Comparing hospital and telephone follow-up after treatment for breast cancer: randomised equivalence trial

Objective To compare traditional hospital follow-up with telephone follow-up by specialist nurses after treatment for breast cancer. Design A two centre randomised equivalence trial in which women remained in the study for a mean of 24 months. Setting Outpatient clinics in two NHS hospital trusts in the north west of England Participants 374 women treated for breast cancer who were at low to moderate risk of recurrence. Interventions Participants were randomised to traditional hospital follow-up (consultation, clinical examination, and mammography as per hospital policy) or telephone follow-up by specialist nurses (consultation with structured intervention and mammography according to hospital policy). Main outcome measures Psychological morbidity (state-trait anxiety inventory, general health questionnaire (GHQ-12)), participants’ needs for information, participants’ satisfaction, clinical investigations ordered, and time to detection of recurrent disease. Results The 95% confidence interval for difference in mean state-trait scores adjusted for treatment received (−3.33 to 2.07) was within the predefined equivalence region (−3.5 to 3.5). The women in the telephone group were no more anxious as a result of foregoing clinic examinations and face-to-face consultations and reported higher levels of satisfaction than those attending hospital clinics (intention to treat P<0.001). The numbers of clinical investigations ordered did not differ between groups. Recurrences were few (4.5%), with no differences between groups for time to detection (median 60.5 (range 37-131) days in hospital group v 39.0 (10-152) days in telephone group; P=0.228). Conclusions Telephone follow-up was well received by participants, with no physical or psychological disadvantage. It is suitable for women at low to moderate risk of recurrence and those with long travelling distances or mobility problems and decreases the burden on busy hospital clinics

Residential Indoor and Outdoor PM Measured Using Low-cost Monitors during the Heating Season in Monroe County, NY

Continuous 1-minute indoor and outdoor PM concentrations (~PM2.5) were measured from November through April of 2015/16 and 2016/17 at 50 single family residences in Monroe County, NY (25 per season) using Speck (Airviz Inc., Pittsburgh, PA) low-cost monitors (LCMs). While the accuracy of LCMs is inconsistent and source dependent, the LCMs provided reasonable precision for estimating indoor/outdoor (I/O) ratios based on laboratory and field testing, understanding the relationship between indoor sources and concentration, and comparing PM concentrations across residences for the detected size range (0.5-3 mm). The indoor PM2.5 concentration pattern showed clear morning and evening peaks as well as higher indoor concentrations during the weekends when people are typically at home. The mean I/O PM2.5 ratio was 1.1 for all homes and increased to 1.7 when a combustion source was in use as indicated by an elevated CO concentration whereas most prior studies have found this ratio to be &lt; 1. Increases in wood-burning appliance temperature and indoor CO concentrations were found to be associated with an overall moderate (mean value of 2.1 µg/m3) increase in indoor PM concentration averaged over the heating season. Short-term PM increases greater than 100 µg/m3 were periodically observed in homes with and without wood-burning appliances operating. This study provides an approach for exposure assessment in homes that can be utilized by employing appropriate calibration and quality assurance procedures for the LCMs

Labour market experiences of young UK Bangladeshi men: Identity, inclusion and exclusion in inner-city London

Detailed qualitative data are used to explore the processes perpetuatinglabour market disadvantage among young UK-Bangladeshi men living in central London. Strong forces of inclusion within the Bangladeshi community are found to interact with forces of exclusion from ‘mainstream’ society to constrain aspirations and limit opportunities. Though diverse forms of young Bangladeshi masculinity are found, a common pattern is heavy dependency on intra-ethnic networks. Negative experiences of and isolation from ‘mainstream’ society further reinforce reliance on ‘our own people’. However, acute ambivalence towards belonging to a dense Bangladeshi community exists, exemplified in the widespread denigration of the restaurant trade. Many respondents express the desire to ‘break out’ and access new experiences. The findings support current policy emphasis on ‘connecting people to work’ but highlight the more fundamental need to connect people across ethnic boundaries. The paper urges researchers to ‘unpack’ ethnicity to consider carefully what ethnic identity implies in terms of access to resources and opportunities for different individuals in different contexts in order better to understand the diversity of labour market outcomes and the persistence of disadvantage

A methodology to define risk matrices–application to inland water ways autonomous ships

The autonomous ships’ introduction is associated with a number of challenges including the lack of appropriate risk acceptance criteria to support the risk assessment process during the initial design phases. This study aims to develop a rational methodology for selecting appropriate risk matrix ratings, which are required to perform the risk assessment of autonomous and conventional ships at an early design stage. This methodology consists of four phases and employs the individual and societal risk acceptance criteria to determine the risk matrix ratings for the groups of people exposed to risks. During the first and second phase, the required input parameters for the risk matrix ratings based on the individual risk and societal risk are calculated, respectively. During the third phase, the risk matrix ratings are defined using input from the first and second phases. During the fourth phase, the equivalence between the different types of consequences is specified. The methodology is applied for the case study of a crewless inland waterways ship to assess her typical operation within north-European mainland. The results demonstrate that the inclusion of societal risk resulted in more stringent risk matrix ratings compared to the ones employed in previous studies. Moreover, the adequacy of the proposed methodology and its effectiveness to provide risk acceptance criteria aligned with societal and individual risk acceptance criteria as well as its applicability to conventional ships are discussed

Density and distinctiveness in early word learning:Evidence from neural network simulations

High phonological neighborhood density has been associated with both advantages and disadvantages in early word learning. High density may support the formation and fine-tuning of new word sound memories; a process termed lexical configuration (e.g. Storkel, 2004). However, new high-density words are also more likely to be misunderstood as instances of known words, and may therefore fail to trigger the learning process (e.g. Swingley & Aslin, 2007). To examine these apparently contradictory effects, we trained an autoencoder neural network on 587,954 word tokens (5497 types; including mono- and multi-syllabic words of all grammatical classes) spoken by 279 caregivers to English-speaking children aged 18 to 24 months. We then simulated a communicative development inventory administration and compared network performance to that of 2292 children aged 18 to 24 months. We argue that autoencoder performance illustrates concurrent density advantages and disadvantages, in contrast to prior behavioural and computational literature treating such effects independently. Low network error rates signal a configuration advantage for high-density words, while high network error rates signal a triggering advantage for low-density words. This interpretation is consistent with the application of autoencoders in academic research and industry, for simultaneous feature extraction (i.e. configuration) and anomaly detection (i.e. triggering). Autoencoder simulation therefore illustrates how apparently contradictory density and distinctiveness effects can emerge from a common learning mechanism

Prediction of length of stay for stroke patients using artificial neural networks

Strokes are neurological events that affect a certain area of the brain. Since brain controls fundamental body activities, brain cell deterioration and dead can lead to serious disabilities and poor life quality. This makes strokes the leading cause of disabilities and mortality worldwide. Patients that suffer strokes are hospitalized in order to be submitted to surgery and receive recovery therapies. Thus, it’s important to predict the length of stay for these patients, since it can be costly to them and their family, as well as to the medical institutions. The aim of this study is to make a prediction on the number of days of patients’ hospital stays based on information available about the neurological event that happened, the patient’s health status and surgery details. A neural network was put to test with three attribute subsets with different sizes. The best result was obtained with the subset with fewer features obtaining a RMSE and a MAE of 5.9451 and 4.6354, respectively.FCT - Fundação para a Ciência e a Tecnologia (UID/CEC/00319/2019