EPA guidance on the early detection of clinical high risk states of psychoses

The aim of this guidance paper of the European Psychiatric Association is to provide evidence-based recommendations on the early detection of a clinical high risk (CHR) for psychosis in patients with mental problems. To this aim, we conducted a meta-analysis of studies reporting on conversion rates to psychosis in non-overlapping samples meeting any at least any one of the main CHR criteria: ultra-high risk (UHR) and/or basic symptoms criteria. Further, effects of potential moderators (different UHR criteria definitions, single UHR criteria and age) on conversion rates were examined. Conversion rates in the identified 42 samples with altogether more than 4000 CHR patients who had mainly been identified by UHR criteria and/or the basic symptom criterion ‘cognitive disturbances’ (COGDIS) showed considerable heterogeneity. While UHR criteria and COGDIS were related to similar conversion rates until 2-year follow-up, conversion rates of COGDIS were significantly higher thereafter. Differences in onset and frequency requirements of symptomatic UHR criteria or in their different consideration of functional decline, substance use and co-morbidity did not seem to impact on conversion rates. The ‘genetic risk and functional decline’ UHR criterion was rarely met and only showed an insignificant pooled sample effect. However, age significantly affected UHR conversion rates with lower rates in children and adolescents. Although more research into potential sources of heterogeneity in conversion rates is needed to facilitate improvement of CHR criteria, six evidence-based recommendations for an early detection of psychosis were developed as a basis for the EPA guidance on early intervention in CHR states.

Early detection of psychosis: helpful or stigmatizing experience? A qualitative study

AIM Despite the large scientific debate concerning potential stigmatizing effects of identifying an individual as being in an at-risk mental state (ARMS) for psychosis, studies investigating this topic from the subjective perspective of patients are rare. This study assesses whether ARMS individuals experience stigmatization and to what extent being informed about the ARMS is experienced as helpful or harmful. METHODS Eleven ARMS individuals, currently participating in the follow-up assessments of the prospective Basel Früherkennung von Psychosen (FePsy; English: Early Detection of Psychosis) study, were interviewed in detail using a semistructured qualitative interview developed for this purpose. Data were analysed using Interpretative Phenomenological Analysis. RESULTS Most individuals experiencing first symptoms reported sensing that there was 'something wrong with them' and felt in need of help. They were relieved that a specific term was assigned to their symptoms. The support received from the early detection centre was generally experienced as helpful. Many patients reported stigmatization and discrimination that appeared to be the result of altered behaviour and social withdrawal due to the prepsychotic symptoms they experienced prior to contact with the early detection clinic. CONCLUSIONS The results suggest that early detection services help individuals cope with symptoms and potential stigmatization rather than enhancing or causing the latter. More emphasis should be put on the subjective experiences of those concerned when debating the advantages and disadvantages of early detection with regard to stigma. There was no evidence for increased perceived stigma and discrimination as a result of receiving information about the ARMS.

Experiences with a voluntary surveillance system for early detection of equine diseases in Switzerland

Clinical observations made by practitioners and reported using web- and mobile-based technologies may benefit disease surveillance by improving the timeliness of outbreak detection. Equinella is a voluntary electronic reporting and information system established for the early detection of infectious equine diseases in Switzerland. Sentinel veterinary practitioners have been able to report cases of non-notifiable diseases and clinical symptoms to an internet-based platform since November 2013. Telephone interviews were carried out during the first year to understand the motivating and constraining factors affecting voluntary reporting and the use of mobile devices in a sentinel network. We found that non-monetary incentives attract sentinel practitioners; however, insufficient understanding of the reporting system and of its relevance, as well as concerns over the electronic dissemination of health data were identified as potential challenges to sustainable reporting. Many practitioners are not yet aware of the advantages of mobile-based surveillance and may require some time to become accustomed to novel reporting methods. Finally, our study highlights the need for continued information feedback loops within voluntary sentinel networks.

A supervised cooperative learning system for early detection of language disorders

The Quality of Life of a person may depend on early attention to his neurodevel-opment disorders in childhood. Identification of language disorders under the age of six years old can speed up required diagnosis and/or treatment processes. This paper details the enhancement of a Clinical Decision Support System (CDSS) aimed to assist pediatricians and language therapists at early identification and re-ferral of language disorders. The system helps to fine tune the Knowledge Base of Language Delays (KBLD) that was already developed and validated in clinical routine with 146 children. Medical experts supported the construction of Gades CDSS by getting scientific consensus from literature and fifteen years of regis-tered use cases of children with language disorders. The current research focuses on an innovative cooperative model that allows the evolution of the KBLD of Gades through the supervised evaluation of the CDSS learnings with experts¿ feedback. The deployment of the resulting system is being assessed under a mul-tidisciplinary team of seven experts from the fields of speech therapist, neonatol-ogy, pediatrics, and neurology.

