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It is unclear whether frequently used cutoff values for outcome measures defining minimal clinically important differences (MCIDs) can accurately identify meaningful deterioration in chronic inflammatory demyelinating polyneuropathy (CIDP). We used data from the immunoglobulin overtreatment in CIDP (IOC) trial, in which 60 clinically stable patients with CIDP were randomized to intravenous immunoglobulin (IVIg) withdrawal or continuation. We calculated change scores of the Inflammatory Rasch‐Built Overall Disability Scale (I‐RODS), grip strength, and Medical Research Council‐sum score (MRC‐SS) and classified visits based on a treatment anchor (ie, decision to restart/increase treatment after reaching a predefined early endpoint of deterioration). The variability of scores in patients without deterioration was calculated using the limits of agreement. We defined optimized MCIDs for deterioration and specific combinations of MCIDs from different outcome measures, and subsequently calculated the accuracies of the (combined) MCIDs. Substantial variability was found in scores of the I‐RODS, grip strength and MRC‐SS in patients without deterioration over time, and most MCIDs were within the limits of the variability observed in patients without deterioration. Some MCID cut‐offs were insensitive but highly specific for detecting deterioration, for example, the MCID‐SE of −1.96 of the I‐RODS and −2 point on the MRC‐SS. Others were sensitive, but less specific, for example, −4 centiles of the I‐RODS. Some combined MCIDs resulted in high specificities and moderate sensitivities. Our results suggest that clinically important deterioration cannot be distinguished from variability over time with currently used MCIDs on the individual level. Combinations of MCIDs might improve the accuracy of determining deterioration, but this needs validation. [ABSTRACT FROM AUTHOR]

Background: Natalizumab treatment provides a model for non-inflammation-induced disease progression in multiple sclerosis (MS). Objective: To study serum contactin-1 (sCNTN1) as a novel biomarker for disease progression in natalizumab-treated relapsing-remitting MS (RRMS) patients. Methods: Eighty-nine natalizumab-treated RRMS patients with minimum follow-up of 3 years were included. sCNTN1 was analyzed at baseline (before natalizumab initiation), 3, 12, 24 months (M) and last follow-up (median 5.2 years) and compared to 222 healthy controls (HC) and 15 primary progressive MS patients (PPMS). Results were compared between patients with progressive, stable, or improved disability according to EDSS-plus criteria. Results: Median sCNTN1 levels (ng/mL,) in RRMS (baseline: 10.7, 3M: 9.7, 12M: 10.4, 24M: 10.8; last follow-up: 9.7) were significantly lower compared to HC (12.5; p ⩽ 0.001). It was observed that 48% of patients showed progression during follow-up, 11% improved, and 40% remained stable. sCNTN1 levels were significantly lower in progressors both at baseline and at 12M compared to non-progressors. A 1 ng/mL decrease in baseline sCNTN1 was consistent with an odds ratio of 1.23 (95% confidence interval 1.04–1.45) (p = 0.017) for progression during follow-up. Conclusion: Lower baseline sCNTN1 concentrations were associated with long-term disability progression during natalizumab treatment, making it a possible blood-based prognostic biomarker for RRMS. [ABSTRACT FROM AUTHOR]

Purpose: There is limited knowledge on how the source of infection impacts the host response to sepsis. We aimed to compare the host response in sepsis patients with a single, known source at admission (< 24 h) to the intensive care unit. Methods: From the molecular diagnosis and risk stratification of sepsis (MARS) prospective cohort, we measured 16 plasma host response biomarkers reflective of key host response pathways in 621 sepsis patients. In a subgroup (n = 335), blood leukocyte transcriptomes were compared between the sources. Differences in clinical patient profiles and survival were compared in the whole sepsis cohort (n = 2019). Results: The plasma biomarker cohort was categorized into sepsis originating from the respiratory tract (n = 334, 53.8%), abdomen (n = 159, 25.6%), urinary tract (n = 44, 7.1%), cardiovascular (n = 41, 6.6%), central nervous system (CNS) (n = 18, 2.9%), or skin (n = 25, 4%). This analysis revealed stronger inflammatory and cytokine responses, loss of vascular integrity and coagulation activation in abdominal sepsis relative to respiratory. Endothelial cell activation was prominent in urinary, cardiovascular and skin infections, while CNS infection was associated with the least host response aberrations. The leukocyte transcriptional response showed the largest overlap between abdominal and pulmonary infections (76% in common); notable differences between the sources were detected regarding hemostasis, cytokine signaling, innate and adaptive immune, and metabolic transcriptional pathways. After adjustment for confounders, the source of infection remained an independent contributor to 30-day mortality (unadjusted p = 0.001, adjusted p = 0.028). Conclusion: Sepsis heterogeneity is partly explained by source-specific host response dysregulations and should be considered when selecting patients for trials testing immune modulatory drugs. [ABSTRACT FROM AUTHOR]

The article discusses the pathogenesis of Guillain-Barré syndrome (GBS) and the role of peripherin as a biomarker of axonal damage. The authors acknowledge the historical and clinical literature that has contributed to our understanding of GBS, but emphasize the need for modern data to further enhance our knowledge. They discuss the neurophysiological classification of GBS and the concept of nodo-paranodopathies, where immunological attack at or around the nodes of Ranvier can result in various forms of damage. The authors also mention ongoing research on peripherin and its potential correlations with different aspects of GBS. Overall, while progress has been made in understanding the pathogenesis of GBS, there is still much to learn. [Extracted from the article]

