Heart Rate Fluctuation and Mortality in Critically Ill Myocardial Infarction Patients: A Retrospective Cohort Study

Abstract

Background: Whether heart rate (HR) fluctuation after admission has an impact on the outcomes of critically ill myocardial infarction (MI) patients in intensive care unit remains unknown.Methods: A total of 2,031 MI patients were enrolled from the Medical Information Mart for Intensive Care (MIMIC-III) database. HR fluctuation was calculated as the maximum HR minus the minimum HR in the initial 24 h after admission. Participants were divided into 3 groups, namely, low HR fluctuation [<30 beats per minute (bpm)], medium HR fluctuation (30–49 bpm), and high HR fluctuation (≥ 50 bpm). The main outcomes were 30–day and 1-year mortality. Cox regression and restricted cubic spline model were used.Results: Each 10-bpm increase in HR fluctuation was associated with a higher risk of 30-day mortality and 1-year mortality, with adjusted hazard ratios of 1.122 (95% CI, 1.083–1.162) and 1.107 (95% CI, 1.074–1.140), respectively. Compared with the low HR fluctuation group, the high HR fluctuation group suffered a significantly higher risk of mortality after adjustment, with hazard ratios of 2.156 (95% CI, 1.483–3.134) for 30-day mortality and 1.796 (95% CI, 1.354–2.381) for 1-year mortality. A typical J-type curve was observed in restricted cubic splines for the association between HR fluctuation and 30-day or 1-year mortality of MI patients, with the lowest risk on the HR fluctuation of 30 bpm. Sensitivity analyses emphasized the robustness of our results.Conclusions: This retrospective cohort study revealed an independent positive association between HR fluctuation and 30-day and 1-year mortality in critically ill MI patients, which warrants further investigation.

Admission Resting Heart Rate as an Independent Predictor of All-Cause Mortality in Elderly Patients with Hip Fracture

“…Also, the U-shaped curve was seen in critically ill patients, providing a new insight for optimizing HR control strategies. 20 Yet, other studies observed a J-shaped association in acute ischemic stroke patients, 21 myocardial infarction patients, 22 and even in the general population. 23 In agreement with the latter observations, we also observed a typical J-shaped curve for the association between RHR and 1-year mortality, and 70 bpm exhibited the lowest mortality risk.…”

“…Also, the U-shaped curve was seen in critically ill patients, providing a new insight for optimizing HR control strategies. 20 Yet, other studies observed a J-shaped association in acute ischemic stroke patients, 21 myocardial infarction patients, 22…”

The Use of Antibiotics for Ventilator-Associated Pneumonia in the MIMIC-IV Database

“…MIMIC is the largest open source and free clinical database in the critical care and emergency department, based on BIDMC’s intensive care inpatient system. MIMIC-IV (version 1.0) is the latest version, which contains data from 2008 to 2019 ( Guo et al, 2021 ; Lu et al, 2021 ; Song et al, 2021 ). We completed the courses required to use the database and obtained the corresponding certificate.…”

Development and Validation of Nomogram to Predict Long-Term Prognosis of Critically Ill Patients with Acute Myocardial Infarction

“…Laboratory tests included counting the number of or estimating the levels of white blood cells (WBC), hemoglobin, platelets, anion gap, sodium, potassium, chloride, bicarbonate, creatinine, blood urea nitrogen (BUN), prothrombin time, activated partial thromboplastin time, troponin T (cTnT), and lactate within the first 24 h after ICU admission. 17,18 Interventions involved the use of vasopressor medicine, dialysis, mechanical ventilation, and percutaneous coronary intervention (PCI). Except for cTnT and lactate, the missing values of the other variables were all within 10%, which were filled by multivariate multiple imputation with chained equations; by contrast, cTnT and lactate were regarded as dummy variables in the statistical analysis to reduce the possible bias of simple filling.…”