Wang Chenlong, Zhu Qingcheng, Cao Liuzhao, Walline Joseph, Wang Bingxia, Tan Dingyu
Department of Emergency Department, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China.
Department of Pulmonary and Critical Care Medicine, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China.
Am J Emerg Med. 2025 Apr;90:157-163. doi: 10.1016/j.ajem.2025.01.046. Epub 2025 Jan 22.
Currently, there is a deficiency in nomograms specifically designed for predicting the failure of high-flow nasal cannula (HFNC) oxygen therapy in patients with hypercapnic acute respiratory failure (hypercapnic ARF). The aim of this retrospective study is to develop and evaluate a nomogram that assesses the risk of HFNC failure in this patient population.
Patients with ARF and hypercapnia (PaCO ≥ 45 mmHg in the initial arterial blood gas) who received HFNC in the intensive care unit (ICU) from January 1, 2020 to December 31, 2023 were enrolled in this study. Risk factors were identified through least absolute shrinkage and selection operator regression analysis. A novel nomogram model was subsequently developed using multivariable logistic regression analysis. The model's predictive performance was assessed via receiver operating characteristic curves, calibration curves, and decision curve analysis (DCA).
A total of 189 patients were included in the analysis, comprising 128 patients in the HFNC success group and 61 in the HFNC failure group. Multivariate logistic regression identified blood urea nitrogen, calcium, sepsis, and the respiratory rate oxygenation index (ROX) after 4 h of oxygen therapy as independent prognostic factors for HFNC failure. The nomogram exhibited superior performance compared to the Sequential Organ Failure Assessment score (P = 0.011) and the 4-h ROX index (P = 0.001). Additionally, the calibration curve demonstrated satisfactory predictive accuracy, while DCA highlighted the clinical utility of the nomogram.
Key demographic and laboratory parameters associated with the failure of HFNC in patients with hypercapnic ARF have been identified. These parameters were used to develop a precise and user-friendly nomogram, which could serve as an effective clinical tool for clinicians.
目前,专门用于预测高碳酸血症急性呼吸衰竭(高碳酸血症性急性呼吸衰竭,hypercapnic ARF)患者高流量鼻导管(HFNC)氧疗失败的列线图存在不足。这项回顾性研究的目的是开发并评估一种列线图,以评估该患者群体中HFNC失败的风险。
纳入2020年1月1日至2023年12月31日在重症监护病房(ICU)接受HFNC治疗的急性呼吸衰竭和高碳酸血症(初始动脉血气中PaCO₂≥45 mmHg)患者。通过最小绝对收缩和选择算子回归分析确定风险因素。随后使用多变量逻辑回归分析开发了一种新型列线图模型。通过受试者操作特征曲线、校准曲线和决策曲线分析(DCA)评估模型的预测性能。
共有189例患者纳入分析,其中HFNC成功组128例,HFNC失败组61例。多变量逻辑回归确定血尿素氮、钙、脓毒症以及氧疗4小时后的呼吸频率氧合指数(ROX)为HFNC失败的独立预后因素。与序贯器官衰竭评估评分(P = 0.011)和4小时ROX指数(P = 0.001)相比,该列线图表现更优。此外,校准曲线显示出令人满意的预测准确性,而DCA突出了列线图的临床实用性。
已确定与高碳酸血症性急性呼吸衰竭患者HFNC失败相关的关键人口统计学和实验室参数。这些参数用于开发一种精确且用户友好的列线图,可为临床医生提供有效的临床工具。