Testing Of Treatment Strategies Research Articles

AI-Driven Traffic Simulation using Unity: Implementing Finite State Machines for Adaptive NPC Behaviour

This research develops an AI-powered traffic simulation using the Unity Engine, leveraging finite state machines (FSM) to enable adaptive and responsive non-player characters (NPCs). The integration of FSM with advanced pathfinding algorithms, such as A*, allows NPCs to dynamically adjust their behavior based on traffic conditions, obstacles, and environmental changes. The experimental results indicate a 25% improvement in route optimization and a 30% reduction in path conflicts compared to conventional static models, demonstrating the robustness of the proposed approach. Optimized navmesh deployment further enhances navigation fluidity, ensuring efficient agent movement in high-density scenarios without compromising system performance. The findings establish the effectiveness of the FSM-driven NPC behavior in simulating realistic traffic environments, contributing both to the advancement of AI applications in game development and urban planning. By providing an interactive platform for traffic management, this simulation offers a practical tool to study congestion patterns and test intervention strategies. In addition, it improves player engagement by fostering emergent gameplay through dynamic NPC interactions. Future work could explore the integration of real-time procedural generation or multiplayer functionality to enrich simulation depth and scalability. This study provides a comprehensive framework that bridges AI-based mechanics with simulation technology, providing significant insights for researchers and practitioners in game design, artificial intelligence, and urban planning.

An agent-based model of the spread of behavioural risk-factors for cardiovascular disease in city-scale populations.

Cardiovascular disease (CVD) is the leading cause of mortality globally, and is the second main cause of mortality in the UK. Four key modifiable behaviours are known to increase CVD risk, namely: tobacco use, unhealthy diet, physical inactivity and harmful use of alcohol. Behaviours that increase the risk of CVD can spread through social networks because individuals consciously and unconsciously mimic the behaviour of others they relate to and admire. Exploiting these social influences may lead to effective and efficient public health interventions to prevent CVD. This project aimed to construct and validate an agent-based model (ABM) of how the four major behavioural risk-factors for CVD spread through social networks in a population, and examine whether the model could be used to identify targets for public health intervention and to test intervention strategies. Previous ABMs have typically focused on a single risk factor or considered very small populations. We created a city-scale ABM to model the behavioural risk-factors of individuals, their social networks (spousal, household, friendship and workplace), the spread of behaviours through these social networks, and the subsequent impact on the development of CVD. We compared the model output (predicted CVD events over a ten year period) to observed data, demonstrating that the model output is realistic. The model output is stable up to at least a population size of 1.2M agents (the maximum tested). We found that there is scope for the modelled interventions targeting the spread of these behaviours to change the number of CVD events experienced by the agents over ten years. Specifically, we modelled the impact of workplace interventions to show that the ABM could be useful for identifying targets for public health intervention. The model itself is Open Source and is available for use or extension by other researchers.

Lime for Lyme: Treatment of Leaf Litter with Dolomitic Lime Powder Impairs Activity of Immature Ixodes scapularis Ticks.

Background: Tick-borne diseases are an emerging threat to public health throughout the temperate world, leading to a growing field of research aimed at developing and testing intervention strategies for reducing human-tick encounters or prevalence of infection in ticks. Various wide-spectrum chemical acaricides have proven effective for controlling tick populations, but many of these have potential deleterious side-effects on health and the environment. In addition to chemical acaricides, certain compounds such as diatomaceous earth have been shown to have physical acaricidal properties. We hypothesized that dolomitic lime (CaMg(CO3)2, a corrosive, desiccant mineral that is already used extensively in agricultural and forestry contexts to balance the pH of soils, may affect ticks' locomotory activity, habitat position, or survival and that this should manifest as a reduction in the number of questing ticks collected by dragging. Objective: This study aimed to formally assess this hypothesis in a controlled laboratory setting. Methods: We carried out a microcosm experiment, with one control and three treated microcosm trays, each replicating the natural substrate characterizing I. scapularis habitat in northeastern North America. Each tray was infested with 200 living larvae and 50 nymphs, and then treated with 0 (control), 50, 100, or 500 g/m2 of lime powder. Ticks were collected by microdragging 24 and 72 h postliming. Results: Efficacy of liming at reducing the number of collected questing ticks ranged from 87% to 100% for larvae and 0% to 69% for nymphs 24 h postliming and from 91% to 93% for larvae and -47% to 65% for nymphs 72 postliming. Conclusion: This study provides the first experimental evidence of the potential efficacy of liming for impairing activity of questing immature ticks. Given that lime is a low-cost material, that methods for widespread application in deciduous woodlands already exist, and that it has been documented as having a limited negative impact on the environment, further assessment of lime application as a public health risk reduction intervention for tick-borne diseases is warranted.

