Acute hepatic porphyrias (AHP) can cause severe neurological symptoms involving the central, autonomic, and peripheral nervous system. Due to their relative rarity and their chameleon‐like ...presentation, delayed diagnosis and misdiagnosis are common. AHPs are genetically inherited disorders that result from heme biosynthesis enzyme deficiencies and comprise four forms: acute intermittent porphyria (AIP), variegate porphyria (VP), hereditary coproporphyria (HCP), and ALA‐dehydratase porphyria (ALADP). Depending on the clinical presentation, the main differential diagnoses are Guillain‐Barré syndrome and autoimmune encephalitis. Red flags that could raise the suspicion of acute porphyria are neurological symptoms starting after severe (abdominal) pain, in association with reddish urine, hyponatremia or photodermatitis, and the presence of encephalopathy and/or axonal neuropathy. We highlight the diagnostic difficulties by presenting three cases from our neurological intensive care unit and give a comprehensive overview about the diagnostic findings in imaging, electrophysiology, and neuropathology.
Acute hepatic porphyrias (AHP) can cause severe neurological symptoms involving the central, autonomic and peripheral nervous system. Due to their relative rarity and their chameleon‐like presentation awareness among neurologists is low and delayed diagnosis and misdiagnosis are common. Red flags that should raise the suspicion of acute porphyria are neurological symptoms starting after severe (abdominal) pain, in association with reddish urine, hyponatremia or photodermatitis and the presence of encephalopathy and/or axonal neuropathy.
Myasthenia gravis (MG) is a rare autoimmune disease characterized by fatigable weakness of the voluntary muscles and can exacerbate to life-threatening myasthenic crisis (MC), requiring intensive ...care treatment. Routine laboratory parameters are a cost-effective and widely available method for estimating the clinical outcomes of several diseases, but so far, such parameters have not been established to detect disease progression in MG.
We conducted a retrospective analysis of selected laboratory parameters related to inflammation and hemogram for MG patients with MC compared to MG patients without MC. To identify potential risk factors for MC, we applied time-varying Cox regression for time to MC and, as a sensitivity analysis, generalized estimating equations logistic regression for the occurrence of MC at the next patient visit.
15 of the 58 examined MG patients suffered at least one MC. There was no notable difference in the occurrence of MC by antibody status or sex. Both regression models showed that higher counts of basophils (per 0.01 unit increase: HR = 1.32, 95% CI = 1.02-1.70), neutrophils (per 1 unit increase: HR = 1.40, 95% CI = 1.14-1.72), potentially leukocytes (per 1 unit increase: HR = 1.15, 95% CI = 0.99-1.34), and platelets (per 100 units increase: HR = 1.54, 95% CI = 0.99-2.38) may indicate increased risk for a myasthenic crisis.
This pilot study provides proof of the concept that increased counts of basophils, neutrophils, leukocytes, and platelets may be associated with a higher risk of developing MC in patients with MG.
(1) To assess the accuracy of a standard operating procedure (SOP) regarding the utilization of atrial fibrillation (AF) alarms in everyday clinical practice, and (2) to evaluate the performance of ...automated continuous surveillance for atrial fibrillation (AF) in hospitalized acute stroke patients.
Retrospective cohort study.
Two stroke units from two tertiary care hospitals in Berlin, Germany.
We identified 635 patients with ischemic stroke diagnosis for the time period between 01. January and 30. September 2021 of which 176 patients had recorded AF alarms during monitoring. Of those, 115 patients were randomly selected for evaluation. After excluding 6 patients with hemorrhagic stroke in their records, 109 patients (mean age: 79.1 years, median NIHSS at admission: 6, 57% female) remained for analysis.
Using a clinical data warehouse for comprehensive data storage we retrospectively downloaded and visualized ECG data segments of 65 s duration around the automated AF alarms. We restricted the maximum number of ECG segments to ten per patient. Each ECG segment plot was uploaded into a REDCap database and categorized as either AF, non-AF or artifact by manual review. Atrial flutter was subsumed as AF. These classifications were then matched with 1) medical history and known diseases before stroke, 2) discharge diagnosis, and 3) recommended treatment plan in the medical history using electronic health records.
The primary outcome was the proportion of previously unknown AF diagnoses correctly identified by the monitoring system but missed by the clinical team during hospitalization. Secondary outcomes included the proportion of patients in whom a diagnosis of AF would likely have led to anticoagulant therapy. We also evaluated the accuracy of the automated detection system in terms of its positive predictive value (PPV).
We evaluated a total of 717 ECG alarm segments from 109 patients. In 4 patients (3.7, 95% confidence interval CI 1.18–9.68%) physicians had missed AF despite at least one true positive alarm. All four patients did not receive long-term secondary prevention in form of anticoagulant therapy. 427 out of 717 alarms were rated true positives, resulting in a positive predictive value of 0.6 (CI 0.56–0.63) in this cohort.
By connecting a data warehouse, electronic health records and a REDCap survey tool, we introduce a path to assess the monitoring quality of AF in acute stroke patients. We find that implemented standards of procedure to detect AF during stroke unit care are effective but leave room for improvement. Such data warehouse-based concepts may help to adjust internal processes or identify targets of further investigations.
