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Determination of prognosis in patients with status epilepticus (SE)—a life-threatening state of ongoing or repetitive seizures—is difficult, and current outcome prediction scales do not take into account novel outcome markers, such as EEG and imaging findings. Here, Sutter et al . review the available data on major prognostic determinants of outcome in SE, and propose a novel paradigm for assessment of these predictive factors over the course of the seizure. In adult patients with status epilepticus (SE)—a life-threatening state of ongoing or repetitive seizures—the current evidence regarding outcome prediction is based on clinical, biochemical and EEG determinants. These predictors of outcome involve clinical features such as age, history of prior seizures or epilepsy, SE aetiology, level of consciousness, and seizure type at SE onset. The clinical risk–benefit calculation between the danger of undertreated persistent seizure activity and, conversely, the potential damage from unwarranted aggressive treatments remains a constant challenge. Improved knowledge of outcome determinants, as well as increased availability of reliable outcome prediction models early in the course of SE, is paramount for optimization of treatment of patients who develop this disorder. In this Review, we discuss the major prognostic determinants of outcome in SE. Through consideration of studies that provide measures of association between predictors of SE outcome and death, we propose a detailed—but as yet unvalidated—paradigm for assessment of these predictors during the course of SE. Such an algorithm could guide the organization of results from existing trials and provide direction with regard to the parameters that should be monitored in future studies of SE. Key Points The most reliable clinical determinants for early prediction of outcome in status epilepticus (SE) are age, prior seizures or epilepsy, SE aetiology, level of consciousness, and seizure type at onset These variables have been integrated and validated in a clinical scoring system (the Status Epilepticus Outcome Score) for rapid outcome prognostication at SE onset The current outcome score for SE does not encompass the totality of aetiological, biochemical and EEG characteristics—factors that interact in a complex manner and show promise for outcome prognostication On the basis of the available data, we propose a detailed—but as yet unvalidated—paradigm for the assessment of outcome predictors during the course of SE

Due to the dramatic measures accompanying isolation and the general uncertainty and fear associated with COVID-19, patients and relatives may be at high risk for adverse psychological outcomes. Until now there has been limited research focusing on the prevalence of psychological distress and associated factors in COVID-19 patients and their relatives. The objective of our study was to assess psychological distress in COVID-19 patients and their relatives 30 days after hospital discharge. In this prospective observational cohort study at two Swiss tertiary-care hospitals we included consecutive adult patients hospitalized between March and June 2020 for a proven COVID-19 and their relatives. Psychological distress was defined as symptoms of anxiety and/or depression measured with the Hospital Anxiety and Depression Scale (HADS), i.e., a score of ≥8 on the depression and/or anxiety subscale. We further evaluated symptoms of post-traumatic stress disorder (PTSD), defined as a score of ≥1.5 on the Impact of Event Scale-Revised (IES-R). Among 126 included patients, 24 (19.1%) had psychological distress and 10 (8.7%) had symptoms of PTSD 30 days after hospital discharge. In multivariate logistic regression analyses three factors were independently associated with psychological distress in patients: resilience (OR 0.82; 95%CI 0.71 to 0.94; p = 0.005), high levels of perceived stress (OR 1.21; 95%CI 1.06 to 1.38; p = 0.006) and low frequency of contact with relatives (OR 7.67; 95%CI 1.42 to 41.58; p = 0.018). The model showed good discrimination, with an area under the receiver-operating characteristic curve (AUC) of 0.92. Among 153 relatives, 35 (22.9%) showed symptoms of psychological distress, and 3 (2%) of PTSD. For relatives, resilience was negatively associated (OR 0.85; 95%CI 0.75 to 0.96; p = 0.007), whereas perceived overall burden caused by COVID-19 was positively associated with psychological distress (OR 1.72; 95%CI 1.31 to 2.25; p<0.001). The overall model also had good discrimination, with an AUC of 0.87. A relevant number of COVID-19 patients as well as their relatives exhibited psychological distress 30 days after hospital discharge. These results might aid in development of strategies to prevent psychological distress in COVID-19 patients and their relatives.

