Likelihood Of Illness Research Articles

Risk Assessment and Diagnosis Code Prediction from Electronic Health Records (EHR) using deep learning

Knowledge in the medical field is often expressed by distinct and subjective norms. Much research and development efforts have focused on using deep learning algorithms to predict the likelihood of illnesses from EHR in recent years. When it comes to risk prediction, deep learning-based techniques outperform more conventional machine learning models. But nothing in the literature fully accounts for what doctors already know, such as the connections between illnesses and their risk factors. This research examines the use of Multi-layer Perceptron models for the categorisation of diagnoses in electronic health records. The raw data and a modified version of the EHR dataset are used to train two MLPs with distinct topologies. For comparative purposes, a Random Forest is used as a baseline. To phenotype patients using their electronic health records, we provide a deep learning method. Predictive modelling of chronic illnesses is the particular scenario used to verify the suggested model on a real-world EHR data warehouse. Many deep learning applications on EHRs have been effective, and there is still a lot of potential to be realised. It has been discovered that deep learning models can learn from the limited EHR dataset, but not to a level where they outperform the baseline model.

Contrasting Objective and Perceived Risk: Predicting COVID-19 Health Behaviors in a Nationally Representative U.S. Sample.

Individuals confronting health threats may display an optimistic bias such that judgments of their risk for illness or death are unrealistically positive given their objective circumstances. We explored optimistic bias for health risks using k-means clustering in the context of COVID-19. We identified risk profiles using subjective and objective indicators of severity and susceptibility risk for COVID-19. Between 3/18/2020-4/18/2020, a national probability sample of 6,514 U.S. residents reported both their subjective risk perceptions (e.g., perceived likelihood of illness or death) and objective risk indices (e.g., age, weight, pre-existing conditions) of COVID-19-related susceptibility and severity, alongside other pandemic-related experiences. Six months later, a subsample (N = 5,661) completed a follow-up survey with questions about their frequency of engagement in recommended health protective behaviors (social distancing, mask wearing, risk behaviors, vaccination intentions). The k-means clustering procedure identified five risk profiles in the Wave 1 sample; two of these demonstrated aspects of optimistic bias, representing almost 44% of the sample. In OLS regression models predicting health protective behavior adoption at Wave 2, clusters representing individuals with high perceived severity risk were most likely to report engagement in social distancing, but many individuals who were objectively at high risk for illness and death did not report engaging in self-protective behaviors. Objective risk of disease severity only inconsistently predicted health protective behavior. Risk profiles may help identify groups that need more targeted interventions to increase their support for public health policy and health enhancing recommendations more broadly.

The relationship between maladaptive health beliefs, pandemic-related stress, and health anxiety during the COVID-19 pandemic.

Research has demonstrated that people experience specific distress and anxiety regarding COVID-19. This distress may consist of interconnected symptom categories corresponding to a COVID stress syndrome. Susceptibility to COVID stress syndrome may be related to one's maladaptive health beliefs; however, no research has investigated the association between maladaptive health beliefs and COVID stress. The present study explored the impact of health beliefs on COVID stress, health anxiety, and associated psychological constructs. This cross-sectional survey study included 221 adults (M age = 20.59, SD = 2.28). Participants completed an online survey including demographic questionnaires and self-report measures of health beliefs, COVID stress, health anxiety, and related psychological constructs. Health anxiety, anxiety sensitivity, state/trait anxiety, intolerance of uncertainty, and depression accounted for significant variance in COVID stress (F(6, 214) = 11.18, R2 = .24, p < .001). Health beliefs (i.e., perceived likelihood of illness, medical service inadequacy, and difficulty coping) were associated with greater COVID stress, although health beliefs were not found to mediate the relationship between health anxiety and COVID stress. Health beliefs were associated with greater COVID stress, although health beliefs did not mediate the relationship between health anxiety and COVID stress. The relationship between health anxiety and COVID stress may be better explained by other COVID-related cognitions (e.g., vaccine efficacy, dangerousness of COVID-19). The findings highlight the importance of peoples' health beliefs during the pandemic. Given anxiety's influence on peoples' behavioural responses to the pandemic, further research should identify COVID-specific cognitions for prevention of COVID stress and health anxiety.

