Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study.

INTRODUCTION: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. OBJECTIVE: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. METHODS: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. RESULTS: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. CONCLUSIONS: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research.

Global safety monitoring of COVID-19 vaccines: how pharmacovigilance rose to the challenge.

Pharmacovigilance (PV) came suddenly into the spotlight when several new vaccines, developed as a response to the COVID-19 pandemic, received emergency authorisation and were rolled out on a large scale in late 2020. The vaccines underwent stringent clinical trials and evaluation from regulatory authorities, but with the use of novel technology and an anticipated rapid and vast deployment of the vaccines, the importance of a well-functioning international post marketing safety surveillance system was stressed. International PV stakeholders were faced with several challenges due to the extent of the global vaccination campaign. The unprecedented volume of reports of suspected adverse events following immunization has led to the development and use of new tools. Furthermore, the collaboration between various PV stakeholders was encouraged and strengthened. PV rose to the challenges posed by the currently ongoing global COVID-19 vaccination campaign and successful adaptations were made in a short period of time. However, the pandemic has not ended yet, the vaccination campaign is far from being completed, and further challenges are anticipated. Advances made during the pandemic will be important to strengthen PV in future and ensure to advance medicines' safety together. Plain Language Summary: Global safety monitoring of the COVID-19 vaccines: challenges, preparations, and outlooks Pharmacovigilance (PV) is the umbrella term for all sciences and activities relating to the detection, assessment, understanding, and prevention of adverse effects relating to medicines or vaccines. PV came into the spotlight when several new vaccines were authorised and rolled out as a response to the COVID-19 pandemic.The anticipated extent of the global vaccine rollout stressed the importance of a well-functioning safety surveillance system and international collaborations between patients, health care workers, vaccine producers, regulatory authorities, and PV centres.The identification and communication of potential safety concerns showed that adaptations to PV processes made in a short period of time as well as international collaborations were successful. However, it is important to learn from experiences made so far and to make sure the positive advances are maintained in the future to advance medicines' safety together.

The ZCCHC14/TENT4 complex is required for hepatitis A virus RNA synthesis.

Despite excellent vaccines, resurgent outbreaks of hepatitis A have caused thousands of hospitalizations and hundreds of deaths within the United States in recent years. There is no effective antiviral therapy for hepatitis A, and many aspects of the hepatitis A virus (HAV) replication cycle remain to be elucidated. Replication requires the zinc finger protein ZCCHC14 and noncanonical TENT4 poly(A) polymerases with which it associates, but the underlying mechanism is unknown. Here, we show that ZCCHC14 and TENT4A/B are required for viral RNA synthesis following translation of the viral genome in infected cells. Cross-linking immunoprecipitation sequencing (CLIP-seq) experiments revealed that ZCCHC14 binds a small stem-loop in the HAV 5' untranslated RNA possessing a Smaug recognition-like pentaloop to which it recruits TENT4. TENT4 polymerases lengthen and stabilize the 3' poly(A) tails of some cellular and viral mRNAs, but the chemical inhibition of TENT4A/B with the dihydroquinolizinone RG7834 had no impact on the length of the HAV 3' poly(A) tail, stability of HAV RNA, or cap-independent translation of the viral genome. By contrast, RG7834 inhibited the incorporation of 5-ethynyl uridine into nascent HAV RNA, indicating that TENT4A/B function in viral RNA synthesis. Consistent with potent in vitro antiviral activity against HAV (IC50 6.11 nM), orally administered RG7834 completely blocked HAV infection in Ifnar1-/- mice, and sharply reduced serum alanine aminotransferase activities, hepatocyte apoptosis, and intrahepatic inflammatory cell infiltrates in mice with acute hepatitis A. These results reveal requirements for ZCCHC14-TENT4A/B in hepatovirus RNA synthesis, and suggest that TENT4A/B inhibitors may be useful for preventing or treating hepatitis A in humans.

Caspase-7 activates ASM to repair gasdermin and perforin pores.

