Objective: To evaluate the ability of three scoring systems to predict hospital mortality in adult patients of an interdisciplinary intensive care unit in Germany.
Design: A prospective cohort study.
Setting: A mixed medical and surgical intensive care unit at a teaching hospital in Germany.
Patients: From a total of 3,108 patients, 2,795 patients (89.9%) for Acute Physiology and Chronic Health Evaluation (APACHE) II and 2,661 patients (85.6%) for APACHE III and Simplified Acute Physiology Score (SAPS) II could be enrolled to the study because of defined exclusion criteria.
Interventions: None.
Measurements And Main Results: Probabilities of hospital death for patients were estimated by applying APACHE II and III and SAPS II and compared with observed outcomes. The overall goodness-of-fit of the three models was assessed. Hospital death rates were equivalent to those predicted by APACHE II but higher than those predicted by APACHE III and SAPS II. Calibration was good for APACHE II. For the other systems, it was insufficient, but better for SAPS II than for APACHE III. The overall correct classification rate, applying a decision criterion of 50%, was 84% for APACHE II and 85% for APACHE III and SAPS II. The areas under the receiver operating characteristic curve were 0.832 for APACHE II and 0.846 for APACHE III and SAPS II. Risk estimates for surgical and medical admissions differed between the three systems. For all systems, risk predictions for diagnostic categories did not fit uniformly across the spectrum of disease categories.
Conclusions: Our data more closely resemble those of the APACHE II database, demonstrating a higher degree of overall goodness-of-fit of APACHE II than APACHE III and SAPS II. Although discrimination was slightly better for the two new systems, calibration was good with a close fit for APACHE II only. Hospital mortality was higher than predicted for both new models but was underestimated to a greater degree by APACHE III. Both score systems demonstrated a considerable variation across the spectrum of diagnostic categories, which also differed between the two models.
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http://dx.doi.org/10.1097/00003246-200001000-00005 | DOI Listing |
BMC Anesthesiol
January 2025
Department of Critical Care Medicine, West China Hospital, Sichuan University, 37 Guo Xue Xiang St, Chengdu, 610041, Sichuan, China.
Objective: Early diagnosis of intensive care unit-acquired weakness (ICUAW) is crucial for improving the outcomes of critically ill patients. Hence, this study was designed to identify predisposing factors for ICUAW and establish a predictive model for the early diagnosis of ICUAW.
Methods: This prospective observational multicenter study included septic patients from the comprehensive ICUs of West China Hospital of Sichuan University and 10 other hospitals between September and November 2023.
Medicina (Kaunas)
January 2025
Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
This study sought to identify predictors for peripartum patients admitted to non-intensive care wards who later upgraded to the Intensive Care Unit (ICU). This was a retrospective observational study of patients admitted to the Maternal Fetal Ward between 01/2017 and 12/2022, who later upgraded to the ICU. Upgraded patients were 1:1 propensity score matched with those who remained on the Maternal Fetal Ward (control).
View Article and Find Full Text PDFBiomedicines
January 2025
Department I, Discipline of Anatomy and Embryology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Background And Objectives: The interplay of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and infection (CDI) poses a critical clinical challenge. The resultant inflammatory milieu and its impact on outcomes remain incompletely understood, especially among vulnerable subgroups such as elderly patients, those with diabetes, and individuals with cancer. This study aimed to characterize inflammatory markers and composite inflammatory severity scores-such as Acute Physiology and Chronic Health Evaluation II (APACHE II), Confusion, Urea, Respiratory rate, Blood pressure, and age ≥ 65 years (CURB-65), National Early Warning Score (NEWS), and the Systemic Immune-Inflammation Index (SII)-in hospitalized Coronavirus Disease 2019 (COVID-19) patients with and without CDI, and to evaluate their prognostic implications across key clinical subgroups.
View Article and Find Full Text PDFJ Crit Care
January 2025
Department of Intensive Care, Austin Hospital, Heidelberg, VIC, Australia; Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
Background: In critically ill patients with acute kidney injury (AKI), a fluid balance (FB) > 2 L at 72 h after AKI diagnosis is associated with adverse outcomes. Identification of patients at high-risk for such fluid accumulation may help prevent it.
Methods: We used Australian electronic medical record (EMR)-based clinical data to develop the "AKI-FB risk score", validated it in a British cohort and used it to predict a positive FB >2 L at 72 h after AKI diagnosis.
Bioinformatics
January 2025
European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom.
Summary: In recent years there has been a surge in prokaryotic genome assemblies, coming from both isolated organisms and environmental samples. These assemblies often include novel species that are poorly represented in reference databases creating a need for a tool that can annotate both well-described and novel taxa, and can run at scale. Here, we present mettannotator-a comprehensive, scalable Nextflow pipeline for prokaryotic genome annotation that identifies coding and non-coding regions, predicts protein functions, including antimicrobial resistance, and delineates gene clusters.
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