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Background This network meta-analysis was performed to determine the optimal surgical approach for pancreatoduodenectomy by comparing outcomes after laparoscopic pancreatoduodenectomy, robotic pancreatoduodenectomy and open pancreatoduodenectomy. Methods A systematic search of the PubMed, EMBASE, Scopus, and Web of Science databases was conducted to identify eligible randomized controlled trials and propensity-score matched studies. Results Four randomized controlled trials and 23 propensity-score matched studies comprising a total of 4,945 patients were included for analysis. Operation time for open pancreatoduodenectomy was shorter than both laparoscopic pancreatoduodenectomy (mean difference –57.35, 95% CI 26.25–88.46 minutes) and robotic pancreatoduodenectomy (mean difference –91.08, 95% CI 48.61–133.56 minutes), blood loss for robotic pancreatoduodenectomy was significantly less than both laparoscopic pancreatoduodenectomy (mean difference –112.58, 95% CI 36.95–118.20 mL) and open pancreatoduodenectomy (mean difference –209.87, 95% CI 140.39–279.36 mL), both robotic pancreatoduodenectomy and laparoscopic pancreatoduodenectomy were associated with reduced rates of delayed gastric emptying compared with open pancreatoduodenectomy (odds ratio 0.59, 95% CI 0.39–0.90 and odds ratio 0.69, 95% CI 0.50–0.95, respectively), robotic pancreatoduodenectomy was associated with fewer wound infections compared with open pancreatoduodenectomy (odds ratio 0.35, 95% CI 0.18–0.71), and laparoscopic pancreatoduodenectomy patients enjoyed significantly shorter length of stay compared with open pancreatoduodenectomy (odds ratio 0.43, 95% CI 0.28–0.95). There were no differences in other outcomes. Conclusion This network meta-analysis of high-quality studies suggests that when laparoscopic pancreatoduodenectomy and robotic pancreatoduodenectomy are performed in high-volume centers, short-term perioperative and oncologic outcomes are largely comparable, if not slightly improved, compared with traditional open pancreatoduodenectomy. These findings should be corroborated in further prospective randomized studies.

Background The exact role of laparoscopic liver resection (LLR) in patients with hepatocellular carcinoma (HCC) and underlying liver cirrhosis (LC) is not well defined. In this meta-analysis, both long- and short-term outcomes following LLR versus open liver resection (OLR) were analysed. Methods PubMed, EMBASE, Scopus and Web of Science databases were searched systematically for randomised controlled trials (RCTs) and propensity-score matched (PSM) studies reporting outcomes of LLR versus OLR of HCC in patients with cirrhosis. Primary outcome was overall survival (OS). This was analysed using one-stage (individual participant data meta-analysis) and two-stage (aggregate data meta-analysis) approaches. Secondary outcomes were operation duration, blood loss, blood transfusion, Pringle manoeuvre utilization, overall and major complications, length of hospital stay (LOHS), 90-day mortality and R0 resection rates. Results Eleven studies comprising 1618 patients (690 LLR versus 928 OLR) were included for analysis. In the one-stage meta-analysis, an approximately 18.7 per cent lower hazard rate (HR) of death in the LLR group (random effects: HR 0.81, 95 per cent confidence interval [C.I.] 0.68 to 0.96; P = 0.018) was observed. Two-stage meta-analysis resulted in a pooled HR of 0.84 (95 per cent C.I. 0.74 to 0.96; P = 0.01) in the overall LLR cohort. This indicated a 16–26 per cent reduction in the HR of death for patients with HCC and cirrhosis who underwent LLR. For secondary outcomes, LLR was associated with less blood loss (mean difference [MD] −99 ml, 95 per cent C.I. −182 to −16 ml), reduced overall complications (odds ratio 0.49, 95 per cent C.I. 0.37 to 0.66) and major complications (odds ratio 0.45, 95 per cent C.I. 0.26 to 0.79), and shorter LOHS (MD −3.22 days, 95 per cent C.I. −4.38 to −2.06 days). Conclusion Laparoscopic resection of HCC in patients with cirrhosis is associated with improved survival and perioperative outcomes.