Intergenerational Reminiscence Approach in Improving Emotional Well-Being of Older Asian Americans in Early-Stage Dementia Using Virtual Reality: Protocol for an Explanatory Sequential Mixed Methods Study.

After a dementia diagnosis, Asian Americans experience anxiety, feelings of shame, and other negative effects. Emotional well-being is not only an important aspect of mental health, but also a quality of resilience that helps people bounce back faster from difficulties. However, few studies have addressed issues in developing, implementing, and testing intervention strategies to promote emotional well-being among older adults. Intergenerational solidarity between grandparents and grandchildren has been emphasized in Asian families and is beneficial for the health of persons with dementia. Reminiscence and life review have been identified as potentially effective intervention strategies for helping depression and emotional well-being for older adults. This proposed study aims to develop and implement an intergenerational reminiscence approach and evaluate its potential feasibility and effectiveness in improving the emotional well-being of older Asian American adults who have a recent dementia diagnosis. An explanatory sequential mixed methods design will be used in which quantitative data will first be collected and analyzed to identify subsamples of participants who report the greatest and least change in emotional well-being; then, these subsamples will be interviewed to further understand why or why not this intervention works for them. Older adults will receive 6 sessions of life review with grandchildren in virtual reality (VR; 1-1.5 hours each week for 6 weeks), aided by pictures and virtually traveling to important places in their life using Google Earth to look around at those places and remember important times. Quantitative survey data will be collected pre- and postintervention and at a 3-month follow-up. Qualitative interviews with selected participants will also be integrated into the study design. The quantitative data from the surveys will be entered into SPSS (IBM Corp) and analyzed using descriptive analyses, Pearson chi-square tests, nonparametric Friedman tests, or nonparametric Wilcox signed-rank tests (2-tailed). The qualitative data will be transcribed by research assistants, coded by the investigators independently, and analyzed with guidance from content analysis software (Atlas.ti; Atlas.ti Scientific Software Development GmbH). The project was delayed due to the COVID-19 pandemic. Data collection started in late 2021, and 26 participants were recruited as of December 2022. While we are still cleaning and analyzing the quantitative data, the qualitative interviews showed promising results of this intergenerational reminiscence approach in improving emotional well-being among older Asian American adults who have cognitive impairment. Intergenerational reminiscence provided by grandchildren is promising in improving the emotional well-being of grandparents. VR technology is likely to be accepted by older adults. Future research may consider scaling up this pilot into a trackable, replicable model that includes more participants and develops a more rigorous study design with control groups to test the effectiveness of this intervention for older adults with dementia. DERR1-10.2196/48927.

Applying GRADE for diagnosis revealed methodological challenges: an illustrative example for guideline developers

ObjectiveTo identify challenges in the application of GRADE for diagnosis when assessing the certainty of evidence in the test-treatment strategy (diagnostic accuracy, test burden, management effectiveness, natural course, linked evidence) in an illustrative example and to propose solutions to these challenges. Study Design and SettingA case study in applying GRADE for diagnosis that looked at the added value of IgE for diagnosing allergic rhinitis. ResultsEvaluation of the full test-treatment strategy showed a lack of (high-quality) evidence for all elements. In our example, we found a lack of evidence for test burden, natural course, and link between the test result and clinical management. Overall, systematically reviewing the evidence for all elements of a test-treatment strategy is more time-consuming than only considering test accuracy results and management effectiveness. For increasing efficiency, the guideline panel could determine critical elements of the test-treatment strategy that need a systematic review of the evidence. For less critical elements, a guideline panel can rely on gray literature and professional expertise. ConclusionA lack of high-quality evidence and time investment if the full test-treatment strategy is assessed, creating challenges in applying GRADE for diagnosis. Discussion within guideline panels about critical elements that need to be reviewed might help.

Icarus and Sports After COVID 19: Too Close to the Sun?

