Purpose: Clinicians lack a validated tool for risk stratification for need for mechanical ventilation (MV) in acute exacerbations of chronic obstructive pulmonary disease (AECOPD). We sought to compare 2 risk scores, BAP-65 and CURB-65, at predicting a need for MV in AECOPDs.
Materials And Methods: We analyzed 34,478 AECOPD admissions to 195 US hospitals (2007). We compared the rates of MV at admission and at any point during hospitalization based on the respective BAP-65 and CURB-65 scores. We compared the accuracy of the 2 scores via the area under the receiver operating characteristic curves.
Results: The overall MV rate at admission was 7.9%, and the rate of MV any time equaled 9.3%. Use of MV increased with escalating BAP-65 and CURB-65 scores. The area under the receiver operating characteristic curve for BAP-65 was higher than that for CURB-65 for both early MV, 0.81 (95% confidence interval [CI], 0.80-0.82) vs 0.76 (95% CI, 0.75-0.77), P < .0001, and MV any time, 0.78 (95% CI, 0.77-0.79) vs 0.74 (95% CI, 0.73-0.75), P < .0001.
Conclusions: BAP-65 identifies patients with AECOPD at high risk for need of MV more accurately than does CURB-65. BAP-65 may represent a useful tool for initial MV risk stratification in AECOPD.
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http://dx.doi.org/10.1016/j.jcrc.2012.02.015 | DOI Listing |
Respiration
September 2024
Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Introduction: Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to intensive care unit (ICU) are exposed to poor clinical outcomes, and no specific prognostic models are available among this population. We aimed to develop and validate a risk score for prognosis prediction for these patients.
Methods: This was a multicenter observation study.
J Thorac Dis
May 2024
Department of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, China.
Background: Serum anion gap (AG) can potentially be applied to the diagnosis of various metabolic acidosis, and a recent study has reported the association of AG with the mortality of patients with coronavirus disease 2019 (COVID-19). However, the relationship of AG with the short-term mortality of patients with ventilator-associated pneumonia (VAP) is still unclear. Herein, we aimed to investigate the association between AG and the 30-day mortality of VAP patients, and construct and assess a multivariate predictive model for the 30-day mortality risk of VAP.
View Article and Find Full Text PDFLancet Digit Health
March 2024
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Advanced Life Support, Emergency Medical Services (SACYL), Valladolid, Spain.
Background: A myriad of early warning scores (EWSs) exist, yet there is a need to identify the most clinically valid score to be used in prehospital respiratory assessments to estimate short-term and midterm mortality, intensive-care unit admission, and airway management in life-threatening acute respiratory distress.
Methods: This is a prospective, observational, multicentre, ambulance-based, external validation study performed in 44 ambulance services and four hospitals across three Spanish provinces (ie, Salamanca, Segovia, and Valladolid). We identified adults (ie, those aged 18 years and older) discharged to the emergency department with suspected acute respiratory distress.
Respir Res
February 2024
Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Guo-xue-xiang 37#, Wuhou District, Chengdu, 610041, Sichuan Province, China.
J Asthma
March 2024
Department of Respiratory and Critical Care Medicine, First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China.
Objective: While linear regression and LASSO models have been established for predicting in-hospital mortality, there is currently no validated clinical prediction algorithm to predict in-hospital mortality for patients with chronic obstructive pulmonary disease (COPD) exacerbations using machine learning. Thus, we will evaluate the BAP-65 and CURB-65, and construct a novel prediction model using the random forest (RF) technique.
Methods: A dataset of 1,418 patients with COPD exacerbations was collected.
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