Among the caspases that cause regulated cell death, a unique function for caspase-7 has remained elusive. Caspase-3 performs apoptosis, whereas caspase-7 is typically considered an inefficient back-up. Caspase-1 activates gasdermin D pores to lyse the cell; however, caspase-1 also activates caspase-7 for unknown reasons1. Caspases can also trigger cell-type-specific death responses; for example, caspase-1 causes the extrusion of intestinal epithelial cell (IECs) in response to infection with Salmonella enterica subsp. enterica serovar Typhimurium (S. Typhimurium)2,3. Here we show in both organoids and mice that caspase-7-deficient IECs do not complete extrusion. Mechanistically, caspase-7 counteracts gasdermin D pores and preserves cell integrity by cleaving and activating acid sphingomyelinase (ASM), which thereby generates copious amounts of ceramide to enable enhanced membrane repair. This provides time to complete the process of IEC extrusion. In parallel, we also show that caspase-7 and ASM cleavage are required to clear Chromobacterium violaceum and Listeria monocytogenes after perforin-pore-mediated attack by natural killer cells or cytotoxic T lymphocytes, which normally causes apoptosis in infected hepatocytes. Therefore, caspase-7 is not a conventional executioner but instead is a death facilitator that delays pore-driven lysis so that more-specialized processes, such as extrusion or apoptosis, can be completed before cell death. Cells must put their affairs in order before they die.

A Question-and-Answer System to Extract Data From Free-Text Oncological Pathology Reports (CancerBERT Network): Development Study.

BACKGROUND: Information in pathology reports is critical for cancer care. Natural language processing (NLP) systems used to extract information from pathology reports are often narrow in scope or require extensive tuning. Consequently, there is growing interest in automated deep learning approaches. A powerful new NLP algorithm, bidirectional encoder representations from transformers (BERT), was published in late 2018. BERT set new performance standards on tasks as diverse as question answering, named entity recognition, speech recognition, and more. OBJECTIVE: The aim of this study is to develop a BERT-based system to automatically extract detailed tumor site and histology information from free-text oncological pathology reports. METHODS: We pursued three specific aims: extract accurate tumor site and histology descriptions from free-text pathology reports, accommodate the diverse terminology used to indicate the same pathology, and provide accurate standardized tumor site and histology codes for use by downstream applications. We first trained a base language model to comprehend the technical language in pathology reports. This involved unsupervised learning on a training corpus of 275,605 electronic pathology reports from 164,531 unique patients that included 121 million words. Next, we trained a question-and-answer (Q&A) model that connects a Q&A layer to the base pathology language model to answer pathology questions. Our Q&A system was designed to search for the answers to two predefined questions in each pathology report: What organ contains the tumor? and What is the kind of tumor or carcinoma? This involved supervised training on 8197 pathology reports, each with ground truth answers to these 2 questions determined by certified tumor registrars. The data set included 214 tumor sites and 193 histologies. The tumor site and histology phrases extracted by the Q&A model were used to predict International Classification of Diseases for Oncology, Third Edition (ICD-O-3), site and histology codes. This involved fine-tuning two additional BERT models: one to predict site codes and another to predict histology codes. Our final system includes a network of 3 BERT-based models. We call this CancerBERT network (caBERTnet). We evaluated caBERTnet using a sequestered test data set of 2050 pathology reports with ground truth answers determined by certified tumor registrars. RESULTS: caBERTnet's accuracies for predicting group-level site and histology codes were 93.53% (1895/2026) and 97.6% (1993/2042), respectively. The top 5 accuracies for predicting fine-grained ICD-O-3 site and histology codes with 5 or more samples each in the training data set were 92.95% (1794/1930) and 96.01% (1853/1930), respectively. CONCLUSIONS: We have developed an NLP system that outperforms existing algorithms at predicting ICD-O-3 codes across an extensive range of tumor sites and histologies. Our new system could help reduce treatment delays, increase enrollment in clinical trials of new therapies, and improve patient outcomes.

Internal carotid artery blister aneurysm rupture: a unifying diagnosis for massive epistaxis and unilateral embolic strokes.