Icarus and Sports After COVID 19: Too Close to the Sun?

Strategies to identify individuals with monogenic diabetes: results of an economic evaluation

ObjectivesTo evaluate and compare the lifetime costs associated with strategies to identify individuals with monogenic diabetes and change their treatment to more appropriate therapy.DesignA decision analytical model from the perspective...

Partial Achievement of the 90-90-90 UNAIDS Target in a Cohort of HIV Infected Patients from Central Italy.

BackgroundDespite progress in the prevention and treatment of HIV, persistent issues concerning the evaluation of continuum in care from the serological diagnosis to virologic success remains. Considering the 2020 UNAIDS target 90-90-90 for diagnosis, treatment, and viral suppression of people living with HIV (PLWH), our purpose was to verify if, starting from new diagnoses, the viral suppression rate of our cohort of new PLWH satisfied the second and the third steps.MethodsThis retrospective study regards all patients aged ≥15 undergoing HIV test at our clinic between January 2005 and December 2017. We evaluated the second and the third ‘90 UNAIDS targets and the unclaimed tests, linkage to care, retention in ART, and the viral suppression at 1 and 2 years. Logistic regression (odds ratio, 95% confidence interval) was performed.ResultsWe observed 592 new diagnoses for HIV infection: 61.4% on Italians, 38.5% on foreigners. An antiretroviral treatment was started on 78.8% of the new diagnoses (467/592) (second UNAIDS target), and a viral suppression was obtained at 2 years on 82% of PLWH who had started ART (383/467) (third UNAIDS target), namely only 64.7% of the new diagnoses instead of the hoped-for 81% of the UNAIDS target. Logistic regressions demonstrated that second and third ‘90 UNAIDS targets were unrelated to sex, nationality, CD4 cells count, HIV-RNA and CDC stage (p>0.05). The age class 25–50 years (OR=2.24; 95% CI = 1.06–4.37; p=0.04) achieves more likely viral suppression when compared with patients <25 years. Considering the continuum of care, 88 (15%) PLWH were lost to engagement in care (55 unclaimed tests and 33 unlinked to care), 37 didn’t start ART, 51 were LFTU at 2 years.ConclusionsUNAIDS goal was far to be reached. The main challenges were unreturned tests as well as the retention in ART. Rapid tests for a test-treat strategy and frequent phone communications in the first ART years could facilitate UNAIDS target achievement.

HSP27 Expression as a Novel Predictive Biomarker for Bevacizumab: is it Cost Effective?

BackgroundDespite the extensive use of bevacizumab in a range of oncology indications, the US FDA revoked its approval for breast cancers, and multiple negative trials in several solid malignancies have been reported, so the need for predictive biomarkers has increased. The development of predictive biomarkers for anti-angiogenic bevacizumab therapy has long been pursued but without success.IntroductionHeat shock protein (HSP)-27 expression has recently been identified as a predictive biomarker for bevacizumab in treating metastatic melanoma. This study aimed to evaluate the cost effectiveness of HSP27 biomarker testing before administration of bevacizumab.MethodsA partitioned survival analysis model with three mutually exclusive health states (progression-free survival, progressed disease, and death) was developed using a Norwegian health system perspective. The proportion of patients in each state was calculated using the area under the Kaplan–Meier curve for progression-free and overall survival derived from trials of bevacizumab and dacarbazine. Three strategies were compared: (1) test-treat with HSP27 biomarker and bevacizumab, (2) treat-all with dacarbazine without HSP27 testing, (3) treat-all with bevacizumab without HSP27 testing. Quality-adjusted life-years (QALYs) and costs were calculated for each strategy and discounted at 4%. A lifetime horizon was applied. Uncertainty analyses were performed. Expected value of perfect information (EVPI) was estimated to assess the potential value of further research to generate more evidence.ResultsAlthough the test-treat strategy was cost effective compared with treat-all with dacarbazine, it was not cost effective compared with treat-all with bevacizumab without HSP27 testing. However, EVPI results showed very minimal or no value in conducting further research efforts to reduce uncertainties around current information.ConclusionThe results of this study suggested that testing for HSP27 expression before administering bevacizumab is not cost effective compared with treat-all with bevacizumab without testing. It indicates that HSP27 expression is not cost effective as a potential predictive biomarker for bevacizumab. This may not necessarily mean that HSP27 is a bad biomarker for bevacizumab, but it may mean that bevacizumab is much better than dacarbazine regardless of HSP27 expression, so patient stratification according to HSP27 status is meaningless. Or, indeed, it may imply that HSP27 is not sufficiently good at identifying the right patients for bevacizumab.Electronic supplementary materialThe online version of this article (10.1007/s41669-019-00193-8) contains supplementary material, which is available to authorized users.