Impact of ambient air pollution and socio-environmental factors on the health of children younger than 5 years in India: a population-based analysis

Ambient air pollution and household environmental factors affect child health, particularly in low-income and middle-income countries. This study aimed to investigate the association between ambient air pollution (PM2·5) levels, socio-environmental factors (including household wealth, housing quality measures, smoking status), and the occurrence of respiratory illness in Indian children. In this retrospective and observational study, we analysed data from India's National Family Health Survey (NFHS-5, 2019-2021) combined with NASA's Global Annual PM2·5 Grids database. Bivariate and multivariable generalized additive models were employed to examine associations between key social-environmental factors and respiratory illness in children younger than 5 years. We analysed data from 224,214 children younger than 5 years, representing 165,561 families from 29,757 geographic clusters. Our results showed extremely high annual PM2·5 levels throughout India (median 63·4·g/m3, IQR 41·9-81·6), with higher exposure for rural and impoverished families. In bivariate analyses, PM2·5 was significantly associated with reported respiratory illness (p<0·001). Using generalized additive models and after accounting for key social and environmental factors, a monotonic increasing and non-linear relationship was observed between PM2·5 and respiratory illness (p<0·001), with increased likelihood of illness observed even at values near and below India's National Ambient Air Quality Standards of 40μg/m3. The study highlights the significant association of social-environmental conditions with health outcomes among young children in India. Efforts specifically targeting ambient air pollution and child health during monsoon season could have significant health benefits among this population and help achieve the goal of ending preventable deaths of children younger than 5 years. National Institutes of Health (NIH T-32-HL139443-3).

Cross Contamination during Simulated Food Pantry Handling of Apples, Oranges and Potatoes

Food pantries receive, store, distribute and serve food to hundreds of people throughout a community. Safe food handling during all these activities is of paramount importance or food may support growth of pathogens and result in foodborne illnesses after consumption. Year round, and more frequently during holiday seasons, food pantries are seeking food donations to support people in need. Since most food pantries products are donated, the safety of these products from a health perspective can be tricky. The quality of food donations coupled with the way food is handled in these facilities can pose major safety concerns. To determine the potential for transfer of bacteria during handling of food at food pantries, apples, potatoes and oranges were inoculated with a non-pathogenic, fluorescently-labeled strain of Escherichia coli, then handled with gloved hands after which another non-inoculated apple, potato or orange was handled. E. coli was then enumerated from each piece of food and gloves to determine the transfer rate from the inoculated piece of food to gloves and the non-inoculated food. The average transfer rate from the inoculated food to gloves was 36.4%, from glove to un-inoculated food was 42.4% and from the inoculated food to un-inoculated food was 15.2%. Whether it be from surfaces or hands, cross-contamination of food and surfaces can readily occur and can result in increased likelihood of illness unless proper hygiene is employed. Food pantries can reduce the likelihood of microbial cross-contamination using proper handwashing techniques, and sanitation of surfaces and utensils. Proper hygiene is critical for food pantries to reduce the likelihood of bacterial transfer to previously uncontaminated surfaces.

