1
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Shen X, Wu J, Su J, Yao Z, Huang W, Zhang L, Jiang Y, Yu W, Li Z. Revisiting artificial intelligence diagnosis of hepatocellular carcinoma with DIKWH framework. Front Genet 2023; 14:1004481. [PMID: 37007970 PMCID: PMC10064216 DOI: 10.3389/fgene.2023.1004481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 02/14/2023] [Indexed: 03/09/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high morbidity and fatality rate. Traditional diagnostic methods for HCC are primarily based on clinical presentation, imaging features, and histopathology. With the rapid development of artificial intelligence (AI), which is increasingly used in the diagnosis, treatment, and prognosis prediction of HCC, an automated approach to HCC status classification is promising. AI integrates labeled clinical data, trains on new data of the same type, and performs interpretation tasks. Several studies have shown that AI techniques can help clinicians and radiologists be more efficient and reduce the misdiagnosis rate. However, the coverage of AI technologies leads to difficulty in which the type of AI technology is preferred to choose for a given problem and situation. Solving this concern, it can significantly reduce the time required to determine the required healthcare approach and provide more precise and personalized solutions for different problems. In our review of research work, we summarize existing research works, compare and classify the main results of these according to the specified data, information, knowledge, wisdom (DIKW) framework.
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Affiliation(s)
- Xiaomin Shen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jinxin Wu
- School of Computer Science, The University of Sydney, Sydney, NSW, Australia
| | - Junwei Su
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Zhenyu Yao
- School of Computer Science, King’s College London, London, United Kingdom
| | - Wei Huang
- Department of Gastroenterology II, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Li Zhang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yiheng Jiang
- Clinical Medicine, Nanjing Medical University, Nanjing, China
| | - Wei Yu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Zhao Li
- School of Computer Science, Zhejiang University, Hangzhou, China
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2
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Lewis D, Salmi L, Staley A, Harlow J. From Individuals to Systems and Contributions to Creations: Novel Framework for Mapping the Efforts of Individuals by Convening The Center of Health and Health Care. J Particip Med 2022; 14:e39339. [DOI: 10.2196/39339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/05/2022] [Accepted: 09/06/2022] [Indexed: 11/06/2022] Open
Abstract
Background
People with lived health care experiences (often referred to as “patients”) are increasingly contributing to health care and are most effective when they are involved as partners who can contribute complementary knowledge alongside other stakeholders in health care.
Objective
Convening The Center aimed to bring together “people known as patients”—the center of health care—to address priorities as they defined them.
Methods
According to the original project design, an in-person gathering was to be conducted; however, as a result of the COVID-19 pandemic, the in-person gathering was transformed into a series of digital gatherings, including an in-depth interview phase, small-group gatherings, and a collective convening of 25 participants (22 women and 3 men from the United States, India, Costa Rica, Sweden, and Pakistan). Each participant was interviewed on Zoom (Zoom Video Communications Inc), and the interview data were thematically analyzed to design a subsequent small group and then full cohort Zoom sessions. Visual note-taking was used to reinforce a shared understanding of each individual- and group-level conversation.
Results
The interviews and gatherings for Convening The Center offered unique perspectives on patient activities in research, health innovation, and problem-solving. This project further developed a novel, two-spectrum framework for assessing different experiences that patients may have or seek to gain, based on what patients actually do, and different levels of patients’ involvement, ranging from individual to community to systemic involvement.
Conclusions
The descriptors of patients in academic literature typically focus on what health care providers think patients “are” rather than on what patients “do.” The primary result of this project is a framework for mapping what patients “do” and “where” they do their work along two spectra: from creating their own projects to contributing to work initiated by others and from working at levels ranging from individual to community to systems. A better understanding of these spectra may enable researchers to more effectively engage and leverage patient expertise in health care research and innovation.