Multiplexed immunofluorescence imaging allows the multidimensional molecular profiling of cellular environments at subcellular resolution. However, identifying and characterizing disease-relevant microenvironments from these rich datasets is challenging. Here we show that a graph neural network that leverages spatial protein profiles in tissue specimens to model tumour microenvironments as local subgraphs captures distinctive cellular interactions associated with differential clinical outcomes. We applied this spatial cellular-graph strategy to specimens of human head-and-neck and colorectal cancers assayed with 40-plex immunofluorescence imaging to identify spatial motifs associated with cancer recurrence and with patient survival after treatment. The graph deep learning model was substantially more accurate in predicting patient outcomes than deep learning approaches that model spatial data on the basis of the local composition of cell types, and it generated insights into the effect of the spatial compartmentalization of tumour cells and granulocytes on patient prognosis. Local graphs may also aid in the analysis of disease-relevant motifs in histology samples characterized via spatial transcriptomics and other -omics techniques.

Clinical trials are the gatekeepers and bottlenecks of progress in medicine. In recent years, they have become increasingly complex and expensive, driven by a growing number of stakeholders requiring more endpoints, more diverse patient populations, and a stringent regulatory environment. Trial designers have historically relied on investigator expertise and legacy norms established within sponsor companies to improve operational efficiency while achieving study goals. As such, data-driven forecasts of operational metrics can be a useful resource for trial design and planning. We develop a machine learning model to predict clinical trial operational efficiency using a novel dataset from Roche containing over 2,000 clinical trials across 20 years and multiple disease areas. The data includes important operational metrics related to patient recruitment and trial duration, as well as a variety of trial features such as the number of procedures, eligibility criteria, and endpoints. Our results demonstrate that operational efficiency can be predicted robustly using trial features, which can provide useful insights to trial designers on the potential impact of their decisions on patient recruitment success and trial duration.

Due to limited treatment options, many patients with diabetic gastroparesis (DG) or idiopathic gastroparesis (IG) experience inadequate symptom control resulting in increased health-care resource utilization (HRU) and associated costs. We compared all-cause HRU and health-care costs over the 3 years after patients' first gastroparesis diagnosis with that of matched controls without gastroparesis.Newly diagnosed adults with DG or IG were identified in Optum's de-identified ClinformaticsDemographics and comorbidities were balanced between patients with gastroparesis (n = 18,015 [DG]; n = 14,305 [IG]) and controls. In each of the Years 1-3 post-index, patients with DG or IG had significantly higher annual HRU and costs versus controls (mean total cost differences PPY: DG Year 1 $34,885, Year 2 $28,071, Year 3 $25,606; IG Year 1 $23,176, Year 2 $16,627, Year 3 $14,396) (all p 0.05). Across all 3 years, DG/IG cohorts had approximately twice the costs of controls. HRU and costs were highest in Year 1 post-index for both DG and IG.The economic burden of gastroparesis remains high several years after diagnosis, emphasizing the need for chronic treatment to effectively manage symptoms and consequently reduce the burden of this disorder.

Radical antegrade modular pancreatosplenectomy (RAMPS) was introduced to improve the tangential resection margin rates and N1 node clearance following resection of malignancies of the pancreatic body and tail. Owing to its technical complexity, minimally invasive RAMPS (MI-RAMPS) has only been reported by a few centers worldwide. We performed this meta-analysis to compare both short- and long-term outcomes between open RAMPS (O-RAMPS) and minimally invasive RAMPS (MI-RAMPS). A systematic search of the electronic databases PubMed, Medline (via PubMed), Cochrane Register of Controlled Trials (CENTRAL), EMBASE, Scopus and Web of Science was performed to identify eligible studies published in the English language regardless of study design. The outcomes of interest were operation time, estimated blood loss, transfusion rates, overall complications, Grade B/C post-operative pancreatic fistula (POPF) rates, post-pancreatectomy hemorrhage (PPH), delayed gastric emptying (DGE), length of stay (LOS), R0 resection rates, lymph node (LN) yield and overall survival (OS). Five non-randomized studies comprising of a total 229 patients (89 MI-RAMPS, 140 O-RAMPS) were included for analysis. Intra-operative blood loss was observed to be significantly reduced in MI-RAMPS as compared to O-RAMPS (MD –256.16, P