The Relationship between COVID-19 Phobia and Health Cognitions and Psychosocial Factors

Objective: The study aimed to determine the levels of corona-phobia experienced by individuals in a broad population representative of Turkish society, and the correlation with health cognitions and psychosocial factors. &#x0D; Material and Method: This descriptive, cross-sectional, and correlational study was conducted with 1620 participants who lived in different regions of Turkey. Data were collected using an information form, the COVID-19 Phobia Scale (C19P-S), and the Health Cognitions Questionnaire. &#x0D; Results: The mean age of the participants was 34.13±10.90 and 62.8% of them were female. The mean score of COVID-19 phobia score was 51.84±13.53 and health cognition was 60.17±9.61. COVID-19 phobia was significantly related to cognitions of difficulty coping with illness, medical services adequacy, the awfulness of illness and the likelihood of illness. The factors influencing the C19P-S of participants were, being female, having a chronic illness, having too much impact on daily life, difficulty coping with illness, awfulness of illness, and likelihood of illness. &#x0D; Conclusion: It is recommended to plan interventions to increase public awareness of COVID-19 and to reduce corona-phobia. These interventions should be especially about the negative impact of corona-phobia on people with a chronic illness and women’s mental health.

A Survey of Vaping Use, Perceptions, and Access in Adolescents from South-Central Texas Schools.

Despite efforts to dissuade major manufacturers and retailers from marketing and selling vape products to adolescents, the practice of vaping continues to increase in this population. Few studies have assessed adolescent perceptions of vaping, access to vaping, and use of vaping, and most rely, at least in part, on inferential conclusions drawn from data on smoking traditional combustible cigarettes. A novel electronic survey was created to assess the use of vapes, perceptions of vaping, and access to vaping among a convenience sample of adolescents (ages 12-20 years) in eleven schools in South-Central Texas from May to August 2021. The students' perceived threat of negative health outcomes due to vaping was calculated based on questions soliciting perceptions of severity (perceived danger) and susceptibility (perceived likelihood of illness). Trends were identified using descriptive and bivariate statistical tests. A total of 267 respondents were included; 26% had tried vaping. A majority (63%) did not believe vaping and smoking were synonymous. Most (70%) thought it was easy to obtain supplies and (76%) vape before and after (88%) or even during (64%) school. Respondents who vaped had a 34% lower perceived threat when compared to respondents who did not vape. In this sample of adolescents from South-Central Texas, one in four reported that they had tried vaping. Easy access to vapes and misperceptions regarding the safety of vaping might create a false sense of security with respect to vaping as an alternative to smoking, particularly among those who reported vaping, and is likely contributing to the increased use of vapes.

Comprehensive bioinformatics analysis reveals the crosstalk genes and immune relationship between the systemic lupus erythematosus and venous thromboembolism.

It is well known that patients with systemic lupus erythematosus (SLE) had a high risk of venous thromboembolism (VTE). This study aimed to identify the crosstalk genes between SLE and VTE and explored their clinical value and molecular mechanism initially. We downloaded microarray datasets of SLE and VTE from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis was applied to identify the crosstalk genes (CGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the shared genes. The shared diagnostic biomarkers of the two diseases were further screened from CGs using least absolute shrinkage and selection operator (Lasso) regression. Two risk scores for SLE and VTE were constructed separately to predict the likelihood of illness according to the diagnostic biomarkers using a logical regression algorithm. The immune infiltration levels of SEL and VTE were estimated via the CIBERSORT algorithm and the relationship of CGs with immune cell infiltration was investigated. Finally, we explored potential phenotype subgroups in SLE and VTE based on the expression level of CGs through the consensus clustering method and studied immune cell infiltration in different subtypes. A total of 171 CGs were obtained by the intersection of differentially expressed genes (DEGs) between SLE and VTE cohorts. The functional enrichment shown these CGs were mainly related to immune pathways. After screening by lasso regression, we found that three hub CGs (RSAD2, HSP90AB1, and FPR2) were the optimal shared diagnostic biomarkers for SLE and VTE. Based on the expression level of RSAD2 and HSP90AB1, two risk prediction models for SLE and VTE were built by multifactor logistic regression and systemically validated in internal and external validation datasets. The immune infiltration results revealed that CGs were highly correlated with multiple infiltrated immunocytes. Consensus clustering was used to respectively regroup SLE and VTE patients into C1 and C2 clusters based on the CGs expression profile. The levels of immune cell infiltration and immune activation were higher in C1 than in C2 subtypes. In our study, we further screen out diagnostic biomarkers from crosstalk genes SLE and VTE and built two risk scores. Our findings reveal a close relationship between CGs and the immune microenvironment of diseases. This provides clues for further exploring the common mechanism and interaction between the two diseases.