Assessing the performance of a physically based hydrological model using a proxy‐catchment approach in an agricultural environment

AbstractPhysically based models are useful frameworks for testing intervention strategies designed to reduce elevated sediment loads in agricultural catchments. Evaluating the success of these strategies depends on model accuracy, generally established by a calibration and evaluation process. In this contribution, the physically based SHETRAN model was assessed in two similar U.K. agricultural catchments. The model was calibrated on the Blackwater catchment (18 km2) and evaluated in the adjacent Kit Brook catchment (22 km2) using 4 years of 15 min discharge and suspended sediment flux data. Model sensitivity to changes in single and multiple combinations of parameters and sensitivity to changes in digital elevation model resolution were assessed. Model flow performance was reasonably accurate with a Nash–Sutcliffe efficiency coefficient of 0.78 in Blackwater and 0.60 in Kit Brook. In terms of event prediction, the mean of the absolute percentage of difference (μAbsdiff) between measured and simulated flow volume (Qv), peak discharge (Qp), sediment yield (Sy), and peak sediment flux (Sp) showed larger values in Kit Brook (48% [Qv], 66% [Qp], 298% [Sy], and 438% [Sp]) compared with the Blackwater catchment (30% [Qv], 41% [Qp], 106% [Sy], and 86% [Sp]). Results indicate that SHETRAN can produce reasonable flow prediction but performs less well in estimation of sediment flux, despite reasonably similar hydrosedimentary behaviour between catchments. The sensitivity index showed flow volume sensitive to saturated hydraulic conductivity and peak discharge to the Strickler coefficient; sediment yield was sensitive to the overland flow erodibility coefficient and peak sediment flux to raindrop/leaf soil erodibility coefficient. The multiparameter sensitivity analysis showed that different combinations of parameters produced similar model responses. Model sensitivity to grid resolution presented similar flow volumes for different digital elevation model resolutions, whereas event peak and duration (for both flow and sediment flux) were highly sensitive to changes in grid size.

Validation of a Psychosocial Chronic Stress Model in the Pig Using a Multidisciplinary Approach at the Gut-Brain and Behavior Levels.

Psychological chronic stress is an important risk factor for major depressive disorder, of which consequences have been widely studied in rodent models. This work aimed at describing a pig model of chronic stress based on social isolation, environmental impoverishment and unpredictability. Three groups of animals of both sexes were constituted. Two were exposed to the psychosocial stressors while receiving (SF, n = 12) or not (SC, n = 22) the antidepressant fluoxetine, and a third group (NSC, n = 22) remained unstressed. Animals were observed in home pens and during dedicated tests to assess resignation and anxiety-like behaviors. Brain structure and function were evaluated via proton MRS and fMRI. Hippocampal molecular biology and immunodetection of cellular proliferation (Ki67+) and neuron maturation (DCX+) in the dentate gyrus were also performed. Salivary cortisol, fecal short-chain fatty acids (SCFAs), and various plasmatic and intestinal biomarkers were analyzed. Compared to NSC, SC animals showed more resignation (p = 0.019) and had a higher level of salivary cortisol (p = 0.020). SC brain responses to stimulation by a novel odor were lower, similarly to their hippocampal neuronal density (p = 0.015), cellular proliferation (p = 0.030), and hippocampal levels of BDNF and 5-HT1AR (p = 0.056 and p = 0.007, respectively). However, the number of DCX+ cells was higher in the ventral dentate gyrus in this group (p = 0.025). In addition, HOMA-IR was also higher (p < 0.001) and microbiota fermentation activity was lower (SCFAs, SC/NSC: p < 0.01) in SC animals. Fluoxetine partially or totally reversed several of these effects. Exposure to psychosocial stressors in the pig model induced effects consistent with the human and rodent literature, including resignation behavior and alterations of the HPA axis and hippocampus. This model opens the way to innovative translational research exploring the mechanisms of chronic stress and testing intervention strategies with good face validity related to human.

