Two main psychopathology-based approaches to detection of the prodrome have emerged; the Ultra High Risk (UHR) and Basic Symptom approaches. Conversion risk varies between studies using these approaches and in one centre conversion rates are reported to be decreasing year on year. There is a need examine the conversion risk across studies to establish a pooled estimate of risk for instruments designed to detect the prodrome of psychosis. To maximise the detection of those thought to present a risk of psychosis the Lancashire Early Assessment and Detection (LEAD) clinic uses an UHR instrument, the Comprehensive Assessment of at Risk Mental States (CAARMS) and A Basic Symptom instrument, the Schizophrenia Proneness Instrument (SPI-A). The thesis had two broad aims 1) to conduct a systematic review with meta-analysis of the research field to date and identify areas for further research, 2) to establish the accuracy of the LEAD clinic predictions. The meta-analysis involved a systematic search of MEDLINE, EMBASE, PsychINFO and CINHAL identifying studies of psychopathology-based instruments for the detection of the psychosis prodrome. The service evaluation examined for conversion to psychosis in patients examined for Basic Symptoms (SPI-A), attenuated positive symptoms (CAARMS), schizotypy (SPQ-A) and social functioning (SOFAS).The meta-analysis found that both the UHR and Basic Symptom approaches yield similar results. The differences in the positive predictive values (PPV) of the two approaches were not significant (Basic Symptoms, 0.34, UHR 0.25). The service evaluation found over a third (n=58) of referrals to the LEAD clinic to be psychotic at baseline and sixty-four patients to have an at risk mental state (ARMS). Conversion risk for CAARMS was 36.67%. and was 28.57% for SPI-A. The COGDIS criterion of SPI-A was found to be the most predictive with a PPV of 0.43, a sensitivity of 0.80. When patients met a combination of both COGDIS and CAARMS the likelihood ratio increased to 5.25 although the sensitivity was low (0.47).Overall, the findings of the thesis indicate that both the Basic Symptom and UHR approaches are valid for use in routine clinical settings for the assessment of psychosis risk. The thesis found that a combination of both approaches could provide future opportunities research. The SPQ-A schizotypy assessment was found to correlate with the attenuated symptom criterion of CAARMS and evidence suggests that the SPQ-A score increases closer to transition. The SPQ-A could offer opportunities for developing efficient methods of monitoring progression of prodromal symptoms.

<p>Rak dojke je trenutno po incidenciji vodeća maligna bolest kod žena kako u razvijenim tako i u zemljama u razvoju. Osnovni cilj istraživanja bio je da se defini&scaron;u faktori rizika u populaciji žena uzrasta 50-69 godina koje su obuhvaćene Nacionalnim skrining programom ranog otkrivanja raka dojke mamografijom na teritoriji Autonomne Pokrajine Vojvodine (APV). U istraživanju je kori&scaron;ćena retrospektivno-prospektivna studija. Za potrebe istraživanja formirana je grupa obolelih žena i kontrolna grupa žena na teritoriji APV. Istraživanje je obuhvatilo 510 žena sa teritorije AP Vojvodine, uzrasta od 50 do 69 godina. Rezultati istraživanja pokazali su da su se kao značajni prediktori raka dojke u na&scaron;em istraživanju izdvojili: 1. Hormonska terapija &ndash; one osobe koje su uzimale hormonsku terapiju značajno imaju veću verovatnoću da imaju rak dojke i obrnuto. 2. Prethodna maligna bolest &ndash; osobe koje su prethodno imale neku drugu malignu bolest imaju manju &scaron;ansu da imaju rak dojke&nbsp; 3. One žene koje vr&scaron;e samokontrolu dojke če&scaron;će su u nekliničkom uzorku. 4. Žene koje su u grupi starijih su če&scaron;će u kliničkom uzorku. 5. One osobe koje imaju u porodici nekog ko je oboleo od raka dojke če&scaron;će i same oboljevaju. Ovo je prvo istraživanje o faktorima rizika za rak dojke na populaciji žena AP Vojvodine u okviru Nacionalnog programa ranog otkrivanja raka dojke. Rezultati istraživanja daju osnove za buduća istraživanja iz ove oblasti, takođe mogu da utiču na podizanje svesti žena o značaju redovnih pregleda i ranom otkrivanju raka dojke kao i pružanje podr&scaron;ke programu skrininga.</p> / <p>Breast cancer is currently theleading malignant disease in women both in developed and developing countries. The main goal of the research was to define risk factors in the population of women aged 50-69 years, covered by the National Screening Program for Early Detection of Breast Cancer by Mammography on the territory of the Autonomous Province of Vojvodina. The researchwasconducted asretrospective-prospective study. For the purpose of the research,were formed a group of diseased women and a control group of women in the territory of AP Vojvodina . The research involved 510 women with the territory of AP Vojvodina, aged 50 to 69 years. The results of the study showed that as significant predictors ofbreast cancer in our study. 1.Hormone Therapy -Those who have taken hormone therapy are significantly more likely to have breast cancer and vice versa. 2. Pre-existing malignant disease -people who previously had any other malignant disease have a lowerchance of having breast cancer 3. Women who perform self-control of their breasts are more often in a non-clinical sampl.e 4. Women in the elderly group are more often in the clinical sample. 5. Those who have a family member who has breast cancer are more likely to suffer from their own illness. This is the first study on the risk factors for breast cancer in the population of AP Vojvodina women within the National Breast Cancer Screening Program. The results of the research provide the basics for future research in this area, they can also help raise women&#39;s awareness of the importance of regular screening and early detection of breast cancer, as well as supporting the screening program</p>