Concurrent epistaxis, embolic stroke and a ruptured internal carotid artery are rare but life-threatening delayed complications of cured nasopharyngeal squamous cell carcinoma. A timely diagnosis and effective management can be problematic. We report a case that highlights the unique diagnostic features of this presentation and contemporary endovascular treatment options available.

Weakly Supervised Skull Stripping of Magnetic Resonance Imaging of Brain Tumor Patients.

Automatic brain tumor segmentation is particularly challenging on magnetic resonance imaging (MRI) with marked pathologies, such as brain tumors, which usually cause large displacement, abnormal appearance, and deformation of brain tissue. Despite an abundance of previous literature on learning-based methodologies for MRI segmentation, few works have focused on tackling MRI skull stripping of brain tumor patient data. This gap in literature can be associated with the lack of publicly available data (due to concerns about patient identification) and the labor-intensive nature of generating ground truth labels for model training. In this retrospective study, we assessed the performance of Dense-Vnet in skull stripping brain tumor patient MRI trained on our large multi-institutional brain tumor patient dataset. Our data included pretreatment MRI of 668 patients from our in-house institutional review board-approved multi-institutional brain tumor repository. Because of the absence of ground truth, we used imperfect automatically generated training labels using SPM12 software. We trained the network using common MRI sequences in oncology: T1-weighted with gadolinium contrast, T2-weighted fluid-attenuated inversion recovery, or both. We measured model performance against 30 independent brain tumor test cases with available manual brain masks. All images were harmonized for voxel spacing and volumetric dimensions before model training. Model training was performed using the modularly structured deep learning platform NiftyNet that is tailored toward simplifying medical image analysis. Our proposed approach showed the success of a weakly supervised deep learning approach in MRI brain extraction even in the presence of pathology. Our best model achieved an average Dice score, sensitivity, and specificity of, respectively, 94.5, 96.4, and 98.5% on the multi-institutional independent brain tumor test set. To further contextualize our results within existing literature on healthy brain segmentation, we tested the model against healthy subjects from the benchmark LBPA40 dataset. For this dataset, the model achieved an average Dice score, sensitivity, and specificity of 96.2, 96.6, and 99.2%, which are, although comparable to other publications, slightly lower than the performance of models trained on healthy patients. We associate this drop in performance with the use of brain tumor data for model training and its influence on brain appearance.

Appendicitis as a possible safety signal for the COVID-19 vaccines.

This study reviewed cases of appendicitis following administration of COVID-19 vaccines reported to VigiBase, the WHO database of individual case safety reports (ICSRs). Three hundred fifty-eight cases were identified, and disproportionate reporting was noted, with 329 calculated expected cases. Upon review, 24 ICSRs were excluded, so 334 unique ICSRs underwent clinical review from 19 countries. Forty-eight percent of ICSRs reported imaging and 69% noted surgical intervention. The cases were clinically coherent, with an apparent increase in reporting in the four days post-vaccination and a possible dose-response relationship. Appendicitis has been suggested as an adverse event of special interest post-vaccination against COVID-19 after a numerical increase in the vaccine arm of a clinical trial. The case series may be affected by differences in global patterns of reporting, and it is not possible to prove nor disprove causality from this case series. Global longitudinal studies are required to clarify any possible relationship.

Trends, relationships and case attribution of antibiotic resistance between children and environmental sources in rural India.

Bacterial antibiotic resistance is an important global health threat and the interfaces of antibiotic resistance between humans, animals and the environment are complex. We aimed to determine the associations and overtime trends of antibiotic resistance between humans, animals and water sources from the same area and time and estimate attribution of the other sources to cases of human antibiotic resistance. A total of 125 children (aged 1-3 years old) had stool samples analysed for antibiotic-resistant bacteria at seven time points over two years, with simultaneous collection of samples of animal stools and water sources in a rural Indian community. Newey-West regression models were used to calculate temporal associations, the source with the most statistically significant relationships was household drinking water. This is supported by use of SourceR attribution modelling, that estimated the mean attribution of cases of antibiotic resistance in the children from animals, household drinking water and wastewater, at each time point and location, to be 12.6% (95% CI 4.4-20.9%), 12.1% (CI 3.4-20.7%) and 10.3% (CI 3.2-17.3%) respectively. This underlines the importance of the 'one health' concept and requires further research. Also, most of the significant trends over time were negative, suggesting a possible generalised improvement locally.