Risk Attitudes Affect Livestock Biosecurity Decisions With Ramifications for Disease Control in a Simulated Production System.

Hog producers' operational decisions can be informed by an awareness of risks associated with emergent and endemic diseases. Outbreaks of porcine epidemic diarrhea virus (PEDv) have been re-occurring every year since the first onset in 2013 with substantial losses across the hog production supply chain. Interestingly, a decreasing trend in PEDv incidence is visible. We assert that changes in human behaviors may underlie this trend. Disease prevention using biosecurity practices is used to minimize risk of infection but its efficacy is conditional on human behavior and risk attitude. Standard epidemiological models bring important insights into disease dynamics but have limited predictive ability. Since research shows that human behavior plays a driving role in the disease spread process, the explicit inclusion of human behavior into models adds an important dimension to understanding disease spread. Here we analyze PEDv incidence emerging from an agent-based model (ABM) that uses both epidemiological dynamics and algorithms that incorporate heterogeneous human decisions. We investigate the effects of shifting fractions of hog producers between risk tolerant and risk averse positions. These shifts affect the dynamics describing willingness to increase biosecurity as a response to disease threats and, indirectly, change infection probabilities and the resultant intensity and impact of the disease outbreak. Our ABM generates empirically verifiable patterns of PEDv transmission. Scenario results show that relatively small shifts (10% of the producer agents) toward a risk averse position can lead to a significant decrease in total incidence. For significantly steeper decreases in disease incidence, the model's hog producer population needed at least 37.5% of risk averse. Our study provides insight into the link between risk attitude, decisions related to biosecurity, and consequent spread of disease within a livestock production system. We suggest that it is possible to create positive, lasting changes in animal health by nudging the population of livestock producers toward more risk averse behaviors. We make a case for integrating social and epidemiological aspects in disease spread models to test intervention strategies intended to improve biosecurity and animal health at the system scale.

Addressing Moral Distress in Critical Care Nurses: A Systemized Literature Review of Intervention Studies

Background: The literature on moral distress highlights the need for hospitals and healthcare organizations to improve the work environment in critical care. However, only few studies delve into the types of intervention programs and administrative processes that can be put into effect to help nurses effectively deal with moral distress. Aim: The aim of this study was to systematically synthesize evidence from published studies of interventions that address moral distress in critical care nurses. The attributes, measures, and outcomes of published interventions were described. Methods: Systemized literature review based on searches in four biomedical sciences databases (CINAHL, MEDLINE, COCHRANE, and SCOPUS). The Cochrane Collaboration's tool was employed for risk of bias. Eligibility criteria included published full-text articles exploring any type of intervention for critical care nurses' moral distress. Results: Based on the selection criteria, seven studies were included in the review (two quasi-experimental, two randomized clinical trials, three mixed method). The majority of studies exhibited high risk of bias. Only two studies had moderate risk of bias. The most common type of interventions were workshops. Conclusion: We identified a small number of overall low-quality intervention studies, which provided weak evidence on the effectiveness of workshops for moral distress. Based on the indications for potentially large effect size of workshops, more well-designed studies are needed in order to elucidate the characteristics, content, and duration of effective workshops for moral distress. The results of this review can inform future efforts to develop and test intervention strategies for moral distress among intensive care unit (ICU) nurses.

Metabolomics for Animal Models of Rare Human Diseases: An Expert Review and Lessons Learned.

Rare diseases occur with a frequency ≤1:1500-1:2500 depending on the location and applicable definitions across countries. Although individually rare, they collectively affect as much as 4-8% of population imposing a large burden on public health. Rarity in prevalence means prolonged path to accurate diagnosis, lack of treatment options, and also limited chances for preclinical studies of pathogenesis. I discuss in this expert review (1) what metabolomics, as a high throughput systems sciences technology, offers for rare disease studies, (2) why animal models are important for the study of rare human diseases and what should be kept in mind while using animal models, and finally, (3) provide examples of recent research to highlight how metabolomics on animal models of rare diseases perform, and how these results can lead to the knowhow, which raises genome, metabolome, and phenotype integration to a whole new level. In sum, metabolomics has been for years in clinical use for diagnosis of certain types of rare diseases. Determination of pathogenesis of more complex diseases and testing of treatment strategies is where animal models and systems biology analytical approaches are necessary. From gathered data, it is possible to go back to diagnostic and prognostic markers for rare diseases, which so far lack reliable and robust diagnosis and therapeutic options. In the future, a major challenge is to reveal the links between genotype, metabolism, and phenotype. Rare diseases could be the key in that process.

