An updated HACOR score for predicting the failure of noninvasive ventilation: a multicenter prospective observational study

Duan, Jun; Chen, Lijuan; Liu, Xiaoyi; Bozbay, Suha; Liu, Yuliang; Wang, Ke; Esquinas, António M.; Shu, Weiwei; Yang, Fuxun; He, Dehua; Chen, Qimin; Wei, Bilin; Chen, Baixu; Li, Liucun; Tang, Manyun; Yuan, Guodan; Ding, Fei; Huang, Tao; Zhang, Zhongxing; Tang, ZhiJun; Han, Xiaoli; Jiang, Lei; Bai, Linfu; Hu, Wenhui; Zhang, Rui; Mina, Bushra

doi:10.1186/s13054-022-04060-7

Cited by 32 publications

(34 citation statements)

References 34 publications

(47 reference statements)

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“…This was a secondary analysis of a multicenter prospective observational study performed to update HACOR scoring [ 17 ]. It was conducted in 18 hospitals in China and Turkey from September 2017 to September 2021.…”

Section: Methodsmentioning

confidence: 99%

“…However, hypercapnic patients were excluded. De novo acute respiratory failure was defined as occurrence of respiratory failure without chronic respiratory disease, chronic heart disease, asthma, cardiogenic pulmonary edema, cardiac problems other than cardiogenic pulmonary edema, or postoperative hypoxemia [ 2 – 4 , 17 , 18 ].…”

Section: Methodsmentioning

confidence: 99%

“…Patients who were admitted to the participating centers were managed by the attending physicians, respiratory therapists, and nurses in charge. NIV was used to avert respiratory failure if the respiratory rate (RR) was > 25 breaths/min, if a clinical presentation of breathlessness at rest emerged (such as active contraction of the accessory inspiratory muscles or paradoxical abdominal motion), or PaO 2 fell to < 60 mmHg at room air pressure or PaO 2 /FiO 2 fell to < 300 mmHg with supplemental oxygen [ 17 ]. The formula of 21 + 4 × flow (L/min) was used to estimate the FiO 2 if supplemental oxygen was used [ 19 , 20 ].…”

Section: Methodsmentioning

confidence: 99%

“…Disease severity was assessed with the sequential organ failure assessment (SOFA) score. The primary outcome was NIV failure, which was defined as the requirement of intubation [ 17 ]. The secondary outcomes were duration of ICU stay and duration of hospital stay.…”

Section: Methodsmentioning

confidence: 99%

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Prediction of noninvasive ventilation failure using the ROX index in patients with de novo acute respiratory failure

Duan

Yang

Jiang

et al. 2022

Ann. Intensive Care

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Background The ratio of SpO2/FiO2 to respiratory rate (ROX) index is commonly used to predict the failure of high-flow nasal cannula. However, its predictive power for noninvasive ventilation (NIV) failure is unclear. Methods This was a secondary analysis of a multicenter prospective observational study, intended to update risk scoring. Patients with de novo acute respiratory failure were enrolled, but hypercapnic patients were excluded. The ROX index was calculated before treatment and after 1–2, 12, and 24 h NIV. Differences in predictive power for NIV failure using the ROX index, PaO2/FiO2, and PaO2/FiO2/respiratory rate were tested. Results A total of 1286 patients with de novo acute respiratory failure were enrolled. Of these, 568 (44%) experienced NIV failure. Patients with NIV failure had a lower ROX index than those with NIV success. The rates of NIV failure were 92.3%, 70.5%, 55.3%, 41.1%, 35.1%, and 29.5% in patients with ROX index values calculated before NIV of ≤ 2, 2–4, 4–6, 6–8, 8–10, and > 10, respectively. Similar results were found when the ROX index was assessed after 1–2, 12, and 24 h NIV. The area under the receiver operating characteristics curve was 0.64 (95% CI 0.61–0.67) when the ROX index was used to predict NIV failure before NIV. It increased to 0.71 (95% CI 0.68–0.74), 0.74 (0.71–0.77), and 0.77 (0.74–0.80) after 1–2, 12, and 24 h NIV, respectively. The predictive power for NIV failure was similar for the ROX index and for the PaO2/FiO2. Likewise, no difference was found between the ROX index and the PaO2/FiO2/respiratory rate, except at the time point of 1–2 h NIV. Conclusions The ROX index has moderate predictive power for NIV failure in patients with de novo acute respiratory failure.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Prediction of noninvasive ventilation failure using the ROX index in patients with de novo acute respiratory failure

