Postoperative Anaemia Might Be a Risk Factor for Postoperative Delirium and Prolonged Hospital Stay: A Secondary Analysis of a Prospective Cohort Study

Background: Postoperative anaemia is a frequent surgical complication and in contrast to preoperative anaemia has not been validated in relation to mortality, morbidity and its associated health economic effect. Postoperative anaemia can predispose postoperative delirium through impairment of cerebral oxygenation. The aim of this secondary analysis is to investigate the association of postoperative anaemia in accordance with the sex specific World Health Organization definition of anaemia to postoperative delirium and its impact on the duration of hospital stay. Methods: A secondary analysis of the prospective multicentric observational CESARO-study was conducted. 800 adult patients undergoing elective surgery were enrolled from various operative disciplines across seven hospitals ranging from university hospitals, district general hospitals to specialist clinics of minimally invasive surgery in Germany. Patients were classified as anaemic according to the World Health Organization parameters, setting the haemoglobin level cut off below 12g/dl for females and below 13g/dl for males. Focus of the investigation were patients with acute anaemia. Patients with present preoperative anaemia or missing haemoglobin measurement were excluded from the sample set. Delirium screening was established postoperatively for at least 24 hours and up to three days, applying the validated Nursing Delirium Screening Scale. Results: The initial sample set contained 800 patients of which 183 were suitable for analysis in the study. Ninety out of 183 (49.2%) suffered from postoperative anaemia. Ten out of 93 (10.9%) patients without postoperative anaemia developed a postoperative delirium. In the group with postoperative anaemia, 28 (38.4%) out of 90 patients suffered from postoperative delirium (odds ratio 3.949, 95% confidence interval, (1.358-11.480)) after adjustment for NYHA-stadium, severity of surgery, cutting/suture time, duration of anaesthesia, transfusion of packed red cells and sedation status with Richmond Agitation Scale after surgery. Additionally, patients who suffered from postoperative anaemia showed a significantly longer duration of hospitalisation (7.75 vs. 12.42 days, odds ratio = 1.186, 95% confidence interval, 1.083-1.299, after adjustments). Conclusion: The study results reveal that postoperative anaemia is not only a frequent postsurgical complication with an incidence probability of almost 50%, but could also be associated with a postoperative delirium and a prolonged hospitalisation

Assessment of Brain Age in Posttraumatic Stress Disorder: Findings from the ENIGMA PTSD and Brain Age Working Groups

Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder:Results from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LME INT), (2) LME that models both site-specific random intercepts and age-related random slopes (LME INT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ 2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ 2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ 2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects

Crucial role of SLP-76 and ADAP for neutrophil recruitment in mouse kidney ischemia-reperfusion injury

Neutrophils trigger inflammation-induced acute kidney injury (AKI), a frequent and potentially lethal occurrence in humans. Molecular mechanisms underlying neutrophil recruitment to sites of inflammation have proved elusive. In this study, we demonstrate that SLP-76 (SH2 domain–containing leukocyte phosphoprotein of 76 kD) and ADAP (adhesion and degranulation promoting adaptor protein) are involved in E-selectin–mediated integrin activation and slow leukocyte rolling, which promotes ischemia-reperfusion–induced AKI in mice. By using genetically engineered mice and transduced Slp76(−/−) primary leukocytes, we demonstrate that ADAP as well as two N-terminal–located tyrosines and the SH2 domain of SLP-76 are required for downstream signaling and slow leukocyte rolling. The Tec family kinase Bruton tyrosine kinase is downstream of SLP-76 and, together with ADAP, regulates PI3Kγ (phosphoinositide 3-kinase–γ)- and PLCγ2 (phospholipase Cγ2)-dependent pathways. Blocking both pathways completely abolishes integrin affinity and avidity regulation. Thus, SLP-76 and ADAP are involved in E-selectin–mediated integrin activation and neutrophil recruitment to inflamed kidneys, which may underlie the development of life-threatening ischemia-reperfusion–induced AKI in humans

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

The Effect of Structural Design on Mechanical Properties and Cellular Response of Additive Manufactured Titanium Scaffolds

Restoration of segmental defects in long bones remains a challenging task in orthopedic surgery. Although autologous bone is still the ‘Gold Standard’ because of its high biocompatibility, it has nevertheless been associated with several disadvantages. Consequently, artificial materials, such as calcium phosphate and titanium, have been considered for the treatment of bone defects. In the present study, the mechanical properties of three different scaffold designs were investigated. The scaffolds were made of titanium alloy (Ti6Al4V), fabricated by means of an additive manufacturing process with defined pore geometry and porosities of approximately 70%. Two scaffolds exhibited rectangular struts, orientated in the direction of loading. The struts for the third scaffold were orientated diagonal to the load direction, and featured a circular cross-section. Material properties were calculated from stress-strain relationships under axial compression testing. &lt;em&gt;In vitro&lt;/em&gt; cell testing was undertaken with human osteoblasts on scaffolds fabricated using the same manufacturing process. Although the scaffolds exhibited different strut geometry, the mechanical properties of ultimate compressive strength were similar (145–164 MPa) and in the range of human cortical bone. Test results for elastic modulus revealed values between 3.7 and 6.7 GPa. &lt;em&gt;In vitro&lt;/em&gt; testing demonstrated proliferation and spreading of bone cells on the scaffold surface