Relative Clinical Outcomes Comparing Manual and Robotic-Assisted Total Knee Arthroplasty at Minimum 1-Year Follow-up.

Background: Total knee arthroplasty (TKA) demonstrates excellent durability using jig-based manual techniques (manual TKA [mTKA]), but significant rates of dissatisfaction remain. Modifications of mTKA techniques and TKA implant designs to improve outcomes have had minimal success. Studies comparing relative outcomes of mTKA and robotic-assisted TKA (raTKA) are limited. Purpose: This study sought to compare outcomes of mTKA and raTKA in patients at a single institution. Methods: We retrospectively reviewed all primary TKAs performed by 1 surgeon from 2015 to 2017. In all, 139 consecutive mTKAs (2015-2016) and 148 consecutive raTKAs (2016-2017) were included. No cases were excluded. Patient demographics, complications, readmission rates, and clinical and patient-reported outcomes were compared at a minimum of 1-year follow-up. A post hoc student t test and Pearson χ2 test were used for continuous and categorical data. Results: We found that mTKA patients compared with raTKA patients required significantly longer length of stay (LOS) (1.73 vs 1.18 days, respectively), greater morphine milligram equivalents consumption (89.6 vs 65.2, respectively), and increased physical therapy (PT) visits (13.0 vs 11.0, respectively) with increased 30-day readmission rates (4.3 vs 0.7%, respectively) that approached significance. Knee Injury and Osteoarthritis Outcome Score for Joint Replacement and the University of California at Los Angeles activity score did not differ significantly comparing raTKA with mTKA patients at 1 year. There were no differences in complication rates. Conclusion: Significant early clinical benefits were noted with raTKA, including lower opioid requirements, shorter LOS, and fewer PT visits when compared with mTKA. A reduction in 30-day readmission rates was noted with raTKA that was not significant. Excellent clinical results with similar patient-reported outcomes were noted in both groups at 1-year follow-up. Further prospective investigations at longer follow-up intervals comparing these techniques are warranted.

T cells protect against hepatitis A virus infection and limit infection-induced liver injury.

BACKGROUND & AIMS: Hepatitis A virus (HAV) is a common cause of enterically transmitted viral hepatitis. In non-immune individuals, infection results in typically transient but occasionally fulminant and fatal inflammatory liver injury. Virus-specific T cell frequencies peak when liver damage is at its zenith, leading to the prevalent notion that T cells exacerbate liver disease, as suspected for other hepatotropic virus infections. However, the overall contribution of T cells to the control of HAV and the pathogenesis of hepatitis A is unclear and has been impeded by a historic lack of small animal models. METHODS: Ifnar1-/- mice are highly permissive for HAV and develop pathogenesis that recapitulates many features of hepatitis A. Using this model, we identified HAV-specific CD8+ and CD4+ T cells by epitope mapping, and then used tetramers and functional assays to quantify T cells in the liver at multiple times after infection. We assessed the relationships between HAV-specific T cell frequency, viral RNA amounts, and liver pathogenesis. RESULTS: A large population of virus-specific T cells accumulated within the livers of Ifnar1-/- mice during the first 1-2 weeks of infection and persisted over time. HAV replication was enhanced and liver disease exacerbated when mice were depleted of T cells. Conversely, immunization with a peptide vaccine increased virus-specific CD8+ T cell frequencies in the liver, reduced viral RNA abundance, and lessened liver injury. CONCLUSION: These data show that T cells protect against HAV-mediated liver injury and can be targeted to improve liver health. LAY SUMMARY: Hepatitis A virus is a leading cause of acute viral hepatitis worldwide. T cells were thought to contribute to liver injury during acute infection. We now show that virus-specific T cells protect against infection and limit liver injury.

