Publications by authors named "S G Leaver"

Aim: Levetiracetam is a widely used anti-epileptic in the critical care setting that is almost exclusively (>90%) renally excreted. The altered pharmacokinetics of levetiracetam have been widely studied in intermittent haemodialysis but the evidence and guidance on dosage in continuous renal replacement therapy is varied and poorly defined. Understanding this is critical as a significant number of critically unwell patients develop renal failure requiring continuous renal replacement therapy.

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Purpose: The heterogeneity of very old patients (age ≥ 80 years) and the prevalence of complex geriatric syndromes in this cohort constitute major challenges for the classical methods of evidence-based medicine to inform clinical practice. The lack of robust guidance for the management of critical conditions in these patients contributes to considerable uncertainty among practitioners and unwarranted variations of care. The European Society of Intensive Care Medicine (ESICM) initiated a Delphi study to translate the empirical knowledge of experts in this field into consensus-based recommendations for clinical practice.

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Purpose: There are limited data about the outcome of old intensive care (ICU) patients suffering from Covid-19 in the post-vaccination era. This study distinguishes the pre- and post-acute illness living conditions of ICU survivors from non-survivors.

Methods: This prospective international multicenter study included 642 old (≥ 70 years) ICU patients, including data ranging from pre-illness condition to functional 90-days follow-up.

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Shock is a life-threatening condition. This study evaluated if sublingual microcirculatory perfusion on admission is associated with 30-day mortality in older intensive care unit (ICU) shock patients. This trial prospectively recruited ICU patients (≥ 80 years old) with arterial lactate above 2 mmol/L, requiring vasopressors despite adequate fluid resuscitation, regardless of shock cause.

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Prognosis determines major decisions regarding treatment for critically ill patients. Statistical models have been developed to predict the probability of survival and other outcomes of intensive care. Although they were trained on the characteristics of large patient cohorts, they often do not represent very old patients (age ≥ 80 years) appropriately.

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