A-kinase interacting protein 1 is sufficiently expressed and positively associates with WHO grade,meanwhile predicts unfavorable overall survival independently in glioma patients

The present study aimed to investigate the association of A-kinase interacting protein 1 (AKIP1) with clinical characteristics, and further explore the prognostic value of AKIP1 in glioma patients.Totally 168 glioma patients who underwent tumor resection were analyzed, and their tumor tissue specimens were acquired for the detection of AKIP1 expression by immunohistochemistry (IHC), which was scored by a semi-quantitative method considering staining intensity and staining density.According to AKIP1 expression in tumor tissues of glioma patients, there were 65 (38.7%) patients with AKIP1 low expression (IHC score 0–3), 48 (28.6%) patients with AKIP1 high + expression (IHC score 4–6), 42 (25.0%) patients with AKIP1 high++ expression (IHC score 7–9) and 13 (7.7%) patients with AKIP1 high+++ expression (IHC score 10–12), respectively. AKIP1 expression was positively associated with World Health Organization grade. Overall survival (OS) was the lowest in the patients with AKIP1 high+++ expression, followed by those with AKIP1 high++ expression and those with AKIP1 high+ expression, and highest in those with AKIP1 low expression. Further subgroup analysis exhibited that AKIP1 expression was negatively associated with OS especially in high-grade glioma patients. In addition, AKIP1 expression was negatively associated with OS in all subgroups of patients with/without adjuvant radiotherapy, with/without adjuvant chemotherapy. Further multivariate Cox''s regression exhibited that AKIP1 high expression was an independent predictive factor for worse OS.AKIP1 presents with the potential to be a novel biomarker for tumor management and prognosis surveillance in glioma patients.     

The research for the function evaluation of facial nerve and the mechanisms of rehabilitation training

Background:Peripheral facial paralysis (PFP) is a common peripheral neural disease. Acupuncture treatment combined with PFP rehabilitation exercises is a routine method of PFP treatment. This article is to provide a new visual and objective evaluation method for exploring the mechanism and efficacy of acupuncture treatment on PFP, and develop an interactive augmented facial nerve function rehabilitation training system with multiple training models.Methods:This prospective and observational trial will recruit 200 eligible participants for the following study. In the trial, the laser speckle contrast analysis (LASCA) technology will be applied to monitor the microcirculation of facial blood flow during acupuncture, and real-time monitoring algorithms, data sampling, and digital imaging methods will be conducted by machine learning and image segmentation. Then, a database of patient facial expressions will be built, the correlation between surface blood flow perfusion volume and facial structure symmetry will be analyzed, combined with scale assessment and electrophysiological detection. In addition, we will also explore the objectivity and effectiveness of LASCA in the evaluation of facial paralysis (FP), and the changes in blood flow microcirculation before and after acupuncture treatment will be analyzed.Results:The standard image of the facial target area with facial nerve injury will be manually segmented by the convolutional neural network method. The blood flow images of the eyelid, cheek, and mandible of the patients’ affected and healthy side will be compared and evaluated. Laser speckle blood flow symmetry Pr and its changes in FP condition evolution and prognosis outcome will be measured, and relevant characteristic signals values will be extracted. Finally, COX regression analysis method is conducted to establish a higher accuracy prediction model of FP with cross-validation based on laser speckle blood flow imaging technology.Conclusions:We use modern interdisciplinary high-tech technologies to explore the mechanism of acupuncture rehabilitation training in PFP. And we will provide evidence for the feasibility of using the LASCA technique as a typing diagnosis of FP in the acupuncture rehabilitation treatment of PFP.Registration number:ChiCTR1800019463     

Association between 30-day readmission rates and health information technology capabilities in US hospitals

Health information technology (IT) is often proposed as a solution to fragmentation of care, and has been hypothesized to reduce readmission risk through better information flow. However, there are numerous distinct health IT capabilities, and it is unclear which, if any, are associated with lower readmission risk.To identify the specific health IT capabilities adopted by hospitals that are associated with hospital-level risk-standardized readmission rates (RSRRs) through path analyses using structural equation modeling.This STROBE-compliant retrospective cross-sectional study included non-federal U.S. acute care hospitals, based on their adoption of specific types of health IT capabilities self-reported in a 2013 American Hospital Association IT survey as independent variables. The outcome measure included the 2014 RSRRs reported on Hospital Compare website.A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis, and corroborated by confirmatory factor analysis. Subsequent path analysis using Structural equation modeling revealed that a one-point increase in the hospital adoption of patient engagement capability latent scores (median path coefficient ß = −0.086; 95% Confidence Interval, −0.162 to −0.008), including functionalities like direct access to the electronic health records, would generally lead to a decrease in RSRRs by 0.086%. However, computerized hospital discharge and information exchange capabilities with other inpatient and outpatient providers were not associated with readmission rates.These findings suggest that improving patient access to and use of their electronic health records may be helpful in improving hospital performance on readmission; however, computerized hospital discharge and information exchange among clinicians did not seem as beneficial – perhaps because of the quality or timeliness of information transmitted. Future research should use more recent data to study, not just adoption of health IT capabilities, but also whether their usage is associated with lower readmission risk. Understanding which capabilities impact readmission risk can help policymakers and clinical stakeholders better focus their scarce resources as they invest in health IT to improve care delivery.     