UTX promotes CD8+ T cell-mediated antiviral defenses but reduces T cell durability.

Persistent virus infections can cause pathogenesis that is debilitating or lethal. During these infections, virus-specific T cells fail to protect due to weakened antiviral activity or failure to persist. These outcomes are governed by histone modifications, although it is unknown which enzymes contribute to T cell loss or impaired function over time. In this study, we show that T cell receptor-stimulated CD8+ T cells increase their expression of UTX (ubiquitously transcribed tetratricopeptide repeat, X chromosome) to enhance gene expression. During chronic lymphocytic choriomeningitis virus (LCMV) infection in mice, UTX binds to enhancers and transcription start sites of effector genes, allowing for improved cytotoxic T lymphocyte (CTL)-mediated protection, independent of its trimethylation of histone 3 lysine 27 (H3K27me3) demethylase activity. UTX also limits the frequency and durability of virus-specific CD8+ T cells, which correspond to increased expression of inhibitory receptors. Thus, UTX guides gene expression patterns in CD8+ T cells, advancing early antiviral defenses while reducing the longevity of CD8+ T cell responses.

Statistical shape modelling to analyse the talus in paediatric clubfoot.

One fifth of idiopathic clubfoot deformities cannot be fully corrected by Serial Ponseti casting and deformity recurs in 20%-30% of cases. To avoid x-ray exposure, the joints with largely unossified bones are diagnosed with magnetic resonance images (MRI). Typically, geometric measurements are made in the MRI planes; however, this method is inaccurate compared to measurements on three-dimensional (3D) models of the joint. More accurate measurements using the 3D bone shapes may be better at identifying differences between groups; and therefore, improve diagnosis. The entire set of shape features from MRI can be analysed simultaneously through statistical shape modelling (SSM) which assesses bone morphology of clubfoot in a more sensitive way. A method for SSM of the talus is developed in this study and the shape of the normal talus is compared with the one in clubfeet with residual deformity through both geometric measurements and SSM. Significant differences between two groups were found by both methods; and therefore, might contribute to improve diagnosis of clubfoot.

A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity.

Community occupancy models estimate species-specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates toward the community mean can mask differences among groups. Infinite-mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species-level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP-COM with different dimensions (i.e., different numbers of model parameters with species-level DP random effects) and under varying cluster differences. Because the DP-COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP-COM model to a bird data set from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community-level covariate coefficients on occupancy probability were generally unbiased with (near-) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP-COM was similar. The DP-COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP-COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP-COM, and considering the computational burden for the DP models, we recommend using the DP-COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP-COM.

Insulin Resistance at the Crossroad of Alzheimer Disease Pathology: A Review.

Insulin plays a major neuroprotective and trophic function for cerebral cell population, thus countering apoptosis, beta-amyloid toxicity, and oxidative stress; favoring neuronal survival; and enhancing memory and learning processes. Insulin resistance and impaired cerebral glucose metabolism are invariantly reported in Alzheimer's disease (AD) and other neurodegenerative processes. AD is a fatal neurodegenerative disorder in which progressive glucose hypometabolism parallels to cognitive impairment. Although AD may appear and progress in virtue of multifactorial nosogenic ingredients, multiple interperpetuative and interconnected vicious circles appear to drive disease pathophysiology. The disease is primarily a metabolic/energetic disorder in which amyloid accumulation may appear as a by-product of more proximal events, especially in the late-onset form. As a bridge between AD and type 2 diabetes, activation of c-Jun N-terminal kinase (JNK) pathway with the ensued serine phosphorylation of the insulin response substrate (IRS)-1/2 may be at the crossroads of insulin resistance and its subsequent dysmetabolic consequences. Central insulin axis bankruptcy translates in neuronal vulnerability and demise. As a link in the chain of pathogenic vicious circles, mitochondrial dysfunction, oxidative stress, and peripheral/central immune-inflammation are increasingly advocated as major pathology drivers. Pharmacological interventions addressed to preserve insulin axis physiology, mitochondrial biogenesis-integral functionality, and mitophagy of diseased organelles may attenuate the adjacent spillover of free radicals that further perpetuate mitochondrial damages and catalyze inflammation. Central and/or peripheral inflammation may account for a local flood of proinflammatory cytokines that along with astrogliosis amplify insulin resistance, mitochondrial dysfunction, and oxidative stress. All these elements are endogenous stressor, pro-senescent factors that contribute to JNK activation. Taken together, these evidences incite to identify novel multi-mechanistic approaches to succeed in ameliorating this pandemic affliction.