Background A recent study found serum neurofilament light chain (NfL) levels to be strongly associated with poor neurological outcome in patients after cardiac arrest. Our aim was to confirm these findings in an independent validation study and to investigate whether NfL improves the prognostic value of two cardiac arrest-specific risk scores. Methods This prospective, single-center study included 164 consecutive adult after out-of-hospital cardiac arrest (OHCA) patients upon intensive care unit admission. We calculated two clinical risk scores (OHCA, CAHP) and measured NfL on admission within the first 24 h using the single molecule array NF-light ® assay. The primary endpoint was neurological outcome at hospital discharge assessed with the cerebral performance category (CPC) score. Results Poor neurological outcome (CPC > 3) was found in 60% (98/164) of patients, with 55% (91/164) dying within 30 days of hospitalization. Compared to patients with favorable outcome, NfL was 14-times higher in patients with poor neurological outcome (685 ± 1787 vs. 49 ± 111 pg/mL), with an adjusted odds ratio of 3.4 (95% CI 2.1 to 5.6, p  < 0.001) and an area under the curve (AUC) of 0.82. Adding NfL to the clinical risk scores significantly improved discrimination of both the OHCA score (from AUC 0.82 to 0.89, p  < 0.001) and CAHP score (from AUC 0.89 to 0.92, p  < 0.05). Adding NfL to both scores also resulted in significant improvement in reclassification statistics with a Net Reclassification Index (NRI) of 0.58 ( p  < 0.001) for OHCA and 0.83 ( p  < 0.001) for CAHP. Conclusions Admission NfL was a strong outcome predictor and significantly improved two clinical risk scores regarding prognostication of neurological outcome in patients after cardiac arrest. When confirmed in future outcome studies, admission NfL should be considered as a standard laboratory measures in the evaluation of OHCA patients.

This work aims to assess the performance of two post-arrest (out-of-hospital cardiac arrest, OHCA, and cardiac arrest hospital prognosis, CAHP) and one pre-arrest (good outcome following attempted resuscitation, GO-FAR) prediction model for the prognostication of neurological outcome after cardiac arrest in a systematic review and meta-analysis. A systematic search was conducted in Embase, Medline, and Web of Science Core Collection from November 2006 to December 2021, and by forward citation tracking of key score publications. The search identified 1′021 records, of which 25 studies with a total of 124′168 patients were included in the review. A random-effects meta-analysis of C-statistics and overall calibration (total observed vs. expected [O:E] ratio) was conducted. Discriminatory performance was good for the OHCA (summary C-statistic: 0.83 [95% CI 0.81–0.85], 16 cohorts) and CAHP score (summary C-statistic: 0.84 [95% CI 0.82–0.87], 14 cohorts) and acceptable for the GO-FAR score (summary C-statistic: 0.78 [95% CI 0.72–0.84], five cohorts). Overall calibration was good for the OHCA (total O:E ratio: 0.78 [95% CI 0.67–0.92], nine cohorts) and the CAHP score (total O:E ratio: 0.78 [95% CI 0.72–0.84], nine cohorts) with an overestimation of poor outcome. Overall calibration of the GO-FAR score was poor with an underestimation of good outcome (total O:E ratio: 1.62 [95% CI 1.28–2.04], five cohorts). Two post-arrest scores showed good prognostic accuracy for predicting neurological outcome after cardiac arrest and may support early discussions about goals-of-care and therapeutic planning on the intensive care unit. A pre-arrest score showed acceptable prognostic accuracy and may support code status discussions. Graphical Abstract

Patients discharged from intensive care are at risk for post-intensive care syndrome (PICS), which consists of physical, psychological, and/or neurological impairments. This study aimed to analyze PICS at 24 months follow-up, to identify potential risk factors for PICS, and to assess health-related quality of life in a long-term cohort of adult cardiac arrest survivors. This prospective cohort study included adult cardiac arrest survivors admitted to the intensive care unit of a Swiss tertiary academic medical center. The primary endpoint was the prevalence of PICS at 24 months follow-up, defined as impairments in physical (measured through the European Quality of Life 5-Dimensions-3-Levels instrument [EQ-5D-3L]), neurological (defined as Cerebral Performance Category Score > 2 or Modified Rankin Score > 3), and psychological (based on the Hospital Anxiety and Depression Scale and the Impact of Event Scale-Revised) domains. Among 107 cardiac arrest survivors that completed the 2-year follow-up, 46 patients (43.0%) had symptoms of PICS, with 41 patients (38.7%) experiencing symptoms in the physical domain, 16 patients (15.4%) in the psychological domain, and 3 patients (2.8%) in the neurological domain. Key predictors for PICS in multivariate analyses were female sex (adjusted odds ratio [aOR] 3.17, 95% CI 1.08 to 9.3), duration of no-flow interval during cardiac arrest (minutes) (aOR 1.17, 95% CI 1.02 to 1.33), post-discharge job-loss (aOR 31.25, 95% CI 3.63 to 268.83), need for ongoing psychological support (aOR 3.64, 95% CI 1.29 to 10.29) or psychopharmacologic treatment (aOR 9.49, 95% CI 1.9 to 47.3), and EQ-visual analogue scale (points) (aOR 0.88, 95% CI 0.84 to 0.93). More than one-third of cardiac arrest survivors experience symptoms of PICS 2 years after resuscitation, with the highest impairment observed in the physical and psychological domains. However, long-term survivors of cardiac arrest report intact health-related quality of life when compared to the general population. Future research should focus on appropriate prevention, screening, and treatment strategies for PICS in cardiac arrest patients.

