Heart rate variability and mortality in critically ill COVID-19 pneumonia patients

Autor: Chalermchai Komaenthammasophon, Monvasi Pachinburavan, Ronpichai Chokesuwattanaskul
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Heliyon, Vol 10, Iss 15, Pp e34842- (2024)
Druh dokumentu: article
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2024.e34842
Popis: Background: Heart rate variability (HRV) has prognostic value for predicting mortality in both cardiovascular and sepsis patients. Decreased HRV has been associated with increased mortality and morbidity. However, the prognostic significance of HRV in critically ill patients COVID-19 pneumonia still remains unknown. The current study aimed to (1) evaluate prognostic utility of HRV parameters on outcomes in patients with severe COVID-19 pneumonia and (2) assess the correlation between HRV parameters and inflammatory markers. Methods: Consecutive critically ill patients with COVID-19 pneumonia admitted to a tertiary referral intensive care unit from October 2021 to June 2022 in Bangkok, Thailand were enrolled. HRV parameters over the 24 h following intensive care unit admission were recorded using telemetry and analyzed using the Holter program (Philips Holter 2010 Plus/1810 Series). Receiver-operating characteristic (ROC) curve analysis was used to determine optimum threshold cutoffs of various HRV parameters. Formal comparisons of in-hospital mortality between patients with and without a decrease in HRV were performed using Cox regression after adjusting for potential confounders. Results: A total of 65 patients were enrolled in the study. Patients were classified into two groups: survivors (n = 44, 68 %) and non-survivors (n = 21, 32 %). The standard deviation of normal-to-normal intervals (SDNN) was significantly lower in non-survivors than in survivors (70.30 vs. 105.95; p = 0.03). The SDNN predicted in-hospital mortality with an area under the ROC curve of 0.67 (95 % CI 0.55–0.79). At a cutoff of 70 ms, the SDNN showed a sensitivity and specificity of 0.48 and 0.86. The low SDNN group (
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