Construction of a prediction model for non-invasive respiratory strategies failure of patients with moderate acute hypoxemic respiratory failure based on ultrasonic parameters
10.3760/cma.j.issn.1671-0282.2023.08.008
- VernacularTitle:超声导向中度急性呼吸衰竭患者无创呼吸支持失败的预测模型构建
- Author:
Sun YU
1
;
Chunyang XU
;
Hongwei YE
;
Shun WEN
;
Sheng HUANG
Author Information
1. 苏州大学附属常熟医院（常熟市第一人民医院）重症医学科，常熟 215500
- Keywords:
Ultrasound,moderate acute respiratory failure;
Non-invasive respiratory strategies;
High-flow nasal cannula oxygen therapy;
Non-invasive ventilation;
Trea
- From:
Chinese Journal of Emergency Medicine
2023;32(8):1053-1060
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a predict model based on ultrasomics parameters that can identify moderate acute hypoxemic respiratory failure patients at risk of non-invasive respiratory strategies(NIRS) failure and evaluate its value.Methods:This is a prospective observational trial.The patients with moderate acute respiratory failure (100 mmHg≤PaO 2/FiO 2≤200 mmHg) in intensive care unit(ICU) ,emergency and respiratory ward of Changshu Hospital Affiliated to Soochow University from Oct 2020 to Jan 2023 were included, NIRS failure is defined as death or intubation while on therapy.At admission time and 24 h after treatment vital signs,biological and ultrasound parameters were determined.The study subjects were randomly ( random number) divided into a development group (70%) and a validation group (30%).Univariate and multivariate logistic regression was performed.The treatment failure prediction models were constructed according to ultrasonic parameters combined with clinical parameters.The models were also validated by ROC curves, calibration curves, NRI index and decision curve analysis (DCA).The nomograms were drawn. Results:A total of 193 patients were included in the study, 137 were allocated to the development group, and 56 to the validation group, there was no statistically significant difference between the two groups. NIRS failed in 112 (58%) of 193 patients..Univariate analysis revealed that PaO 2/FiO 2, DE at the time of admission and 24 h in the failure group were found to be statistically lower than the success group, RV/LV was higher (all P<0.05). RR, LUS at 24 h in the failure group were higher and ROX index was lower (all P<0.01). In addition, more patients in the failure group received vasopressors ( P= 0.001). Use of vasopressors( OR=4.709, P=0.012), RR( OR=1.254, P=0.035), LUS( OR=1.250, P=0.037), RV/LV( OR=1.057, P=0.008), PaO 2/FiO 2 ( OR=0.950, P=0.001), DE ( OR=0.107, P=0.001) in the development group were independent risk factors for NIRS failure.ROC analysis revealed that model B achieved a larger area under curve (AUC) than model A in the development group, with their AUC values of 0.928 and 0.872 ( P=0.009), AUC of model A and model B in the validation group were 0.867 and 0.932 respectively ( P=0.07).Two prediction models showed a good degree of calibration (all P>0.05). NRI analysis showed significant improvement in the predictive power of model B ( P<0.01). DCA showed that the model B had a good net benefit between the threshold probabilities of 0-80%. Conclusions:Ultrasomics parameters combined with Clinical parameters can effectively predict NIRS failure in moderate acute hypoxemic respiratory failure patients.