Etavopivat (FT-4202) is an orally administered, small-molecule allosteric activator of erythrocyte pyruvate kinase-R (PKR) in clinical development for the treatment of sickle cell disease and other hemoglobin disorders. This randomized, placebo-controlled, double-blind, first-in-human combination single-ascending dose and multiple-ascending dose phase 1 trial (NCT03815695) evaluated the safety and pharmacokinetics/pharmacodynamics of etavopivat in 90 healthy adult subjects. In 4 single-ascending dose cohorts, 8 participants were randomized 3:1 to a single oral dose of either etavopivat (n = 6) or placebo (n = 2). In four 14-day multiple-ascending dose cohorts, 12 participants were randomized 3:1 to 14 days of etavopivat (n = 9) or placebo (n = 3). In these studies, most treatment-emergent adverse events were of mild severity (grade 1) and none led to study discontinuation. Etavopivat exhibited a linear and time-independent pharmacokinetic profile (at doses ≤400 mg) and elicited the expected pharmacodynamic effects of PKR activation (decreased 2,3-diphosphoglycerate and increased adenosine triphosphate) and evidence of improved hemoglobin-oxygen affinity. In addition, pharmacodynamic responses were durable with effects continuing for 48 to 72 hours after the last dose, thereby supporting once-daily dosing. Food appeared to have no clinically meaningful effects on etavopivat exposure, thus facilitating administration with or without food. In conclusion, the evaluation of etavopivat in healthy subjects demonstrated proof of mechanism (PKR activation) without significant adverse events. This study also allowed for the selection of dose levels, projected to have an acceptable safety profile and provide therapeutic benefit, for evaluation in future trials in patients with sickle cell disease.

Various real-world data (RWD) sources have emerged in China with the intention of generating real-world evidence (RWE) that can be used in clinical and regulatory decision-making. Despite these efforts, significant barriers remain that hinder high-quality healthcare research. A workshop with 30 representatives from healthcare research agencies, technology companies focused on healthcare big data and pharmaceutical companies was held in December 2020 to identify strategies to overcome the barriers associated with the usability and quality of RWD in China. Across all sectors, examples of barriers identified included inconsistencies in terminology and non-standardised coding practices; the absence of longitudinal data; the absence of transparent data processing and validation practices; and the inability to access and share RWD. While cutting-edge technological innovations and data solutions provided powerful tools, the development of collaborative and synergistic research networks across multiple stakeholders is key to generate accessible, high-quality RWD in China. RWD has the potential to provide clinical, regulatory and reimbursement decision-makers with critical insights that can improve healthcare delivery in China. However, barriers to its access, collection and use must be addressed to generate RWE to guide healthcare stakeholders.

A comprehensive overview of medical AI devices approved by the US Food and Drug Administration sheds new light on limitations of the evaluation process that can mask vulnerabilities of devices when they are deployed on patients.