Duan

Yang

Jiang

et al. 2022

Ann. Intensive Care

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“…A recent updated HACOR score that includes additional factors like presence of pneumonia, cardiogenic edema, pulmonary ARDS, immunosuppression, septic shock, and SOFA has shown significantly improved predictive power for NIV failure compared with the original HACOR score. 13 It would be interesting to see whether, in the future, a large-scale multicenter study using the new updated HACOR score helps in weaning failure prediction in patients on invasive ventilation.…”

mentioning

confidence: 99%

Heart Rate, Acidosis, Consciousness, Oxygenation, and Respiratory Rate: A Perfect Weaning Index or Just a New Kid on the Block

Pande¹,

Sharma²

2022

Indian Journal of Critical Care Medicine

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A bstract Successful weaning is when spontaneous breathing is sustained for more than 48 hours after extubation. Despite a plethora of individual and composite weaning indices being available, most indices have not found much clinical utility, and weaning continues to be largely based on clinical assessment. Heart rate, acidosis, consciousness, oxygenation, and respiratory rate (HACOR) is a new score for prediction of failure of noninvasive ventilation (NIV) in hypoxemic patients receiving NIV. The present study explores its utilization in weaning from invasive ventilation. How to cite this article Pande RK, Sharma J. Heart Rate, Acidosis, Consciousness, Oxygenation, and Respiratory Rate: A Perfect Weaning Index or Just a New Kid on the Block. Indian J Crit Care Med 2022;26(8):887–888.

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A risk prediction model for efficient intubation in the emergency department: A 4‐year single‐center retrospective analysis

Ding,

Feng,

Yang

et al. 2024

JACEP Open

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ObjectiveTo analyze the risk factors associated with intubated critically ill patients in the emergency department (ED) and develop a prediction model by machine learning algorithms.MethodsThis study was conducted in an academic tertiary hospital in Hangzhou, China. Critically ill patients admitted to the ED were retrospectively analyzed from May 2018 to July 2022. The demographic characteristics, distribution of organ dysfunction, parameters for different organs’ examination, and status of mechanical ventilation were recorded. These patients were assigned to the intubation and non‐intubation groups according to ventilation support. We used the eXtreme Gradient Boosting (XGBoost) algorithm to develop the prediction model and compared it with other algorithms, such as logistic regression, artificial neural network, and random forest. SHapley Additive exPlanations was used to analyze the risk factors of intubated critically ill patients in the ED.ResultsOf 14,589 critically ill patients, 10,212 comprised the training group and 4377 comprised the test group; 2289 intubated patients were obtained from the electronic medical records. The mean age, mean scores of vital signs, parameters of different organs, and blood oxygen examination results differed significantly between the two groups (p < 0.05). The white blood cell count, international normalized ratio, respiratory rate, and pH are the top four risk factors for intubation in critically ill patients. Based on the risk factors in different predictive models, the XGBoost model showed the highest area under the receiver operating characteristic curve (0.84) for predicting ED intubation.ConclusionsFor critically ill patients in the ED, the proposed model can predict potential intubation based on the risk factors in the clinically predictive model.

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An updated HACOR score for predicting the failure of noninvasive ventilation: a multicenter prospective observational study

Cited by 32 publications

References 34 publications

Prediction of noninvasive ventilation failure using the ROX index in patients with de novo acute respiratory failure

Prediction of noninvasive ventilation failure using the ROX index in patients with de novo acute respiratory failure

Heart Rate, Acidosis, Consciousness, Oxygenation, and Respiratory Rate: A Perfect Weaning Index or Just a New Kid on the Block

A risk prediction model for efficient intubation in the emergency department: A 4‐year single‐center retrospective analysis

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