Predicting 30-day mortality in patients with sepsis: An exploratory analysis of process of care and patient characteristics

预测脓毒症患者30天死亡率:对诊疗过程和患者特征的探索性分析

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Abstract

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 < 0.001), thrombocytopenia (adjOR = 3.10 95%CI = 1.23-7.82 p = 0.016), hospital-acquired sepsis (adjOR = 3.34 95%CI = 1.78-6.27 p < 0.001), increased lactate concentration (adjOR = 1.16 95%CI = 1.06-1.27 p = 0.001), remaining hypotensive after vasopressors (adjOR = 3.89 95%CI = 1.26-11.95 p = 0.02) and mottling (adjOR = 3.80 95%CI = 1.06-13.55 p = 0.04) increased 30-day mortality odds. Conversely, fever (adjOR = 0.46 95%CI = 0.28-0.75 p = 0.002), fluid refractory hypotension (adjOR = 0.29 95%CI = 0.10-0.87 p = 0.027) and being diagnosed in surgical wards (adjOR = 0.35 95%CI = 0.15-0.81 p = 0.015) were protective. Treatment timeliness were not significant factors. 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.

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