Background And Aims: Mortality prediction models help to extract and relate patient data upon admission to intensive or intermediate care units (ImCUs). Considering technical and economic healthcare developments, re-evaluations of score performances are required to warrant their validity. This study validates and compares established scoring systems in cirrhotic ImCU patients.
Methods: Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 2 and 3, Sepsis Organ Failure Assessment (SOFA), Mortality Probability Model at ICU admission (MPMo) II and III, Model for End stage Liver Disease (MELD), CLIF-Consortium Acute-on-Chronic Liver Failure (CLIF-C ACLF), CLIF-Consortium Acute Decompensation (CLIF-C AD), and Intermediate Care Unit Severity Score (ImCUSS) were calculated in patients with cirrhosis (n = 98) at ImCU admission. Discrimination performances were evaluated by area under the receiver operating characteristic curves (AUROCs), calibration performances with calibration belt plots, and their corresponding p values.
Results: Overall, SAPS 3 and CLIF-C ACLF have shown the best 90-day mortality prediction outcomes with AUROCs of 0.825 and 0.783 along with calibration belt p values of 0.128 and 0.061, respectively. In a subgroup analysis of patients with acute-on-chronic liver failure (ACLF), expanded SAPS 2, SOFA, and SAPS 3 reached the best AUROCs, i.e., 0.760, 0.750, and 0.714, but none of the tested scores reached an acceptable calibration.
Conclusion: Ninety-day mortality risk prediction of the SAPS 3 and CLIF-C ACLF was accurate in our cohort of patients with liver cirrhosis admitted to ImCUs. A particular challenge remains that is the mortality prediction in patients with ACLF requiring ImCU-level care; here, further developments are needed to generate scores with acceptable predictive performances.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1159/000522595 | DOI Listing |
BMC Public Health
January 2025
Research Institute for Healthcare Policy, Korean Medical Association, Yongsan-gu, Seoul, South Korea.
Background: In 2024, the Korean Ministry of Health and Welfare enforced a policy to increase the number of medical school students by 2,000 over the next 5 years, despite opposition from doctors. This study aims to predict the trend of excess or shortage of medical personnel in Korea due to the policy of increasing the number of medical school students by 2035.
Methods: Data from multiple sources, including the Ministry of Health and Welfare, National Health Insurance Corporation, and the Korean Medical Association, were used to estimate supply and demand.
Lipids Health Dis
January 2025
Department of Cardiology, West China Hospital, Sichuan University West China School of Medicine, 37 Guoxue Road, Chengdu, Sichuan, 610041, China.
Background: Atrial fibrillation (AF) is the most prevalent arrhythmia encountered in clinical practice. Triglyceride glucose index (Tyg), a convenient evaluation variable for insulin resistance, has shown associations with adverse cardiovascular outcomes. However, studies on the Tyg index's predictive value for adverse prognosis in patients with AF without diabetes are lacking.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Oncology, Zhuji People's Hospital of Zhejiang Province, No. 9 Jianmin Road, Zhuji, Zhejiang, 311800, China.
Background: Evidence is lacking on whether chronic pain is related to the risk of cancer mortality. This study seeks to unveil the association between chronic pain and all-cause, cancer, as well as non-cancer death in cancer patients based on the National Health and Nutrition Examination Survey (NHANES) database.
Methods: Cancer survivors aged at least 20 (n = 1369) from 3 NHANES (1999-2004) cycles were encompassed.
Int J Obes (Lond)
January 2025
Department of Cardiology, Sakakibara Heart Institute, Tokyo, Japan.
Background: Obesity is a risk factor for heart failure (HF) development but is associated with a lower incidence of mortality in HF patients. This obesity paradox may be confounded by unrecognized comorbidities, including cachexia.
Methods: A retrospective assessment was conducted using data from a prospectively recruiting multicenter registry, which included consecutive acute heart failure patients.
Sci Rep
January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!