To assess the association between ultra-short heart rate variability (US-HRV) and short-term mortality in patients with COVID-19 and develop prognostic prediction models to identify high-risk patients as early as possible. A retrospective cohort study was performed on 488 patients diagnosed with COVID-19 and hospitalized in the First Affiliated Hospital of Fujian Medical University from December 2022 to January 2023. 10-s electrocardiogram (ECG) data were available for these patients. The US-HRV parameters including standard deviation of all normal-to-normal R-R intervals (SDNN) and root mean square of successive differences between normal-to-normal R-R intervals (rMSSD) were calculated using Nalong ECG software. The endpoint was short-term mortality, including in-hospital mortality or mortality within 1 week after discharge. Of the 488 patients, 76 (15.6%) died. The SDNN and rMSSD in the death group were significantly lower than those in the survival group ( < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) for SDNN and rMSSD to predict mortality was 0.761 and 0.715, respectively. The combined use of SDNN and rMSSD had an AUC of 0.774. The mortality rate in the group with SDNN ≤7.5 ms was higher than that of SDNN >7.5 ms group ( < 0.05). With the decrease of SDNN, the mortality of patients showed an upward trend, and the mortality of patients with SDNN ≤2 ms was the highest (66.7%). Multivariate logistic regression analysis identified SDNN as an independent predictor of prognosis (odds ratio (OR) = 5.791, 95% confidential interval (CI) 1.615–20.765, = 0.007). The AUC of Model 1 (simple model) was 0.866 (95% CI 0.826–0.905). The AUC of Model 2 (comprehensive model) was 0.914 (95% CI 0.881–0.947). SDNN was associated with short-term mortality and provided the additional discriminatory power of the risk stratification model for hospitalized COVID-19 patients.

中文翻译：

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住院COVID-19患者超短心率变异性与短期死亡率的关系

评估超短心率变异性 (US-HRV) 与 COVID-19 患者短期死亡率之间的关联，并开发预后预测模型以尽早识别高危患者。对2022年12月至2023年1月在福建医科大学附属第一医院住院的488例确诊为COVID-19的患者进行了回顾性队列研究。这些患者可以获得10秒心电图（ECG）数据。使用Nalong心电图软件​​计算US-HRV参数，包括所有正常至正常RR间期（SDNN）的标准差和正常至正常RR间期（rMSSD）之间的连续差异的均方根。终点是短期死亡率，包括院内死亡率或出院后1周内的死亡率。488 名患者中，76 名（15.6%）死亡。死亡组的SDNN和rMSSD显着低于存活组（<0.001）。SDNN 和 rMSSD 预测死亡率的受试者工作特征 (ROC) 曲线 (AUC) 下面积分别为 0.761 和 0.715。SDNN 和 rMSSD 联合使用的 AUC 为 0.774。SDNN≤7.5ms组的死亡率高于SDNN>7.5ms组（<0.05）。随着SDNN的降低，患者的死亡率呈上升趋势，其中SDNN≤2 ms的患者死亡率最高（66.7%）。多变量逻辑回归分析确定 SDNN 是预后的独立预测因子（比值比 (OR) = 5.791，95% 置信区间 (CI) 1.615–20.765，= 0.007）。模型 1（简单模型）的 AUC 为 0.866（95% CI 0.826–0.905）。模型2（综合模型）的AUC为0.914（95% CI 0.881–0.947）。SDNN 与短期死亡率相关，并为住院的 COVID-19 患者提供了风险分层模型的额外区分能力。