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Comorbidity clinical trials

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NCT ID: NCT05204186 Recruiting - Bladder Cancer Clinical Trials

Impact of COMORBIDities After Radical Cystectomy Using a Predictive Method With Artificial Intelligence

COMORBID-AI
Start date: January 10, 2021
Phase:
Study type: Observational

Clinician and the multidisciplinary team meeting in oncologic urology (MMO) play a key-role in the decision making. An unexplained surgeon attributable variance, probably linked to the subjective "eyeball test" effect, was identified as a strongest factor underlying non-compliance with guide line recommendations in the management of bladder cancer. So high-quality studies that identify barriers and modulators (such as comorbidities) of provider-level adoption of guidelines and how comorbidities are associated in making therapeutic choice and their impact in bladder cancer specific survival and overall survival, are crucial. To identify patients at high risk of early death, and to improve specific guideline for treatment might be decisive. In order to assess survival, where mortality events compete, it will be more appropriate to compute a Cumulative Incidence Function (namely CIF). The investigators will compare outcomes across patient populations to obtain information to improve clinical decision-making. Such learning will be done through the use of neural networks or by applying population-based approaches, such as Genetic Algorithms (GA), Ant Colony Systems (ACS) and Particle Swarm Optimization (PSO), using as a four-stage based approach. First, the investigators propose a "pretopology space" in order to study a dynamic phenomenon. Second, the investigators recall that the K-means approach remains one of the most used approaches for classifying a set of elements (patients / persons / others) into K (disjunctive) clusters. Third, the investigators propose a learning pretopology space for enhancing the clustering. Such an approach can be assimilated in spirit to one applied with high success on deep learning. Fourth and last, the investigators propose a reactive method that is able to include some new elements or remove some contained elements

NCT ID: NCT04176510 Recruiting - Self-Management Clinical Trials

Preventing Tipping Points in High Comorbidity Patients: A Lifeline From Health Coaches

Tipping Points
Start date: November 20, 2019
Phase: N/A
Study type: Interventional

This pragmatic cluster randomized clinical trial (cRCT) aims to evaluate the comparative effectiveness (CER) of two approaches to preventing destabilization ("tipping points") that lead to unplanned hospitalization and increased disability. The cRCT compares the outcomes of patients randomized in clusters by site within four Federally Qualified Health Center (FQHC) networks in New York City (NYC) and Chicago to either: 1) the Patient Centered Medical Home (PCMH); or 2) the Patient Centered Home plus a health coaching intervention that employs a positive affect/self-affirmation intervention to help motivate patients to succeed at implementing self-management by setting life goals (experimental). This RCT embeds novel effective interventions within large FQHC networks, namely, Community Healthcare Network and the Family Health Centers of New York University (NYU) Langone in NYC and Erie Family Health Centers and Friend Family Health Center in Chicago, serving patients with multiple chronic diseases or high comorbidity. This CER study compares two PCMH-based strategies and will provide a manualized training system that can be disseminated and implemented across the national FQHC networks, with over 9,000 delivery sites that serve nearly 25 million low-income and minority patients, and can be implemented in a wider range of practice settings, organization types and population characteristics. Among 1920 adult patients with a Charlson Comorbidity Index ≥4 who are established primary care patients of 16 Federally Qualified Health Centers (FQHCs) in NYC (8 FQHCs) and Chicago (8 FQHCs) this pragmatic cRCT aims to evaluate the effectiveness of two approaches to preventing destabilization that leads to unplanned hospitalization and increased disability. This Patient-Centered Outcomes Research Institute (PCORI) study builds on the National Patient-Centered Clinical Research Network (PCORnet) Clinical Data Research Networks (CDRNs) in NYC and Chicago. Patients will be identified via electronic health records (EHRs) and their outcomes assessed through comprehensive, longitudinal, electronic health records that are aggregated by these PCORnet CDRNs.

NCT ID: NCT00980824 Recruiting - Substance Abuse Clinical Trials

ENGAGE - Meeting Mental Health Needs of Complex Comorbid Patients

ENGAGE
Start date: November 2009
Phase: Phase 1/Phase 2
Study type: Interventional

Scotland has higher rates of suicide than other parts of the UK, an average rate of 15.1 per 100,000 in Scotland compared to 11.4 for England and Wales. The Scottish Government is committed to reducing suicide by 2013. Choose Life has led to staff in services such as Accident and Emergency (A&E) receiving recent training in suicide prevention through ASIST and STORM. Evidence for interventions specific to A&E setting is limited despite the fact that this is the most likely point of first contact with health services for people at risk of this behaviour. Brief interventions that reduce repetition of self harm have not been particularly effective partly because of poor attendance and lack of focus on comorbidity. We propose to pilot an evaluation of a brief focused intervention, ENGAGE (based on MAnualised Cognitive Therapy,MACT, developed by the investigator (Kate Davidson) and Prof Ulrike Schmidt of the Institute of Psychiatry, London) for those who present at A&E with a suicide attempt and who have a complex presentation - a combination of substance abuse and or personality disorder, all of which are recognized as high risk factors for suicide. ENGAGE will specifically encourage patients to seek appropriate services to meet their mental health needs. This pilot will allow us to assess the feasibility of a full scale study.