To examine the extent to which there is a basic economic case for the provision of rehabilitation services within a publicly funded, device-centred approach to adult hearing services.Five representative cross-sectional surveys of people aged 50 years and over were conducted in Australia between 2013 and 2019 (Among respondents 27% reported that their hearing was fair or poor, and 14% reported hearing aid ownership. 45% of hearing aid owners were regular device users. Approximately 1:4 people (24%) who owned a hearing aid had not used it in the past three months; with an estimated cost of $au87.4 million per annum. The provision of hearing rehabilitation services in addition to or instead of hearing aids could provide clients with a more comprehensive service at an estimated saving of between 62% to 81% of existing program costs.Cost benefit analysis supports the provision of hearing rehabilitation within a hearing services program, either as an alternative to the existing service, or adjunct to it. Such a service would enhance client outcomes and reduce the level of wastage currently associated with the current device-centred approach.Implications for rehabilitationClients identified as not being immediately ready to progress to hearing aids could benefit from rehabilitation programs while still having access to either assistive listening devices or hearing aids.The proposed approach could result in significant cost savings to publicly funded programs while ensuring better outcomes for service users through the more effective, efficient and ethical use of public monies.

Breast cancer remains a global challenge, causing over 600,000 deaths in 2018 (ref. 1). To achieve earlier cancer detection, health organizations worldwide recommend screening mammography, which is estimated to decrease breast cancer mortality by 20–40% (refs. 2,3). Despite the clear value of screening mammography, significant false positive and false negative rates along with non-uniformities in expert reader availability leave opportunities for improving quality and access4,5. To address these limitations, there has been much recent interest in applying deep learning to mammography6–18, and these efforts have highlighted two key difficulties: obtaining large amounts of annotated training data and ensuring generalization across populations, acquisition equipment and modalities. Here we present an annotation-efficient deep learning approach that (1) achieves state-of-the-art performance in mammogram classification, (2) successfully extends to digital breast tomosynthesis (DBT; ‘3D mammography’), (3) detects cancers in clinically negative prior mammograms of patients with cancer, (4) generalizes well to a population with low screening rates and (5) outperforms five out of five full-time breast-imaging specialists with an average increase in sensitivity of 14%. By creating new ‘maximum suspicion projection’ (MSP) images from DBT data, our progressively trained, multiple-instance learning approach effectively trains on DBT exams using only breast-level labels while maintaining localization-based interpretability. Altogether, our results demonstrate promise towards software that can improve the accuracy of and access to screening mammography worldwide. A generalizable and interpretable artificial-intelligence system achieves clinical accuracy for screening and early breast-cancer detection on 2D and 3D mammograms.

Background An estimated 6500 undocumented immigrants with end-stage renal disease (ESRD) live in the United States. Those living in states that do not provide undocumented immigrants scheduled hemodialysis receive intermittent hemodialysis only when life-threatening conditions arise. Little is known about catheter-related bloodstream infections (CRBSIs) in this population. Methods We conducted a retrospective cohort study of emergency-only hemodialysis patients in the Harris Health System in Houston, Texas, between January 2012 and December 2015. We assessed CRBSI risk factors including demographics, comorbidities, and duration and frequency of hemodialysis. We investigated the microbiologic etiology of these infections, rates of recurrent CRBSI, and associated morbidity and mortality. Results The cohort included 329 patients; 90% were Hispanic, 60% had diabetes, and the average age was 51 years. A total of 101 CRBSIs occurred, with a rate of 0.84 infections per 1000 catheter-days. Cirrhosis and duration of hemodialysis during the study period were associated with increased risk of CRBSI. Seventeen CRBSIs were recurrent; infection with gram-positive bacteria predicted recurrence. Adherence to catheter-related infection guidelines was improved by infectious diseases consultation and associated with fewer recurrent infections. CRBSI was associated with prolonged hospitalization (mean, 15 days), composite complication rate of 8%, and a 4% mortality rate. Conclusions Patients receiving emergency-only hemodialysis via tunneled catheters have a high CRBSI rate compared with infection rates previously reported in patients receiving scheduled maintenance hemodialysis. Increased CRSBI risk likely contributes to the increased morbidity and mortality seen in ESRD patients receiving emergency-only hemodialysis.

