A classification model (Stress Classification-Net) of emotional stress and physical stress is proposed, which can extract classification features based on multispectral and tissue blood oxygen ...saturation (StO
) characteristics. Related features are extracted on this basis, and the learning model with frequency domain and signal amplification is proposed for the first time. Given that multispectral imaging signals are time series data, time series StO
is extracted from spectral signals. The proper region of interest (ROI) is obtained by a composite criterion, and the ROI source is determined by the universality and robustness of the signal. The frequency-domain signals of ROI are further obtained by wavelet transform. To fully utilize the frequency-domain characteristics, the multi-neighbor vector of locally aggregated descriptors (MN-VLAD) model is proposed to extract useful features. The acquired time series features are finally put into the long short-term memory (LSTM) model to learn the classification characteristics. Through SC-NET model, the classification signals of emotional stress and physical stress are successfully obtained. Experiments show that the classification result is encouraging, and the accuracy of the proposed algorithm is over 90%.
Payers and providers still primarily use ordinary least squares (OLS) to estimate expected economic and clinical outcomes for risk adjustment purposes. Penalized linear regression represents a ...practical and incremental step forward that provides transparency and interpretability within the familiar regression framework. This study conducted an in-depth comparison of prediction performance of standard and penalized linear regression in predicting future health care costs in older adults.
This retrospective cohort study included 81,106 Medicare Advantage patients with 5 years of continuous medical and pharmacy insurance from 2009 to 2013. Total health care costs in 2013 were predicted with comorbidity indicators from 2009 to 2012. Using 2012 predictors only, OLS performed poorly (e.g., R2 = 16.3%) compared to penalized linear regression models (R2 ranging from 16.8 to 16.9%); using 2009-2012 predictors, the gap in prediction performance increased (R2:15.0% versus 18.0-18.2%). OLS with a reduced set of predictors selected by lasso showed improved performance (R2 = 16.6% with 2012 predictors, 17.4% with 2009-2012 predictors) relative to OLS without variable selection but still lagged behind the prediction performance of penalized regression. Lasso regression consistently generated prediction ratios closer to 1 across different levels of predicted risk compared to other models.
This study demonstrated the advantages of using transparent and easy-to-interpret penalized linear regression for predicting future health care costs in older adults relative to standard linear regression. Penalized regression showed better performance than OLS in predicting health care costs. Applying penalized regression to longitudinal data increased prediction accuracy. Lasso regression in particular showed superior prediction ratios across low and high levels of predicted risk. Health care insurers, providers and policy makers may benefit from adopting penalized regression such as lasso regression for cost prediction to improve risk adjustment and population health management and thus better address the underlying needs and risk of the populations they serve.
Coronavirus disease 2019 (COVID-19) has spread rapidly in China and other overseas areas, which has aroused widespread concern. The sharp increase in the number of patients has led to great ...psychological pressure on health care workers. The purpose of this study was to understand their mental health status and needs, so as to provide a scientific basis for alleviating the psychological pressure of health care workers.
Using a cross-sectional study design, 540 health care workers were randomly selected from two designated tuberculosis medical institutions in Anhui Province. The basic situation, perceived social support, depression level, loneliness and COVID-19 related knowledge were collected and analyzed by questionnaire.
A total of 511 valid questionnaires were finally retrieved. There were 139 people in epidemic prevention and control positions (27.20%). Depression level: People in isolation ward, fever clinic and pre-check triage were at the level of mild to moderate depression. Female was higher than male; nurse was higher than doctor; middle and junior job titles were higher than senior titles; junior college degree or below were higher than bachelor's degree, master's degree and above; isolation ward, fever clinic and pre-check triage were significantly higher than those of non-prevention and control positions (p < 0.05). Loneliness scores: Doctors were higher than that of medical technicians, and isolation ward, fever clinic and pre-check triage were higher than those of other medical departments (p < 0.05). Social support: Doctors were lower than that of medical technicians, and isolation ward, fever clinic and pre-check triage were significantly lower than those of other departments (p < 0.05). The score of social support was negatively correlated with depression and loneliness (p < 0.001), while depression was positively correlated with loneliness (p < 0.001). Health care workers most want to receive one-to-one psychological counseling (29.75%), and provide crisis management (24.07%). The awareness rate of health care workers on COVID-19's knowledge was relatively high.
The psychological problems of health care workers, especially women, nurses with low educational background, low professional title, and staff in the epidemic prevention and control positions are relatively serious.