Intensive care unit patients are at risk for post-intensive care syndrome (PICS), which includes psychological, physical and/or cognitive sequelae after their hospital stay. Our aim was to investigate PICS in adult patients with out-of-hospital cardiac arrest (OHCA). In this prospective observational cohort study, we assessed risks for PICS at 3 and 12-month follow-up within the following domains: a) physical impairment (EuroQol [EQ-5D-3L]), b) cognitive functioning (Cerebral Performance Category [CPC] score >1, modified Rankin Scale [mRS] >2) and c) psychological burden (Hospital Anxiety and Depression Scale [HADS], Impact of Event Scale-Revised [IES-R]). At 3 months, 69/139 patients (50%) met the definition of PICS including 37% in the physical domain, 25% in the cognitive domain and 13% in the psychological domain. Intubation (OR 2.3, 95%CI 1.1 to 5,0 p = 0.03), sedatives (OR 3.4, 95%CI 1 to 11, p = 0.045), mRS at discharge (OR 4.3, 95%CI 1.70 to 11.01, p = 0.002), CPC at discharge (OR 3.3, 95%CI 1.4 to 7.6, p = 0.005) and post-discharge work loss (OR 13.4, 95%CI 1.7 to 107.5, p = 0.014) were significantly associated with PICS. At 12 months, 52/110 (47%) patients had PICS, which was associated with prolonged duration of rehabilitation, higher APACHE scores, and higher mRS and CPC scores at hospital discharge. Nearly half of long-term OHCA survivors show PICS after 3 and 12 months. These high numbers call for more emphasis on appropriate screening and treatment in this patient population. Future studies should evaluate whether early identification of these patients enables preventive strategies and treatment options.

Background Cerebrospinal fluid (CSF) analyses are recommended in patients with meningitis and/or encephalitis, but evidence regarding its diagnostic yield is low. We aimed to determine predictors of infectious pathogens in the CSF of adult patients presenting with meningitis, and/or encephalitis. Methods Consecutive patients with meningitis and/or encephalitis form 2011–17 at a Swiss academic medical care center were included in this cross-sectional study. Clinical, neuroradiologic, and laboratory data were collected as exposure variables. Infectious meningitis and/or encephalitis were defined as the composite outcome. For diagnosis of bacterial meningitis the recommendations of the European Society of Clinical Microbiology and Infectious Diseases were followed. Viral meningitis was diagnosed by detection of viral ribonucleic or deoxyribonucleic acid in the CSF. Infectious encephalitis was defined according to the International Encephalitis Consortium (IEC). Meningoencephalitis was diagnosed if the criteria for meningitis and encephalitis were fulfilled. Multinomial logistic regression was performed to identify predictors of the composite outcome. To quantify discriminative power, the c statistic analogous the area under the receiver-operating curve (AUROC) was calculated. An AUROC between 0.7–0.8 was defined as “good”, 08–0.9 as “excellent”, and > 0.9 as “outstanding”. Calibration was defined as “good” if the goodness of fit tests revealed insignificant p -values. Results Among 372 patients, infections were diagnosed in 42.7% presenting as meningitis (51%), encephalitis (32%), and meningoencephalitis (17%). Most frequent infectious pathogens were Streptococcus pneumoniae , Varicella zoster, and Herpes simplex 1&2. While in multivariable analysis lactate concentrations and decreased glucose ratios were the only independent predictors of bacterial infection (AUROCs 0.780, 0.870, and 0.834 respectively), increased CSF mononuclear cells were the only predictors of viral infections (AUROC 0.669). All predictors revealed good calibration. Conclusions Prior to microbiologic workup, CSF data may guide clinicians when infection is suspected while other laboratory and neuroradiologic characteristics seem less useful. While increased CSF lactate and decreased glucose ratio are is the most reliable predictors of bacterial infections in patients with meningitis and/or encephalitis, only mononuclear cell counts predicted viral infections. Trial registration ClinicalTrials.gov identifier NCT03856528 . Registered on February 26th 2019.