The newly identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic respiratory disease. Moreover, thromboembolic events throughout the body, including in ...the CNS, have been described. Given the neurological symptoms observed in a large majority of individuals with COVID-19, SARS-CoV-2 penetrance of the CNS is likely. By various means, we demonstrate the presence of SARS-CoV-2 RNA and protein in anatomically distinct regions of the nasopharynx and brain. Furthermore, we describe the morphological changes associated with infection such as thromboembolic ischemic infarction of the CNS and present evidence of SARS-CoV-2 neurotropism. SARS-CoV-2 can enter the nervous system by crossing the neural-mucosal interface in olfactory mucosa, exploiting the close vicinity of olfactory mucosal, endothelial and nervous tissue, including delicate olfactory and sensory nerve endings. Subsequently, SARS-CoV-2 appears to follow neuroanatomical structures, penetrating defined neuroanatomical areas including the primary respiratory and cardiovascular control center in the medulla oblongata.
According to the discharge report, the patient presented comatose with hypersalivation and increased diaphoresis and was diagnosed to have respiratory failure, myoclonic status, disturbed ...carbohydrate metabolism, electrolyte disorders, and metabolic encephalopathy. ...obidoxime was stopped after 1 day.5 Atropine was continued for 10 days and titrated to suppress cholinergic symptoms (figure 1). CT on admission and plain chest radiography on days 3, 5, 9, 10, and 13 showed no clear signs of pulmonary infiltration. Because of purulent bronchoalveolar fluid in conjunction with increased levels of C-reactive protein, the patient received colistin inhalations for 9 days, subsequently tapered to prophylactic doses. The range of findings caused by overstimulation of muscarinic and nicotinic receptors seen in our patient was in line with published literature: miosis, conjunctival injection, hypersalivation, diaphoresis, bradycardia, and elevation of plasma lipase and amylase, which are attributed to pancreatic and salivary gland stimulation, hyperactive deep tendon reflexes, pyramidal signs, and prolonged muscular hyperactivity.11 Moreover, we observed typical pathological changes in electrophysiology and single-fibre electromyography studies.12,13 After normalisation of neuromuscular transmission, the patient started to breathe spontaneously on day 12.
Background and purpose
To investigate severe autoimmune encephalitis (AE) in the intensive care unit (ICU) with regard to standard treatment in responsive patients and additional escalation therapies ...for treatment‐refractory cases.
Methods
This retrospective, single‐center study analyzed medical records of ICU‐dependent AE patients for clinical characteristics, treatments, prognostic factors, and neurological outcome as quantified by modified Rankin Scale (mRS) and Clinical Assessment Scale for Autoimmune Encephalitis (CASE).
Results
From 40 enrolled patients (median age = 52 years; range = 16–89 years) with AE mediated by neuronal surface antibodies (nsAb; 90%) and AE with onconeuronal antibodies (10%), 98% received first‐line therapy. Of those, 62% obtained additional second‐line therapy, and 33% received escalation therapy with bortezomib and/or daratumumab. Good neurological outcome, defined as mRS = 0–2, was observed in 47% of AE with nsAb (CASE = 5), 77% of anti‐N‐methyl D‐aspartate receptor encephalitis patients (CASE = 1), whereas AE patients with onconeuronal antibodies had the poorest outcome (mRS = 6, 100%). Treatment‐refractory AE patients with nsAb requiring escalation therapy achieved similarly good recovery (mRS = 0–2, 39%, CASE = 3) as patients improving without (mRS = 0–2, 54%, CASE = 4), although they presented a higher disease severity at disease maximum (mRS = 5 100% versus 68%, CASE = 24 versus 17; p = 0.0036), had longer ICU stays (97 versus 23 days; p = 0.0002), and a higher survival propability during follow‐up (p = 0.0203). Prognostic factors for good recovery were younger age (p = 0.025) and lack of preexisting comorbidities (p = 0.011).
Conclusions
Our findings suggest that treatment‐refractory AE patients with nsAb in the ICU can reach similarly good outcomes after plasma cell–depleting escalation therapy as patients already responding to standard first‐ and/or second‐line therapies.
Our retrospective study analyzed 40 patients with intensive care unit (ICU)‐dependent autoimmune encephalitis (AE) for clinical characteristics, diagnostics, prognostic factors, and clinical outcomes regarding standard treatment in responsive patients versus additional escalation therapies for treatment‐refractory cases. Our findings suggest that treatment‐refractory AE patients with neuronal surface antibodies (nsAb) in the ICU can reach similarly good outcomes after plasma cell–depleting escalation therapy as patients already responding to standard first‐ and/or second‐line therapies.