No description available.

Le dépistage du cancer de la prostate est largement controversé de par l’équilibre de la balance bénéfices-risques de cette procédure. L’enjeu de santé publique est alors d’accompagner au mieux les hommes susceptibles de se faire dépister pour qu’ils puissent être informés et participer au choix. L’objectif de ce doctorat est de contribuer à comprendre pourquoi les hommes participent au dépistage du cancer de la prostate, pour pouvoir améliorer dans un second temps leur accompagnement. Nous avons tout d’abord interrogé des hommes sur leurs connaissances, leurs sources d’informations et leur rôle dans le choix de participer au dépistage du cancer de la prostate. Ces entretiens ont abouti à la nécessité de concevoir un nouvel outil d’information pour améliorer les connaissances des hommes, en particulier sur les risques de la procédure de dépistage. Enfin, nous avons estimé comment les bénéfices et les risques étaient intégrés dans le choix des individus selon si ces derniers avaient eu accès à notre outil d’information. Les résultats de ce travail montrent que les hommes semblent moins favorables à une proposition de dépistage après avoir eu accès à notre outil d’information. Cependant, cela ne modifie pas leur appréciation des bénéfices et des risques du dépistage. Il est nécessaire de poursuivre les efforts pour permettre aux hommes de faire un choix éclairé. / Prostate cancer screening is highly controversial because of the benefit risk ratio. An issue is to support men susceptible to perform this screening towards informed choice and shared decision-making. The aim of this doctorate is to understand why men adhere to prostate cancer screening, and in a second time to improve their support. We interviewed men about their knowledge, their information seeking behaviour, and their implication in prostate cancer screening decision. This highlighted the necessity to create a new information tool to improve men’s knowledge, in particular regarding risks of the screening procedure. Finally, we investigate benefit risk trade-off with and without our information tool access. Results of this work shows that men are less favourable to a screening option after taking into account our information tool. However, benefit and risk of this screening appreciation was not changed. We need to continue efforts to allow men to make an informed choice.

Objective: Prospective study designs ideally allow patients to be followed from the first manifestations of the illness or even from an at-risk stage. It can thus provide data on the predictive value of changes in clinical symptomatology, cognition or further biological markers to broaden our understanding of the etiopathology and symptomatic trajectory of bipolar disorders. The scope of this narrative review is to summarize evidence from prospectively collected data on psychopathological and other clinical and biological changes in the early developmental course of bipolar disorders. Methods: The narrative review was based on a literature search conducted in February 2016 within the PubMed library for prospective study data of persons in antecedent and early manifest stages of manifest bipolar disorder published within the last 15 years. Results: A total of 19 prospective studies were included. Regarding psychopathological features; personality, temperament and character traits as well as changes in sleep and circadian rhythm, the evidence suggests that risk factors for the development of bipolar disorder can already be described and should be studied further to understand their interaction, mediation with other factors and timing in the developmental process of bipolar disorder. Apart from the positive family history, childhood anxiety, sleep problems, subthreshold (hypo)manic symptoms and certain character traits/emotionality should be identified and monitored already in clinical practice as their presence likely increases risk of bipolar disorder. Up to date no substantiated evidence was found from prospective studies addressing cognitive features, life events, immunological parameters and morphological central nervous system changes as potential risk factors for bipolar disorder. Conclusion: For an improved understanding of episodic disorders, longitudinal data collection is essential. Since the etiology of bipolar disorders is complex, a number of potential risk factors have been proposed. Prospective studies addressing this spectrum and resilience factors are critical and will be best conducted within multi-site research networks or initiatives.

