Yes / Introduction: Evolution of a patient-reported symptom-based risk stratification system to redesign the suspected head and neck cancer (HNC) referral pathway (EVEREST-HN) will use a broad and open approach to the nomenclature and symptomatology. It aims to capture and utilise the patient reported symptoms in a modern way to identify patients’ clinical problems more effectively and risk stratify the patient. Method: The review followed the PRISMA checklist for scoping reviews. A search strategy was carried out using Medline, Embase and Web of Science between January 1st 2012 and October 31st 2023. All titles, abstracts and full paper were screened for eligibility, papers were assessed for inclusion using predetermined criteria. Data was extracted pertaining to the aims, type of study, cancer type, numbers of patients included and symptoms, presenting complaints or signs and symptoms. Results: There were 9,331 publications identified in the searches, following title screening 350 abstracts were reviewed for inclusion and 120 were considered for eligibility for the review. 48 publications met the eligibility criteria and were included in the final review. Data from almost 11,000 HNC patients was included. Twenty-one of the publications were from the UK, most were retrospective examination of patient records. Data was extracted and charted according to the anatomical area of the head and neck where the symptoms are subjectively and objectively found, and presented according to lay terms for symptoms, clinical terms for symptoms and the language of objective clinical findings. Discussion: Symptoms of HNC are common presenting complaints, interpreting these along with clinical history, examination and risk factors will inform a clinician’s decision to refer as suspected cancer. UK Head and Neck specialists believe a different way of triaging the referrals is needed to assess the clinical risk of an undiagnosed HNC. EVEREST-HN aims to achieve this using the patient history of their symptoms. This review has highlighted issues in terms of what is considered a symptom, a presenting complaint and a clinical finding or sign. / National Institute for Health and Care Research Programme Grant for Applied Research NIHR 202862.

The clinical utility of the Intermediate Category Test, a measure of executive functioning in children 9 to 14 years of age, is currently limited by the availability of only a Total Error score for normative interpretation. The Process Scoring System (PSS) was developed to provide a standardized method of assessing specific processing patterns and problem-solving errors. The purpose of this study was to determine the ability of the PSS scores to discriminate between children with and without suspected executive deficits, thereby providing evidence of criterion-related validity.

Antecedentes: La neumonía es una infección grave común en la infancia y principal causa de muerte en niños menores de 5 años. Se sabe poco sobre escalas que evalúen el riesgo de muerte por neumonía. Objetivos: Establecer qué escala tiene mejor desempeño como predictor de muerte por neumonía adquirida en la comunidad (NAC) en niños menores de cinco años. Métodos: Se realizo un estudio observacional, retrospectivo, analítico con un diseño de precisión diagnóstica en una cohorte de registros clínicos de pacientes con NAC entre 2013 y 2015 en las primeras 24 horas de ingreso al hospital. El desempeño de las tres escalas se evaluó comparando el área bajo la curva (ABC) como medida de capacidad discriminativa. Resultados: La escala PIRO modificada (Predisposition, Insult, Response and Organic dysfunction) tiene mayor capacidad discriminatoria con un ABC de 0,93 (IC del 95%: 0,89 a 0,96), siendo la mejor de las tres escalas evaluados. En segundo lugar, la escala RISC (Respiratory Index of Severity in Children) con ABC 0,83 (IC 95%: 0.79-0.87) y, finalmente, la escala PRESS (Pediatric Respiratory Severity Score) ABC 0.67 (IC 95% 0.61 - 0.74). Conclusión: Las escalas PIROm y RISC son buenos predictores de muerte en niños menores de 59 meses, basados en criterios clínicos, radiológicos y laboratoriales. La primera escala podría ser utilizada en centros de salud de mayor complejidad. La segunda escala netamente clínica podría ser utilizada en centros de atención primaria de salud. Se sugiere realizar más estudios en poblaciones con diversas características clínicas, demográficas y ambientales. / Background: Pneumonia is a common serious infection in childhood, being the major cause of death in children under 5 years. Little is kwon about clinical scales predicting risk of death owing to pneumonia Objectives: Establish which scale has better performance as a predictor of death due to community-acquired pneumonia (CAP) in children under five years. Methods: An observational, retrospective, analytical study with a diagnostic precision design was conducted in a cohort of clinical records of patients with CAP between 2013 and 2015 that were review in the first 24 hours of admission to the hospital. The performance of the three scales were evaluated by the comparison of the area under the curve (AUC) as a measure of discriminative capacity. Results: The PIRO modified scale (Predisposition, Insult, Response and Organic dysfunction) has greater discrimination capacity AUC of 0.93 (95% CI 0.89 - 0.96) being the best of the three evaluated. Secondly, the RISC scale (Respiratory Severity Index in children) with AUC 0.83 (95% CI: 0.79-0.87) and, finally, the PRESS scale (Pediatric Respiratory Severity Score) AUC 0.67 (95% CI 0.61 - 0.74). Conclusion: The PIROm and RISC scales are good predictors of death in children under 59 months, based on clinical, radiological and laboratory criteria. The first scale could be used in healthcare centers of higher complexity. The second scale purely clinical could be used in centers of primary health care attention. It is suggested to carry out more studies in diverse populations with different clinical, demographical and environmental characteristics. / Tesis

