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Purpose: Intensive care requires extensive resources. The ICUs' resource use can be compared using standardized resource use ratios (SRURs). We assessed the effect of mortality prediction models on the SRURs.
Materials And Methods: We compared SRURs using different mortality prediction models: the recent Finnish Intensive Care Consortium (FICC) model and the SAPS-II model (n = 68,914 admissions). We allocated the resources to severity of illness strata using deciles of predicted mortality. In each risk and year stratum, we calculated the expected resource use per survivor from our modelling approaches using length of ICU stay and Therapeutic Intervention Scoring System (TISS) points.
Results: Resource use per survivor increased from one length of stay (LOS) day and around 50 TISS points in the first decile to 10 LOS-days and 450 TISS in the tenth decile for both risk scoring systems. The FICC model predicted mortality risk accurately whereas the SAPS-II grossly overestimated the risk of death. Despite this, SRURs were practically identical and consistent.
Conclusions: SRURs provide a robust tool for benchmarking resource use within and between ICUs. SRURs can be used for benchmarking even if recently calibrated risk scores for the specific population are not available.
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http://dx.doi.org/10.1016/j.jcrc.2024.154814 | DOI Listing |
JMIR Res Protoc
September 2025
University of Nevada, Las Vegas, Las Vegas, NV, United States.
Background: In-hospital cardiac arrest (IHCA) remains a public health conundrum with high morbidity and mortality rates. While early identification of high-risk patients could enable preventive interventions and improve survival, evidence on the effectiveness of current prediction methods remains inconclusive. Limited research exists on patients' prearrest pathophysiological status and predictive and prognostic factors of IHCA, highlighting the need for a comprehensive synthesis of predictive methodologies.
View Article and Find Full Text PDFPurpose: In Armenia, a lower-middle-income country, cancer causes 21% of all deaths, with over half of cases diagnosed at advanced stages. Without universal health insurance, patients rely on out-of-pocket payments or black-market channels for costly immunotherapies, underscoring the need for real-world data to inform equitable policy reforms.
Methods: We conducted a multicenter, retrospective cohort study of patients who received at least one dose of an immune checkpoint inhibitor (ICI) between January 2017 and December 2023 across six Armenian oncology centers.
Microb Genom
September 2025
International Centre of Excellence for Aquatic Animal Health, The Centre for Environment, Fisheries and Aquaculture Science, Weymouth, DT4 8UB, UK.
High rates of mortality of the common cockle, , have occurred in the Wash Estuary, UK, since 2008. A previous study linked the mortalities to a novel genotype of , with a strong correlation between cockle moribundity and the presence of . Here, we characterize a novel iridovirus, identified by chance during metagenomic sequencing of a gradient purification of cells, with the presence also correlated to cockle moribundity.
View Article and Find Full Text PDFCrit Care Explor
September 2025
Department of Biostatistics, University of Florida Colleges of Medicine and Public Health and Health Professions, Gainesville, FL.
Objectives Background: Monocyte anisocytosis (monocyte distribution width [MDW]) has been previously validated to predict sepsis and outcome in patients presenting in the emergency department and mixed-population ICUs. Determining sepsis in a critically ill surgical/trauma population is often difficult due to concomitant inflammation and stress. We examined whether MDW could identify sepsis among patients admitted to a surgical/trauma ICU and predict clinical outcome.
View Article and Find Full Text PDFCrit Care Explor
September 2025
Division of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Importance: Sepsis remains a leading cause of death in infectious cases. The heterogeneity of immune responses is a major challenge in the management and prognostication of patients with sepsis. Identifying distinct immune response subphenotypes using parsimonious classifiers may improve outcome prediction, particularly in resource-limited settings.
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