scholarly journals A Diagnostic Model for Dementia in Clinical Practice—Case Methodology Assisting Dementia Diagnosis

2020 ◽  
Author(s):  
Elisabet Londos
Keyword(s):  
Clinical Practice ◽  
Diagnostic Model ◽  
Dementia Diagnosis ◽  
Case Methodology

scholarly journals Sociotherapy in the Time of COVID-19: A Critical Position Paper on the Importance of Sociology

2021 ◽  
pp. 193672442199827
Author(s):  
Sheila L. Cavanagh
Keyword(s):  
Clinical Practice ◽  
Behavioral Treatment ◽  
Health Professions ◽  
Position Paper ◽  
Diagnostic Model ◽  
Cognitive Behavioral Treatment ◽  
Critical Position ◽  
Freudian Psychoanalysis ◽  
The Social ◽  
Regulated Health Professions Act

This paper contends that sociotherapy, a sociologically informed approach to therapy, is a viable alternative to the diagnostic model recognized by the College of Registered Psychotherapists in Ontario (CRPO). The Psychotherapy Act (2007) along with the Regulated Health Professions Act (1991) gives the CRPO authorization to regulate the practice of psychotherapy and to control titles affiliated with the act of psychotherapy. I offer a discussion of sociotherapy and socioanalysis as clinical alternatives to the conservative and normalizing approaches endorsed by the College. I situate sociotherapy and socioanalysis in the discipline of sociology and in relation to Freudian psychoanalysis. I offer my own sociotherapeutic practice as an illustration of how the societal and the psychological, the social, and the psychic must be engaged in concert. I underscore the importance of dialogue, as opposed to diagnostics, interpretation as opposed to assessments and psychosocial contemplation as opposed to cognitive-behavioral treatment in clinical practice.

scholarly journals Deep Learning Based Syndrome Diagnosis of Chronic Gastritis

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Guo-Ping Liu ◽  
Jian-Jun Yan ◽  
Yi-Qin Wang ◽  
Wu Zheng ◽  
Tao Zhong ◽  
...  
Keyword(s):  
Deep Learning ◽  
Clinical Practice ◽  
Chronic Gastritis ◽  
Diagnostic Model ◽  
Nonlinear Relationship ◽  
Cognitive Perspective ◽  
Multilabel Learning ◽  
Diagnostic Models ◽  
Syndrome Diagnosis ◽  
The Brain

In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.

Integrating routine clinical interventions with single-case methodology: Parallels, differences and bridging strategies

2019 ◽  
Vol 21 (1) ◽  
pp. 99-109
Author(s):  
Robyn L. Tate ◽  
Michael Perdices ◽  
Donna Wakim
Keyword(s):  
Clinical Practice ◽  
Randomised Controlled Trial ◽  
Treatment Effectiveness ◽  
Single Case ◽  
Controlled Trial ◽  
Routine Clinical Practice ◽  
Case Methods ◽  
Case Methodology ◽  
Randomised Controlled ◽  
Building Practice

AbstractClinical practice offers the opportunity for the clinician to be a scientist-practitioner in the workplace. This, in turn, facilitates building practice-based evidence. But this can only occur if the effects of the interventions are objectively and systematically evaluated. To this end, single-case methodology is a valuable tool to implement an intervention in a scientifically rigorous manner and gather data on treatment effectiveness. It is possible to incorporate single-case methods into routine clinical practice by using a few simple strategies. This paper examines the ways in which single-case methodology departs from (a) routine clinical practice and (b) the familiar between-groups research design, such as the randomised controlled trial. It presents five practical strategies that will bridge the gap between routine clinical practice and single-case methodology. The Model for Assessing Treatment Effect is described as providing context for and a framework to self-evaluate the scientific rigour in clinical practice and benchmark service delivery.

scholarly journals Against the stream: early diagnosis of dementia, is it so desirable?