<p>The severity of illness was scored in a cohort of 11751 non-surgical patients presenting at the Emergency Department (ED) during 12 consecutive months and followed for 4.7 years. The scoring system Rapid Acute Physiology score (RAPS) (including blood pressure, respiratory rate, pulse rate and Glasgow coma scale) was calculated for all arrivals at the ED. The RAPS system was also additionally developed by including the peripheral oxygen saturation and patient age, resulting in the new Rapid Emergency Medicine Score, (REMS). REMS was superior to RAPS in predicting in-hospital mortality according to ROC-curve analysis. An increase of one point in the 26 point REMS scale was associated with an Odds ratio of 1.40 for in-hospital death (95% CI 1.36-1.45, p<0.0001). Similar results were obtained in the major patient groups (chest pain, stroke, coma, dyspnea and diabetes). The association between REMS and length of stay in hospital was modest. Charlson Co-morbidity Index could add prognostic information to REMS in a long-term (4.7 years), but not in a short-term perspective (3 and 7 days). REMS was shown to be as powerful a predictor of in-hospital mortality as the more complicated APACHE II. REMS at the ED could also predict long-term mortality (4.7 years) in the total cohort (Hazard ratio 1.26, p<0.0001).</p><p>REMS is a potentially useful prognostic tool for non-surgical patients at the ED, regarding both in-hospital and long-term mortality. It is less complicated to use than APACHE II and has equal predictive accuracy.</p>

The severity of illness was scored in a cohort of 11751 non-surgical patients presenting at the Emergency Department (ED) during 12 consecutive months and followed for 4.7 years. The scoring system Rapid Acute Physiology score (RAPS) (including blood pressure, respiratory rate, pulse rate and Glasgow coma scale) was calculated for all arrivals at the ED. The RAPS system was also additionally developed by including the peripheral oxygen saturation and patient age, resulting in the new Rapid Emergency Medicine Score, (REMS). REMS was superior to RAPS in predicting in-hospital mortality according to ROC-curve analysis. An increase of one point in the 26 point REMS scale was associated with an Odds ratio of 1.40 for in-hospital death (95% CI 1.36-1.45, p&lt;0.0001). Similar results were obtained in the major patient groups (chest pain, stroke, coma, dyspnea and diabetes). The association between REMS and length of stay in hospital was modest. Charlson Co-morbidity Index could add prognostic information to REMS in a long-term (4.7 years), but not in a short-term perspective (3 and 7 days). REMS was shown to be as powerful a predictor of in-hospital mortality as the more complicated APACHE II. REMS at the ED could also predict long-term mortality (4.7 years) in the total cohort (Hazard ratio 1.26, p&lt;0.0001). REMS is a potentially useful prognostic tool for non-surgical patients at the ED, regarding both in-hospital and long-term mortality. It is less complicated to use than APACHE II and has equal predictive accuracy.

