Tissue discrimination in magnetic resonance imaging of the rator cuff

Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients' health

Rapid progression of prostate cancer in men with a BRCA2 mutation.

Men with BRCA2 mutations have been found to be at increased risk of developing prostate cancer. There is a recent report that BRCA2 carriers with prostate cancer have poorer survival than noncarrier prostate cancer patients. In this study, we compared survival of men with a BRCA2 mutation and prostate cancer with that of men with a BRCA1 mutation and prostate cancer. We obtained the age at diagnosis, age at death or current age from 182 men with prostate cancer from families with a BRCA2 mutation and from 119 men with prostate cancer from families with a BRCA1 mutation. The median survival from diagnosis was 4.0 years for men with a BRCA2 mutation vs 8.0 years for men with a BRCA1 mutation, and the difference was highly significant (P<0.01). It may be important to develop targeted chemotherapies to treat prostate cancer in men with a BRCA2 mutation

Supporting genetics in primary care: investigating how theory can inform professional education

Evidence indicates that many barriers exist to the integration of genetic case finding into primary care. We conducted an exploratory study of the determinants of three specific behaviours related to using breast cancer genetics referral guidelines effectively: 'taking a family history', 'making a risk assessment', and 'making a referral decision'. We developed vignettes of primary care consultations with hypothetical patients, representing a wide range of genetic risk for which different referral decisions would be appropriate. We used the Theory of Planned Behavior to develop a survey instrument to capture data on behavioural intention and its predictors (attitude, subjective norm, and perceived behavioural control) for each of the three behaviours and mailed it to a sample of Canadian family physicians. We used correlation and regression analyses to explore the relationships between predictor and dependent variables. The response rate was 96/125 (77%). The predictor variables explained 38-83% of the variance in intention across the three behaviours. Family physicians' intentions were lower for 'making a risk assessment' (perceived as the most difficult) than for the other two behaviours. We illustrate how understanding psychological factors salient to behaviour can be used to tailor professional educational interventions; for example, considering the approach of behavioural rehearsal to improve confidence in skills (perceived behavioural control), or vicarious reinforcement as where participants are sceptical that genetics is consistent with their role (subjective norm)

Hormone Therapy and the Risk of Breast Cancer in BRCA1 Mutation Carriers

Background: Hormone therapy (HT) is commonly given to women to alleviate the climacteric symptoms associated with menopause. There is concern that this treatment may increase the risk of breast cancer. The potential association of HT and breast cancer risk is of particular interest to women who carry a mutation in BRCA1 because they face a high lifetime risk of breast cancer and because many of these women take HT after undergoing prophylactic surgical oophorectomy at a young age. Methods: We conducted a matched case-control study of 472 postmenopausal women with a BRCA1 mutation to examine whether or not the use of HT is associated with subsequent risk of breast cancer. Breast cancer case patients and control subjects were matched with respect to age, age at menopause, and type of menopause (surgical or natural). Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated with conditional logistic regression. Statistical tests were two-sided. Results: In this group of BRCA1 mutation carriers, the adjusted OR for breast cancer associated with ever use of HT compared with never use was 0.58 (95% CI = 0.35 to 0.96; P =. 03). In analyses by type of HT, an inverse association with breast cancer risk was observed with use of estrogen only (OR = 0.51, 95% CI = 0.27 to 0.98; P =. 04); the association with use of estrogen plus progesterone was not statistically significant (OR = 0.66, 95% CI = 0.34 to 1.27; P =. 21). Conclusion: Among postmenopausal women with a BRCA1 mutation, HT use was not associated with increased risk of breast cancer; indeed, in this population, it was associated with a decreased risk

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Postpartum psychiatric disorders

Pregnancy is a complex and vulnerable period that presents a number of challenges to women, including the development of postpartum psychiatric disorders (PPDs). These disorders can include postpartum depression and anxiety, which are relatively common, and the rare but more severe postpartum psychosis. In addition, other PPDs can include obsessive–compulsive disorder, post-traumatic stress disorder and eating disorders. The aetiology of PPDs is a complex interaction of psychological, social and biological factors, in addition to genetic and environmental factors. The goals of treating postpartum mental illness are reducing maternal symptoms and supporting maternal–child and family functioning. Women and their families should receive psychoeducation about the illness, including evidence-based discussions about the risks and benefits of each treatment option. Developing effective strategies in global settings that allow the delivery of targeted therapies to women with different clinical phenotypes and severities of PPDs is essential