Deep Q-networks with web-based survey data for simulating lung cancer intervention prediction and assessment in the elderly: a quantitative study

Background Lung cancer screening and intervention might be important to help detect lung cancer early and reduce the mortality, but little was known about lung cancer intervention strategy associated with intervention effect for preventing lung cancer. We employed Deep Q-Networks (DQN) to respond to this gap. The aim was to quantitatively predict lung cancer optimal intervention strategy and assess intervention effect in aged 65 years and older (the elderly). Methods We screened lung cancer high risk with web-based survey data and conducted simulative intervention. DQN models were developed to predict optimal intervention strategies to prevent lung cancer in elderly men and elderly women separately. We assessed the intervention effects to evaluate the optimal intervention strategy. Results Proposed DQN models quantitatively predicted and assessed lung cancer intervention. DQN models performed well in five stratified groups (elderly men, elderly women, men, women and the whole population). Stopping smoking and extending quitting smoking time were optimal intervention strategies in elderly men. Extending quitting time and reducing smoked cigarettes number were optimal intervention strategies in elderly women. In elderly men and women, the maximal reductions of lung cancer incidence were 31.81% and 24.62% separately. Lung cancer incidence trend was deduced from the year of 1984 to 2050, which predicted that the difference of lung cancer incidence between elderly men and women might be significantly decreased after thirty years quitting time. Conclusions We quantitatively predicted optimal intervention strategy and assessed lung cancer intervention effect in the elderly through DQN models. Those might improve intervention effects and reasonably prevent lung cancer.

Google Trends as a Method to Predict New COVID-19 Cases and Socio-Psychological Consequences of the Pandemic

Understanding how people react to the COVID-19 crisis, and what the consequences are of the COVID-19 pandemic is key to enable public health and other agencies to develop optimal intervention strategies. Because the timely identification of new cases of infection has proven to be the key to timely respond to the spread of infection within a particular region, we have developed a method that can detect and predict the emergence of new cases of COVID-19 at an early stage. Further, this method can give useful insights into a family’s life during the pandemic and give the prediction of birth rates. The basic methodological concept of our approach is to monitor the digital trace of language searches with the Google Trends analytical tool (GT). We divided the keyword frequency for selected words giving us a search frequency index and then compared searches with official statistics to prove the significations of results. 1) Google Trends tools are suitable for predicting the emergence of new COVID-19 cases in Croatia. The data collected by this method correlate with official data. In Croatia search activities using GT for terms such as “PCR +COVID”, and symptoms “cough + corona”, “pneumonia + corona”; “muscle pain + corona” correlate strongly with officially reported cases of the disease. 2) The method also shows effects on family life, increase in stress, and domestic violence. 3) Birth rate in 2021 will be just 87% of what it would be “a normal year” in Croatia. 4) This tool can give useful insights into domestic violence. Unquestionably, there are still significant open methodological issues and the questionable integrity of the data obtained using this source. The fact is also a problem that GT does not provide data on which population was sampled or how it was structured. Although these open-ended issues pose serious challenges for making clear estimates, statistics offer a range of tools available to deal with imperfect data as well as to develop controls that take data quality into account. All these insights show that GT has the potential to capture attitudes in the broad spectrum of family life themes. The benefit of this method is reliable estimates that can enable public health officials to prepare and better respond to the possible return of a pandemic in certain parts of the country and the need for responses to protect family well-being. Keywords: Google trends, COVID-19, birth rates, domestic violence, Croatia, predicting demographic trends, family

Barriers to and Facilitators for Optimal Intervention for Apathy in Older Adults With Dementia

Apathy is a persistent symptom in brain disorders. It affects 84% of people with brain disorders. Those affected are more than two times likely to die early than those without. Yet it is often ignored and undertreated. An integrative review guided by Whittemore and Knafl's (2005) framework was carried out to identify the factors that inhibit or facilitate the diagnosis and management of apathy among older adults with dementia. The result of the findings revealed five barriers and three facilitators. Barriers included inconsistencies in the definition and diagnostic criteria, lack of awareness, overlap with other neuropsychiatric disorders, a paucity of evidence-based information, and lack of familiarity. Facilitators were standardized definition and assessment tools, good communication among the interdisciplinary team, and adequate training, education, and experience. In conclusion, efforts should be geared towards raising awareness and developing a practice guideline to aid healthcare professionals in detecting and managing apathy optimally.