Abstract The aim of the studie was to investigate if the Pediatric Early Warning Score system, PEWS, is an useful instrument on a children's inpatient ward, regarding the detecting of deterioration in children's vital signs. For this, a quantitative descriptive design with qualitative elements was used. Method: Study specific questionnaires were distributed to 86 persons (helpnurses, nurses and doctors). Of these, 36 answered and sent back the surveys. Results: Of 36 responses 25 felt experienced a faster detection of deterioration of vital signs in the child. Many felt that they had faster response from the physician on call by providing an assessment figure of the child's condition. Conclusion: Most of the persons experienced that the use of the assessment intrument PEWS detected a deterioration of the child´s vital signs earlier than before using the instrument. Staff experienced greater security in their work when they had a tool to help and they also experienced an earlier response from physicians. / SAMMANFATTNING   Syftet med studien var att undersöka om bedömningsinstrumentet Pediatric Early Warning Score, PEWS, är till användning och vägledning på barnavdelning med avseende att upptäcka försämring av barns vitalparametrar. För detta användes en beskrivande kvantitativ design med kvalitativa inslag. Metod: Ett studiespecifikt enkätformulär gick ut till 86 personer (undersköterskor, sjuksköterskor och läkare på två pediatriska vårdavdelningar). Av dessa besvarades 36 enkäter. Resultat: Av 36 svarande ansåg 25 att man snabbare upptäckte försämring av vitalparametrarna hos barnet. Många ansåg att de fick snabbare gensvar från jourläkare genom att uppge en bedömningssiffra över barnets hälsotillstånd. Slutsats: Med hjälp av bedömningsinstrumentet PEWS upplevde personalen att en upptäckt av försämring av barnets vitalparametrar gjordes tidigare, samt att gensvar från jourläkare erhölls snabbare. Personalen upplevde en ökad trygghet i sitt arbete då man hade ett arbetsredskap till hjälp.

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It is widely accepted that modern computer networks (often presented as a heterogeneous collection of functioning organisations, applications, software, and hardware) contain vulnerabilities. This research proposes a new methodology to compute a dynamic severity cost for each state. Here a state refers to the behaviour of a system during an attack; an example of a state is where an attacker could influence the information on an application to alter the credentials. This is performed by utilising a modified variant of the Common Vulnerability Scoring System (CVSS), referred to as a Dynamic Vulnerability Scoring System (DVSS). This calculates scores of intrinsic, time-based, and ecological metrics by combining related sub-scores and modelling the problem’s parameters into a mathematical framework to develop a unique severity cost. The individual static nature of CVSS affects the scoring value, so the author has adapted a novel model to produce a DVSS metric that is more precise and efficient. In this approach, different parameters are used to compute the final scores determined from a number of parameters including network architecture, device setting, and the impact of vulnerability interactions. An attack graph (AG) is a security model representing the chains of vulnerability exploits in a network. A number of researchers have acknowledged the attack graph visual complexity and a lack of in-depth understanding. Current attack graph tools are constrained to only limited attributes or even rely on hand-generated input. The automatic formation of vulnerability information has been troublesome and vulnerability descriptions are frequently created by hand, or based on limited data. The network architectures and configurations along with the interactions between the individual vulnerabilities are considered in the method of computing the Cost using the DVSS and a dynamic cost-centric framework. A new methodology was built up to present an attack graph with a dynamic cost metric based on DVSS and also a novel methodology to estimate and represent the cost-centric approach for each host’ states was followed out. A framework is carried out on a test network, using the Nessus scanner to detect known vulnerabilities, implement these results and to build and represent the dynamic cost centric attack graph using ranking algorithms (in a standardised fashion to Mehta et al. 2006 and Kijsanayothin, 2010). However, instead of using vulnerabilities for each host, a CostRank Markov Model has developed utilising a novel cost-centric approach, thereby reducing the complexity in the attack graph and reducing the problem of visibility. An analogous parallel algorithm is developed to implement CostRank. The reason for developing a parallel CostRank Algorithm is to expedite the states ranking calculations for the increasing number of hosts and/or vulnerabilities. In the same way, the author intends to secure large scale networks that require fast and reliable computing to calculate the ranking of enormous graphs with thousands of vertices (states) and millions of arcs (representing an action to move from one state to another). In this proposed approach, the focus on a parallel CostRank computational architecture to appraise the enhancement in CostRank calculations and scalability of of the algorithm. In particular, a partitioning of input data, graph files and ranking vectors with a load balancing technique can enhance the performance and scalability of CostRank computations in parallel. A practical model of analogous CostRank parallel calculation is undertaken, resulting in a substantial decrease in calculations communication levels and in iteration time. The results are presented in an analytical approach in terms of scalability, efficiency, memory usage, speed up and input/output rates. Finally, a countermeasures model is developed to protect against network attacks by using a Dynamic Countermeasures Attack Tree (DCAT). The following scheme is used to build DCAT tree (i) using scalable parallel CostRank Algorithm to determine the critical asset, that system administrators need to protect; (ii) Track the Nessus scanner to determine the vulnerabilities associated with the asset using the dynamic cost centric framework and DVSS; (iii) Check out all published mitigations for all vulnerabilities. (iv) Assess how well the security solution mitigates those risks; (v) Assess DCAT algorithm in terms of effective security cost, probability and cost/benefit analysis to reduce the total impact of a specific vulnerability.