Background: Mechanical ventilation can induce or even worsen lung injury, at least in part via overdistension caused by too large volumes or too high pressures. The complement system has been suggested to play a causative role in ventilator-induced lung injury. Aims and methods: This was a single-center prospective study investigating associations between pulmonary levels of complement activation products and two ventilator settings, tidal volume (VT) and driving pressure (ΔP), in critically ill patients under invasive ventilation. A miniature bronchoalveolar lavage (BAL) was performed for determination of pulmonary levels of C5a, C3b/c, and C4b/c. The primary endpoint was the correlation between BAL fluid (BALF) levels of C5a and VT and ΔP. Levels of complement activation products were also compared between patients with and without ARDS or with and without pneumonia. Results: Seventy-two patients were included. Median time from start of invasive ventilation till BAL was 27 [19 to 34] hours. Median VT and ΔP before BAL were 6.7 [IQR 6.1 to 7.6] ml/kg predicted bodyweight (PBW) and 15 [IQR 11 to 18] cm H2O, respectively. BALF levels of C5a, C3b/c and C4b/c were neither different between patients with or without ARDS, nor between patients with or without pneumonia. BALF levels of C5a, and also C3b/c and C4b/c, did not correlate with VT and ΔP. Median BALF levels of C5a, C3b/c, and C4b/c, and the effects of VT and ΔP on those levels, were not different between patients with or without ARDS, and in patients with or without pneumonia. Conclusion: In this cohort of critically ill patients under invasive ventilation, pulmonary levels of complement activation products were independent of the size of VT and the level of ΔP. The associations were not different for patients with ARDS or with pneumonia. Pulmonary complement activation does not seem to play a major role in VILI, and not even in lung injury per se, in critically ill patients under invasive ventilation. [ABSTRACT FROM AUTHOR]

Objectives: An early diagnosis of intensive care unit–acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Methods: Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Results: Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). Conclusions: The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Deep learning methods have shown potential in automating the detection of interictal epileptiform discharges (IEDs) in electroencephalography (EEG). We compared IED detection using our previously trained deep neural network with a group of experts to assess its potential applicability.First, we performed clinical validation on an internal data set. Seven experts reviewed all EEG studies. Performance agreement between experts and the network was compared at both the EEG and IED levels. All EEG recordings were also processed with Persyst. Subsequently, we performed external validation, with data from four centers, using a hybrid approach, where detections by the deep neural network were reviewed by an expert. In case of disagreement with the original report, the EEG recording was annotated independently by five experts.For internal validation we included 22 EEG studies with IEDs and 28 EEG studies from controls. At the EEG level, our network showed performance similar to that of the experts. For individual IED detection, the sensitivities between experts ranged from 20.7%–86.4%, whereas the sensitivity of our network was 82.5% (confidence interval [CI]: 77.7%–87.4%) at 99% specificity and a false detection rate (FDR) of <.2/min, outperforming Persyst, with 64.6% sensitivity (CI: 61.4%–67.9%) at 98% specificity. External validation in 174 EEG studies demonstrated that all 85 EEG recordings classified as normal in the original report were classified correctly, with an FDR of .10/min. Of the 89 EEG studies with IEDs according to the report, 56 were correctly classified (Cohen's κ = .62). Visual analysis of the remaining 33 EEG recordings showed high interobserver variability among the five experts (Fleiss’ κ = .13).Our deep neural network detects IEDs on par with clinical experts. The external validation in a hybrid approach showed substantial agreement with the original report. Disagreement was due mainly to high interobserver variability. Our deep neural network may support visual EEG analysis and assist in diagnostics, particularly when human resources are limited. [ABSTRACT FROM AUTHOR]

Background: Intensive care unit–acquired weakness (ICU-AW) is a common complication of critical illness and is associated with increased mortality, longer mechanical ventilation and longer hospital stay. Little is known about the causes of mortality in patients with ICU-AW. In this study, we aimed to give an overview of the causes of death in a population diagnosed with ICU-AW during hospital admission. Methods: Data from a prospective cohort study in the mixed medical–surgical ICU of the Academic Medical Center in Amsterdam were used. Patients were included when mechanically ventilated for more than 48 hours. Intensive care unit–acquired weakness was defined as a mean medical research council score <4. Baseline data and data on the time of death were collected. Results: Fifty-three patients were included. Irreversible shock with multiple organ failure (MOF) was the most common cause of death (28/53 of patients; 26 patients with septic shock and 2 patients with hypovolemic shock). Most common site of sepsis was abdominal (38.5%) and pulmonary (19.2%). On admission to the ICU, 53% had a do-not-resuscitate code. In 74% of the patients, further treatment limitations were implemented during their ICU stay. Conclusion: In this cohort of patients with ICU-AW, most patients died of irreversible shock with MOF, caused by sepsis. [ABSTRACT FROM AUTHOR]

B-cell activating factor (BAFF) is a crucial cytokine for differentiation and survival of B-cells and correlates to disease activity in some auto-immune diseases. To evaluate BAFF as a biomarker for disease activity in chronic inflammatory demyelinating polyneuropathy (CIDP), serum BAFF levels were measured at varying disease stages: patients starting treatment, patients starting treatment withdrawal, patients in remission and healthy controls. Serum BAFF levels were elevated in patients compared to healthy controls, but did not differ between patients starting treatment and patients in remission. Serum BAFF levels did not change with or predict treatment response or relapse. Serum BAFF is not a responsive biomarker reflecting disease activity in CIDP. [ABSTRACT FROM AUTHOR]

Objectively as possible using disability and impairment scales. Applying these outcome measures consistently in clinical practice aids in recognizing the effectiveness (or lack thereof) of a treatment and facilitates timely consideration of alternative diagnoses or treatments. This review provides an overview of the current perspectives on the diagnostic process and first-line treatments for managing the disease. [ABSTRACT FROM AUTHOR]