No description available.

Since the field of computer networks has rapidly grown in the last two decades, congestion control of traffic loads within networks has become a high priority. Congestion occurs in network routers when the number of incoming packets exceeds the available network resources, such as buffer space and bandwidth allocation. This may result in a poor network performance with reference to average packet queueing delay, packet loss rate and throughput. To enhance the performance when the network becomes congested, several different active queue management (AQM) methods have been proposed and some of these are discussed in this thesis. Specifically, these AQM methods are surveyed in detail and their strengths and limitations are highlighted. A comparison is conducted between five known AQM methods, Random Early Detection (RED), Gentle Random Early Detection (GRED), Adaptive Random Early Detection (ARED), Dynamic Random Early Drop (DRED) and BLUE, based on several performance measures, including mean queue length, throughput, average queueing delay, overflow packet loss probability, packet dropping probability and the total of overflow loss and dropping probabilities for packets, with the aim of identifying which AQM method gives the most satisfactory results of the performance measures. This thesis presents a new AQM approach based on the RED algorithm that determines and controls the congested router buffers in an early stage. This approach is called Dynamic RED (REDD), which stabilises the average queue length between minimum and maximum threshold positions at a certain level called the target level to prevent building up the queues in the router buffers. A comparison is made between the proposed REDD, RED and ARED approaches regarding the above performance measures. Moreover, three methods based on RED and fuzzy logic are proposed to control the congested router buffers incipiently. These methods are named REDD1, REDD2, and REDD3 and their performances are also compared with RED using the above performance measures to identify which method achieves the most satisfactory results. Furthermore, a set of discrete-time queue analytical models are developed based on the following approaches: RED, GRED, DRED and BLUE, to detect the congestion at router buffers in an early stage. The proposed analytical models use the instantaneous queue length as a congestion measure to capture short term changes in the input and prevent packet loss due to overflow. The proposed analytical models are experimentally compared with their corresponding AQM simulations with reference to the above performance measures to identify which approach gives the most satisfactory results. The simulations for RED, GRED, ARED, DRED, BLUE, REDD, REDD1, REDD2 and REDD3 are run ten times, each time with a change of seed and the results of each run are used to obtain mean values, variance, standard deviation and 95% confidence intervals. The performance measures are calculated based on data collected only after the system has reached a steady state. After extensive experimentation, the results show that the proposed REDD, REDD1, REDD2 and REDD3 algorithms and some of the proposed analytical models such as DRED-Alpha, RED and GRED models offer somewhat better results of mean queue length and average queueing delay than these achieved by RED and its variants when the values of packet arrival probability are greater than the value of packet departure probability, i.e. in a congestion situation. This suggests that when traffic is largely of a non bursty nature, instantaneous queue length might be a better congestion measure to use rather than the average queue length as in the more traditional models.

Autism Spectrum Disorder (ASD) is a condition that carries high costs for families and the healthcare system, requiring extensive management both in terms of diagnosis and treatment. The implementation of AI-based systems in clinical practice represents a possible supportive solution that can help clinicians by providing more systematic meth- ods to monitor child behavior. The main advantage over more traditional observational approaches is to offer quantitative and refined analysis solutions that can be ecological at the same time. The relevance of AI in clinical applications can have a role both in the challenge of early detection and in designing intervention programs better tai- lored to the specific functioning of children with ASD. The research project presented in this dissertation focused on developing AI-based systems for fine-grained analysis of autism-related social behaviors and their validation in concrete clinical environments. Specifically, in Chapter 2, our first study is presented, which targets on implementing a computational phenotyping system to address the need for new early markers of the condition. Through fine-grained analytics of facial dynamics in videos, we identified a set of features that distinguished young (6-12 months) infants with ASD (18 ASD, 15 non-ASD) during unconstrained at-home interactions. In Chapters 3 and 4, we introduce EYE-C, a Behavior Imaging model for robust analysis of eye contact episodes in eco- logical therapist-child interactions. The system was validated in the clinical setting for personalized early intervention. First, we investigated the influence of extracted features in categorizing spectrum heterogeneity across a sample of 62 preschool (&lt;6 years) chil- dren with ASD. Further, we tested our metrics as predictors of early intensive treatment outcomes in a sub-sample of 18 subjects with ASD. The project aims to demonstrate the feasibility of effective computational systems that are robust to the high variability of unstructured interactions, with emphasis on the applicative value in real-world scenar- ios. Even though based on limited sample sizes, the work presented may offer interesting insights into the perspective of integrating AI into clinical practice. The research project was funded by an FBK scholarship and developed in a double in- ternship at ODFLab (University of Trento) and the FBK Data Science for Health (DSH) research unit.

