The heart rate characteristics (HRC) analysis is a technique for predicting and monitoring neonatal infectious diseases in infants with a risk for infectious disease, such as sepsis, using the HRC index based on the electrocardiogram (ECG) data transmitted from a HeRO® device connected to an ECG monitor.

The assessments were performed via a systematic review. Searching five databases (KoreaMed, Ovid-MEDLINE, Ovid-EMBASE, and Cochrane) yielded 284 related studies. Two reviewers independently assessed the quality of these studies, using the Scottish Intercollegiate Guidelines Network checklist and the assessment results were described based on the results of the quality appraisal and level of evidence.

The safety and effectiveness of the technique were assessed based on eight non-Korean studies (one randomized controlled trial (RCT), five cohort studies, one case-control study, one case series). The four studies that reported area under the curve (AUC) values, the timing of the analysis and AUC values (0.67– 0.75) were inconsistent among the studies. The elevation of the HRC index prior to the diagnosis of an infectious disease was not observed for meningitis or for multiple infectious diseases. In addition, although the group with additional monitoring using the technique had a significantly lower mortality rate, whether the HRC index had a direct impact on the infection prevention activities and the possibility of bias arising from the researchers’ precautionary treatment based on the clinical symptoms and other test results as well as the actual time of disease onset are unknown.

Therefore, the committee presented the following recommendations based on the available evidence and expert opinion. HRC analysis is a safe technique for predicting and monitoring neonatal infectious diseases in infants with a risk for infectious disease, such as sepsis, using the HRC index based on the ECG data transmitted from a HeRO® device connected to an ECG monitor; however, further research is needed to determine its effectiveness (Level of evidence C, Technology category II-a).