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BackgroundHelicobacter pylori infection is a major cause of peptic ulcers and gastric cancer. This study aimed to compare the eradication rate and essential costs of culture-based and empiric therapy strategies in treating pediatric H. pylori infection.MethodsWe retrospectively enrolled patients aged

BackgroundMachine learning (ML) achieves better predictions of postoperative mortality than previous prediction tools. Free-text descriptions of the preoperative diagnosis and the planned procedure are available preoperatively. Because reading these descriptions helps anesthesiologists evaluate the risk of the surgery, we hypothesized that deep learning (DL) models with unstructured text could improve postoperative mortality prediction. However, it is challenging to extract meaningful concept embeddings from this unstructured clinical text. ObjectiveThis study aims to develop a fusion DL model containing structured and unstructured features to predict the in-hospital 30-day postoperative mortality before surgery. ML models for predicting postoperative mortality using preoperative data with or without free clinical text were assessed. MethodsWe retrospectively collected preoperative anesthesia assessments, surgical information, and discharge summaries of patients undergoing general and neuraxial anesthesia from electronic health records (EHRs) from 2016 to 2020. We first compared the deep neural network (DNN) with other models using the same input features to demonstrate effectiveness. Then, we combined the DNN model with bidirectional encoder representations from transformers (BERT) to extract information from clinical texts. The effects of adding text information on the model performance were compared using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). Statistical significance was evaluated using P

BackgroundMental illness diagnostic criteria are made based on assumptions. This pilot study aims to assess the public’s perspectives on mental illness diagnoses and these assumptions.MethodsAn anonymous survey with 30 questions was made available online in 2021. Participants were recruited via social media, and no personal information was collected. Ten questions focused on participants’ perceptions regarding mental illness diagnoses, and 20 questions related to the assumptions of mental illness diagnoses. The participants’ perspectives on these assumptions held by professionals were assessed.ResultsAmong 14 survey participants, 4 correctly answered the relationships of 6 symptom pairs (28.57%). Two participants could not correctly conduct the calculations involved in mood disorder diagnoses (14.29%). Eleven (78.57%) correctly indicated that 2 or more sets of criteria were available for single diagnoses of mental illnesses. Only 1 (7.14%) correctly answered that the associations between symptoms and diagnoses were supported by including symptoms in the diagnostic criteria of the diagnoses. Nine (64.29%) correctly answered that the diagnosis variances were not fully explained by their symptoms. The confidence of participants in the major depressive disorder diagnosis and the willingness to take medications for this diagnosis were the same (mean = 5.50, standard deviation [SD] = 2.31). However, the confidence of participants in the symptom-based diagnosis of non-solid brain tumor was significantly lower (mean = 1.62, SD = 2.33, p < 0.001).ConclusionOur study found that mental illness diagnoses are wrong from the perspectives of the public because our participants did not agree with all the assumptions professionals make about mental illness diagnoses. Only a minority of our participants obtained correct answers to the calculations involved in mental illness diagnoses. In the literature, neither patients nor the public have been engaged in formulating the diagnostic criteria of mental illnesses.

Multiple versions of the Chinese Remote Associates Test (CRAT) have been developed. Thus far, all CRATs have employed verbal stimuli; other forms of stimuli have not yet been used. In this context, the present study compiled a Chinese Visual Remote Associates Test (CVRAT) that conforms to the Chinese language and culture based on a picture naming database. The developed CVRAT has two versions, CVRAT-A and CVRAT-B, each comprising 20 test questions. A typical CVRAT question consists of three stimuli pictures, requiring respondents to propose a target word that is semantically associated with all the pictures. When compiling the CVRAT, this study first selected target words, sifted through stimuli words and corresponding pictures, and analyzed pilot test questions. After compilation, their reliability and validity were examined. The results showed that the CVRAT had moderate internal consistency reliability, good criterion-related validity for the Chinese Word Remote Associates Test (CWRAT), Chinese Radical Remote Associates Test (CRRAT), Chinese Compound Remote Associates Test (CCRAT), insight problem-solving, as well as acceptable discriminant validity for fluency, flexibility, and originality of a divergent thinking test. In other words, CVRAT can effectively measure remote associative capability and provides a figural creativity test that facilitates the understanding of different kinds of remote associations.

Service industries contribute significantly to the economic, social, and even life aspect of the world. However, service innovation has been rarely discussed in healthcare context, especially in the digital healthcare context Service innovation needs to be organized in the premise of mutual trust to be efficient, thereby improving service performance. The trust and efficiency here demands a good online platform service to both virtualize the interaction processes and maintain trust and agency. This research uses social network theory and agency theory to emphasize the importance of trust in cooperation in hospitals, and the relationship between organizational trust and organizational performance. Furthermore, we analyzed the role of agents in enhancing the relationship between service innovation and trust. Based on the analyses, five propositions and future research directions are proposed.