Autoimmune diseases encompass a broad spectrum of disorders characterized by disturbed immunoregulation leading to the development of specific autoantibodies, resulting in inflammation and multiple ...organ involvement. A distinction should be made between connective tissue diseases (mainly systemic lupus erythematosus, systemic scleroderma, inflammatory muscle diseases, and rheumatoid arthritis) and vasculitides (mainly small-vessel vasculitis such as antineutrophil cytoplasmic antibody-associated vasculitis and immune-complex mediated vasculitis). Admission of patients with autoimmune diseases to the intensive care unit (ICU) is often triggered by disease flare-ups, infections, and organ failure and is associated with high mortality rates. Management of these patients is complex, including prompt disease identification, immunosuppressive treatment initiation, and life-sustaining therapies, and requires multi-disciplinary involvement. Data about autoimmune diseases in the ICU are limited and there is a need for multicenter, international collaboration to improve patients’ diagnosis, management, and outcomes. The objective of this narrative review is to summarize the epidemiology, clinical features, and selected management of severe systemic autoimmune diseases.
Cell therapy with mesenchymal stromal cells (MSCs) was found to protect neurons from damage after experimental stroke and is currently under investigation in clinical stroke trials. In order to ...elucidate the mechanisms of MSC-induced neuroprotection, we used the in vitro oxygen–glucose deprivation (OGD) model of cerebral ischemia. Co-culture of primary cortical neurons with MSCs in a transwell co-culture system for 48 h prior to OGD-reduced neuronal cell death by 30–35%. Similar protection from apoptosis was observed with MSC-conditioned media when added 48 h or 30 min prior to OGD, or even after OGD. Western blot analysis revealed increased phosphorylation of STAT3 and Akt in neuronal cultures after treatment with MSC-conditioned media. Inhibition of the PI3K/Akt pathway completely abolished the neuroprotective potential of MSC-conditioned media, suggesting that MSCs can improve neuronal survival by an Akt-dependent anti-apoptotic signaling cascade. Using mass spectrometry, we identified plasminogen activator inhibitor-1 as an active compound in MSC-conditioned media. Thus, paracrine factors secreted by MSCs protect neurons from apoptotic cell death in the OGD model of cerebral ischemia.
In neurocritical care, data from multiple biosensors are continuously measured, but only sporadically acknowledged by the attending physicians. In contrast, machine learning (ML) tools can analyze ...large amounts of data continuously, taking advantage of underlying information. However, the performance of such ML-based solutions is limited by different factors, for example, by patient motion, manipulation, or, as in the case of external ventricular drains (EVDs), the drainage of CSF to control intracranial pressure (ICP). The authors aimed to develop an ML-based algorithm that automatically classifies normal signals, artifacts, and drainages in high-resolution ICP monitoring data from EVDs, making the data suitable for real-time artifact removal and for future ML applications.
In their 2-center retrospective cohort study, the authors used labeled ICP data from 40 patients in the first neurocritical care unit (University Hospital Zurich) for model development. The authors created 94 descriptive features that were used to train the model. They compared histogram-based gradient boosting with extremely randomized trees after building pipelines with principal component analysis, hyperparameter optimization via grid search, and sequential feature selection. Performance was measured with nested 5-fold cross-validation and multiclass area under the receiver operating characteristic curve (AUROC). Data from 20 patients in a second, independent neurocritical care unit (Charité - Universitätsmedizin Berlin) were used for external validation with bootstrapping technique and AUROC.
In cross-validation, the best-performing model achieved a mean AUROC of 0.945 (95% CI 0.92-0.969) on the development dataset. On the external validation dataset, the model performed with a mean AUROC of 0.928 (95% CI 0.908-0.946) in 100 bootstrapping validation cycles to classify normal signals, artifacts, and drainages.
Here, the authors developed a well-performing supervised model with external validation that can detect normal signals, artifacts, and drainages in ICP signals from patients in neurocritical care units. For future analyses, this is a powerful tool to discard artifacts or to detect drainage events in ICP monitoring signals.
Background
Post-stroke heart rate (HR) and heart rate variability (HRV) changes have been proposed as outcome predictors after stroke. We used data lake-enabled continuous electrocardiograms to ...assess post-stroke HR and HRV, and to determine the utility of HR and HRV to improve machine learning-based predictions of stroke outcome.
Methods
In this observational cohort study, we included stroke patients admitted to two stroke units in Berlin, Germany, between October 2020 and December 2021 with final diagnosis of acute ischemic stroke or acute intracranial hemorrhage and collected continuous ECG data through data warehousing. We created circadian profiles of several continuously recorded ECG parameters including HR and HRV parameters. The pre-defined primary outcome was short-term unfavorable functional outcome after stroke indicated through modified Rankin Scale (mRS) score of > 2.
Results
We included 625 stroke patients, 287 stroke patients remained after matching for age and National Institute of Health Stroke Scale (NIHSS; mean age 74.5 years, 45.6% female, 88.9% ischemic, median NIHSS 5). Both higher HR and nocturnal non-dipping of HR were associated with unfavorable functional outcome (
p
< 0.01). The examined HRV parameters were not associated with the outcome of interest. Nocturnal non-dipping of HR ranked highly in feature importance of various machine learning models.
Conclusions
Our data suggest that a lack of circadian HR modulation, specifically nocturnal non-dipping, is associated with short-term unfavorable functional outcome after stroke, and that including HR into machine learning-based prediction models may lead to improved stroke outcome prediction.
PDF
