No abstract

Neuromuscular adverse events following cancer treatment with anti-programmed cell death protein 1 (PD-1) monoclonal antibodies are relatively rare, yet potentially fatal. We performed a systematic review to characterize the clinical presentation, diagnostic workup, and management of neuromuscular disorders (NMDs) in patients treated with nivolumab or pembrolizumab monotherapy or concurrent with other immunologic agents, such as ipilimumab. Sixty-one publications on 85 patients (mean age 66.9 years [range 34–86]; male/female 2.6:1; 59% metastatic melanoma) were identified from selected indexing databases until June 2018. Forty-eight patients had received nivolumab and 39 pembrolizumab. The mean number of PD-1 inhibitor treatment cycles prior to onset of symptoms was 3.6 (range 1–28). Symptoms included oculomotor (47%), respiratory (43%), bulbar (35%), and proximal weakness (35%), as well as muscle pain (28%). Diagnoses were categorized as myasthenia gravis (27%), neuropathy (23%), myopathy (34%), or a combination of these (16%). After a critical review of the data, however, evidence did not support the stated NMD diagnosis in 13% of cases, while up to 25% of patients had signs of additional NMDs. Cardiac complications occurred in more than 30% of patients diagnosed with myasthenia gravis or myositis. Mortality was high in these patients, despite adequate treatment strategies including corticosteroid, IV immunoglobulins, and plasma exchange. The clinical presentation of NMDs associated with PD-1 inhibitors is often atypical, with considerable overlap between myasthenia gravis and myopathy, and cardiac/respiratory complications are common.

Extracranial carotid artery occlusion or high-grade stenosis with concomitant intracranial embolism causes severe ischemic stroke and shows poor response rates to intravenous thrombolysis (IVT). Endovascular therapy (EVT) utilizing thrombectomy assisted by carotid stenting was long considered risky because of procedural complexities and necessity of potent platelet inhibition-in particular following IVT. This study assesses the benefits and harms of thrombectomy assisted by carotid stenting and identifies factors associated with clinical outcome and procedural complications. Retrospective single-center analysis of 47 consecutive stroke patients with carotid occlusion or high-grade stenosis and concomitant intracranial embolus treated between September 2011 and December 2014. Benefits included early improvement of stroke severity (NIHSS ≥ 10) or complete remission within 72 h and favorable long-term outcome (mRS ≤ 2). Harms included complications during and following EVT. Mean age was 64.3 years (standard deviation ±12.5), 40 (85%) patients received IVT initially. Median NIHSS was 16 (inter-quartile range 14-19). Mean time from stroke onset to recanalization was 311 min (standard deviation ±78.0). Early clinical improvement was detected in 22 (46%) patients. Favorable outcome at 3 months occurred in 32 (68%) patients. Expedited patient management was associated with favorable clinical outcome. Two (4%) patients experienced symptomatic hemorrhage. Eight (17%) patients experienced stent thrombosis. Four (9%) patients died. Thrombectomy assisted by carotid stenting seems beneficial and reasonably safe with a promising rate of favorable outcome. Nevertheless, adverse events and complications call for additional clinical investigations prior to recommendation as clinical standard. Expeditious patient management is central to achieve good clinical outcome.

Functional MRI (fMRI) and EEG may reveal residual consciousness in patients with disorders of consciousness (DoC), as reflected by a rapidly expanding literature on chronic DoC. However, acute DoC is rarely investigated, although identifying residual consciousness is key to clinical decision-making in the intensive care unit (ICU). Therefore, the objective of the prospective, observational, tertiary center cohort, diagnostic phase IIb study ‘Consciousness in neurocritical care cohort study using EEG and fMRI’ (CONNECT-ME, NCT02644265) was to assess the accuracy of fMRI and EEG to identify residual consciousness in acute DoC in the ICU. Between April 2016 and November 2020, 87 acute DoC-patients with traumatic or non-traumatic brain injury were examined with repeated clinical assessments, fMRI and EEG. Resting-state EEG and EEG with external stimulations were evaluated by visual analysis, spectral band analysis and a Support Vector Machine (SVM) consciousness classifier. In addition, within- and between-network resting-state connectivity for canonical resting-state fMRI networks were assessed. Next, we used EEG and fMRI data at study enrollment in two different machine-learning algorithms (Random Forest and SVM with a linear kernel), to distinguish patients in a minimally conscious state or better (≥MCS) from those in coma or unresponsive wakefulness state (≤UWS), at time of study enrollment and at ICU-discharge (or before death). Prediction performances were assessed with area under the curve (AUC). Of 87 DoC-patients (mean age, 50.0 ± 18 years, 43% women), 51 (59%) were ≤ UWS and 36 (41%) were ≥ MCS at study enrollment. Thirty-one (36%) patients died in the ICU, including 28 who had life-sustaining therapy withdrawn. EEG and fMRI predicted consciousness levels at study enrollment and ICU-discharge, with maximum AUCs of 0.79 (95% CI 0.77-0.80) and 0.71 (95% CI 0.77-0.80), respectively. Models based on combined EEG and fMRI features predicted consciousness levels at study enrollment and ICU-discharge with maximum AUCs of 0.78 (95% CI 0.71-0.86) and 0.83 (95% CI 0.75-0.89), respectively, with improved positive predictive value and sensitivity. Overall, both machine-learning algorithms (SVM and Random Forest) performed equally well. In conclusion, we suggest that acute DoC prediction models in the ICU be based on a combination of fMRI and EEG features, regardless of the machine-learning algorithm used.