High-sensitivity array analysis of gene expression for the early detection of disseminated breast tumor cells in peripheral blood

Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P ≤ 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 × 108 transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.

Developing a Citizen Volunteer Lake Monitoring Program for the Flathead Basin in Northwestern Montana for the early Detection and Prevention of the Introduction of Zebra Mussels and other Aquatic Invasive Species (AIS)

Preventing the introduction of aquatic invasive species (AIS) like zebra and quagga mussels in the U.S. is a high priority. This Capstone demonstrates zebra and quagga mussels are of concern as aquatic invasive species and a volunteer monitoring and intervention program is an effective means for early detection of AIS. This Capstone developed an AIS citizen volunteer lake monitoring program consistent with other programs concerned about AIS prevention and early detection. This Capstone concludes implementing such a voluntary program will help reduce the spread of zebra and quagga mussels and will provide early detection information to appropriate agencies empowered with response actions if species are found.

Sentiment classification for early detection of health alerts in the chemical textile domain

In the chemical textile domain experts have to analyse chemical components and substances that might be harmful for their usage in clothing and textiles. Part of this analysis is performed searching opinions and reports people have expressed concerning these products in the Social Web. However, this type of information on the Internet is not as frequent for this domain as for others, so its detection and classification is difficult and time-consuming. Consequently, problems associated to the use of chemical substances in textiles may not be detected early enough, and could lead to health problems, such as allergies or burns. In this paper, we propose a framework able to detect, retrieve, and classify subjective sentences related to the chemical textile domain, that could be integrated into a wider health surveillance system. We also describe the creation of several datasets with opinions from this domain, the experiments performed using machine learning techniques and different lexical resources such as WordNet, and the evaluation focusing on the sentiment classification, and complaint detection (i.e., negativity). Despite the challenges involved in this domain, our approach obtains promising results with an F-score of 65% for polarity classification and 82% for complaint detection.

A simplified PCR test for early detection of dwarf off-types in micropropagated Cavendish bananas (Musa spp. AAA)

The dwarf somaclonal variant is a major problem affecting micropropagation of the banana cultivar Williams (Musa spp. AAA; subgroup Cavendish). This problem arises from genetic changes that occur during the tissue culture process. Early identification of this problem is difficult and propagators must wait until plants are ex vitro in order to visualise the dwarfism phenotype. In this study, we have improved a SCAR-based molecular diagnostic technique, developed by Damasco et al. [Acta Hortic. 461 (1997) 157], for the early identification of dwarf off-types. We have included a positive internal control in a multiplex PCR and adapted the technique for use with small amounts of fresh in vitro leaf material as PCR template. The control product is a 500 bp fragment from 18S rRNA and is amplified in all tissues irrespective of phenotype. The use of small in vitro leaf material removing the need for genomic DNA extraction. (C) 2004 Elsevier B.V. All rights reserved.

The use of cusum analysis in the early detection and management of hospital bed occupancy crises

Objective: To assess the value of cusum analysis in hospital bed management. Design: Comparative analysis of medical patient flows, bed occupancy, and emergency department admission rates and access block over 2 years. Setting: Internal Medicine Services and Emergency Department in a teaching hospital. Interventions: Improvements in bed use and changes in the level of available beds. Main outcome measures: Average length of stay; percentage occupancy of available beds; number of patients waiting more than 8 hours for admission (access block); number of medical patients occupying beds in non-medical wards; and number of elective surgical admissions. Results: Cusum analysis provided a simple means of revealing important trends in patient flows that were not obvious in conventional time-series data. This prompted improvements in bed use that resulted in a decrease of 9500 occupied bed-days over a year. Unfortunately and unexpectedly, after some initial improvement, the levels of access block, medical ward congestion and elective surgical admissions all then deteriorated significantly. This was probably caused by excessive bed closures in response to the initial improvement in bed use. Conclusion: Cusum analysis is a useful technique for the early detection of significant changes in patient flows and bed use, and in determining the appropriate number of beds required for a given rate of patient flow.

An educational workshop on the early detection of prostate cancer

The authors have developed an education program for GPs to facilitate informed choice about PSA testing.