Automatic Diagnosis of Neurodegenerative Diseases: An Evolutionary Approach for Facing the Interpretability Problem

Background: The use of Artificial Intelligence (AI) systems for automatic diagnoses is increasingly in the clinical field, being a useful support for the identification of several diseases. Nonetheless, the acceptance of AI-based diagnoses by the physicians is hampered by the black-box approach implemented by most performing systems, which do not clearly state the classification rules adopted. Methods: In this framework we propose a classification method based on a Cartesian Genetic Programming (CGP) approach, which allows for the automatic identification of the presence of the disease, and concurrently, provides the explicit classification model used by the system. Results: The proposed approach has been evaluated on the publicly available HandPD dataset, which contains handwriting samples drawn by Parkinson’s disease patients and healthy controls. We show that our approach compares favorably with state-of-the-art methods, and more importantly, allows the physician to identify an explicit model relevant for the diagnosis based on the most informative subset of features. Conclusion: The obtained results suggest that the proposed approach is particularly appealing in that, starting from the explicit model, it allows the physicians to derive a set of guidelines for defining novel testing protocols and intervention strategies.

Utility of the Neonatal Calf Model for Testing Vaccines and Intervention Strategies for Use against Human RSV Infection.

Respiratory syncytial virus (RSV) is a significant cause of pediatric respiratory tract infections. It is estimated that two-thirds of infants are infected with RSV during the first year of life and it is one of the leading causes of death in this age group worldwide. Similarly, bovine RSV is a primary viral pathogen in cases of pneumonia in young calves and plays a significant role in bovine respiratory disease complex. Importantly, naturally occurring infection of calves with bovine RSV shares many features in common with human RSV infection. Herein, we update our current understanding of RSV infection in cattle, with particular focus on similarities between the calf and human infection, and the recent reports in which the neonatal calf has been employed for the development and testing of vaccines and therapeutics which may be applied to hRSV infection in humans.

A study of projective test responses and intervention strategies in children with unexplained pain symptoms

Psychiatric morbidity is high in children with unexplained chronic pain and thus needs to be assessed and treated. Unexplained pain symbolizes emotional distress and conflicts in children. The most common somatic symptoms are headache, abdominal pain, and musculoskeletal symptoms. Aim: The aim of this case series is to qualitatively analyze the responses obtained on projective tests and intervention strategies employed in children with unexplained pain symptoms. Materials and Methods: Our cases included a total of 12 children and adolescents who were referred to us from the pediatric department for complaints of unexplained pain symptoms for a period of at least 6 months. The investigations done for these children were reportedly normal. After the initial rapport and initial intake, the children underwent projective testing. The projective tests used were Children apperception test, Thematic Apperception Test and Sentence Completion test. Results: The findings observed were conflict with primary caregivers, over-involvement and overly critical parents, sibling rivalry and intrapersonal conflicts. Intervention strategies primarily focused on psychoeducation, addressing secondary gain, parents session to address their relationship with the child and cognitive behavioral strategies as applicable to the case. Conclusion: Children with unexplained pain symptoms require detailed history taking and psychological evaluation. Projective tests facilitate conflict identification and early intervention to address psychological factors. Keywords: Projective test, Uexplained pain symptoms, Management.

Performance of malaria rapid diagnostic test in febrile under-five children at Oni Memorial Children's Hospital in Ibadan, Nigeria, 2016.