Effects of sociodemographic and socioeconomic factors on stroke development in Lebanese patients with atrial fibrillation: a cross-sectional study

Background: Non-communicable diseases, the major cause of death and disability, are susceptible to modifiable and non-modifiable risk factors. Atrial fibrillation (AF) increases the risk of stroke by 4 to 5 times and can lead to cardiovascular mortality. This study was conducted to assess the effects of different sociodemographic and socioeconomic factors on stroke development in patients with AF. Methods: A cross-sectional study was conducted between January and June 2018 on patients recruited from Lebanese community pharmacies. The CHA2DS2-VASc scoring system is utilized as a stroke risk stratification tool in AF patients. Participants with a previous physician diagnosis of AF, documented on medical records, were included in this study. Data was collected through a survey that was distributed to all eligible patients. Results: A total of 524 patients were enrolled in the study with a mean age (± SD) of 58.75 ± 13.59 years with hypertension (78.4%) being the most predominant disease. The results showed that obesity (Beta=0.61, p-value =0.011), retirement and unemployment compared to employment (Beta=1.44 and 1.44, p-value=0.001 respectively), divorced/widow compared to married (Beta=1.38, p-value =0.001) were significantly associated with higher CHA2DS2-VASc scores whereas high versus low socio-economic status (Beta=-1.03, p=0.009) and high school education versus primary education level (Beta=-0.49, p-value=0.025) were significantly associated with lower CHA2DS2-VASc scores. Conclusions: The study highlights that the CHA2DS2-VASc score is affected by the presence of various sociodemographic and socioeconomic characteristics in patients with AF. Thus, screening for those factors may predict the progression of cardiovascular disease and may provide an optimal intervention.

Mathematical and numerical analyses of a stochastic impulse control model with imperfect interventions

A stochastic impulse control problem with imperfect controllability of interventions is formulated with an emphasis on applications to ecological and environmental management problems. The imperfectness comes from uncertainties with respect to the magnitude of interventions. Our model is based on a dynamic programming formalism to impulsively control a 1-D diffusion process of a geometric Brownian type. The imperfectness leads to a non-local operator different from the many conventional ones, and evokes a slightly different optimal intervention policy. We give viscosity characterizations of the Hamilton–Jacobi–Bellman Quasi-Variational Inequality (HJBQVI) governing the value function focusing on its numerical computation. Uniqueness and verification results of the HJBQVI are presented and a candidate exact solution is constructed. The HJBQVI is solved with the two different numerical methods, an ordinary differential equation (ODE) based method and a finite difference scheme, demonstrating their consistency. Furthermore, the resulting controlled dynamics are extensively analyzed focusing on a bird population management case from a statistical standpoint.

626Epidemiology of facial injuries in the context of fatal family violence in the Victorian population

