Do men regret prostate biopsy: Results from the PiCTure study

Abstract Background Understanding men\u2019s experience of prostate biopsy is important as the procedure is common, invasive and carries potential risks. The psychological aspects of prostate biopsy have been somewhat neglected. The aim of this study was to explore the level of regret experienced by men after prostate biopsy and identify any associated factors. Methods Men attending four clinics in Republic of Ireland and two in Northern Ireland were given a questionnaire to explore their experience of prostate biopsy. Regret was measured on a Likert scale asking men how much they agreed with the statement \u201cIt [the biopsy] is something I regret.\u201d Results Three hundred thirty-five men responded to the survey. The mean age was 63\ua0years (SD \ub17\ua0years). Three quarters of respondents (76%) were married or co-habiting, and (75%) finished education at primary or secondary school level. For just over two thirds of men (70%) their recent biopsy represented their first ever prostate biopsy. Approximately one third of men reported a diagnosis of cancer, one third a negative biopsy result, and the remaining third did not know their result. Two thirds of men reported intermediate or high health anxiety. 5.1% of men agreed or strongly agreed that they regretted the biopsy. Conclusions Level of regret was low overall. Health anxiety was the only significant predictor of regret, with men with higher anxiety reporting higher levels of regret than men with low anxiety (OR\u2009=\u20093.04, 95% CI 1.58, 5.84). Men with high health anxiety may especially benefit from careful counselling before and after prostate biopsy

Using Case-Level Context to Classify Cancer Pathology Reports

Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence-for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We test our approach on a corpus of 431,433 cancer pathology reports, and we show that incorporating case-level context significantly boosts classification accuracy across six classification tasks-site, subsite, laterality, histology, behavior, and grade. We expect that with minimal modifications, our add-on can be applied towards a wide range of other clinical text-based tasks

Evaluation of an ambulatory system for the quantification of cough frequency in patients with chronic obstructive pulmonary disease

BACKGROUND: To date, methods used to assess cough have been primarily subjective, and only broadly reflect the impact of chronic cough and/or chronic cough therapies on quality of life. Objective assessment of cough has been attempted, but early techniques were neither ambulatory nor feasible for long-term data collection. We evaluated a novel ambulatory cardio-respiratory monitoring system with an integrated unidirectional, contact microphone, and report here the results from a study of patients with COPD who were videotaped in a quasi-controlled environment for 24 continuous hours while wearing the ambulatory system. METHODS: Eight patients with a documented history of COPD with ten or more years of smoking (6 women; age 57.4 ± 11.8 yrs.; percent predicted FEV(1 )49.6 ± 13.7%) who complained of cough were evaluated in a clinical research unit equipped with video and sound recording capabilities. All patients wore the LifeShirt(® )system (LS) while undergoing simultaneous video (with sound) surveillance. Video data were visually inspected and annotated to indicate all cough events. Raw physiologic data records were visually inspected by technicians who remained blinded to the video data. Cough events from LS were analyzed quantitatively with a specialized software algorithm to identify cough. The output of the software algorithm was compared to video records on a per event basis in order to determine the validity of the LS system to detect cough in COPD patients. RESULTS: Video surveillance identified a total of 3,645 coughs, while LS identified 3,363 coughs during the same period. The median cough rate per patient was 21.3 coughs·hr(-1 )(Range: 10.1 cghs·hr(-1 )– 59.9 cghs·hr(-1)). The overall accuracy of the LS system was 99.0%. Overall sensitivity and specificity of LS, when compared to video surveillance, were 0.781 and 0.996, respectively, while positive- and negative-predictive values were 0.846 and 0.994. There was very good agreement between the LS system and video (kappa = 0.807). CONCLUSION: The LS system demonstrated a high level of accuracy and agreement when compared to video surveillance for the measurement of cough in patients with COPD

Sex Differences in Neurological Emergencies Presenting to Multiple Urban Level 1 Trauma Centers

Previous studies have suggested that there are sex differences in the treatment and outcome of neurological emergencies; however, research identifying the role these sex differences play in the management of neurological emergencies is lacking. More knowledge of the way sex factors into the pathophysiology of neurological emergencies will be helpful in improving outcomes for these patients. The aim of this cross-sectional study was to assess the prevalence and management of neurological emergencies while evaluating sex differences in the diagnosis and treatment of these emergencies. We analyzed a cohort of 530 adult patients from four level 1 trauma centers over a period of 4 weeks who had a chief complaint of a neurological emergency, including seizures, cerebrovascular events, headache disorders, traumatic brain injuries, and central nervous system infections. Among patients with neurological emergencies, a significantly lower proportion of female patients underwent neurosurgery and were admitted to the intensive care unit compared to male patients, but there were no significant differences between sexes in the time of symptom onset, type of hospital transportation, amount of neuroimaging performed, admission rates, hospital length of stay, and disposition from the emergency department. Although female patients were more likely to have a chief complaint of headache compared to traumatic injuries in male patients, this was not statistically significant. A significantly higher proportion of female patients had health insurance coverage than male patients

