Neurocritical care
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Neurocritical care relies on the continuous, real-time measurement of numerous physiologic parameters. While our capability to obtain such measurements from patients has grown markedly with multimodal monitoring in many neurologic or neurosurgical intensive care units (ICUs), our ability to transform the raw data into actionable information is limited. One reason is that the proprietary nature of medical devices and software often prevents neuro-ICUs from capturing and centrally storing high-density data. ⋯ Although many different approaches to informatics are discussed and considered, here we focus on the Bayesian probabilistic paradigm. It quantifies the uncertainty inherent in neurocritical care instead of ignoring it, and formalizes the natural clinical thought process of updating prior beliefs using incoming patient data. We review this and other opportunities, as well as challenges, for the development and refinement of informatics tools in neurocritical care.
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Central nervous system infections requiring treatment with intraventricular (IVT) vancomycin are becoming increasingly common with advent of intracranial devices and increasing prevalence of multi-drug resistant and nosocomial organisms. Administering vancomycin via IVT route bypasses the blood-brain barrier to allow localized and controlled delivery directly to the desired site of action, achieving high concentrations for more reliable bactericidal action. This article systematically reviews current literature on IVT vancomycin in adults, compiles current knowledge, and integrates available evidence to serve as a practical reference. ⋯ Using IVT vancomycin to treat meningitis, ventriculitis, and CNS device-associated infections appears safe and effective based on current evidence. Optimal regimens are still unclear, and dosing of IVT vancomycin requires intricate consideration of patient specific factors and their impact on CNS pathophysiology. Higher-quality clinical trials are necessary to characterize the disposition of vancomycin within CNS, and to determine models for various pathophysiological conditions to facilitate better understanding of effects on pharmacokinetic and pharmacodynamic parameters.
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Understanding the dynamic relationship between cerebral blood flow (CBF) and the circulation of cerebrospinal fluid (CSF) can facilitate management of cerebral pathologies. For this reason, various hydrodynamic models have been introduced in order to simulate the phenomena governing the interaction between CBF and CSF. The identification of hydrodynamic models requires an array of signals as input, with the most common of them being arterial blood pressure, intracranial pressure, and cerebral blood flow velocity; monitoring all of them is considered as a standard practice in neurointensive care. ⋯ This review presents model-derived indices that describe cerebrovascular phenomena, the nature of which is both physiological (carbon dioxide reactivity and arterial hypotension) and pathological (cerebral artery stenosis, intracranial hypertension, and cerebral vasospasm). In a neurointensive environment, real-time monitoring of a patient with these indices may be able to provide a detection of the onset of a cerebrovascular phenomenon, which could have otherwise been missed. This potentially "early warning" indicator may then prove to be important for the therapeutic management of the patient.