School of Nursing, Lanzhou University, Lanzhou, Gansu, People's Republic of China.
School of Nursing, Lanzhou University, Lanzhou, Gansu, People's Republic of China; Department of EICU, Lanzhou University Second Hospital, Lanzhou, Gansu, People's Republic of China.
J Tissue Viability. 2021 Aug;30(3):324-330. doi: 10.1016/j.jtv.2021.06.008. Epub 2021 Jun 23.
Here, we aimed to build a nomogram model to estimate the probability of nasogastric tube-associated pressure injuries (NTAPIs) in intensive care unit(ICU)patients. This prospective cohort study included 219ICU patients with nasogastric tube between September 2019 and January 2020.Univariate and multivariate logistic regression analyses were used to develop the nomogram model. The resulting nomogram was tested for calibration, discrimination, and clinical usefulness. Of the included patients, 58 developed NTAPIs, representing an incidence rate of 26.5%. Binary logistic regression analysis revealed that the prediction nomogram included C-reactive protein, vasopressor use, albumin level, nasogastric tube duration, and Sequential Organ Failure Assessment score. The value of these predictors was again confirmed using theLasso regression analysis. Internal validation presented a good discrimination of the nomogram, with an area under the curve value of 0.850, and good calibration (Hosmer-Lemeshow test, P = 0.177). The decision curve analysis also demonstrated preferable net benefit along with the threshold probability in the prediction nomogram. The nomogram model can accurately predict the risk factors for NTAPIs, to formulate intervention strategies as early as possible to reduce NTAPI incidence.
在这里,我们旨在建立一个列线图模型,以估计重症监护病房(ICU)患者中鼻胃管相关压力性损伤(NTAPIs)的概率。这项前瞻性队列研究纳入了 2019 年 9 月至 2020 年 1 月期间使用鼻胃管的 219 例 ICU 患者。采用单因素和多因素逻辑回归分析来建立列线图模型。对得到的列线图进行校准、判别和临床实用性的检验。在纳入的患者中,有 58 例发生了 NTAPIs,发生率为 26.5%。二元逻辑回归分析显示,预测列线图包括 C 反应蛋白、血管加压素使用、白蛋白水平、鼻胃管持续时间和序贯器官衰竭评估评分。这些预测因子的价值再次通过 Lasso 回归分析得到了确认。内部验证表明,列线图具有良好的判别能力,曲线下面积值为 0.850,且校准良好(Hosmer-Lemeshow 检验,P=0.177)。决策曲线分析也表明,在预测列线图中,随着阈值概率的增加,净获益更优。该列线图模型可准确预测 NTAPIs 的危险因素,尽早制定干预策略,以降低 NTAPI 的发生率。