2019 ◽  
Vol 43 (3) ◽  
pp. 123-125 ◽  
Author(s):  
Carol Brayne ◽  
Sarah Kelly
Keyword(s):  
Clinical Practice ◽  
Early Diagnosis ◽  
Empirical Evidence ◽  
Treatment Options ◽  
Evidence Base ◽  
Current Evidence ◽  
Dementia Diagnosis ◽  
Case Identification ◽  
Current Evidence Base ◽  
Diagnosis Of Dementia

SummaryThe Prime Minister's challenge on dementia called for improved dementia diagnosis rates, based on assumptions of benefit to individuals and those who care for them. Subsequent policies have led to increased target drives for clinical practice to achieve early diagnosis of dementia through intense case identification. However, the current evidence base and treatment options do not support screening for dementia, and there is little empirical evidence that such intensive case identification and early diagnosis for dementia is justified without a better understanding of the benefits, costs and potential harms to individuals and services.Declaration of interestNone.

scholarly journals Variation and Interactional Non-Standardization in Neuropsychological Tests: The Case of the Addenbrooke’s Cognitive Examination

2019 ◽  
Vol 30 (3) ◽  
pp. 458-470
Author(s):  
Danielle Jones ◽  
Ray Wilkinson ◽  
Clare Jackson ◽  
Paul Drew
Keyword(s):  
Clinical Practice ◽  
Conversation Analysis ◽  
Neuropsychological Tests ◽  
Neuropsychological Test ◽  
Memory Clinic ◽  
Dementia Diagnosis ◽  
Addenbrooke’S Cognitive Examination ◽  
The Way

The Addenbrooke’s Cognitive Examination (ACE-111) is a neuropsychological test used in clinical practice to inform a dementia diagnosis. The ACE-111 relies on standardized administration so that patients’ scores can be interpreted by comparison with normative scores. The test is delivered and responded to in interaction between clinicians and patients, which places talk-in-interaction at the heart of its administration. In this article, conversation analysis (CA) is used to investigate how the ACE-111 is delivered in clinical practice. Based on analysis of 40 video/audio-recorded memory clinic consultations in which the ACE-111 was used, we have found that administrative standardization is rarely achieved in practice. There was evidence of both (a) interactional variation in the way the clinicians introduce the test and (b) interactional non-standardization during its implementation. We show that variation and interactional non-standardization have implications for patients’ understanding and how they might respond to particular questions.

Diagnosis of dementia in Australia: a narrative review of services and models of care

2019 ◽  
Vol 43 (4) ◽  
pp. 415 ◽  
Author(s):  
Natalie Su Quin Ng ◽  
Stephanie Alison Ward
Keyword(s):  
Clinical Practice ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Dementia Diagnosis ◽  
Potential Cost ◽  
People With Dementia ◽  
Care Assessment ◽  
New Models ◽  
Diagnosis Of Dementia ◽  
Memory Clinics

Objective There is an impetus for the timely diagnosis of dementia to enable optimal management of patients, carers and government resources. This is of growing importance in the setting of a rising prevalence of dementia in an aging population. The Australian Clinical Practice Guidelines and Principles of Care for People with Dementia advocate referral to comprehensive memory services for dementia diagnosis, but in practice many patients may be diagnosed in other settings. The aim of the present study was to obtain evidence of the roles, effectiveness, limitations and accessibility of current settings and services available for dementia diagnosis in Australia. Methods A literature review was performed by searching Ovid MEDLINE using the terms ‘dementia’ AND ‘diagnosis OR detection’. In addition, articles from pertinent sources, such as Australian government reports and relevant websites (e.g. Dementia Australia) were included in the review. Results Literature was found for dementia diagnosis across general practice, hospitals, memory clinics, specialists, community, care institutions and new models. General practitioners are patients’ preferred health professionals when dealing with dementia, but gaps in symptom recognition and initiation of cognitive testing lead to underdiagnosis. Hospitals are opportunistic places for dementia screening, but time constraints and acute medical issues hinder efficient dementia diagnosis. Memory clinics offer access to multidisciplinary skills, demonstrate earlier dementia diagnosis and potential cost-effectiveness, but are disadvantaged by organisational complexities. Specialists have increased confidence in diagnosing dementia than generalists, but drawbacks include long wait lists. Aged care assessment teams (ACAT) are a potential service for dementia diagnosis in the community. A multidisciplinary model for dementia diagnosis in care institutions is potentially beneficial, but is time and cost intensive. New models with technology allow dementia diagnosis in rural regions. Conclusion Memory clinics are most effective for formal dementia diagnosis, but healthcare professionals in other settings play vital roles in recognising patients with dementia and initiating investigations and referrals to appropriate services. What is known about this topic? Delays in dementia diagnosis are common, and it is unclear where majority of patients receive a diagnosis of dementia in Australia. While the Australian Clinical Practice Guidelines and Principles of Care for People with Dementia advocate referrals to services such as memory clinics for comprehensive assessment and diagnosis of dementia, such services may have limited capacity and may not be readily accessible to all. What does this paper add? This paper presents an overview of the various settings and services available for dementia diagnosis in Australia including evidence of the roles, accessibility, effectiveness and limitations of each setting. What are the implications for practitioners? This concerns a disease that is highly prevalent and escalating, and highlights the roles for practitioners in various settings including general practices, acute hospitals, specialist clinics, community and nursing homes. In particular, it discusses the potential roles, advantages and challenges of dementia diagnosis in each setting.

