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A Nomogram Model for Post-Intubation Hypotension in Patients with Severe Pneumonia in the Emergency Department
BACKGROUND: Post-intubation hypotension (PIH) frequently occurs in the management of critically ill patients and is associated with prognosis. The study aimed to construct a prediction model for PIH events by analyzing risk factors in patients with severe pneumonia in the emergency department. METHO...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10655604/ https://www.ncbi.nlm.nih.gov/pubmed/38026236 http://dx.doi.org/10.2147/JIR.S430488 |
Sumario: | BACKGROUND: Post-intubation hypotension (PIH) frequently occurs in the management of critically ill patients and is associated with prognosis. The study aimed to construct a prediction model for PIH events by analyzing risk factors in patients with severe pneumonia in the emergency department. METHODS: We retrospectively enrolled 572 patients with severe pneumonia diagnosed in the emergency department of West China Hospital of Sichuan University. Five hundred patients with severe pneumonia who underwent endotracheal intubation were included in the study. All patients were randomized according to 7:3 and divided into a training cohort (n=351) and a validation cohort (n=149). Risk factors for PIH were analyzed using Least Absolute Shrinkage and Selection Operator (LASSO) and multivariable logistic regression. Calibration curves, receiver operating characteristic (ROC) curve, and decision curve analysis were applied to assess the predictive model’s fitness, discrimination, and clinical utility. RESULTS: A total of 500 patients with severe pneumonia who underwent endotracheal intubation were enrolled in this study, and PIH occurred in 234 (46.8%) of these patients. Age, heart rate, systolic blood pressure, chronic obstructive pulmonary disease, acute physiology and chronic health evaluation II score, and induction agent use were identified as significant risk factors for the occurrence of PIH. Additionally, the body mass index was the opposite of the above. The area under the ROC curve (AUC) for the model was 0.856 (95% CI, 0.818–0.894) in the training cohort and 0.849 (95% CI, 0.788–0.910) in the validation cohort. The nomogram model was validated and demonstrated good calibration and high net clinical benefit. Finally, to facilitate application by clinicians, an online server has been set up which can be accessed free of charge via the website https://chinahospitals.shinyapps.io/DynNomapp/. CONCLUSION: The nomogram is used for individualized prediction of patients with severe pneumonia prior to intubation and is simple to perform with high clinical value. |
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