Objective To systematically describe central (CNS) and peripheral (PNS) nervous system complications in hospitalized COVID-19 patients. Methods We conducted a prospective, consecutive, observational study of adult patients from a tertiary referral center with confirmed COVID-19. All patients were screened daily for neurological and neuropsychiatric symptoms during admission and discharge. Three-month follow-up data were collected using electronic health records. We classified complications as caused by SARS-CoV-2 neurotropism, immune-mediated or critical illness-related. Results From April to September 2020, we enrolled 61 consecutively admitted COVID-19 patients, 35 (57%) of whom required intensive care (ICU) management for respiratory failure. Forty-one CNS/PNS complications were identified in 28 of 61 (45.9%) patients and were more frequent in ICU compared to non-ICU patients. The most common CNS complication was encephalopathy (n = 19, 31.1%), which was severe in 13 patients (GCS ≤ 12), including 8 with akinetic mutism. Length of ICU admission was independently associated with encephalopathy (OR = 1.22). Other CNS complications included ischemic stroke, a biopsy-proven acute necrotizing encephalitis, and transverse myelitis. The most common PNS complication was critical illness polyneuromyopathy (13.1%), with prolonged ICU stay as independent predictor (OR = 1.14). Treatment-related PNS complications included meralgia paresthetica. Of 41 complications in total, 3 were para/post-infectious, 34 were secondary to critical illness or other causes, and 4 remained unresolved. Cerebrospinal fluid was negative for SARS-CoV-2 RNA in all 5 patients investigated. Conclusion CNS and PNS complications were common in hospitalized COVID-19 patients, particularly in the ICU, and often attributable to critical illness. When COVID-19 was the primary cause for neurological disease, no signs of viral neurotropism were detected, but laboratory changes suggested autoimmune-mediated mechanisms.

IMPORTANCE Prolonged neuropsychiatric and cognitive symptoms are increasingly reported in patients after COVID-19, but studies with well-matched controls are lacking.OBJECTIVE To investigate cognitive impairment, neuropsychiatric diagnoses, and symptoms in survivors of COVID-19 compared with patients hospitalized for non-COVID-19 illness. DESIGN, SETTING, AND PARTICIPANTSThis prospective case-control study from a tertiary referral hospital in Copenhagen, Denmark, conducted between July 2020 and July 2021, followed up hospitalized COVID-19 survivors and control patients hospitalized for non-COVID-19 illness, matched for age, sex, and intensive care unit (ICU) status 6 months after symptom onset. EXPOSURES Hospitalization for COVID-19.MAIN OUTCOMES AND MEASURES Participants were investigated with the Mini-International Neuropsychiatric Interview, the Montreal Cognitive Assessment (MoCA), neurologic examination, and a semi-structured interview for subjective symptoms. Primary outcomes were total MoCA score and new onset of International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) psychiatric diagnoses. Secondary outcomes included specific psychiatric diagnoses, subjective symptoms, and neurologic examination results. All outcomes were adjusted for age, sex, ICU admission, admission length, and days of follow-up. Secondary outcomes were adjusted for multiple testing. RESULTS A total of 85 COVID-19 survivors (36 [42%] women; mean [SD] age 56.8 [14] years) after hospitalization and 61 matched control patients with non-COVID-19 illness (27 [44%] women, mean age 59.4 years [SD, 13]) were enrolled. Cognitive status measured by total geometric mean MoCA scores at 6-month follow-up was lower (P = .01) among 95% CI, 95% CI,). The cognitive status improved substantially (P = .004), from 19.2 (95% CI, 15.2-23.2) at discharge to 26.1 (95% CI, 23.1-29.1) for 15 patients with COVID-19 with MoCA evaluations from hospital discharge. A total of 16 of 85 patients with COVID-19 (19%) and 12 of 61 control patients (20%) had a new-onset psychiatric diagnosis at 6-month follow-up, which was not significantly different (odds ratio, 0.93; 95% CI, 0.39-2.27; P = .87). In fully adjusted models, secondary outcomes were not significantly different, except anosmia, which was more common after COVID-19 (odds ratio, 4.56; 95% CI, 1.52-17.42; P = .006); but no longer when adjusting for multiple testing. CONCLUSIONS AND RELEVANCEIn this prospective case-control study, cognitive status at 6 months was worse among survivors of COVID-19, but the overall burden of neuropsychiatric and neurologic signs and symptoms among survivors of COVID-19 requiring hospitalization was comparable with the burden observed among matched survivors hospitalized for non-COVID-19 causes.

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.