No / Traffic congestion in communication networks can dramatically deteriorate user-perceived Quality-of-Service (QoS). The integration of the Random Early Detection (RED) and priority scheduling mechanisms is a promising scheme for congestion control and provisioning of differentiated QoS required by multimedia applications. Although analytical modelling of RED congestion control has received significant research efforts, the performance models reported in the current literature were primarily restricted to the RED algorithm only without consideration of traffic scheduling scheme for QoS differentiation. Moreover, for analytical tractability, these models were developed under the simplified assumption that the traffic follows Short-Range-Dependent (SRD) arrival processes (e.g., Poisson or Markov processes), which are unable to capture the self-similar nature (i.e., scale-invariant burstiness) of multimedia traffic in modern communication networks. To fill these gaps, this paper presents a new analytical model of RED congestion control for prioritized multi-class self-similar traffic. The closed-form expressions for the loss probability of individual traffic classes are derived. The effectiveness and accuracy of the model are validated through extensive comparison between analytical and simulation results. To illustrate its application, the model is adopted as a cost-effective tool to investigate the optimal threshold configuration and minimize the required buffer space with congestion control.

La detección del autismo por parte del profesional de enfermería permite la intervención temprana del trastorno del espectro autista, disminuyendo su sintomatología que presenta el niño con autismo. Método: Investigación cualitativa, con abordaje descriptivo. Objetivo: Describir las nociones sobre la detección temprana del autismo en profesionales de enfermería en la Microred de salud Lambayeque, 2022. Muestra: 12 profesionales de enfermería que laboran en el servicio integral del niño de la Microred de salud Lambayeque; el muestreo fue no probabilístico por conveniencia, con criterios de inclusión y exclusión, los datos se recolectaron mediante una guía de entrevista semiestructurada, validada por juicio de expertos y prueba piloto previa aprobación del comité de ética, el análisis fue de contenido; se cumplió con los principios de rigor ético y científico. Se obtuvieron 4 categorías: (1) Nociones relacionadas con la detección del autismo desde la atención primaria de salud, (2) Conceptualizando el autismo desde los saberes de los profesionales de enfermería, (3) Reconociendo el rol que deben tener los profesionales de enfermería en la detección precoz del autismo, (4) Necesidad de incluir el autismo en la formación académica, educacióncontinua y planes de capacitación del profesional de enfermería. Conclusiones: Los conocimientos del profesional de enfermería sobre el autismo son superficiales, al parecer el autismo resulta en nuestro medio un trastorno en general poco conocido. / The detection of autism by the nursing professional allows early intervention of autism spectrum disorder, reducing the symptoms presented by the child with autism. Method: Qualitative research, with a descriptive approach. Objective: Describe the notions about the early detection of autism in nursing professionals in the Lambayeque Health Micronetwork, 2022. Sample: 12 nursing professionals who work in the comprehensive child service of the Lambayeque Health Micronetwork; The sampling was non-probabilistic for convenience, with inclusion and exclusion criteria, the data were collected using a semi-structured interview guide, validated by expert judgment and pilot testing prior approval of the ethics committee, the analysis was content; The principles of ethical and scientific rigor were complied with. 4 categories were obtained: (1) Notions related to the detection of autism from primary health care, (2) Conceptualizing autism from the knowledge of nursing professionals, (3) Recognizing the role that nursing professionals should have in early detection of autism, (4) Need to include autism in the academic training, continuing education and training plans of nursing professionals. Conclusions: The knowledge of the nursing professional about autism is superficial; it seems that autism is a generally little- known disorder in our environment.