Predicting 30-day mortality in patients with sepsis: an exploratory analysis of process of care and patient characteristics
| Autor: | Sally Wood, Iain K. Moppett, Tricia M. McKeever, Miriam Sanderson, Esme Blyth, Marc Chikhani, Mark Simmonds |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
medicine.medical_specialty
Survival Epidemiology Exploratory research Patient characteristics Critical Care and Intensive Care Medicine Critical Care Nursing Sepsis 03 medical and health sciences 0302 clinical medicine medicine In patient 030212 general & internal medicine Mortality Activity-based costing business.industry Public health 030208 emergency & critical care medicine Original Articles medicine.disease 30 day mortality Emergency medicine Prediction business |
| ISSN: | 1751-1437 |
| Popis: | Background Sepsis represents a significant public health burden, costing the NHS £2.5 billion annually, with 35% mortality in 2006. The aim of this exploratory study was to investigate risk factors predictive of 30-day mortality amongst patients with sepsis in Nottingham. Methods Data were collected prospectively from adult patients with sepsis in Nottingham University Hospitals NHS Trust as part of an on-going quality improvement project between November 2011 and March 2014. Patients admitted to critical care with the diagnosis of sepsis were included in the study. In all, 97 separate variables were investigated for their association with 30-day mortality. Variables included patient demographics, symptoms of systemic inflammatory response syndrome, organ dysfunction or tissue hypoperfusion, locations of early care, source of sepsis and time to interventions. Results A total of 455 patients were included in the study. Increased age (adjOR = 1.05 95%CI = 1.03–1.07 p Conclusion Several important predictors of 30-day mortality were found by this research. Retrospective analysis of our sepsis data has revealed mortality predictors that appear to be more patient-related than intervention-specific. With this information, care can be improved for those identified most at risk of death. |
| Databáze: | OpenAIRE |
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