HIV-associated bladder cancer: a case series evaluating difficulties in diagnosis and management

<p>Abstract</p> <p>Background</p> <p>Chronic human immunodeficiency virus (HIV) infection is associated with an increased incidence of Non-Acquired Immunodeficiency Syndrome (non-AIDS) defining cancers. To date, only a limited number of cases of bladder cancer have been linked with HIV infection. We sought to describe the clinical characteristics of HIV-associated bladder cancer.</p> <p>Methods</p> <p>A retrospective study was performed involving HIV-positive patients with bladder cancer, combining cases from multiple institutions with published case reports. Data regarding patient demographics, HIV status, clinical presentation, pathology, cancer treatment, and outcome were analyzed using descriptive statistics.</p> <p>Results</p> <p>Eleven patients were identified with a median age of 55 years (range, 33 - 67). The median CD4+ count at cancer diagnosis was 280 cells/mm³(range, 106 - 572 cells/mm³). Six patients (55%) had a known risk factor for bladder cancer, and nine (82%) presented with hematuria. Ten patients had transitional cell carcinoma, and most had superficial disease at presentation. Treatment included mainly transurethral resection of bladder tumor followed by a combination of local and systemic therapies. One patient received intravesical bacillus Calmette-Guèrin (BCG) without complication. Several patients (55%) were alive following therapy, although many (64%) suffered from local relapse and metastatic disease.</p> <p>Conclusion</p> <p>Bladder cancer is part of the growing list of cancers that may be encountered in patients living longer with chronic HIV-infection. Our patients presented at a younger age and with only mild immunosuppression, however, they experienced an expected course for their bladder cancer. Hematuria in an HIV-infected patient warrants a complete evaluation.</p

Effects of beta-hydroxy-beta-methylbutyrate (HMB) on exercise performance and body composition across varying levels of age, sex, and training experience: A review

The leucine metabolite beta-hydroxy-beta-methylbutyrate (HMB) has been extensively used as an ergogenic aid; particularly among bodybuilders and strength/power athletes, who use it to promote exercise performance and skeletal muscle hypertrophy. While numerous studies have supported the efficacy of HMB in exercise and clinical conditions, there have been a number of conflicting results. Therefore, the first purpose of this paper will be to provide an in depth and objective analysis of HMB research. Special care is taken to present critical details of each study in an attempt to both examine the effectiveness of HMB as well as explain possible reasons for conflicting results seen in the literature. Within this analysis, moderator variables such as age, training experience, various states of muscle catabolism, and optimal dosages of HMB are discussed. The validity of dependent measurements, clustering of data, and a conflict of interest bias will also be analyzed. A second purpose of this paper is to provide a comprehensive discussion on possible mechanisms, which HMB may operate through. Currently, the most readily discussed mechanism has been attributed to HMB as a precursor to the rate limiting enzyme to cholesterol synthesis HMG-coenzyme A reductase. However, an increase in research has been directed towards possible proteolytic pathways HMB may operate through. Evidence from cachectic cancer studies suggests that HMB may inhibit the ubiquitin-proteasome proteolytic pathway responsible for the specific degradation of intracellular proteins. HMB may also directly stimulate protein synthesis, through an mTOR dependent mechanism. Finally, special care has been taken to provide future research implications

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Agile risk management using software agents

Risk management is an important process in Software Engineering. However, it can be perceived as somewhat contrary to the more lightweight processes used in Agile methods. Thus an appropriate and realistic risk management model is required as well as tool support that minimizes human effort. We propose the use of software agents to carry out risk management tasks and make use of the data collected from the project environment to detect risks. This paper describes the underlying risk management model in an Agile risk tool where software agents are used to support identification, assessment and monitoring of risk. It demonstrates the interaction between agents, agents’ compliance with designated rules and how agents can react to changes in project environment data. The results, demonstrated using case studies, show that agents are of use for detecting risk and reacting dynamically to changes in project environment thus, help to minimize the human effort in managing risk