British journal of hospital medicine (London, England : 2005) · 2026
Development and Validation of a Nomogram for Predicting the Need for Mechanical Ventilation in Patients Undergoing High-Flow Nasal Cannula Therapy: A Retrospective Study Based on the MIMIC-IV Database.
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Liu Jiaojiao, Yuan Yuan, Liang Yun
Аннотация
AIMS/BACKGROUND: Hypoxemia and respiratory failure are common among critically ill patients, and high-flow nasal cannula (HFNC) therapy has been increasingly utilized as a non-invasive respiratory support modality. However, a subset of patients eventually requires mechanical ventilation (MV), and predicting this transition remains challenging. This study aimed to develop and validate nomograms that predict the risk of MV among patients undergoing HFNC therapy.
METHODS: A retrospective cohort study was conducted using the publicly available Multiparameter Intelligent Monitoring in Intensive Care IV version 2.0 (MIMIC-IV v2.0) database to identify adult intensive care unit (ICU) patients who received HFNC oxygen therapy for 24 hours or longer. Patients who had undergone MV before HFNC initiation were excluded. Key clinical variables, including demographic data and illness severity scores, were extracted. A multivariable logistic regression model was employed to identify independent predictors of subsequent MV, and a nomogram was constructed based on these predictors. The cohort was randomly divided into training (70%) and validation (30%) sets. Model performance was evaluated using the area under the curve (AUC), calibration plots, the Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis (DCA).
RESULTS: Among 4069 patients included in the final analysis, 1332 (32.7%) transitioned from HFNC to MV. Multivariable analysis identified body weight, Sepsis-3 status, urine output score, the ratio of the partial pressure of oxygen in arterial blood (PaO2) to the fraction of inspired oxygen (PaO2/FiO2 ratio), Pulmonary Score, Glasgow Coma Scale (GCS), and creatinine as independent predictors of MV. The constructed nomogram demonstrated AUC values of 0.659 in the training cohort and 0.656 in the validation cohort. Calibration curves and Hosmer-Lemeshow tests indicated good model calibration, while DCA confirmed its clinical utility within low-to-moderate risk thresholds (≤0.4).
CONCLUSION: We developed and validated a nomogram to predict the likelihood of MV requirement in patients receiving HFNC therapy. The nomogram may serve as a practical clinical tool to assist physicians in determining whether to continue HFNC therapy or initiate MV in clinically ill patients.
METHODS: A retrospective cohort study was conducted using the publicly available Multiparameter Intelligent Monitoring in Intensive Care IV version 2.0 (MIMIC-IV v2.0) database to identify adult intensive care unit (ICU) patients who received HFNC oxygen therapy for 24 hours or longer. Patients who had undergone MV before HFNC initiation were excluded. Key clinical variables, including demographic data and illness severity scores, were extracted. A multivariable logistic regression model was employed to identify independent predictors of subsequent MV, and a nomogram was constructed based on these predictors. The cohort was randomly divided into training (70%) and validation (30%) sets. Model performance was evaluated using the area under the curve (AUC), calibration plots, the Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis (DCA).
RESULTS: Among 4069 patients included in the final analysis, 1332 (32.7%) transitioned from HFNC to MV. Multivariable analysis identified body weight, Sepsis-3 status, urine output score, the ratio of the partial pressure of oxygen in arterial blood (PaO2) to the fraction of inspired oxygen (PaO2/FiO2 ratio), Pulmonary Score, Glasgow Coma Scale (GCS), and creatinine as independent predictors of MV. The constructed nomogram demonstrated AUC values of 0.659 in the training cohort and 0.656 in the validation cohort. Calibration curves and Hosmer-Lemeshow tests indicated good model calibration, while DCA confirmed its clinical utility within low-to-moderate risk thresholds (≤0.4).
CONCLUSION: We developed and validated a nomogram to predict the likelihood of MV requirement in patients receiving HFNC therapy. The nomogram may serve as a practical clinical tool to assist physicians in determining whether to continue HFNC therapy or initiate MV in clinically ill patients.