Grandparents with different health statuses as primary caregivers: Are they bad for children's health?

AbstractThe prevalence and intensity of grandparenting have continued to increase in the era of rapid aging. However, little is known about grandparents with different health statuses as primary caregivers and their implications for children's health. A nationally representative cohort of over 8990 Chinese children interviewed from 2010 to 2018 was used. Random effects logit models were constructed to assess the association of the primary caregiver type (grandparents vs. parents) and caregiver health with child health. Subsequently, additive interactions between the primary caregiver type and caregiver health were estimated to determine whether children cared for by grandparents with poor health were the most vulnerable children in terms of health. Deterioration of health status was found among children cared for mainly by grandparents, manifested as a higher likelihood of illness, depressive symptoms and unmet health care needs. However, children looked after by healthy grandparents tended to exhibit better health than their counterparts who were cared for by unhealthy parents. Grandparents as primary caregivers might not have a universally detrimental effect on child health. Thus, interventions to prompt child health could consider grandparents as caregivers, especially healthy grandparents.

Onsite Nonpotable Water Systems Pathogen Treatment Targets: A Comparison of Infection and Disability-Adjusted Life Years (DALYs) Risk Benchmark Approaches.

Pathogen log10 reduction targets for onsite nonpotable water systems were calculated using both annual infection (LRTINF) and disability-adjusted life year (LRTDALY) benchmarks. The DALY is a measure of the health burden of a disease, accounting for both the severity and duration of illness. Results were evaluated to identify if treatment requirements change when accounting for the likelihood, duration, and severity of illness in addition to the likelihood of infection. The benchmarks of 10-4 infections per person per year (ppy) and 10-6 DALYs ppy were adopted along with multilevel dose-response models for Norovirus and Campylobacter jejuni, which characterize the probability of illness given infection (Pill|inf) as dose-dependent using challenge or outbreak data. We found differences between treatment requirements, LRTINF - LRTDALY, for some pathogens, driven by the likelihood of illness, rather than the severity of illness. For pathogens with dose-independent Pill|inf characterizations, such as Cryptosporidium spp., Giardia, and Salmonella enterica, the difference, LRTINF - LRTDALY, was identical across reuse scenarios (<than 1.0). The differences varied across source waters and uses for C. jejuni and Norovirus and widened when the dose-dependent Pill|inf was characterized using challenge data (i.e., when there was evidence of a small probability of illness at low doses). Norovirus LRTs were highest across pathogens, despite low severity and dose-dependent Pill|inf, given the high infection risks predicted by the multilevel framework. This work highlights updated Norovirus dose-response best practices, the quantitative impact of risk endpoint in determining risk-based treatment targets, and the discrepancy in best available science for illness and infection responses across pathogens.

Predicting Breast Cancer with Ensemble Methods on Cloud

There are many dangerous diseases and high mortality rates for women (including breast cancer). If the disease is detected early, correctly diagnosed and treated at the right time, the likelihood of illness and death is reduced. Previous disease prediction models have mainly focused on methods for building individual models. However, these predictive models do not yet have high accuracy and high generalization performance. In this paper, we focus on combining these individual models together to create a combined model, which is more generalizable than the individual models. Three ensemble techniques used in the experiment are: Bagging; Boosting and Stacking (Stacking include three models: Gradient Boost, Random Forest, Logistic Regression) to deploy and apply to breast cancer prediction problem. The experimental results show the combined model with the ensemble methods based on the Breast Cancer Wisconsin dataset; this combined model has a higher predictive performance than the commonly used individual prediction models.

Health gender gap in Uganda: do weather effects and water play a role?

