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Introduction: Hip fracture surgery is associated with high in-hospital and 30-day mortality rates and serious adverse patient outcomes. Evidence from randomised controlled trials regarding effectiveness of spinal versus general anaesthesia on patient-centred outcomes after hip fracture surgery is sparse.
Methods and analysis: The iHOPE study is a pragmatic national, multicentre, randomised controlled, open-label clinical trial with a two-arm parallel group design. In total, 1032 patients with hip fracture (>65 years) will be randomised in an intended 1:1 allocation ratio to receive spinal anaesthesia (n=516) or general anaesthesia (n=516). Outcome assessment will occur in a blinded manner after hospital discharge and inhospital. The primary endpoint will be assessed by telephone interview and comprises the time to the first occurring event of the binary composite outcome of all-cause mortality or new-onset serious cardiac and pulmonary complications within 30 postoperative days. In-hospital secondary endpoints, assessed via in-person interviews and medical record review, include mortality, perioperative adverse events, delirium, satisfaction, walking independently, length of hospital stay and discharge destination. Telephone interviews will be performed for long-term endpoints (all-cause mortality, independence in walking, chronic pain, ability to return home cognitive function and overall health and disability) at postoperative day 30±3, 180±45 and 365±60.
Ethics and dissemination: iHOPE has been approved by the leading Ethics Committee of the Medical Faculty of the RWTH Aachen University on 14 March 2018 (EK 022/18). Approval from all other involved local Ethical Committees was subsequently requested and obtained. Study started in April 2018 with a total recruitment period of 24 months. iHOPE will be disseminated via presentations at national and international scientific meetings or conferences and publication in peer-reviewed international scientific journals.
Trial registration number: DRKS00013644; Pre-results
Poster presentation: The analysis of neuronal processes distributed across multiple cortical areas aims at the identification of interactions between signals recorded at different sites. Such interactions can be described by measuring the stability of phase angles in the case of oscillatory signals or other forms of signal dependencies for less regular signals. Before, however, any form of interaction can be analyzed at a given time and frequency, it is necessary to assess whether all potentially contributing signals are present. We have developed a new statistical procedure for the detection of coincident power in multiple simultaneously recorded analog signals, allowing the classification of events as 'non-accidental co-activation'. This method can effectively operate on single trials, each lasting only for a few seconds. Signals need to be transformed into time-frequency space, e.g. by applying a short-time Fourier transformation using a Gaussian window. The discrete wavelet transform (DWT) is used in order to weight the resulting power patterns according to their frequency. Subsequently, the weighted power patterns are binarized via applying a threshold. At this final stage, significant power coincidence is determined across all subgroups of channel combinations for individual frequencies by selecting the maximum ratio between observed and expected duration of co-activation as test statistic. The null hypothesis that the activity in each channel is independent from the activity in every other channel is simulated by independent, random rotation of the respective activity patterns. We applied this procedure to single trials of multiple simultaneously sampled local field potentials (LFPs) obtained from occipital, parietal, central and precentral areas of three macaque monkeys. Since their task was to use visual cues to perform a precise arm movement, co-activation of numerous cortical sites was expected. In a data set with 17 channels analyzed, up to 13 sites expressed simultaneous power in the range between 5 and 240 Hz. On average, more than 50% of active channels participated at least once in a significant power co-activation pattern (PCP). Because the significance of such PCPs can be evaluated at the level of single trials, we are confident that this procedure is useful to study single trial variability with sufficient accuracy that much of the behavioral variability can be explained by the dynamics of the underlying distributed neuronal processes.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
We present the measured correlation functions for pi+ pi-, pi- pi- and pi+ pi+ pairs in central S+Ag collisions at 200 GeV per nucleon. The Gamov function, which has been traditionally used to correct the correlation functions of charged pions for the Coulomb interaction, is found to be inconsistent with all measured correlation functions. Certain problems which have been dominating the systematic uncertainty of the correlation analysis are related to this inconsistency. It is demonstrated that a new Coulomb correction method, based exclusively on the measured correlation function for pi+ pi- pairs, may solve the problem.
