ArticleFrontiers in medicine2023
A risk nomogram for predicting prolonged intensive care unit stays in patients with chronic obstructive pulmonary disease.
Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Development of a nomogram to predict 30-day mortality in patients with chronic obstructive pulmonary disease complicated by sepsis: insights from the Medical Information Mart for Intensive Care (MIMIC-IV) database.Journal of thoracic disease · 2025Article
- Systemic Immune Inflammation Index (SII) and Prognostic Nutritional Index (PNI) Associated with Prolonged Intensive Care Unit (ICU) Stay in Patients with Pneumonia Complicated with Respiratory Failure.International journal of general medicine · 2025Article
- A Nomogram for Diagnosing Ventilator-Associated Pneumonia Using Circulating Inflammation Indicators in ICU Patients.Journal of inflammation research · 2025Article
- Nomogram model of mortality risk in patients with chronic obstructive pulmonary disease in intensive care unit: based on MIMIC-IV database and external validation study.Frontiers in medicine · 2025Article
- Association between geriatric nutritional risk index and adverse outcomes in critical ill patients with chronic obstructive pulmonary disease: a cohort study of 2824 older adults.BMC pulmonary medicine · 2024Article
- Construction of a prediction model for pulmonary infection and its risk factors in Intensive Care Unit patients.Pakistan journal of medical sciences · 2024Article
- Clinical nomogram prediction model to assess the risk of prolonged ICU length of stay in patients with diabetic ketoacidosis: a retrospective analysis based on the MIMIC-IV database.BMC anesthesiology · 2024Article
- Survival trends and conditional survival in primary non-metastatic esophageal cancer: a SEER population-based study and external validation.Translational cancer research · 2023Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Providing intensive care is increasingly expensive, and the aim of this study was to construct a risk column line graph (nomograms)for prolonged length of stay (LOS) in the intensive care unit (ICU) for patients with chronic obstructive pulmonary disease (COPD). Methods: This study included 4,940 patients, and the data set was randomly divided into training ( Results: This study selected 11 predictors: sepsis, renal replacement therapy, cerebrovascular disease, respiratory failure, ventilator associated pneumonia, norepinephrine, bronchodilators, invasive mechanical ventilation, electrolytes disorders, Glasgow Coma Scale score and body temperature. The models constructed using these 11 predictors indicated good predictive power, with the areas under the ROC curves being 0.826 (95%CI, 0.809-0.842) and 0.827 (95%CI, 0.802-0.853) in the training and validation sets, respectively. The Hosmer-Lemeshow test indicated a strong agreement between the predicted and observed probabilities in the training (χ Conclusion: This study has constructed and validated original and dynamic nomograms for prolonged ICU stay in patients with COPD using 11 easily collected parameters. These nomograms can provide useful guidance to medical and nursing practitioners in ICUs and help reduce the disease and economic burdens on patients.
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