We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre- and posttreatment computed tomography scans of 123 patients (cancers, 129, pre- and posttreatment cancer pairs, 158) undergoing chemotherapy were collected. After chemotherapy 33% of patients had T0 stage cancer (complete response). Regions of interest in pre- and posttreatment scans were extracted from the segmented lesions and combined into hybrid pre -post image pairs (h-ROIs). Training (pairs, 94, h-ROIs, 6209), validation (10 pairs) and test sets (54 pairs) were obtained. The DL-CNN consisted of 2 convolution (C1-C2), 2 locally connected (L3-L4), and 1 fully connected layers. The DL-CNN was trained with h-ROIs to classify cancers as fully responding (stage T0) or not fully responding to chemotherapy. Two radiologists provided lesion likelihood of being stage T0 posttreatment. The test area under the ROC curve (AUC) was 0.73 for T0 prediction by the base DL-CNN structure with randomly initialized weights. The base DL-CNN structure with pretrained weights and transfer learning (no frozen layers) achieved test AUC of 0.79. The test AUCs for 3 modified DL-CNN structures (different C1-C2 max pooling filter sizes, strides, and padding, with transfer learning) were 0.72, 0.86, and 0.69. For the base DL-CNN with (C1) frozen, (C1-C2) frozen, and (C1-C2-L3) frozen, the test AUCs were 0.81, 0.78, and 0.71, respectively. The radiologists' AUCs were 0.76 and 0.77. DL-CNN performed better with pretrained than randomly initialized weights.

Drug monitoring plays crucial roles in doping control and precision medicine. It helps physicians tailor drug dosage for optimal benefits, track patients' compliance to prescriptions, and understand the complex pharmacokinetics of drugs. Conventional drug tests rely on invasive blood draws. While urine and sweat are attractive alternative biofluids, the state-of-the-art methods require separate sample collection and processing steps and fail to provide real-time information. Here, a wearable platform equipped with an electrochemical differential pulse voltammetry sensing module for drug monitoring is presented. A methylxanthine drug, caffeine, is selected to demonstrate the platform's functionalities. Sweat caffeine levels are monitored under various conditions, such as drug doses and measurement time after drug intake. Elevated sweat caffeine levels upon increasing dosage and confirmable caffeine physiological trends are observed. This work leverages a wearable sweat sensing platform toward noninvasive and continuous point-of-care drug monitoring and management.

PURPOSE: Childhood cancer survivors are at risk for deficits in health-related quality of life (HRQL) as they age. Youth (8–12 years) and adolescent (13–20 years) versions of the Minneapolis-Manchester Quality of Life Instrument (MMQL) have been developed to address survivor-specific issues and are currently in use; the MMQL-Adult Form has now been developed to assess HRQL in childhood cancer survivors aged 21 to 55 years. METHODS: The MMQL-Adult Form was administered to 499 adults: 65 cancer patients on-therapy, 107 off-therapy, and 327 healthy controls. Forty-four percent of patients were under 30 years old at cancer diagnosis. Principal components analysis was performed. We evaluated internal consistency reliability, stability (re-administration of the MMQL-Adult Form 2 weeks later), construct validity (concurrent administration of the SF-36), and known-groups validity (score comparisons across the three groups). RESULTS: Principal components analysis resulted in retention of 44 items across six scales: social functioning, physical functioning, cognitive functioning, outlook on life, body image, and psychological functioning. Internal consistency (Cronbach’s α) was 0.80–0.90 for individual scales and 0.95 overall. Strong intraclass correlations (0.98 overall) indicated high stability. The MMQL-Adult Form distinguished between known groups; healthy controls scored better than patients on four of six scales. The MMQL-Adult Form scales correlated highly with similar SF-36 scales, demonstrating construct validity. CONCLUSIONS: The MMQL-Adult Form is a reliable and valid self-report instrument for measuring multidimensional HRQL in cancer survivors. Development of this instrument ensures availability of a tool enabling cross-sectional and longitudinal assessment of HRQL in childhood cancer survivors as they age.