<p>Despite an emphasis on oral communication in most foreign language classrooms, the resource-intensive nature (i.e. time and manpower) of speaking tests hinder regular oral assessments. A possible solution is the development of a (semi-) automated scoring system. When it is used in conjunction with human raters, the consistency of computers can complement human raters’ comprehensive judgments and increase efficiency in scoring (e.g., Enright & Quinlan, 2010). In search of objective and quantifiable variables that are strongly correlated with overall oral proficiency, a number of studies have reported that some utterance fluency variables (e.g., speech rate and mean length of run) might be strong predictors for L2 learners’ speaking ability (e.g., Ginther et al., 2010; Hirotani et al., 2017). However, these findings are difficult to generalize due to small sample sizes, narrow ranges of proficiency levels, and/or a lack of data from languages other than English. The current study analyzed spontaneous speech samples collected from 170 Japanese learners at a wide range of proficiency levels determined by a well-established speaking test, the American Council on the Teaching of Foreign Languages’ (ACTFL) Oral Proficiency Interview (OPI). Prior to analysis, 48 <i>Complexity, Accuracy, Fluency</i> (CAF) measures (with a focus on fluency variables) were calculated from the speech samples. First, the study examined the relationships among the CAF measures and learner oral proficiency assessed by the ACTFL OPI. Then, using an empirically-based approach, a feasibility of using a composite measure to predict L2 oral proficiency was investigated. The results revealed that <i>Speech Speed</i> and <i>Complexity</i> variables demonstrated strong correlation to the OPI levels, and moderately strong correlations were found for the variables in the following categories: <i>Speech Quantity, Pause</i>, <i>Pause Location</i> (i.e., Silent pause ratio within AS-unit), <i>Dysfluency</i> (i.e., Repeat ratio), and <i>Accuracy.</i> Then, a series of multiple regression analyses revealed that a combination of five CAF measures (i.e., Effective articulation rate, Silent pause ratio, Repeat ratio, Syntactic complexity, and Error-free AS-unit ratio) can predict 72.3% of the variance of the OPI levels. This regression model includes variables that correspond to Skehan’s (2009) proposed three categories of fluency (speed, breakdown, and repair) and variables that represent CAF, supporting the literature (e.g., Larsen-Freeman, 1978, Skehan, 1996).</p>

The purpose of this study was to investigate if early childhood educators could reliably score items using a new scoring system for the Assessment, Evaluation, and Programming System for Infants and Children (AEPS; Bricker, 2002). The participants were university students completing their certification in Interdisciplinary Early Childhood Education (IECE) at the University of Kentucky (UK). The six participants completed training on implementing the AEPS and administered the AEPS to measure child outcomes. The results of this study validated the new scoring system for the AEPS by illustrating that the participants could reliably score a curriculum based assessment.