The aim of this study was to determine the safety profile, mitral valve outcome and follow-up functional status after percutaneous balloon mitral valvuloplasty (PBMV) in patients with mitral restenosis post-surgical commissurotomy.Sixteen patients with symptomatic mitral restenosis after previous surgical commissurotomy underwent valvuloplasty using the Inoue balloon stepwise dilatation method. Echocardiography was performed before and after the procedure to evaluate the mitral valve area.All procedures were successfully completed without cardiac perforation, thromboembolism, resultant severe mitral regurgitation or death. The mitral valve area improved from 0.9 +/- 0.2 to 1.6 +/- 0.3 (p = 0.0001), accompanied by a significant immediate reduction in the left atrial pressure and transmitral gradient. Compared with PBMV in patients without past mitral surgery, patients with mitral restenosis undergoing PBMV experienced less valve area improvement but the difference was not significant (p = 0.137). Optimal valve enlargement resulting in mild mitral stenosis was achieved in 12 of the 16 patients. Midterm symptomatic benefit was observed in almost all patients.In view of the excellent success rate, low complication risk, the optimal haemodynamic results and favourable functional outcome afforded by mitral balloon valvuloplasty in patients with mitral restenosis after prior surgical commissurotomy, it is logical that balloon mitral valvuloplasty, where available, should be the initial treatment modality in this group of patients with suitable valve morphology before considering repeat mitral surgery.
Falls in older adults might increase due to polypharmacy. This study aimed to explore the association between preadmission medications and history of falls in older inpatients. This observational study of inpatients aged ≥ 65 years was conducted over 4 years at Ballina Hospital, Australia. The Medication Regimen Complexity Index (MRCI), Drug Burden Index (DBI), and Anticholinergic Effect on Cognition (AEC) scores were calculated for preadmission medications. Polypharmacy and falls questionnaires were administered to identify falls in the past 6 months and aptitude toward medication use. Overall, 194 participants with a mean age of 80.2 (SD 8.0) years were included. The mean daily number of regular medications was 7.8 (SD 3.9) and the mean MRCI score was 22 (SD 12.6). Among the participants, 107 (55%) reported falls in the past 6 months and 47 (24%) reported ≥ 2 falls. Age and hearing impairment were positively associated with falls (p = 0.007 and p = 0.003, respectively). History of falls was positively associated with a MRCI score of ≥ 20 (p = 0.018), an AEC score of ≥ 2 (p = 0.010) and a DBI score of ≥ 1 after adjustment for age (p = 0.041). Forgetting medications was associated with falls (p = 0.043). Antihypertensive use did not increase falls risk. Implementing a decisive approach to simplify complex medication regimens, along with patient-focused medication management strategies, may help reduce the risk of falls in older adults. Sedatives and anticholinergic medications increase the risk of falls and should be avoided whenever possible.
Many real-world problems can be considered as a series of related tasks. For example, related tasks are to predict survival of patients from di erent hospitals. In these multitask problems, the data collected could exhibit a clustered structure due to the relatedness between multiple tasks. Mixture model-based methods assuming independence may not be valid for regression and cluster analyses of data arisen from multiple related tasks. Multitask learning is an inductive transfer mechanism to improve generalization accuracy by sharing task-speci c information from di erent tasks to improve the learning process. In this paper, the multitask learning mechanism is extended for mixtures of generalized linear models via random-e ects modelling to handle multitask problems. The use of random-e ects models implies that a soft sharing mechanism is adopted to leverage task-speci c information from multiple tasks. The proposed method is illustrated using simulated and real data sets from various scienti c elds.
Multimorbidity is becoming more prevalent. Previously-used methods of assessing multimorbidity relied on counting the number of health conditions, often in relation to an index condition (comorbidity), or grouping conditions based on body or organ systems. Recent refinements in statistical approaches have resulted in improved methods to capture patterns of multimorbidity, allowing for the identification of nonrandomly occurring clusters of multimorbid health conditions. This paper aims to identify nonrandom clusters of multimorbidity.The Australian Work Outcomes Research Cost-benefit (WORC) study cross-sectional screening dataset (approximately 78,000 working Australians) was used to explore patterns of multimorbidity. Exploratory factor analysis was used to identify nonrandomly occurring clusters of multimorbid health conditions.Six clinically-meaningful groups of multimorbid health conditions were identified. These were: factor 1: arthritis, osteoporosis, other chronic pain, bladder problems, and irritable bowel; factor 2: asthma, chronic obstructive pulmonary disease, and allergies; factor 3: back/neck pain, migraine, other chronic pain, and arthritis; factor 4: high blood pressure, high cholesterol, obesity, diabetes, and fatigue; factor 5: cardiovascular disease, diabetes, fatigue, high blood pressure, high cholesterol, and arthritis; and factor 6: irritable bowel, ulcer, heartburn, and other chronic pain. These clusters do not fall neatly into organ or body systems, and some conditions appear in more than one cluster.Considerably more research is needed with large population-based datasets and a comprehensive set of reliable health diagnoses to better understand the complex nature and composition of multimorbid health conditions.
Road surveys that quickly and efficiently identify features and assess their condition are keystones of an effective road asset management system. Manual visual surveys are subjective and expensive, but it appears that no software package can be flexible enough to cater to all survey needs. However, nature suggests that a generic system design is possible, a parallel being the way in which animals based on the quadruped design fill a wide range of ecological niches. This paper presents a generic design whose common design components are image acquisition, image processing, feature recognition by artificial neural networks, and condition assessment by expert systems. The system can accept either real time camera feed, or video/DVD recordings made by survey vehicles. Biomimicry principles are outlined to guide the designs application to produce a survey system for a given road feature, such as line-markings and road edges. A road guide post survey is presented as a case study.
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