BMC Cardiovascular Disorders (Nov 2022)

Prediction of SYNTAX score II improvement by adding temporal heart rate changes between discharge and first outpatient visit in patients with acute myocardial infarction

  • Chuang Li,
  • Wanjing Zhang,
  • Yixing Yang,
  • Qian Zhang,
  • Kuibao Li,
  • Mulei Chen,
  • Lefeng Wang,
  • Kun Xia

DOI
https://doi.org/10.1186/s12872-022-02929-7
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 11

Abstract

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Abstract Background The prognostic ability of the temporal changes in resting heart rate (ΔHR) in patients with acute myocardial infarction (AMI) for cardiovascular (CV) mortality and clinical outcomes is rarely examined. This study investigated the predictive value of ΔHR using models with SYNTAX score II (SxS-II) for the long-term prognosis of patients with AMI. Methods Six hundred five AMI patients with vital signs recorded at the first outpatient visit (2–4 weeks after discharge) were retrospectively recruited into this study. The changes between discharge and outpatient resting heart rate (D-O ΔHR) were calculated by subtracting the HR at the first post-discharge visit from the value recorded at discharge. The major adverse cardiovascular and cerebrovascular events (MACCE) include cardiovascular death, recurrent myocardial infarction, revascularization, and nonfatal stroke. The predictive values and reclassification ability of the different models were assessed using a likelihood ratio test, Akaike’s information criteria (AIC), receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results During the follow-up period, a drop-in resting heart rate (RHR) from discharge to first outpatient visit was independently associated with less risk of CV mortality [D-O ΔHR: hazards ratio (HR) = 0.97, 95% CI = 0.96–0.99, P < 0.001] and MACCE (HR = 0.98, 95% CI = 0.97–0.99, p = 0.001). The likelihood test indicated that the combined model of SxS-II and D-O ΔHR yielded the lowest AIC for CV mortality and MACCE (P < 0.001). Moreover, D-O ΔHR alone significantly improved the net reclassification and integrated discrimination of the models containing SxS-II for CV mortality and MACCE (CV mortality: NRI = 0.5600, P = 0.001 and IDI = 0.0759, P = 0.03; MACCE: NRI = 0.2231, P < 0.05 and IDI = 0.0107, P < 0.05). Conclusions The change in D-O ΔHR was an independent predictor of long-term CV mortality and MACCE. The D-O ΔHR combined with SxS-II could significantly improve its predictive probability.

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