRS group (HR = 6.228, 95% CI 1.849-20.984, p = 0.003). The predicting sensitivity and specificity on MACE were 81.4 and 58.2% by sHRV, 69.8 and 69.1% by fQRS in these AMI patients. The specificity (81.8%) was the highest with the combination of sHRV and fQRS. Adding sHRV and fQRS to clinical data offered incremental prognostic value. Present results indicate that fQRS is closely related to sHRV, suggesting significant impairment of sympathetic nerve function in AMI patients with fQRS. Combined assessment with fQRS and sHRV enhances the predicting efficacy on outcome in AMI patients.