Development and validation of a nomogram model for predicting MDRO infections in elderly ICU patients with pulmonary
Bo Wang1, Suming Zhang1, Lei Meng1
1Department of Intensive Care Unit, Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, China.
Background:
MDRO infections are increasingly problematic in ICUs, especially among elderly patients with lung infections, but knowledge about these infections in this group is limited. This study aimed to assess the status and risk factors of MDRO infections in elderly ICU patients and develop a risk prediction model to aid clinical decisions.
Methods:
Using a retrospective cohort study, a total of 494 elderly patients with lung infections admitted to the ICU from January 2017 to December 2022 were selected, and the patients were divided into the MDRO group (259) and the non-MDRO group (235) based on whether or not the patients developed MDRO infections. Lasso and multifactorial logistic regression were applied to analyze the independent risk factors for multidrug-resistant bacterial infections in elderly patients with pulmonary infections, and to construct a nomogram model of the risk of MDRO infections. The differentiation, consistency and clinical benefit of the model were evaluated by receiver operating characteristic curve(ROC), calibration curves and decision curve analysis, respectively, and the stability of the model was verified by Bootstrap method.
Results:
Duration of hospitalization before MDRO diagnosis, chronic obstructive pulmonary disease, personal history of cerebrovascular disease, tracheotomy and prior carbapenem exposure were found to be independent risk factors for multidrug-resistant bacterial infections in elderly patients with pulmonary infections in the intensive care unit (all p < 0.05). The nomogram model, constructed based on the results of logistic regression analysis, exhibited an area under the ROC curve of 0.748 with a 95% confidence interval of 0.705-0.790. The Hosmer-Lemeshow test indicated that the model predicted a good fit (p = 0.75), and the DCA curve suggested that the model had a good clinical utility.
Conclusion:
Risk prediction model is effective in predicting the risk of MDRO infection in the ICU elderly pulmonary infection population and can be used to assess risk and inform preventive treatment and nursing interventions.
Insights
Multidrug-resistant organism (MDRO) infections pose a significant threat in ICUs. A new risk prediction model effectively identifies elderly patients with pulmonary infections at high risk for MDROs, aiding clinical decisions.
Area of Science:
- Critical Care Medicine
- Infectious Diseases
- Geriatrics
Background:
- Multidrug-resistant organism (MDRO) infections are a growing concern in intensive care units (ICUs), particularly among elderly patients with lung infections.
- Limited knowledge exists regarding the specific risks and patterns of MDRO infections in this vulnerable demographic.
Purpose of the Study:
- To assess the prevalence and identify independent risk factors for MDRO infections in elderly ICU patients with pulmonary infections.
- To develop and validate a predictive model for MDRO infection risk in this population to guide clinical management.
Main Methods:
- A retrospective cohort study involving 494 elderly patients with pulmonary infections admitted to the ICU.
- Lasso and multifactorial logistic regression were used to identify risk factors and construct a nomogram prediction model.
- Model performance was evaluated using ROC curves, calibration plots, and decision curve analysis, with Bootstrap validation for stability.
Main Results:
- Independent risk factors for MDRO infections included prolonged hospitalization, chronic obstructive pulmonary disease, cerebrovascular disease history, tracheotomy, and prior carbapenem exposure.
- The developed nomogram model demonstrated good predictive accuracy (AUC = 0.748) and clinical utility.
- The model showed good fit (Hosmer-Lemeshow p=0.75) and clinical benefit according to decision curve analysis.
Conclusions:
- The developed risk prediction model is effective for identifying elderly ICU patients with pulmonary infections at risk of MDRO.
- This tool can aid in risk assessment and inform targeted preventive strategies and nursing interventions to combat MDRO infections.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
04:32Murine Oropharyngeal Aspiration Model of Ventilator-associated and Hospital-acquired Bacterial Pneumonia
Published on: June 28, 2018
Related Concept Videos
01:30Pneumonia III: Complications and Assessment
01:30Pneumonia V: Nursing management and Prevention
The nurse must practice strict medical asepsis and adhere to infection control guidelines to minimize healthcare-associated infections.
Enhance airway patency
Position the patient correctly to facilitate drainage of the affected lung segments. Manual or mechanical percussion and vibration can also be employed....
01:28Pneumonia IV: Management
Bacterial Pneumonia Treatment
For bacterial pneumonia, antibiotics serve as the cornerstone of therapy. Initial treatment often begins with empirical antibiotics, tailored to the anticipated causative organism and adjusted based on culture results. Key antibiotic choices include:
01:27Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies
Medical History