The transverse momentum and rapidity distributions of negative hadrons and participant protons have been measured for central 32S+ 32S collisions at plab=200 GeV/c per nucleon. The proton mean rapidity shift < Delta y>~1.6 and mean transverse momentum <pT>~0.6 GeV/c are much higher than in pp or peripheral AA collisions and indicate an increase in the nuclear stopping power. All pT spectra exhibit similar source temperatures. Including previous results for K0s Lambda , and Lambda -bar, we account for all important contributions to particle production.
The NA35 experiment has collected a high statistics set of momentum analyzed negative hadrons near and forward of midrapidity for central collisions of 200A GeV/c 32S+S, Cu, Ag, and Au. Using momentum space correlations to study the size of the source of particle production, the transverse source radii are found to decrease by ~40% at midrapidity and ~20% at forward rapidity while the longitudinal radius RL is found to decrease by ~50% as pT increases over the interval 50<pT<600 MeV/c. Calculations using a microscopic phase space approach (relativistic quantum molecular dynamics) reproduce the observed trends of the data. PACS: 25.75.+r
Introduction: Deep brain stimulation (DBS) has become a well-established treatment modality for a variety of conditions over the last decades. Multiple surgeries are an essential part in the postoperative course of DBS patients if nonrechargeable implanted pulse generators (IPGs) are applied. So far, the rate of subclinical infections in this field is unknown. In this prospective cohort study, we used sonication to evaluate possible microbial colonization of IPGs from replacement surgery. Methods: All consecutive patients undergoing IPG replacement between May 1, 2019 and November 15, 2020 were evaluated. The removed hardware was investigated using sonication to detect biofilm-associated bacteria. Demographic and clinical data were analyzed. Results: A total of 71 patients with a mean (±SD) of 64.5 ± 15.3 years were evaluated. In 23 of these (i.e., 32.4%) patients, a positive sonication culture was found. In total, 25 microorganisms were detected. The most common isolated microorganisms were Cutibacterium acnes (formerly known as Propionibacterium acnes) (68%) and coagulase-negative Staphylococci (28%). Within the follow-up period (5.2 ± 4.3 months), none of the patients developed a clinical manifest infection. Discussions/Conclusions: Bacterial colonization of IPGs without clinical signs of infection is common but does not lead to manifest infection. Further larger studies are warranted to clarify the impact of low-virulent pathogens in clinically asymptomatic patients.
Background: Reconstitution of cytomegalovirus-specific CD3+CD8+ T cells (CMV-CTLs) after allogeneic hematopoietic stem cell transplantation (HSCT) is necessary to bring cytomegalovirus (CMV) reactivation under control. However, the parameters determining protective CMV-CTL reconstitution remain unclear to date.
Design and Methods: In a prospective tri-center study, CMV-CTL reconstitution was analyzed in the peripheral blood from 278 patients during the year following HSCT using 7 commercially available tetrameric HLA-CMV epitope complexes. All patients included could be monitored with at least CMV-specific tetramer.
Results: CMV-CTL reconstitution was detected in 198 patients (71%) after allogeneic HSCT. Most importantly, reconstitution with 1 CMV-CTL per µl blood between day +50 and day +75 post-HSCT discriminated between patients with and without CMV reactivation in the R+/D+ patient group, independent of the CMV-epitope recognized. In addition, CMV-CTLs expanded more daramtaically in patients experiencing only one CMV-reactivation than those without or those with multiple CMV reactivations. Monitoring using at least 2 tetramers was possible in 63% (n = 176) of the patients. The combinations of particular HLA molecules influenced the numbers of CMV-CTLs detected. The highest CMV-CTL count obtained for an individual tetramer also changed over time in 11% of these patients (n = 19) resulting in higher levels of HLA-B*0801 (IE-1) recognizing CMV-CTLs in 14 patients.
Conclusions: Our results indicate that 1 CMV-CTL per µl blood between day +50 to +75 marks the beginning of an immune response against CMV in the R+/D+ group. Detection of CMV-CTL expansion thereafter indicates successful resolution of the CMV reactivation. Thus, sequential monitoring of CMV-CTL reconstitution can be used to predict patients at risk for recurrent CMV reactivation.