Mastocheck: Notable plasma protein biomarker for diagnosis of breast cancer in the real clinical practice by using multiple reaction monitoring-based mass spectrometry.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 3044-3044
Author(s):  
Yumi Kim ◽  
Un-Beom Kang ◽  
Sungsoo Kim ◽  
Han-Byoel Lee ◽  
Jigwang Jung ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Practice ◽  
Early Detection ◽  
Plasma Protein ◽  
Multiple Reaction Monitoring ◽  
Diagnostic Model ◽  
Protein Biomarker ◽  
The Real ◽  
Significant Difference ◽  
Real Clinical Practice

3044 Background: Breast cancer is the most frequently diagnosed cancer and the most leading cause of cancer-related deaths among women worldwide. Although screening mammography is available, there is an ongoing interest in improved early detection and prognosis. And also, serum tumor marker levels, such as CA 15-3 and others, may reflect disease progression and recurrence, they have not proven to be sensitive for early disease detection. Research investigating biomarkers for early detection, prognosis and the prediction of treatment responses in breast cancer is rapidly expanding. However, no validated biomarker currently exists for use in routine clinical practice, and breast cancer detection and management remains dependent on invasive procedures We aimed to develop biomarker for diagnosis of breast cancer in the real clinical practice by using proteomics technology. Methods: Based on our previous studies, we performed verification and validation of 124 candidate proteins by using proteomics approach. Among these 124 candidate proteins, the three proteins (neural cell adhesion molecule L1-like protein, apolipoprotein C-1, carbonic anhydrase-1) with highest statistical significance were selected. We created the performance algorithm of the 3-protein diagnostic model to predict of the breast cancer. We performed several experiments for establishment and validation of cut-off value. Furthermore we conducted test for acquisition of sample stability and more experiments to achieve the reproducibility and level of evidence, compared with other cancers (colon, thyroid, ovary, pancreas and lung cancer) and established effect of anesthesia. Results: Total 1226 samples (532 patients of breast cancer, 562 healthy women and 100 sample of other cancers) was analyzed. The sensitivity, specificity and accuracy from confirmation experiment was 71.58%, 85.25% and AUC 0.8323, respectively. The result of comparison with other cancers, there are no statistical significant difference and no relevance with effects of anesthesia. With these results, we recently got permission it to use for in vitro diagnostic use from Korea Food and Drug Administration. Conclusions: In this study, we developed a plasma protein biomarker that may help to diagnosis of breast cancer in the real clinical practice. By using MRM approach, the 3-protein biomarker was validated in an independent cohort with acceptable accuracy for early diagnosis of breast cancer.

scholarly journals Comment on “The diagnostic value of D-dimer with simplified Geneva score (SGS) pre-test in the diagnosis of pulmonary embolism (PE)”

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Siamak Sabour
Keyword(s):  
Pulmonary Embolism ◽  
Clinical Practice ◽  
Diagnostic Accuracy ◽  
Diagnostic Test ◽  
Diagnostic Value ◽  
Added Value ◽  
Diagnostic Model ◽  
Test Results ◽  
Single Test ◽  
D Dimer

Abstract Any decision in clinical practice needs to evaluate both reliability (precision) and validity (accuracy) of a diagnostic test. Without knowledge about the reliability, any judgment would be wrong. In diagnostic accuracy research, it is essential to evaluate the diagnostic added value of a test, since a diagnostic accuracy of a single test might be excellent, however for clinical purposes it can be worthless. Like evaluating discrimination, it would be possible to estimate the diagnostic added value by applying ROC of diagnostic model with and without test results in the model.

scholarly journals Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Guo-Ping Liu ◽  
Jian-Jun Yan ◽  
Yi-Qin Wang ◽  
Jing-Jing Fu ◽  
Zhao-Xia Xu ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Chronic Gastritis ◽  
Information Gain ◽  
Diagnostic Model ◽  
Relevant Feature ◽  
Standard Scale ◽  
Multilabel Learning ◽  
Average Accuracy ◽  
Syndrome Diagnosis ◽  
Tcm Theory

Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs).Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale.Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively.Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.

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