BackgroundVulnerabilities of men and women to adverse health effects due to weather variability and climate change are not equal. Uganda was among the countries in the world most affected by extreme weather events during the last decade. However, there is still limited gendered empirical evidence on the links between weather variability and health and the possible pathways through which these health effects occur. Therefore, this study analyses the effect of weather variability on illness, and the extent to which water collection ‘time burden’ mediates the relationship between weather anomalies and illness among men and women of working age in Uganda. The study also quantifies the health inequalities to be eliminated if resources are equalized.MethodsSocioeconomic, health and time use data were obtained from the World Bank Living Standards Measurement Studies - Integrated Surveys on Agriculture (LSMS –ISA), combined with high resolution remotely-sensed weather data. Two-parts and non-linear decomposition regression analysis were used on the national representative pooled dataset from the four household survey waves collected between 2009 to 2014, comprising a total of 22,469 men and women aged between 15 and 64 years.ResultsEmpirical results show that low rainfall below the long-term mean increased the likelihood of illness by at least 8 and 6 percentage points for women and men, respectively. The indirect effect of low rainfall on illness through water access pathway was estimated at 0.16 percentage points in women. Decomposition results reveal that health inequalities among women and men would have been narrowed by 27–61%, if endowments were equalized.ConclusionsStrategies that promote women empowerment (such as education, labor force participation, access to financial services and clean water), health adaptation and time poverty reduction strategies (such as rain water harvesting and improved access to quality health care) would reduce gender-based health inequalities in Uganda despite changing climatic conditions.

The effect of community engagement on healthcare utilization and health insurance enrollment in Ghana: Results from a randomized experiment

Health insurance enrollment in many Sub‐Saharan African countries is low, even with highly subsidized premiums and exemptions for vulnerable populations. One possible explanation is low service quality, which results in a low valuation of health insurance. Using a randomized control trial in 64 primary health care facilities in Ghana, this study assesses the impact of a community engagement intervention designed to improve the quality of healthcare and health insurance services on households living nearby the facilities. Although the intervention improved the medical‐technical quality of health services, our results show that households' subjective perceptions of the quality of healthcare and insurance services did not increase. Nevertheless, the likelihood of illness and concomitant healthcare utilization reduced, and especially households who were not insured at baseline were more likely to enroll in health insurance. The results show that solely increasing the technical quality of care is not sufficient to increase households' subjective assessments of healthcare quality. Still, improving technical quality can directly contribute to health outcomes and further increase health insurance coverage, especially among the previously uninsured.

How online searches fuel health anxiety: Investigating the link between health-related searches, health anxiety, and future intention

The Digital revolution has changed the way in which health information is accessed. While some people feel empowered and less anxious after online searches, others are more anxious or puzzled, which may affect their health-related behaviors. By taking into account health anxiety, this paper examines the processes by which people transition from online health searches to the pursuit of healthcare assistance. Based on Stimulus Organism Response (S–O-R) framework, a research model was developed to illustrate the psychological mechanisms of how searching experience shapes users' healthcare behavior. Using partial least squares-structural equation modeling (PLS-SEM) approach, the results support that the online searches trigger different features of health anxiety, which in turn reinforce further healthcare utilization intention. Results also show that response efficacy positively moderates the relationship between perceived illness likelihood and healthcare utilization intentions, while self-efficacy positively moderates the relationship between perceived illness likelihood and further search intention. Three major recommendations are suggested. Information seekers should rely less on internet searches to alleviate anxiety, and become more aware of, self-monitor, and reduce excessive online health searching. Different stakeholders should orient people to high-quality sources. Healthcare practitioners should engage in improving patient-centered information skills and patients’ health information literacy.

NIOSH Responds to the U.S. Drug Overdose Epidemic.

