Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit

Abstract To develop and evaluate a predictive model for intensive care unit (ICU) admission among patients with acute sedative-hypnotic overdose. We conducted a retrospective analysis of patients admitted to the emergency department of West China Hospital, Sichuan University, between October 11, 200...

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Main Authors: Guo Tang, Tianshan Zhang, Ping Zhang, Sha Yang, Tao Cheng, Rong Yao
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-85559-1
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author Guo Tang
Tianshan Zhang
Ping Zhang
Sha Yang
Tao Cheng
Rong Yao
author_facet Guo Tang
Tianshan Zhang
Ping Zhang
Sha Yang
Tao Cheng
Rong Yao
author_sort Guo Tang
collection DOAJ
description Abstract To develop and evaluate a predictive model for intensive care unit (ICU) admission among patients with acute sedative-hypnotic overdose. We conducted a retrospective analysis of patients admitted to the emergency department of West China Hospital, Sichuan University, between October 11, 2009, and December 31, 2023. Patients were divided into ICU and non-ICU groups based on admission criteria including the need for blood purification therapy, organ support therapy (ventilatory support, vasoactive drugs, renal replacement therapy, artificial liver), or post-cardiopulmonary resuscitation. Patients were randomly split into a training set and a validation set in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to optimize variables, followed by a multivariate logistic regression analysis to identify independent risk factors for ICU admission. A nomogram model was constructed and assessed using receiver operating characteristic (ROC) curves, calibration curves, Decision Curve Analysis (DCA), and Clinical Impact Curve (CIC). Predictors in the nomogram included barbiturate overdose, Glasgow Coma Scale (GCS) score, and anion gap at admission. The nomogram demonstrated strong predictive performance with an area under the curve (AUC) of 0.858 (95% CI: 0.788–0.927) in the training set and 0.845 (95% CI: 0.757–0.933) in the validation set. Calibration curves showed the model closely matched the ideal curve, and DCA and CIC indicated high clinical applicability and utility. Barbiturate overdose, initial decreased GCS score and decreased anion gap were identified as independent risk factors for ICU admission in acute sedative-hypnotic overdose. The nomogram model based on these indicators demonstrates good predictive accuracy, discrimination, and clinical utility.
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spelling doaj-art-7e908ae27a9f4b588c5650838af72b492025-02-02T12:16:52ZengNature PortfolioScientific Reports2045-23222025-01-0115111110.1038/s41598-025-85559-1Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unitGuo Tang0Tianshan Zhang1Ping Zhang2Sha Yang3Tao Cheng4Rong Yao5Emergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan UniversityEmergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan UniversityEmergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan UniversityEmergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan UniversityEmergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan UniversityEmergency Medicine Laboratory and the Department of Emergency, West China Hospital, Sichuan UniversityAbstract To develop and evaluate a predictive model for intensive care unit (ICU) admission among patients with acute sedative-hypnotic overdose. We conducted a retrospective analysis of patients admitted to the emergency department of West China Hospital, Sichuan University, between October 11, 2009, and December 31, 2023. Patients were divided into ICU and non-ICU groups based on admission criteria including the need for blood purification therapy, organ support therapy (ventilatory support, vasoactive drugs, renal replacement therapy, artificial liver), or post-cardiopulmonary resuscitation. Patients were randomly split into a training set and a validation set in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to optimize variables, followed by a multivariate logistic regression analysis to identify independent risk factors for ICU admission. A nomogram model was constructed and assessed using receiver operating characteristic (ROC) curves, calibration curves, Decision Curve Analysis (DCA), and Clinical Impact Curve (CIC). Predictors in the nomogram included barbiturate overdose, Glasgow Coma Scale (GCS) score, and anion gap at admission. The nomogram demonstrated strong predictive performance with an area under the curve (AUC) of 0.858 (95% CI: 0.788–0.927) in the training set and 0.845 (95% CI: 0.757–0.933) in the validation set. Calibration curves showed the model closely matched the ideal curve, and DCA and CIC indicated high clinical applicability and utility. Barbiturate overdose, initial decreased GCS score and decreased anion gap were identified as independent risk factors for ICU admission in acute sedative-hypnotic overdose. The nomogram model based on these indicators demonstrates good predictive accuracy, discrimination, and clinical utility.https://doi.org/10.1038/s41598-025-85559-1Acute Sedative-hypnotic overdoseIntensive care unitPrognosisRisk factorsNomogram
spellingShingle Guo Tang
Tianshan Zhang
Ping Zhang
Sha Yang
Tao Cheng
Rong Yao
Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
Scientific Reports
Acute Sedative-hypnotic overdose
Intensive care unit
Prognosis
Risk factors
Nomogram
title Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
title_full Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
title_fullStr Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
title_full_unstemmed Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
title_short Development and validation of a prognostic nomogram for predicting of patients with acute sedative-hypnotic overdose admitted to the intensive care unit
title_sort development and validation of a prognostic nomogram for predicting of patients with acute sedative hypnotic overdose admitted to the intensive care unit
topic Acute Sedative-hypnotic overdose
Intensive care unit
Prognosis
Risk factors
Nomogram
url https://doi.org/10.1038/s41598-025-85559-1
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