An emotion recognition method based on multispectral imaging technology and tissue oxygen saturation (StO2) is proposed in this study. This method is called spatial-spectral-temporal adjustment ...convolutional neural network (SACNN). First, we use the algorithm to extract the StO2 content of an emotionally sensitive nose area through real-time multispectral imaging technology. Compared with facial expression data, StO2 data are more objective and cannot be controlled and changed artificially. Second, we construct a clustering algorithm based on the emotional state by extracting the spectral, StO2, and spatial features of the nose image to obtain accurate signals of emotionally sensitive areas. To utilize the correlation between spectral and spatial signals, we propose an adjustment-based CNN module, which reorganizes the relationship between all previous layers of the feature map, thereby making the relationship among layers close and highly quantitative. The features extracted through this method are consistent with spatial-spectral features. Third, we incorporate the extracted temporal feature signal into the long short-term memory module and finally complete the correlation between the spatial-spectral-temporal features. Experimental results show that the accuracy of the SACNN algorithm in emotional recognition reaches 90%, and the proposed method is more competitive than state-of-the-art approaches. To the best of our knowledge, this study is the first to use time-series StO2 signals for emotion recognition.
•The emotional state of a person can be obtained by extracting individual stress index, which provides useful information to health field.•This paper directs the frontier of industrializing stress ...recognition by focusing on establishing a set of non-contact imaging based classifications for emotional stress (ES) and Physical stress (PS).•The proposed algorithm successfully extracts weak signal from thermal imaging for stress classification.•The classification algorithm is effective with accuracy as high as 90%. This study can lead to a practical system for the noninvasive assessment of stress states for practical applications.
In affective computing, stress recognition mainly focuses on the relation of stress and photoelectric information. Researchers have used artificial intelligence to determine stress and computer identification channels. However, in applications such as health and security, Emotional stress (ES) information is usually to be alongside physical stress (PS) information, making it urgent to classify ES and PS. The thermal signals of ES and PS have yet to be classified, for which, signal amplification is offered. In this study, we propose a classification algorithm based on signal amplification and correlation analysis called Eulerian magnification-canonical correlation analysis. This signal amplification algorithm expands the signals of ES and PS in different frequency domains. Sparse coding and canonical correlation analysis then fuse the original signal and its amplified features. The extracted entropy features are used to train the correlation weight between ES and PS, which formulates stress classifications. The new classification method achieves an accuracy rate of 90%. This study can lead to a practical system for the noninvasive assessment of stress states for health or security applications.
BACKGROUND:Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates—extracted by comparing electronic health record prescriptions and pharmacy claims ...fills—represent a novel measure of medication adherence and may improve the performance of risk adjustment models.
OBJECTIVE:We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization.
METHODS:We conducted a retrospective cohort study of 43,097 primary care patients from HealthPartners network between 2011 and 2012. Diagnosis and/or pharmacy claims of 2011 were used to build 3 base models using the Johns Hopkins ACG system, in addition to demographics. Model performances were compared before and after adding 3 types of prescription fill ratesprimary 0–7 days, primary 0–30 days, and overall. Overall fill rates utilized all ordered prescriptions from electronic health record while primary fill rates excluded refill orders.
RESULTS:The overall, primary 0–7, and 0–30 days fill rates were 72.30%, 59.82%, and 67.33%. The fill rates were similar between sexes but varied across different medication classifications, whereas the youngest had the highest rate. Adding fill rates modestly improved the performance of all models in explaining medical costs (improving concurrent R by 1.15% to 2.07%), followed by total costs (0.58% to 1.43%), and pharmacy costs (0.07% to 0.65%). The impact was greater for concurrent costs compared with prospective costs. Base models without diagnosis information showed the highest improvement using prescription fill rates.
CONCLUSIONS:Prescription fill rates can modestly enhance claims-based risk prediction models; however, population-level improvements in predicting utilization are limited.
Abstract Objective The objective of this systematic literature review was to evaluate the incidences and risks for adverse events (AEs) associated with oral and parenteral corticosteroids. An ...assessment was performed to estimate the costs of such AEs. Methods A systematic review of literature published from 2007 to 2009 was conducted to identify the incidence rates and risk ratios of corticosteroid-related AEs. The review protocol was developed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The literature search was expanded to include additional search terms for psychiatric conditions, infections, and peptic ulcers. Costs obtained from a separate narrative literature review were applied to AEs likely to affect third-party payers in the United States. Results A total of 357 publications were identified from the primary (n = 323) and secondary (n = 34) searches. Of these, 310 were excluded because they did not evaluate AEs related to corticosteroids, were an excluded publication type, or for other reasons. A final list of 47 studies were used for data extraction. Across patient populations, the most frequently reported corticosteroid-associated AEs were psychiatric events, infections, gastric conditions, and fractures. Corticosteroid-associated AEs reported to occur at an incidence >30% were sleep disturbances, lipodystrophy, adrenal suppression, metabolic syndrome, weight gain, and hypertension. Vertebral fractures were reported at an incidence of 21% to 30%. Dose-response relationships were documented for fractures, acute myocardial infarction, hypertension, and peptic ulcer. The costs of managing AEs that may occur with corticosteroids can be substantial. The literature reported 1-year per-patient costs of up to $26,471.80 for nonfatal myocardial infarction, and per-event costs as high as $18,357.90 for fracture. The findings from the present review should be interpreted cautiously due to several limitations, including the retrospective design of most of the studies identified, risk for confounding due to underlying disease activity or patient population, and the relatively small number of studies that reported each AE association. As this cost analysis was preliminary, a comprehensive pharmacoeconomic analysis should be undertaken to confirm the findings. Conclusion Based on the findings from this review, systemic corticosteroids are a common cause of AEs that may be costly to payers.
