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BACKGROUND: Personal health information, including diagnoses and hospital admissions, is routinely collected in administrative databases. Patients enrolling on clinical trials consent to separate collection and storage of their personal health information. We evaluated patient preferences for linking long-term data from administrative databases with clinical trials. METHODS: Adults with cancer attending outpatient clinics at 3 Ontario hospitals were surveyed about their willingness, when faced with the hypothetical scenario of participating in a clinical trial, to provide potentially identifying information such as initials and date of birth to facilitate long-term research access to normally deidentified publicly collected databases. RESULTS: Of 569 patients surveyed, 335 (59%) were women, 452 (79%) were white, 385 (68%) had a post-secondary education, and 386 (68%) had never participated in a clinical trial. Median age in the group was 59 years. Most participants (93%, cohort 1) would allow long-term access to their information and allow personal information to be used to match clinical trial with administrative data. At the time of clinical trial closure, two thirds of participants (68%, cohort 2) preferred to make additional clinical information available through linkage with administrative databases, and 8 (9%) preferred to have no further information made available to researchers. No significant differences were found in the subset of patients who were part of a clinical trial and those who had never participated (p = 0.65). INTERPRETATION: Almost all patients would allow a clinical trial research team to access their confidential information, providing a more comprehensive assessment of an intervention's long-term risks and benefits.
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The one-unit Oja algorithm plays a very important role in the study of principal component analysis neural networks. In this paper, we propose an energy function whose steepest descent direction (i.e., negative gradient direction) is the same as the average evolution direction of the one-unit Oja algorithm, and the energy function has two global minimal points corresponding to the two converged points of the one-unit Oja algorithm and it has no other local minimal points.
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Principal component analysis (PCA) and minor component analysis (MCA) are a powerful methodology for a wide variety of applications such as pattern recognition and signal processing. In this paper, we first propose a differential equation for the generalized eigenvalue problem.We prove that the stable points of this differential equation are the eigenvectors corresponding to the largest eigenvalue. Based on this generalized differential equation, a class of PCA and MCA learning algorithms can be obtained. We demonstrate that many existing PCA and MCA learning algorithms are special cases of this class, and this class includes some new and simpler MCA learning algorithms. Our results show that all the learning algorithms of this class have the same order of convergence speed, and they are robust to implementation error.
ABSTRACT
Principal component analysis (PCA) and minor component analysis (MCA) are a powerful methodology for a wide variety of applications such as pattern recognition and signal processing. In this paper, we first propose a differential equation for the generalized eigenvalue problem.We prove that the stable points of this differential equation are the eigenvectors corresponding to the largest eigenvalue. Based on this generalized differential equation, a class of PCA and MCA learning algorithms can be obtained. We demonstrate that many existing PCA and MCA learning algorithms are special cases of this class, and this class includes some new and simpler MCA learning algorithms. Our results show that all the learning algorithms of this class have the same order of convergence speed, and they are robust to implementation error.
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We consider an online string matching problem in which we find all the occurrences of a pattern of m characters in a text of n characters, where all the characters of the pattern are available before processing, while the characters of the text are input one after the other. We propose a space-time optimal parallel algorithm for this problem using a neural network approach, This algorithm uses m McCulloch-Pitts neurons connected as a linear array. It processes every input character of the text in one step and hence it requires at most n iteration steps.
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OBJECTIVE: To systematically review the evidence of pre-operative exercise, known as 'prehabilitation', on peri- and postoperative outcomes in adult surgical populations. DESIGN: Systematic review and meta-analysis. DATA SOURCES: CENTRAL, Medline, EMBASE, CINAHL, PsycINFO and PEDro were searched from 1950 to 2011. METHODS: Two reviewers independently examined relevant, English-language articles that examined the effects of pre-operative total-body exercise with peri- and postoperative outcome analysis. Given the nascence of this field, controlled and uncontrolled trials were included. Risk of bias was assessed using the Cochrane Risk of Bias Assessment tool. Only data on length of stay were considered eligible for meta-analysis due to the heterogeneity of measures and methodologies for assessing other outcomes. RESULTS: In total, 4597 citations were identified by the search strategy, of which 21 studies were included. Trials were generally small (median=54 participants) and of moderate to poor methodological quality. Compared with standard care, the majority of studies found that total-body prehabilitation improved postoperative pain, length of stay and physical function, but it was not consistently effective in improving health-related quality of life or aerobic fitness in the studies that examined these outcomes. The meta-analysis indicated that prehabilitation reduced postoperative length of stay with a small to moderate effect size (Hedges' g=-0.39, P=0.033). Intervention-related adverse events were reported in two of 669 exercising participants. CONCLUSION: The literature provides early evidence that prehabilitation may reduce length of stay and possibly provide postoperative physical benefits. Cautious interpretation of these findings is warranted given modest methodological quality and significant risk of bias.
Subject(s)
Exercise/physiology , Physical Therapy Modalities , Postoperative Complications/prevention & control , Preoperative Care , Humans , Quality of LifeABSTRACT
The mode of action of tetracaine hydrochloride in vitro on Pseudomonas aeruginosa was investigates. The inhibitory and bactericidal action of tetracaine hydrochloride in vitro was adversely affected by magnesium ions. Observation of cellular lysis, leakage of intracellular materials, dehydrogenase activity, and a higher sensitivity of spheroplasts than of whole cells to tetracaine led to the conclusion that tetracaine acts by damaging the cell membrane. The lytic action of lysozyme was potentiated by tetracaine; this finding indicates enhanced permeability of the cell wall. Alteration of cell wall permeability was demonstrated by the finding that the cells exposed to subinhibitory amounts of tetracaine became susceptible to otherwise ineffective erythromycin.