Do men regret prostate biopsy: results from the PiCTure study

Background: Understanding men’s experience of prostate biopsy is important as the procedure is common, invasive and carries potential risks. The psychological aspects of prostate biopsy have been somewhat neglected. The aim of this study was to explore the level of regret experienced by men after prostate biopsy and identify any associated factors. Methods: Men attending four clinics in Republic of Ireland and two in Northern Ireland were given a questionnaire to explore their experience of prostate biopsy. Regret was measured on a Likert scale asking men how much they agreed with the statement “It [the biopsy] is something I regret.” Results: Three hundred thirty-five men responded to the survey. The mean age was 63 years (SD ±7 years). Three quarters of respondents (76%) were married or co-habiting, and (75%) finished education at primary or secondary school level. For just over two thirds of men (70%) their recent biopsy represented their first ever prostate biopsy. Approximately one third of men reported a diagnosis of cancer, one third a negative biopsy result, and the remaining third did not know their result. Two thirds of men reported intermediate or high health anxiety. 5.1% of men agreed or strongly agreed that they regretted the biopsy. Conclusions: Level of regret was low overall. Health anxiety was the only significant predictor of regret, with men with higher anxiety reporting higher levels of regret than men with low anxiety (OR = 3.04, 95% CI 1.58, 5.84). Men with high health anxiety may especially benefit from careful counselling before and after prostate biopsy

Deep Active Learning for Classifying Cancer Pathology Reports

Background: Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. Active learning techniques may mitigate this challenge by reducing the amount of labelled data required to effectively train a model. In this study, we analyze the effectiveness of 11 active learning algorithms on classifying subsite and histology from cancer pathology reports using a Convolutional Neural Network as the text classification model. Results: We compare the performance of each active learning strategy using two differently sized datasets and two different classification tasks. Our results show that on all tasks and dataset sizes, all active learning strategies except diversity-sampling strategies outperformed random sampling, i.e., no active learning. On our large dataset (15K initial labelled samples, adding 15K additional labelled samples each iteration of active learning), there was no clear winner between the different active learning strategies. On our small dataset (1K initial labelled samples, adding 1K additional labelled samples each iteration of active learning), marginal and ratio uncertainty sampling performed better than all other active learning techniques. We found that compared to random sampling, active learning strongly helps performance on rare classes by focusing on underrepresented classes. Conclusions: Active learning can save annotation cost by helping human annotators efficiently and intelligently select which samples to label. Our results show that a dataset constructed using effective active learning techniques requires less than half the amount of labelled data to achieve the same performance as a dataset constructed using random sampling

Limitations of Transformers on Clinical Text Classification

Bidirectional Encoder Representations from Transformers (BERT) and BERT-based approaches are the current state-of-the-art in many natural language processing (NLP) tasks; however, their application to document classification on long clinical texts is limited. In this work, we introduce four methods to scale BERT, which by default can only handle input sequences up to approximately 400 words long, to perform document classification on clinical texts several thousand words long. We compare these methods against two much simpler architectures -- a word-level convolutional neural network and a hierarchical self-attention network -- and show that BERT often cannot beat these simpler baselines when classifying MIMIC-III discharge summaries and SEER cancer pathology reports. In our analysis, we show that two key components of BERT -- pretraining and WordPiece tokenization -- may actually be inhibiting BERT\u27s performance on clinical text classification tasks where the input document is several thousand words long and where correctly identifying labels may depend more on identifying a few key words or phrases rather than understanding the contextual meaning of sequences of text

Behavior of Piles and Pile Groups in Cohesionless Soils

DTFH61-82-C-0038In order to gain a better understanding of the behavior of piles in snad, an extensive search of the literature has been performed to collect data on instrumental piles driven in sand and tested under vertical loads. The load transfer characteristics of the piles were then analyzed without considering residual stresses. Wherever the data allowed it, the load transfer analysis was repeated after considering residual driving stresses. The results of this method as well as conventional and new in situ tests methods were then compared to actual load test results. Areas of critical need for further research are pointed out and recommendations are made for their implementation