Opioid Use in Robotic-Arm Assisted Total Knee Arthroplasty: A Comparison to Conventional Manual Total Knee Arthroplasty.

INTRODUCTION: Opioids are frequently prescribed in the postoperative management of total knee arthroplasty (TKA) with multiple factors influencing postoperative opioid use. Robotic-arm-assisted TKA (raTKA) was developed with the goal of improving alignment and outcomes while decreasing soft tissue injury. The purpose of this study was to compare postoperative opioid consumption in raTKA and conventional manual TKA (mTKA) cohorts. MATERIALS AND METHODS: A consecutive series of unilateral primary TKAs performed 1/1/16 to 12/31/17 were included. Patients with major procedures requiring opioids occurring within one year of TKA were excluded. A single-surgeon raTKA cohort of 127 patients (Group 1) was compared to a same-surgeon cohort of 119 mTKAs (Group 2) using the same cemented implant design and a two-surgeon cohort of 410 mTKA (Group 3). Groups were subdivided into opioid naïve (ON) and opioid exposed (OE). Length of hospitalization and postoperative opioid utilization up to one year were compared between groups and collectively without separating raTKA and mTKA. Statistical analysis included Chi-square, Student's t-test, and Wilcoxon rank sum tests. RESULTS: For both ON and OE patients, Group 1 demonstrated reduced inpatient mean daily oral morphine milligram equivalent (MME) compared to Group 3 (ON p=0.007; OE p=0.034), a shorter hospitalization compared to Group 2 (ON p=0.02; OE p=0.012), and fewer opioids prescribed at discharge compared to Group 2 (ON p=0.005; OE p=0.081) and Group 3 (ON p<0.001; OE p=0.036). No differences in opioid prescriptions were seen at three months or after. Regardless of surgical technique OE patients had higher inpatient opioid utilization (p<0.001) as well as cumulative outpatient prescription quantity (MME 1050 ON, 2660 OE) and duration (ON 0.5%; OE 28.3%) at one year (p<0.001). CONCLUSION: Less opioids were prescribed at discharge and used during hospitalization in raTKA compared to mTKA though no differences in opioid use were seen at further time points. Preoperative opioid use remains a dominant factor in postoperative opioid utilization regardless of TKA surgical technique.

Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data.

Purpose: Deep learning (DL) algorithms have shown promising results for brain tumor segmentation in MRI. However, validation is required prior to routine clinical use. We report the first randomized and blinded comparison of DL and trained technician segmentations. Approach: We compiled a multi-institutional database of 741 pretreatment MRI exams. Each contained a postcontrast T1-weighted exam, a T2-weighted fluid-attenuated inversion recovery exam, and at least one technician-derived tumor segmentation. The database included 729 unique patients (470 males and 259 females). Of these exams, 641 were used for training the DL system, and 100 were reserved for testing. We developed a platform to enable qualitative, blinded, controlled assessment of lesion segmentations made by technicians and the DL method. On this platform, 20 neuroradiologists performed 400 side-by-side comparisons of segmentations on 100 test cases. They scored each segmentation between 0 (poor) and 10 (perfect). Agreement between segmentations from technicians and the DL method was also evaluated quantitatively using the Dice coefficient, which produces values between 0 (no overlap) and 1 (perfect overlap). Results: The neuroradiologists gave technician and DL segmentations mean scores of 6.97 and 7.31, respectively ( p < 0.00007 ). The DL method achieved a mean Dice coefficient of 0.87 on the test cases. Conclusions: This was the first objective comparison of automated and human segmentation using a blinded controlled assessment study. Our DL system learned to outperform its "human teachers" and produced output that was better, on average, than its training data.