Background The oral cavity is reported to be a key focus of physical injury in family violence (FV). Our purpose is to explore the potential opportunity for dentists to assist in the prevention of serious injuries in FV. This paper aims to describe the patterns of orofacial injuries in FV homicides. Methods All FV homicides in Victoria, Australia January 2006-December 2018, were identified amongst closed cases of assaults screened for eligible victim-offender relationships. Epidemiologic trends in FV in the Victorian population over the 12-year period were determined. Sociodemographic, interpersonal, incident and injury characteristics including ICD-10 coding were studied and compared across facial and non-facial injury FV subgroups. Results There was a non-significant downward trend in FV homicide over the period. Of 170 adult cases, 150 were included for facial injury analysis. Of these, 117 (78%) showed orofacial injuries in the 12-year period. Two-step cluster analysis revealed blunt force and threat to breathing injury mechanisms to be significantly associated with facial FV and sharp force with nonfacial FV. Among the additional 26 child homicides, descriptive analysis elucidated patterns in 20 cases eligible for facial injury analysis. Coding limitations were found for the FV homicide cases. Conclusions This population study reports significant involvement of the orofacial region in the FV homicide population during the 12-year study period, potentially informing dental practice and the related policy framework in Victoria and internationally. Key messages The significant involvement of the orofacial region in FV homicides may inform optimal intervention outcomes in FV in Victoria.

Limiting-Stress-Elimination Hypothesis: Using Non-hormonal Biostimulant to Reduce Stress and Increase Savanna Cowpea [Vigna unguiculata (L.) Walp.] Productivity

An alternative decision axiom to guide in determining the optimal intervention strategy to maximize cowpea production is proposed. According to the decrement from the maximum concept of Mitscherlich, the decrement from the maximum for each stressor must be minimized to produce the absolute maximum production. In crop production, this means all deficient nutrients must be supplemented to ensure maximum yield and laid the foundation in fertilizer formulation. However, its implementation is not economically feasible in many situations, particularly where multiple environmental factors impact crop productivity as in the case of low resource conditions. We propose and test the hypothesis that yield allocation will increase when the most limiting stressor among prevailing stressors is eliminated at least until the next limiting stressor impacts productivity. We selected drought limiting savanna conditions and cowpea (Vigna unguiculata), adapted to nitrogen dependence. To determine the limiting condition, we measured the response of cowpea to D-sorbitol, nitrogen, and non-hormonal biostimulant (nhB) treatments. The nhB treatment increased total biomass by 45% compared to nitrogen, 13%, and D-sorbitol, 17%, suggesting osmotic stress is more limiting in the observed savanna conditions. The effect of the biostimulant is due to antioxidants and key amino acids that stimulate metabolism and stress resistance. Where nitrogen becomes the next constraining factor, biostimulants can contribute organic nitrogen. The study supports the use of biostimulants as candidate intervention under conditions where crop productivity is limited by multiple or alternating constraints during crop growth.

Effects of sociodemographic and socioeconomic factors on stroke development in Lebanese patients with atrial fibrillation: a cross-sectional study

Background: Non-communicable diseases, the major cause of death and disability, are susceptible to modifiable and non-modifiable risk factors. Atrial fibrillation (AF) increases the risk of stroke by 4-5 times and can lead to cardiovascular mortality. This study was conducted to assess the effects of different sociodemographic factors on stroke development in patients with AF. Methods: A cross-sectional study was conducted between January and June 2018 on patients recruited from Lebanese community pharmacies. The CHA2DS2-VASc scoring system is utilized as a stroke risk stratification tool in AF patients. Participants with a previous physician diagnosis of AF, documented on medical records, were included in this study. Results: A total of 524 patients were enrolled in the study with a mean age of 58.75 (± SD) ± 13.59 years with hypertension (78.38%) being the most predominant disease. The results showed that obesity (Beta=0.610, p-value =0.011), retirement and unemployment compared to employment (Beta=1.440 and 1.440, p-value=0.001 respectively), divorced/widow compared to married (Beta=1.380, p-value =0.001) were significantly associated with higher CHA2DS2-VASc scores whereas high versus low socio-economic status (Beta=-1.030, p=0.009) and high school education versus primary education level (Beta=-0.490, p-value=0.025) were significantly associated with lower CHA2DS2-VASc scores. Conclusions: The study highlights that the CHA2DS2-VASc score is affected by the presence of various sociodemographic and socioeconomic characteristics in patients with AF. Thus, screening for those factors may predict the progression of cardiovascular disease and may provide an optimal intervention.