Influence of co-existing social isolation and homebound status on medical care utilization and expenditure among older adults in Japan

ObjectiveTo examine whether co-existing social isolation and homebound status influence medical care utilization and expenditure in older adults.MethodsPostal surveys on social isolation and homebound status were performed on older adults aged ≥65 years residing in a Japanese suburban city. Information on medical care utilization and expenditure was obtained from insurance claims data. These outcomes were examined over a three-year period (December 2008 to November 2011) for all participants (Analysis I, n = 1386) and during the last year of life for mortality cases (Analysis II, n = 107). A two-part model was used to analyze the influence of social isolation and homebound status on medical care utilization (first model: logistic regression model) and its related expenditure (second model: generalized linear model).ResultsAlmost 12 % of participants were both socially isolated and homebound. Analysis I showed that these participants were significantly less likely to use outpatient and home medical care than participants with neither characteristic (odds ratio: 0.536, 95 % confidence interval: 0.303−0.948). However, Analysis II showed that participants with both characteristics had significantly higher daily outpatient and home medical expenditure in the year before death than participants with neither characteristic (risk ratio: 2.155, 95 % confidence interval: 1.338−3.470).DiscussionOlder adults who are both socially isolated and homebound are less likely to regularly utilize medical care, which may eventually lead to serious health problems that require more intensive treatment. Measures are needed to encourage the appropriate use of medical care in these individuals to effectively manage any existing conditions.     

Using exposomics to assess cumulative risks and promote health

Under the exposome paradigm all nongenetic factors contributing to disease are considered to be ‘environmental’ including chemicals, drugs, infectious agents, and psychosocial stress. We can consider these collectively as environmental stressors. Exposomics is the comprehensive analysis of exposure to all environmental stressors and should yield a more thorough understanding of chronic disease development. We can operationalize exposomics by studying all the small molecules in the body and their influence on biological pathways that lead to impaired health. Here, we describe methods by which this may be achieved and discuss the application of exposomics to cumulative risk assessment in vulnerable populations. Since the goal of cumulative risk assessment is to analyze, characterize, and quantify the combined risks to health from exposures to multiple agents or stressors, it seems that exposomics is perfectly poised to advance this important area of environmental health science. We should therefore support development of tools for exposomic analysis and begin to engage impacted communities in participatory exposome research. A first step may be to apply exposomics to vulnerable populations already studied by more conventional cumulative risk approaches. We further propose that recent migrants, low socioeconomic groups with high environmental chemical exposures, and pregnant women should be high priority populations for study by exposomics. Moreover, exposomics allows us to study interactions between chronic stress and environmental chemicals that disrupt stress response pathways (i.e., ‘stressogens’). Exploring the impact of early life exposures and maternal stress may be an interesting and accessible topic for investigation by exposomics using biobanked samples. Environ. Mol. Mutagen. 56:715–723, 2015. © 2015 Wiley Periodicals, Inc.     

Improving Radiology Report Quality by Rapidly Notifying Radiologist of Report Errors

Radiology report errors occur for many reasons including the use of pre-filled report templates, wrong-word substitution, nonsensical phrases, and missing words. Reports may also contain clinical errors that are not specific to the speech recognition including wrong laterality and gender-specific discrepancies. Our goal was to create a custom algorithm to detect potential gender and laterality mismatch errors and to notify the interpreting radiologists for rapid correction. A JavaScript algorithm was devised to flag gender and laterality mismatch errors by searching the text of the report for keywords and comparing them to parameters within the study’s HL7 metadata (i.e., procedure type, patient sex). The error detection algorithm was retrospectively applied to 82,353 reports 4 months prior to its development and then prospectively to 309,304 reports 15 months after implementation. Flagged reports were reviewed individually by two radiologists for a true gender or laterality error and to determine if the errors were ultimately corrected. There was significant improvement in the number of flagged reports (pre, 198/82,353 [0.24 %]; post, 628/309,304 [0.20 %]; P = 0.04) and reports containing confirmed gender or laterality errors (pre, 116/82,353 [0.014 %]; post, 285/309,304 [0.09 %]; P < 0.0001) after implementing our error notification system. The number of flagged reports containing an error that were ultimately corrected improved dramatically after implementing the notification system (pre, 17/116 [15 %]; post, 239/285 [84 %]; P < 0.0001). We developed a successful automated tool for detecting and notifying radiologists of potential gender and laterality errors, allowing for rapid report correction and reducing the overall rate of report errors.