The United States is experiencing an evolving and worsening drug overdose epidemic. Although the rate of drug use among workers has remained relatively stable, the risk of overdose and death among drug users has not, as illicit drugs have increased in potency and lethality. The cumulative impacts of COVID-19 and the opioid crisis increase the likelihood of illness and death among workers with opioid use disorder. Workplaces represent a critical point of contact for people living in the United States who are struggling with or recovering from a substance use disorder, and employment is a vital source of recovery "capital." The benefits of addressing substance use in the workplace, supporting treatment, and employing workers in recovery are evident. The National Institute for Occupational Safety and Health has published research to inform policy and practice toward prevention efforts and has developed accessible resources and toolkits to support workers, employers, and workplaces in combatting the opioid overdose crisis and creating safer, healthier communities.

Perception Of Stress and Illness Among Nurses in Psychiatry

Homeostasis is important for maintaining balance and normal functioning of the organism. Allostatic mechanisms further help to establish this balance. If the body is under stress for a longer period, a complex condition in the body called allostatic load occurs. If such a load lasts longer, the risk of developing diseases increases significantly. This study was conducted anonymously with the aim of determining the health status of male and female nurses in the Neuropsychiatric hospital “Dr. Ivan Barbot” in Popovača and their exposure to everyday stressors in the workplace. The main purpose was to examine the relationship between stress and the health status of nurses in relation to gender, age, and seniority. A total of 142 nurses participated. The Health Questionnaire and Workplace Stress Questionnaire were used. The results showed that the most common diseases nurses suffer from are cardiovascular diseases, thyroid diseases, gastrointestinal diseases, and allergies. Women showed higher sensitivity to stress than men. The most common stressors faced by nurses in the workplace are inadequate personal income, inadequate workspace and material resources for work, lack of staff, daily contingencies, 24-hour responsibility, and administrative work. This study found an association between age and, consequently, work experience with the likelihood of illness, although both the healthy and the sick perceive equal levels of stress. One disadvantage of this study is that it covers a large area and deals with general issues, but it can certainly be a starting point for further research. Many questions remain open, which means there is a need for further research and study of the link between stress and illness.

Contagious Health Risk and Precautionary Social Distancing.

BackgroundSince humans are social animals, social relations are incredibly important. However, in cases of contagious diseases such as the flu, social contacts also pose a health risk. According to prominent health behavior change theories, perceiving a risk for one’s health motivates precautionary behaviors. The “behavioral immune system” approach suggests that social distancing might be triggered as a precautionary, evolutionarily learned behavior to prevent transmitting contagious diseases through social contact. This study examines the link between personal risk perception for an infectious disease and precautionary behavior for disease-prevention in the context of social relationships.MethodsAt 2-week intervals during the first semester, 100 Psychology freshmen indicated their flu risk perception, whether they had been ill during the previous week, and their friendships within their freshmen network for eight time points.ResultsSocial network analysis revealed that participants who reported a high flu risk perception listed fewer friends (B = −0.10, OR = 0.91, p = 0.026), and were more likely to be ill at the next measuring point (B = 0.26, OR = 1.30, p = 0.005). Incoming friendship nominations increased the likelihood of illness (B = 0.14, OR = 1.15, p = 0.008), while the reduced number of friendship nominations only marginally decreased this likelihood (B = −0.07, OR = 0.93, p = 0.052).ConclusionIn accordance with the concept of a “behavioral immune system,” participants with high flu risk perception displayed a social precautionary distancing even when in an environment, in which the behavior was ineffective to prevent an illness.

IMPACT OF INTERNET ADDICTION ON HEALTH ANXIETY IN MALAYSIAN YOUTH DURING COVID-19 PANDEMIC

The COVID-19 The pandemic affected the mental health of people. Individuals prefer to collect information from the Internet about the virus, disease, symptoms, reports on statistics, treatments, and any other information related to the pandemic. In this study, we aimed to explore the impact of Internet use in three different levels of users (Internet addicts, over-users, and average-users) on health anxiety during the pandemic among the young population in Malaysia. Four hundred and forty-eight young adult in Malaysia completed the online survey including demographic questionnaire, Short-form Health Anxiety Inventory, and Internet Addiction Test. Results showed that the Internet addict users have higher scores in the Total Health Anxiety and Health Anxiety factors (Illness Likelihood and Negative Consequences) compared to the average-users and over-users. It seems that high Internet usage is associated with high health anxiety. People may search more on the Internet for information related to the COVID-19 and the symptoms and it may increase their health anxiety. This study provides knowledge implications for mental health professionals about the association between Internet addiction and health anxiety. The findings may provide awareness to the public and professionals about one of the factors that are linked to individuals’ health anxiety during the pandemic.

