Proposed diagnostic and treatment paradigm for high-grade neurological complications of immune checkpoint inhibitors.

Immune checkpoint inhibitors such as antibodies to cytotoxic lymphocyte-associated protein 4 (ipilimumab) and programmed cell-death 1 (pembrolizumab, nivolumab) molecules have been used in non-small cell lung cancer, metastatic melanoma, and renal-cell carcinoma, among others. With these agents, immune-related adverse events (irAEs) can occur, including those affecting the neurological axis. In this review, high-grade neurological irAEs associated with immune checkpoint inhibitors including cases of Guillain-Barré syndrome (GBS) and myasthenia gravis (MG) are analyzed. Based on current literature and experience at our institution with 4 cases of high-grade neurological irAEs associated with immune checkpoint inhibitors (2 cases of GBS, 1 case of meningo-radiculitis, and 1 case of myelitis), we propose an algorithm for the investigation and treatment of high-grade neurological irAEs. Our algorithm incorporates both peripheral nervous system (meningo-radiculitis, GBS, MG) and central nervous system presentations (myelitis, encephalopathy). It is anticipated that our algorithm will be useful both to oncologists and neurologists who are likely to encounter neurological irAEs more frequently in the future as immune checkpoint inhibitors become more widely used.

Headache in Guillain-Barré Syndrome: Diagnostic and Management Implications.

Headache is an uncommon symptom in Guillain-Barré syndrome (GBS). We review four clinical settings related to GBS in which headache may be present. We focus on pathophysiological explanations, alerting the clinician to further potential investigations and treatment. Most reports of headache in GBS occur in the context of the posterior reversible encephalopathy syndrome, an increasingly recognized dysautonomia-related GBS complication. Less frequent is headache in the setting of increased intracranial pressure and papilledema (secondary intracranial hypertension), Miller Fisher syndrome, and cerebral venous sinus thrombosis. Rarely, headache can occur secondary to aseptic meningitis from IVIg use.

Impact of stroke care unit on patient outcomes in a community hospital.

BACKGROUND AND PURPOSE: Geographically distinct multidisciplinary stroke care units (SCUs) have been shown by systematic reviews to have superior patient outcomes compared with conventional care in general medical wards. However, the effectiveness of SCUs in smaller North American community hospitals is less well defined. The objective of this study was to determine the impact of establishing a specialized SCU at a community hospital on patient outcomes. METHODS: This is a retrospective cohort study of 805 patients with stroke admitted to 2 community hospitals in Edmonton, Canada, from 2003 to 2009 using an administrative database. Stroke was identified by International Classification of Disease, 10th Edition, codes. One of the community hospitals established a SCU on January 1, 2007. This date was used to subdivide the patient population into 2 cohorts: phase 1 from 2003 to 2006 and phase 2 from 2007 to 2009. Outcomes measured were mortality, discharge disposition, length of stay, and complications and were adjusted for age, sex, and medical comorbidities. RESULTS: Patient mortality decreased significantly from 17.1% to 8.3% (adjusted odds ratio [OR], 0.54; 95% confidence interval [CI], 0.31-0.95) after SCU implementation, whereas it remained ≈19% at the control hospital. SCU also increased the odds that patients would be discharged home independently (adjusted OR, 2.17; 95% CI, 1.49-3.15; P<0.001] without increasing length of stay. CONCLUSIONS: Establishing a SCU in a community hospital not only increases the survival of stroke patients, but also the proportion of patients discharged home to live independently. The benefits of SCU reported in larger tertiary centers extend to smaller community hospitals with more limited resources.

Effects of cardiopulmonary bypass on sufentanil pharmacokinetics in patients undergoing coronary artery bypass surgery.

BACKGROUND: Complete pharmacokinetic modeling, including assessment of the effect of cardiopulmonary bypass (CPB) on sufentanil disposition, has not been reported. The aims of this investigation were to define a model that accurately predicted sufentanil concentrations during and after cardiac surgery and to determine if CPB had a clinically significant impact on sufentanil pharmacokinetics. METHODS: Population pharmacokinetic modeling was applied to data from 21 patients undergoing coronary artery bypass grafting. The predictive ability of models was assessed by calculating bias, accuracy, and measured:predicted concentration ratios versus time. A simple three-compartment model, without covariates, was initially compared with models having weight or gender as covariates and was subsequently used as the foundation for multiple CPB-adjusted models (allowing step-changes of parameters at the start or end of CPB). The primary criterion for choosing more complex models was a significant improvement in log-likelihood; secondary criteria were significant improvement in bias or accuracy. RESULTS: Neither covariate (weight or gender) models improved bias or accuracy compared with the simple three-compartment model. A final CPB-adjusted model with V2 and Cl3 changing at the start of CPB and V1, Cl2, and Cl3 changing at the end of CPB had significantly greater log-likelihood values when compared with the simple three-compartment model and with less elaborate CPB-adjusted models. However, bias and accuracy for this final model were not significantly different from the simple three-compartment model. CONCLUSIONS: When sufentanil is infused at a constant rate, with initiation of CPB, a pharmacokinetic model adjusted for CPB predicts that the sufentanil concentration will decrease approximately 17% and that it will begin to return to the prebypass concentration 12 min after initiation of CPB. At the end of CPB, this model also predicts a brief spike of the sufentanil concentration. These predictions reflect changes in the measured sufentanil concentrations. However, compared with a simple, three-compartment model, incorporating step-changes of pharmacokinetic parameters at the start or end of cardiopulmonary bypass (or both) did not significantly improve overall perioperative prediction of measured sufentanil concentrations. This suggests that CPB has clinically insignificant effects on sufentanil kinetics in adults.

Cardiopulmonary bypass has minimal effects on the pharmacokinetics of fentanyl in adults.

BACKGROUND: Although fentanyl has been widely used in cardiac anesthesia, no complete pharmacokinetic model that has assessed the effect of cardiopulmonary bypass (CPB) and that has adequate predictive accuracy has been defined. The aims of this investigation were to determine whether CPB had a clinically significant impact on fentanyl pharmacokinetics and to determine the simplest model that accurately predicts fentanyl concentrations during cardiac surgery using CPB. METHODS: Population pharmacokinetic modeling was applied to concentration-versus-time data from 61 patients undergoing coronary artery bypass grafting using CPB. Predictive ability of models was assessed by calculating bias (prediction error), accuracy (absolute prediction error), and measured:predicted concentration ratios versus time. The predictive ability of a simple three-compartment model with no covariates was initially compared to models with premedication (lorazepam vs. clonidine), sex, or weight as covariates. This simple model was then compared to 18 CPB-adjusted models that allowed for step changes in pharmacokinetic parameters at the start and/or end of CPB. The predictive ability of the final model was assessed prospectively in a second group of 29 patients. RESULTS: None of the covariate (premedication, sex, weight) models nor any of the CPB-adjusted models significantly improved prediction error or absolute prediction error, compared to the simple three-compartment model. Thus, the simple three-compartment model was selected as the final model. Prospective assessment of this model yielded a median prediction error of +3.8%, with a median absolute prediction error of 15.8%. The model parameters were as follows: V1, 14.4 l; V2, 36.4 l; V3, 169 l; Cl1, 0.82 l. min-1; Cl2, 2.31 l x min-1; Cl3, 1.35 l x min-1. CONCLUSIONS: Compared to other factors that cause pharmacokinetic variability, the effect of CPB on fentanyl kinetics is clinically insignificant. A simple three-compartment model accurately predicts fentanyl concentrations throughout surgery using CPB.