Perspiration-based wearable biosensors facilitate continuous monitoring of individuals' health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 µL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, without electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. Our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications.

Recent and rapid human population growth has led to an excess of rare genetic variants that are expected to contribute to an individual’s genetic burden of disease risk. To date, much of the focus has been on rare protein-coding variants, for which potential impact can be estimated from the genetic code, but determining the impact of rare noncoding variants has been more challenging. To improve our understanding of such variants, we combined high-quality genome sequencing and RNA sequencing data from a 17-individual, three-generation family to contrast expression quantitative trait loci (eQTLs) and splicing quantitative trait loci (sQTLs) within this family to eQTLs and sQTLs within a population sample. Using this design, we found that eQTLs and sQTLs with large effects in the family were enriched with rare regulatory and splicing variants (minor allele frequency < 0.01). They were also more likely to influence essential genes and genes involved in complex disease. In addition, we tested the capacity of diverse noncoding annotation to predict the impact of rare noncoding variants. We found that distance to the transcription start site, evolutionary constraint, and epigenetic annotation were considerably more informative for predicting the impact of rare variants than for predicting the impact of common variants. These results highlight that rare noncoding variants are important contributors to individual gene-expression profiles and further demonstrate a significant capability for genomic annotation to predict the impact of rare noncoding variants.

Laser scanning cytometry (LSC) is emerging as a clinical tool. In one application a "Clatch" slide, named after the inventor, is used in conjunction with LSC for cell surface marker immunophenotyping of patient samples. The slide requires time consuming and laborious pipetting steps, making a test tedious and prone to handling errors. The Clatch slide also uses a significant number of cells, limiting the number of analyses on paucicellular samples. This paper presents an automated microfluidic system consisting of a control circuit, a microfluidic system, and an aluminum frame, capable of performing immunophenotyping procedures. This prototype system reduces 36 pipetting steps to 1, reduces the amount of cell sample from 180 μL to 56 μL, and shortens the time used by technicians.

Background Improved survival after childhood cancer has shifted the focus to health-related quality of life (HRQL)—an understudied problem, especially among adolescents. Procedure We assessed HRQL among adolescents utilizing a validated self-report tool, the Minneapolis-Manchester Quality of Life (MMQL) Adolescent Form, consisting of 46 items comprising seven domains: physical, cognitive, psychological and social functioning, body image, intimate relations, and outlook on life, and computed an overall QoL score. The MMQL Adolescent Form was administered to 226 adolescent survivors of childhood cancer a median of 7.8 years from diagnosis (off therapy—median age: 16.2 years), 136 adolescent cancer patients undergoing therapy (on therapy—median age: 16.4 years), and 134 healthy adolescents (controls—median age: 15.5 years). Primary diagnoses included leukemia (46%), lymphoma (26%), brain tumors (5%), and other solid tumors (23%). Results Compared to healthy controls, on-therapy patients were at increased risk for reporting poor overall QoL [Odds Ratio (OR) = 3.3, P = 0.002)] and poor physical functioning (OR = 11.8, P

Objective. To assess the health-related quality of life (HRQL) of 8- to 12-year-old children undergoing therapy for cancer or childhood-cancer survivors by using the Minneapolis-Manchester Quality of Life-Youth Form (MMQL-YF), a comprehensive, multidimensional self-report instrument with demonstrable reliability and validity.Design, Setting, and Patients. The MMQL-YF consists of 32 items comprising 4 scales: physical functioning, psychologic functioning, physical symptoms, and outlook on life. Scoring on the MMQL ranges from 1 to 5; 5 indicates maximal HRQL. An overall quality-of-life (QOL) score is also computed. By using a cross-sectional study design, the MMQL-YF was administered to 90 off-therapy cancer survivors, 72 children with cancer undergoing active therapy, and 481 healthy children without a history of cancer or other chronic disease.Results. Compared with healthy controls, children actively undergoing cancer treatment report low overall QOL, physical functioning, and outlook-on-life scores. However, off-therapy survivors report a superior overall QOL, compared with age-matched healthy controls.Conclusions. Young survivors of childhood cancer report a favorable HRQL relative to healthy controls. These results are reassuring, suggesting that this group of survivors may have been too young to encounter some of the negative psychosocial impacts of cancer and its treatment.

