Overview
Stroke, severe brain injury, uncontrolled seizures and brain infections are the most common life-threatening neurological illnesses in the world with an estimated combined annual hospital management cost of up to 44 billion dollars. Seizures and infections are common complications following acute neurological illnesses and contribute significantly to poor outcomes if not promptly treated with appropriately dosed anti-seizure medications and antibiotics, respectively. Limited research suggested that many of those patients present with a phenomenon called augmented renal clearance (ARC) or, in other words, enhanced kidney function. ARC may have a significant influence on how medications are removed from the body potentially resulting in insufficient doses and treatment failure. Therefore, patients with ARC require higher medication doses; however, ARC is largely undetected using kidney assessment methods currently used in practice. In addition, it is not clear how medications should be dosed in those with ARC. The majority of ARC research has not focused on patients with life-threatening neurological illnesses. Thus, clinicians are likely under-dosing vital medications in those patients, and completely unaware. There is an immediate need to address the gap in knowledge. Therefore, this research aims to characterize the phenomenon of ARC in patients with life-threatening neurological illnesses through identifying the frequency, duration, contributing factors and clinical impact of ARC. Adult patients admitted to the neurosciences intensive care unit for life-threatening neurological illnesses will be enrolled in the study. Urine and blood samples wil be collected from participants to determine the presence of ARC and identify its contributing factors. In addition, blood samples will be collected from participants treated with select antibiotics and anti-seizure medications to determine their concentration and propose dose adjustment in those with ARC. This research is expected to improve the care of patients with life-threatening neurological illnesses through efficient identification and monitoring of patients exhibiting ARC facilitating timely medication dosage optimization. Furthermore, recommendations of optimal doses of commonly used medications in patients with ARC would improve the likelihood of treatment success with potential to improve patients' health and wellbeing.
Description
Background and Importance: Stroke, severe brain injury, status epilepticus and meningitis are the most common life-threatening neurological illnesses in the world with an estimated combined annual hospital management cost of up to 44 billion dollars. Seizures and infections are common complications following acute neurological illnesses and contribute significantly to poor outcomes if not promptly treated with appropriately dosed antiseizure medications (ASMs) and antimicrobials, respectively. Limited evidence suggests that augmented renal clearance (ARC) is present in many of those patients. Defined as a creatinine clearance (CrCl) \> 130 ml/min/m2, the prevalence of ARC has been reported as high as 80%. ARC has a significant impact on clearance of renally eliminated drugs including some ASMs and antimicrobials, potentially resulting in low exposure with subsequent therapy failure. Therefore, patients with ARC require higher drug doses; however, ARC is largely undetected using the common CrCl equations and it is not clear how drugs should be dosed. The majority of ARC literature has not focused on neurocritical care patients; thus, clinicians are likely under-dosing vital medications in these patients and completely unaware. There is an immediate need to address the gap in knowledge.
The overall goal is to characterize the phenomenon of ARC in patients with life-threatening neurological illnesses in order to create a guide to clinicians regarding identification, monitoring and drug dosing in patients exhibiting ARC to facilitate treatment success.
Research Aims:
- To characterize the phenomenon of ARC in neurocritical care population (prevalence, duration and impact on hospital outcomes).
- To measure the impact of ARC on the disposition of commonly used renally eliminated medications in neurocritical care.
- To develop guidelines to clinicians regarding the identification, monitoring and drug dosing in neurocritical care patients exhibiting ARC (Knowledge Translation).
Methods/Approaches/Expertise: This will be a multicenter prospective observational study in adult patients admitted to the Neuroscience Intensive Care Units (ICU) for acute neurological illnesses. Participants' CrCl will be measured using the 8-h urine collection method daily for 10 days or until ICU discharge. Participants with a urine CrCl \> 130 ml/min/m2 will be included in the ARC group. Regression modeling will be utilized to determine predictors of ARC and propose an ARC prediction model. In addition, patients treated with levetiracetam, lacosamide, vancomycin, meropenem, cefepime or piperacillin-tazobactam will have blood samples collected for plasma concentration determination. Pharmacokinetic parameters will be calculated and dosage regimens will be proposed.
This work will be a collaborative effort among investigators with diverse expertise in pharmacokinetics, critical care and clinical research.
Expected Outcomes: This research is expected to improve the care of patients with life-threatening neurological illnesses through efficient identification and monitoring of patients exhibiting ARC facilitating timely medication dosage optimization. Furthermore, recommendations of optimal doses of commonly used medications in patients with ARC would improve the likelihood of treatment success with potential to improve patient outcomes.
Eligibility
Inclusion Criteria:
- Age 18-85 years
- Admitted to ICU at one of the participating sites
- Diagnosis: SAH, TBI, ICH, meningitis, SE or ischemic stroke
- Provision of informed consent
- Foley catheter in place at time of consent (to facilitate urine collection)
Exclusion Criteria:
- Incarceration
- Anticipated ICU length of stay is \< 72 hours (insufficient time for monitoring)