This study assessed ChatGPT’s adherence to established management guidelines for status epilepticus (SE) from major neurological societies (NCS, AES, EFNS) and examined how prompt specificity affected the quality of its recommendations. Four prompts varying in detail were each submitted four times, and the generated recommendations were analyzed for consistency with guidelines, along with an assessment of source relevance and accuracy. ChatGPT consistently recommended securing the airway and a breathing check (100% of responses) and always suggested benzodiazepines as first-line treatment. However, it rarely recommended key measures such as side positioning (25%) to prevent potential aspiration and neurological assessments (0–25%). Likewise, alternative administration routes for benzodiazepines were mentioned inconsistently (0–100%). While second- and third-line antiseizure medications were suggested consistently, proper dosage guidance was lacking when unprompted. EEG monitoring was recommended in 50–100%. More specific and detailed prompts increased guideline adherence most markedly regarding vital sign assessment (from 33 to 91%), correct dosages of second-line (from 50 to 100%), third-line drugs (from 0 to 100%), and screening for complications (from 0 to 100%). The findings underscore that Chat-GPT shows promise as a clinical support tool but requires structured prompts for accuracy and should not replace clinical judgment or professional oversight.

Relatives of patients admitted to the intensive care unit (ICU) with out-of-hospital cardiac arrest (OHCA) may suffer from adverse psychological outcomes. We assessed prevalence and risk factors for depression and anxiety in such relatives 90 days after ICU admission. This study included consecutive relatives of OHCA patients admitted to the ICU of University Hospital in Basel, Switzerland. Relatives were interviewed upon admission regarding psychosocial risk factors and satisfaction with communication. Symptoms of depression and anxiety were assessed by Hospital Anxiety and Depression Scale (HADS) 90 days after inclusion. Of 101 included relatives, 17% and 13% of relatives reported symptoms of depression and anxiety, respectively. Witnessing cardiopulmonary resuscitation was associated with depression (gender- and age-adjusted odds ratio [OR] 6.71; 95%CI 1.27 to 35.34; p = .025). Satisfaction with information and decision-making was associated with lower risk of depression (adjusted OR 0.95; 95%CI 0.91 to 0.99; p = .013). Unemployment (adjusted OR 10.42; 95%CI 1.18 to 92.35; p = .035) and lower perceived health status were associated with anxiety (adjusted OR 0.93; 95%CI 0.87 to 0.99; p = .025). Many relatives of OHCA patients report symptoms of depression and anxiety after 90 days. Improving initial care and communication may help to reduce these risks. •Relatives of out-of hospital cardiac arrest patients are at risk for symptoms of depression and anxiety•Risk factors for symptoms of depression are witnessing cardiopulmonary resuscitation and dissatisfaction with communication•Lower perceived health status and relatives' unemployment are associated with a higher risk of anxiety

The red blood cell distribution width (RDW) is a routinely available blood marker that measures the variation of the size/volume of red blood cells. The aim of our study was to investigate the prognostic value of RDW in cardiac arrest patients and to assess whether RDW improves the prognostic value of three cardiac arrest-specific risk scores. Consecutive adult cardiac arrest patients admitted to the ICU of a Swiss university hospital were included. The primary outcome was poor neurological outcome at hospital discharge assessed by Cerebral Performance Category. Of 702 patients admitted to the ICU after cardiac arrest, 400 patients (57.0%) survived, of which 323 (80.8%) had a good neurological outcome. Higher mean RDW values showed an independent association with poor neurological outcomes at hospital discharge (adjusted OR 1.27, 95% CI 1.14 to 1.41; p < 0.001). Adding the maximum RDW value to the OHCA- CAHP- and PROLOGUE cardiac arrest scores improved prognostic performance. Within this cohort of cardiac arrest patients, RDW was an independent outcome predictor and slightly improved three cardiac arrest-specific risk scores. RDW may therefore support clinical decision-making.