Aortic insufficiency (AI) is usually repaired prior to rotary blood pump (RBP) implantation but can develop during support due, in part, to the sustained RBP-induced high pressure gradient across the aortic valve. Repair of the aortic valve before or during RBP support predisposes these critically ill patients to even higher risks. This study used an in vitro mock circulation loop to identify the severity of AI and/or left heart failure (LHF) that might benefit from valve repair while investigating RBP operating strategies to reduce the hemodynamic influence of AI. Reproduction of AI with RBP-supported LHF reduced device efficiency, particularly in the more severe cases of AI and LHF. The requirement for repair or closure of the aortic valve was demonstrated in all conditions other than those with only mild AI. When a sinusoidal RBP speed pulse was induced, small changes in systemic flow rate and regurgitant volume were observed with all degrees of AI. Variation of the pulse phase delay only resulted in minor changes to systemic flow rate, with a maximum difference of 0.17 L/min. Although the clinical implications of these small changes may be insignificant, changes in systemic flow rate and transvalvular pressure were shown when the sinusoidal RBP speed pulse was applied with no AI. In these cases, transvalvular pressure was reduced by up to 8% through sinusoidal copulsation of the RBP, which may prevent or delay the onset of AI. This in vitro study suggests that surgical intervention is required with moderate or worse AI and that RBP operating strategies should be further explored to delay the onset and reduce the harmful effects of AI.

Keeping a delicate balance in the immune system by eliminating invading pathogens, while still maintaining self-tolerance to avoid autoimmunity, is critical for the body’s health. The gut microbiota that resides in the gastrointestinal tract provides essential health benefits to its host, particularly by regulating immune homeostasis. Moreover, it has recently become obvious that alterations of these gut microbial communities can cause immune dysregulation, leading to autoimmune disorders. Here we review the advances in our understanding of how the gut microbiota regulates innate and adaptive immune homeostasis, which in turn can affect the development of not only intestinal but also systemic autoimmune diseases. Exploring the interaction of gut microbes and the host immune system will not only allow us to understand the pathogenesis of autoimmune diseases but will also provide us new foundations for the design of novel immuno- or microbe-based therapies.

To establish a new imaging protocol to acquire the most appropriate fluoro-images for fluoro-navigated percutaneous fixation of acetabular fracture and to evaluate the safety and efficiency of the procedures.Guide needles were inserted into the bilateral anterior and posterior columns of the acetabula of 4 dry human cadaver pelvic skeletons and 4 plastic pelvic models. Then the pelvis skeletons were fixed to imaging guided surgery mimic operation modules. Dynamic fluoroscopy was conducted with C-arm X-ray machine vertically on the 4 virtual planes of the acetabulum, inner, outer, anterior, and posterior from multiple angles. The fluoroscopic images clearly showing the guide needles, anterior and posterior columns, and acetabulum were selected as registration images, and the relative space positions between the C-arm X-ray fluoroscope and pelvis and operation table. Guided by the navigation system, totally 16 titanium hollow screws were inserted into bilateral anterior and posterior columns of acetabula of the 4 pelvis skeletons. The screw positions were estimated by visual method. The time needed to position the C-arm so as to obtain the standard registration image, time needed for fluoroscopy, and operation time, including establishment of navigation system, software interface operation, and screw insertion, were recorded.All the screws were inserted to the satisfying positions: placed within the desired bony corridor of the column and none of then were inserted into the joint. While inserting the screw into the anterior column fluoroscopy should be conducted with obturated oblique view, obturated inlet view, obturated oblique outlet view, or pelvic AP view. While inserting the screw into the posterior column fluoroscopy should be conducted with iliac-oblique view, obturated oblique view, pelvic inlet view, or obturated oblique outlet view. The total surgical time required for screw insertion was 11.7 min for anterior column, and was 9.2 min for posterior column. 9.5 and 7.3 minutes were needed to position the C-arm X-ray machine so as to obtain the images of the anterior and posterior columns respectively. 2.9 and 1.7 seconds were needed for the actual fluoroscopy during insertion of the screws into the anterior and posterior columns respectively.The standard registered fluoro-images are different from the conventional standard Judet-Letournel oblique views. How to get appropriate fluoro-images is the key point for fluoro-navigated percutaneous fixation of acetabular fractures.