Developmental signalling pathways such as Wnt/β-catenin, Notch and Sonic hedgehog play a central role in nearly all the stages of neuronal development. The term ‘embryonic’ might appear to be a misnomer to several people because these pathways are functional during the early stages of embryonic development and adulthood, albeit to a certain degree. Therefore, any aberration in these pathways or their associated components may contribute towards a detrimental outcome in the form of neurological disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis and stroke. In the last decade, researchers have extensively studied these pathways to decipher disease-related interactions, which can be used as therapeutic targets to improve outcomes in patients with neurological abnormalities. However, a lot remains to be understood in this domain. Nevertheless, there is strong evidence supporting the fact that embryonic signalling is indeed a crucial mechanism as is manifested by its role in driving memory loss, motor impairments and many other processes after brain trauma. In this review, we explore the key roles of three embryonic pathways in modulating a range of homeostatic processes such as maintaining blood–brain barrier integrity, mitochondrial dynamics and neuroinflammation. In addition, we extensively investigated the effect of these pathways in driving the pathophysiology of a range of disorders such as Alzheimer's, Parkinson's and diabetic neuropathy. The concluding section of the review is dedicated to neurotherapeutics, wherein we identify and list a range of biological molecules and compounds that have shown enormous potential in improving prognosis in patients with these disorders.

PurposeTo conduct stratified analysis of the association between periodontitis exposure and the risk of female breast cancer based on age, comorbidities and level of urbanization.MethodsUsing claims data taken from the 1997-2013 Taiwanese National Health Insurance Research Database (NHIRD), we identified 60,756 newly-diagnosed female breast cancer patients during the period 2003-2013 from all beneficiaries. We then randomly selected 243,024 women without breast cancer matching (1:4) for age and the year of the index date during 1997-2013 from a one million representative population acting as the control group. A conditional logistic regression analysis was used to examine the association between periodontitis (ICD-9-CM codes 523.3-4) and the risk of breast cancer, shown as an odds ratio (OR) with a 95% confidence interval (CI) after adjustments for the Charlson Comorbidity Index (CCI) and level of urbanization. Subgroup analyses were conducted based on age, CCI and level of urbanization.ResultsThe mean ± standard deviation age was 53 ± 14 years. After adjusting for potential confounders, the risk of female breast cancer was found to be associated with a history of periodontitis (OR, 1.12; 95% CI, 1.10-1.14). Such an association was significantly different between patients aged < 65 years (OR, 1.09; 95% CI, 1.06-1.11) and patients aged ≥ 65 years (OR, 1.23; 95% CI, 1.18-1.28; p for interaction 0 (OR, 0.99; 95% CI, 0.96-1.03; p for interaction ConclusionsThis population-based nested case-control study demonstrated that periodontitis was significantly associated with the risk of female breast cancer and such an association was modified by both age and comorbidities.

ObjectiveThis study aims to investigate the cost-effectiveness of the add-on exenatide to conventional pharmacotherapy in patients with Parkinson's disease (PD) when considering the coexistence of diabetes mellitus (DM).MethodsWe used the Keelung and Community-based Integrated Screening databases to understand the medical utilisation in the Hoehn and Yahr stages of patients with PD. A Markov model with 1-year cycle length and 50-year time horizon was used to assess the cost-effectiveness of add-on exenatide to conventional pharmacotherapy compared to conventional pharmacotherapy alone. All costs were adjusted to the value of the new Taiwanese dollar (NT$) as of the year 2020. One-way sensitivity and probability analyses were performed to test the robustness of the results.ResultsFrom a societal perspective, the add-on exenatide brought an average of 0.39 quality-adjusted life years (QALYs) gained, and a cost increment of NT$104,744 per person in a 50-year horizon compared to conventional pharmacotherapy. The incremental cost-effectiveness ratio (ICER) was NT$268,333 per QALY gained. As the ICER was less than the gross domestic product per capita (NT$839,558), the add-on exenatide was considered to be very cost-effective in the two models, according to the World Health Organization recommendation. Add-on exenatide had a 96.9% probability of being cost-effective in patients with PD, and a 100% probability of being cost-effective in patients with PD and DM.ConclusionAdd-on exenatide is cost-effective in PD combined with DM. Considering that DM may be a risk factor for neurodegenerative diseases, exenatide provides both clinical benefits and cost-effectiveness when considering both PD and DM.

BackgroundFrailty is associated with major health outcomes. However, the relationships between frailty and frailty symptoms haven't been well studied. This study aims to show the associations between frailty and frailty symptoms.MethodsThe Health and Retirement Study (HRS) is an ongoing longitudinal biannual survey in the United States. Three of the most used frailty diagnoses, defined by the Functional Domains Model, the Burden Model, and the Biologic Syndrome Model, were reproduced according to previous studies. The associations between frailty statuses and input symptoms were assessed using odds ratios and correlation coefficients.ResultsThe sample sizes, mean ages, and frailty prevalence matched those reported in previous studies. Frailty statuses were weakly correlated with each other (coefficients = 0.19 to 0.38, p < 0.001 for all). There were 49 input symptoms identified by these three models. Frailty statuses defined by the three models were not significantly correlated with one or two symptoms defined by the same models (p > 0.05 for all). One to six symptoms defined by the other two models were not significantly correlated with each of the three frailty statuses (p > 0.05 for all). Frailty statuses were significantly correlated with their own bias variables (p < 0.05 for all).ConclusionFrailty diagnoses lack significant correlations with some of their own frailty symptoms and some of the frailty symptoms defined by the other two models. This finding raises questions like whether the frailty symptoms lacking significant correlations with frailty statuses could be included to diagnose frailty and whether frailty exists and causes frailty symptoms.