IntroductionThe World Health Organization (WHO) recommends testing of suspected malaria cases before treatment. Malaria rapid diagnostic test (mRDT) has been recommended for this purpose in endemic countries where microscopy is not accessible. However, its diagnostic performance remains a concern in clinical settings. We assessed diagnostic performance of RDT among febrile under-five children (U5) presenting at Oni Memorial Children's Hospital, Ibadan (OMCH).MethodsA cross-sectional study was conducted among 370 febrile U5 attending OMCH February to May, 2016. We examined their finger prick blood samples for malaria parasitaemia using CareStartTM histidine rich protein II (HRP-2) RDT and microscopy. The sensitivity, specificity, positive and negative predictive values (PPV, NPV), false positive (FP), invalid rates (IR), likelihood ratio of positive and negative tests (LRP and LRN), were calculated.ResultsMean age of the children was 28.17 ± 15.59 months. Malaria prevalence was 21.6% and 15.1% by mRDT and microscopy, respectively. Sensitivity of CareStartTM HRP-2 RDT was 94.6% (95% confidence interval (CI): 84.2-98.6), specificity: 91.4% (CI: 87.6-94.2), PPV: 66.3% (CI: 54.7-76.2), NPV: 98.9% (CI: 96.8-99.7), FPR 6.5%, IR 8.1%, LRP:10.6 and LRN:0.1.ConclusionDiagnostic performance of CareStartTM used in the study met the ≥ 95% sensitivity at 100 parasites/µL recommended by WHO. This finding provides clinical evidence that testing before anti-malarial treatment as recommended by WHO will identify cases of malaria infection and reduce unnecessary use of drugs. Healthcare workers should be educated on diagnostic accuracy of mRDT and adhere to the WHO's test-treat strategy for anti-malaria therapy.

Delirium-A Framework to Improve Acute Care for Older Persons.

This article is based on the M. Powell Lawton Award Lecture that I delivered at the 2016 Gerontological Society of America Annual Meeting. I provide an overview of my journey in geriatric medicine and delirium research. I created new measures, including the Confusion Assessment Method, for identification of delirium; conceptualized a multifactorial risk model; and developed and tested intervention strategies for delirium prevention. The Hospital Elder Life Program arose from this work. In addition, like Dr. Lawton, I am working to apply my work to the policy arena. As the population ages, we face an unprecedented opportunity to realize the full benefit of aging in our society, an untapped resource. The field of aging is facing innumerable challenges in terms of continued stigma and funding shortfalls for clinical care and research. I issue a call to action to clinicians, researchers, and leaders in aging to seize this opportunity to use our know-how and expertise to transform the experience of aging for all.

Demand-related factors influencing caregivers\u2019 awareness of malaria tests and health workers\u2019 testing practices, in Makarfi, Nigeria

BackgroundDespite the World Health Organization’s recommendation of malaria test-treat strategy, which is the treatment of parasitological confirmed malaria cases with anti-malarials, presumptive diagnosis of malaria remains fairly common in Nigeria. The reasons for this have not been established in Makarfi, Nigeria, despite the high burden of malaria in the area. A study was conducted among caregivers of febrile children less than 5 years presenting for treatment to understand their awareness of malaria diagnostic testing and being offered testing by clinicians, the determinants of these outcomes, and caregivers’ perspectives of health workers’ testing practices.MethodsUsing mixed-methods, data was combined from sub-analysis of cross-sectional survey data (n = 295) and focus group discussions (n = 4) with caregivers conducted in Makarfi General Hospital (Kaduna State, Nigeria) and surrounding communities in 2011. Bivariate and multivariate analysis of the quantitative survey data was conducted to examine associations of caregivers’ sociodemographic characteristics with testing awareness and having ever been offered testing. Transcripts from focus group discussions (FGD) were analysed for emerging themes related to caregivers’ perspectives on malaria testing.ResultsAmong surveyed caregivers who were predominantly female (81.7%), not formally educated (72.5%), and were housewives (68.8%); only 5.3% were aware of any diagnostic testing for malaria, and only 4.3% had ever been offered a malaria test by a health worker. Having at least a primary level education (adjusted odds ratio [aOR] 20.3, 95% CI 4.5–92.1) and living within 5 km of the hospital (aOR 4.3, 95% CI 1.5–12.5) were determinants of awareness of malaria testing. Also, these were determinants of previously having been offered a test (aOR 9.9, 95% CI 2.1–48.7; and aOR 4.0, 95% CI 1.1–14.7). FGD showed many caregivers believed that malaria testing was for severe illness only, and that proximity to a health facility and cost of treatment influenced the seeking and receiving of care.ConclusionsUptake of malaria testing prior to treatment can be improved by increasing its awareness and addressing misunderstandings among caregivers, promoting testing practices among health workers, and availing caregivers living farther from health centres alternative opportunities for community case management of febrile illnesses.