Investigating the effectiveness of tele-counseling for the mental health of staff in hospitals and COVID-19 clinics: a clinical control trial.

To investigate the effectiveness of tele-counseling for the mental health of staff working in hospitals and reference clinics during the COVID-19 outbreak. In the first stage of the study, using a convenience sampling strategy, 313 staff members working at Iran's hospitals and COVID-19 clinics answered a Hospital Anxiety and Depression Scale and the Short Health Anxiety Inventory online. In a second stage, 95 staff members who were willing to participate in the intervention were randomly assigned to the intervention (n = 51) or control (n = 44) groups. The intervention consisted of seven intensive tele-counseling sessions. In the first stage, the percentages of anxiety and depression related to coronavirus were 79.2% and 82.1% and the mean health anxiety score was 17.42. In the intervention phase, anxiety related to coronavirus and to perceived risk of illness (likelihood of illness) were significantly lower in the intervention group in comparison with the control group (p = 0.001). Depression related to coronavirus and anxiety related to the negative consequences of infection were non-significantly reduced in the intervention group compared to the control group (p = 0.08 and 0.12; respectively). Continuous monitoring of the negative psychological impacts on medical staff of outbreaks as well as implementation of appropriate interventions to respond to them should be emphasized in order to improve staff mental health.

Risk stratification through implementation and evaluation of aCOVID-19 score : Aretrospective diagnostic study

HintergrundDie COVID-19-Erkrankung (Coronavirus Disease 2019) ist in ihrer klinischen Manifestation unspezifisch und sehr variabel, wodurch die Diskriminationsfähigkeit zu anderen (Virus‑)Infekten erschwert ist. Weder Einzelbefunde noch Befundkombinationen sind spezifisch genug, um eine COVID-19-Erkrankung mit hoher Sicherheit diagnostizieren zu können. Ziel war es, in der Notaufnahme durch Anwendung eines Scores frühzeitig Patienten identifizieren zu können, die ein Risiko für eine COVID-19-Erkrankung haben und somit präemptiv isoliert werden müssen.MethodeEntwicklung und Implementierung eines symptombasierten COVID-19-Scores anhand einer multizentrischen retrospektiven Diagnostikstudie in 3 deutschen Notaufnahmen vom 09.03. bis 30.04.2020 an Patienten mit Verdacht auf COVID-19 und anschließender SARS-CoV-2-PCR-Diagnostik.ErgebnisseDas Studienkollektiv umfasste 697 Patienten, bei 9,4 % dieser Patienten wurde eine COVID-19-Infektion diagnostiziert. Ein COVID-19-Score ≥5 Punkte ging mit einer deutlich erhöhten Erkrankungswahrscheinlichkeit einher. Die Sensitivität des Scores lag bei 98,4 % bei einer allerdings mäßigen Spezifität von 48,3 %.SchlussfolgerungDer während der Ersteinschätzung einfach zu erhebende Score unterstützt im Rahmen der Risikostratifizierung die Beurteilung der Vortestwahrscheinlichkeit für eine COVID-19-Infektion und kann frühzeitig den Behandlungspfad bezüglich präemptiver Isolation, PCR-Testung und weiterer Behandlungsoptionen beeinflussen. Aufgrund der unspezifischen Symptomatik der Erkrankung muss allerdings in Kauf genommen werden, dass für das Ziel einer hohen Sensitivität eine relativ geringe Spezifität des Scores resultiert.