A bstract Exposure to high levels of glucose induces the production of reactive oxygen species (ROS) in cardiomyocytes that may contribute to the development of cardiomyopathy in diabetes. Nuclear ...factor erythroid 2-related factor 2 (Nrf2) controls the antioxidant response element (ARE)-dependent gene regulation in response to oxidative stress. The role of Nrf2 in defense against high glucose-induced oxidative damage in cardiomyocytes was investigated. Glucose at high concentrations induced ROS production in both primary neonatal and adult cardiomyocytes from the Nrf2 wild type (WT) mouse heart, whereas, in Nrf2 knockout (KO) cells, ROS was significantly higher under basal conditions and high glucose markedly further increased ROS production in concentration and time-dependent manners. Concomitantly, high glucose induced significantly higher levels of apoptosis at lower concentrations and in shorter time in Nrf2 KO cells than in WT cells. Primary adult cardiomyocytes from control and diabetic mice also showed dependence on Nrf2 function for isoproterenol-stimulated contraction. Additionally, cardiomyocytes from Nrf2 KO mice exhibited increased sensitivity to 3-nitropropionic acid, an inhibitor of mitochondrial respiratory complex II, for both ROS production and apoptosis compared with Nrf2 WT cells, further emphasizing the role of Nrf2 in ROS defense in the cells. Mechanistically, Nrf2 was shown to mediate the basal expression and induction of ARE-controlled cytoprotective genes, Nqo1 and Ho1 , at both mRNA and protein levels in cardiomyocytes, as both the basal and inducible expressions of the genes were lost in Nrf2 KO cells or largely reduced by Nrf2 SiRNA. The findings, for the first time, established Nrf2 as a critical regulator of defense against ROS in normal and diabetic hearts.
Our previous study demonstrated that gypenosides (Gp) exert protective effects on retinal nerve fibers and axons in a mouse model of experimental autoimmune optic neuritis. However, the therapeutic ...mechanisms remain unclear. Thus, in this study, a model of oxidative damage in retinal ganglion cells (RGCs) was established to investigate the protective effect of Gp, and its possible influence on oxidative stress in RGCs. Treatment of cells with H
2
O
2
induced RGC injury owing to the generation of intracellular reactive oxygen species (ROS). In addition, the activities of antioxidative enzymes decreased and the expression of inflammatory factors increased, resulting in an increase in cellular apoptosis. Gp helped RGCs to become resistant to oxidation damage by directly reducing the amount of ROS in cells and exerting protective effects against H
2
O
2
-induced apoptosis. Treatment with Gp also reduced the generation of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), and increased nuclear respiratory factor 2 (Nrf-2) levels so as to increase the levels of heme oxygenase-1 (HO-1) and glutathione peroxidase 1/2 (Gpx1/2), which can enhance antioxidation in RGCs. In conclusion, our data indicate that neuroprotection by Gp involves its antioxidation and anti-inflammation effects. Gp prevents apoptosis through a mitochondrial apoptotic pathway. This finding might provide novel insights into understanding the mechanism of the neuroprotective effects of gypenosides in the treatment of optic neuritis.
Abstract The evaluation of the cost and health implications of agreeing to cover a new health technology is best accomplished using a model that mathematically combines inputs from various sources, ...together with assumptions about how these fit together and what might happen in reality. This need to make assumptions, the complexity of the resulting framework, the technical knowledge required, as well as funding by interested parties have led many decision makers to distrust the results of models. To assist stakeholders reviewing a model’s report, questions pertaining to the credibility of a model were developed. Because credibility is insufficient, questions regarding relevance of the model results were also created. The questions are formulated such that they are readily answered and they are supplemented by helper questions that provide additional detail. Some responses indicate strongly that a model should not be used for decision making: these trigger a “fatal flaw” indicator. It is hoped that the use of this questionnaire, along with the three others in the series, will help disseminate what to look for in comparative effectiveness evidence, improve practices by researchers supplying these data, and ultimately facilitate their use by health care decision makers.
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