BACKGROUND Previous anesthesia information management systems-based studies have focused on intraoperative data analysis. Reviewing preoperative data could provide insight into the outpatient treatment of patients presenting for surgical procedures. As gender-based disparities have been demonstrated in the treatment of patients with cardiac disease, we hypothesized that there would be gender disparities in the outpatient pharmacologic management of patients with coronary artery disease (CAD) scheduled for elective noncardiac surgery. METHODS We analyzed electronic medical records of ambulatory patients with CAD (prior myocardial infarction [MI], coronary artery bypass surgery, and angioplasty with or without stenting, angina) presenting for elective noncardiac surgery between 1/2004 and 6/2006 (30 mo) at an inner city hospital. RESULTS Of 21,039 ambulatory patients seen in the preanesthesia clinic, 6.4% (1346) had CAD. Patients with CAD: Men were more likely to be taking beta-blockers (P < 0.002), statins (P < 0.0001), aspirin (P < 0.0001), and antiplatelet medications (P < 0.04), although there was a trend of increased use of aspirin (P < 0.01) by women over the course of the study. Patients with history of prior MI: Men with a prior MI were more likely to be taking beta-blockers (P < 0.0001) and statins (P < 0.02), although there was a trend of increased use of beta-blockers (P < 0.0005) and aspirin (P < 0.03) by women over the course of the study. Quarterly prevalence rates for outpatient medication use were greatest for beta-blockers and least for aspirin. Patients were more likely to be taking a statin, aspirin, or oral antiplatelet medication if they were receiving chronic beta-blocker therapy (P < 0.0001 for each medication). CONCLUSION Aggregating anesthesia management information systems data provides an epidemiological perspective of community care of patients presenting for surgery. We found that gender disparities in outpatient medical treatment of patients with CAD, which previously favored men, have diminished primarily as a result of increased use of these medications in women. Nonetheless, despite evidence supporting the use of risk-reduction strategies, our patients are undertreated with standard medical therapies.

Objective Improvements in survival after childhood cancer have increased emphasis on health-related quality of life (HRQoL) of survivors. We developed the Minneapolis-Manchester Quality of Life-Youth Form (MMQL-YF) as a standardized patient self-report instrument designed to assess HRQoL in childhood cancer survivors between the ages of 8 and 12 years. Study design To validate the instrument, the MMQL-YF was administered to 643 children (481 healthy, 162 with cancer). Factor analysis was conducted to refine the instrument, and Cronbach's α coefficient was used to measure its internal reliability. Known-groups validity was determined by comparing healthy children with those with cancer. Construct validity was studied by a comparison of similar domains in the MMQL-YF and the Child Health Questionnaire (CHQ). Stability was tested by re-administration of the MMQL-YF 2 weeks later. Results Internal consistency reliability was in the acceptable range for this instrument. The MMQL-YF was able to distinguish between known groups, and its scales correlated highly with similar CHQ domains. Test-retest reliability showed that the instrument was extremely stable in all scales tested. Conclusion Data provide evidence for the validity and reliability of the MMQL-YF as a comprehensive, multidimensional, self-report instrument for measuring HRQoL among childhood cancer survivors.