Comparing Zwitterionic and PEG Exteriors of Polyelectrolyte Complex Micelles.

A series of model polyelectrolyte complex micelles (PCMs) was prepared to investigate the consequences of neutral and zwitterionic chemistries and distinct charged cores on the size and stability of nanocarriers. Using aqueous reversible addition-fragmentation chain transfer (RAFT) polymerization, we synthesized a well-defined diblock polyelectrolyte system, poly(2-methacryloyloxyethyl phosphorylcholine methacrylate)-block-poly((vinylbenzyl) trimethylammonium) (PMPC-PVBTMA), at various neutral and charged block lengths to compare directly against PCM structure-property relationships centered on poly(ethylene glycol)-block-poly((vinylbenzyl) trimethylammonium) (PEG-PVBTMA) and poly(ethylene glycol)-block-poly(l-lysine) (PEG-PLK). After complexation with a common polyanion, poly(sodium acrylate), the resulting PCMs were characterized by dynamic light scattering (DLS) and small angle X-ray scattering (SAXS). We observed uniform assemblies of spherical micelles with a diameter ~1.5-2× larger when PMPC-PVBTMA was used compared to PEG-PLK and PEG-PVBTMA via SAXS and DLS. In addition, PEG-PLK PCMs proved most resistant to dissolution by both monovalent and divalent salt, followed by PEG-PVBTMA then PMPC-PVBTMA. All micelle systems were serum stable in 100% fetal bovine serum over the course of 8 h by time-resolved DLS, demonstrating minimal interactions with serum proteins and potential as in vivo drug delivery vehicles. This thorough study of the synthesis, assembly, and characterization of zwitterionic polymers in PCMs advances the design space for charge-driven micelle assemblies.

Methicillin-Resistant Staphylococcus Aureus Carrier Rate in Orthopaedic Trauma Patients: A Prospective Cohort Study.

OBJECTIVES: To identify the methicillin-resistant Staphylococcus aureus (MRSA) carrier rate among surgical patients on an orthopaedic trauma service and to determine whether screening is an effective tool for reducing postoperative MRSA infection in this population. DESIGN: Prospective. SETTING: Level 1 trauma center. PATIENTS/PARTICIPANTS: Two hundred forty-eight patients with operatively managed orthopaedic trauma conditions during the study period. Two hundred three patients (82%) had acute orthopaedic trauma injuries. Forty-five patients (18%) underwent surgery for a nonacute orthopaedic trauma condition, including 36 elective procedures and 9 procedures to address infection. INTERVENTION: MRSA screening protocol, preoperative antibiotics per protocol. MAIN OUTCOME MEASUREMENTS: MRSA carrier rate, overall infection rate, MRSA infection rate. RESULTS: Our screening captured 71% (175/248) of operatively treated orthopaedic trauma patients during the study period. The overall MRSA carrier rate was 3.4% (6/175). When separated by group, the acute orthopaedic trauma cohort had an MRSA carrier rate of 1.4% (2/143), and neither MRSA-positive patient developed a surgical site infection. Only one MRSA infection occurred in the acute orthopaedic trauma cohort. The nonacute group had a significantly higher MRSA carrier rate of 12.5% (4/32, P = 0.01), and the elective group had the highest MRSA carrier rate of 15.4% (4/26, P < 0.01). The odds ratio of MRSA colonization was 10.1 in the nonacute group (95% confidence interval, 1.87-75.2) and 12.8 for true elective group (95% confidence interval, 2.36-96.5) when compared with the acute orthopaedic trauma cohort. CONCLUSIONS: There was a low MRSA colonization rate (1.4%) among patients presenting to our institution for acute fracture care. Patients undergoing elective surgery for fracture-related conditions such as nonunion, malunion, revision surgery, or implant removal have a significantly higher MRSA carrier rate (15.4%) and therefore may benefit from MRSA screening. Our results do not support routine vancomycin administration for orthopaedic trauma patients whose MRSA status is not known at the time of surgery. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.