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3
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Singla RK, Behzad S, Khan J, Tsagkaris C, Gautam RK, Goyal R, Chopra H, Shen B. Natural Kinase Inhibitors for the Treatment and Management of Endometrial/Uterine Cancer: Preclinical to Clinical Studies. Front Pharmacol 2022; 13:801733. [PMID: 35264951 PMCID: PMC8899191 DOI: 10.3389/fphar.2022.801733] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 01/17/2022] [Indexed: 02/05/2023] Open
Abstract
Endometrial cancer (EC) is the sixth most prevalent type of cancer among women. Kinases, enzymes mediating the transfer of adenosine triphosphate (ATP) in several signaling pathways, play a significant role in carcinogenesis and cancer cells’ survival and proliferation. Cyclin-dependent kinases (CDKs) are involved in EC pathogenesis; therefore, CDK inhibitors (CDKin) have a noteworthy therapeutic potential in this type of cancer, particularly in EC type 1. Natural compounds have been used for decades in the treatment of cancer serving as a source of anticancer bioactive molecules. Many phenolic and non-phenolic natural compounds covering flavonoids, stilbenoids, coumarins, biphenyl compounds, alkaloids, glycosides, terpenes, and terpenoids have shown moderate to high effectiveness against CDKin-mediated carcinogenic signaling pathways (PI3K, ERK1/2, Akt, ATM, mTOR, TP53). Pharmaceutical regimens based on two natural compounds, trabectedin and ixabepilone, have been investigated in humans showing short and midterm efficacy as second-line treatments in phase II clinical trials. The purpose of this review is twofold: the authors first provide an overview of the involvement of kinases and kinase inhibitors in the pathogenesis and treatment of EC and then discuss the existing evidence about natural products’ derived kinase inhibitors in the management of the disease and outline relevant future research.
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Affiliation(s)
- Rajeev K Singla
- Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.,IGlobal Research and Publishing Foundation, New Delhi, India
| | - Sahar Behzad
- Evidence-based Phytotherapy and Complementary Medicine Research Center, Alborz University of Medical Sciences, Karaj, Iran.,Department of Pharmacognosy, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Johra Khan
- Department of Medical Laboratory Sciences, College of Applied Medical Sciences, Majmaah University, Al Majmaah, Saudi Arabia.,Health and Basic Sciences Research Center, Majmaah University, Majmaah, Saudi Arabia
| | | | - Rupesh K Gautam
- Department of Pharmacology, MM School of Pharmacy, MM University, Ambala, India
| | - Rajat Goyal
- Department of Pharmacology, MM School of Pharmacy, MM University, Ambala, India
| | | | - Bairong Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
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De Maria Marchiano R, Di Sante G, Piro G, Carbone C, Tortora G, Boldrini L, Pietragalla A, Daniele G, Tredicine M, Cesario A, Valentini V, Gallo D, Babini G, D’Oria M, Scambia G. Translational Research in the Era of Precision Medicine: Where We Are and Where We Will Go. J Pers Med 2021; 11:216. [PMID: 33803592 PMCID: PMC8002976 DOI: 10.3390/jpm11030216] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 03/09/2021] [Accepted: 03/15/2021] [Indexed: 12/13/2022] Open
Abstract
The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ineffective therapies and reduce adverse effects. The spread of "multi-omics" analysis and the use of sensors, together with the ability to acquire clinical, behavioral, and environmental information on a large scale, will allow the digitization of the state of health or disease of each person, and the creation of a global health management system capable of generating real-time knowledge and new opportunities for prevention and therapy in the individual person (high-definition medicine). Real world data-based translational applications represent a promising alternative to the traditional evidence-based medicine (EBM) approaches that are based on the use of randomized clinical trials to test the selected hypothesis. Multi-modality data integration is necessary for example in precision oncology where an Avatar interface allows several simulations in order to define the best therapeutic scheme for each cancer patient.
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Affiliation(s)
- Ruggero De Maria Marchiano
- Department of Translational Medicine and Surgery, Section of General Pathology, Università Cattolica del Sacro Cuore, 00168 Rome, Italy or (R.D.M.M.); (M.T.)
- Scientific Direction, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (A.C.); (M.D.); or (G.S.)
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
| | - Gabriele Di Sante
- Department of Translational Medicine and Surgery, Section of General Pathology, Università Cattolica del Sacro Cuore, 00168 Rome, Italy or (R.D.M.M.); (M.T.)
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
| | - Geny Piro
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Medical Oncology, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Carmine Carbone
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Medical Oncology, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Giampaolo Tortora
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Medical Oncology, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
- Department of Translational Medicine and Surgery, Section of Oncology, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Luca Boldrini
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Department of Radiology, Radiation Oncology and Hematology, UOC Radioterapia Oncologica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Antonella Pietragalla
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Unità di Medicina Traslazionale per la Salute della Donna e del Bambino, Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Gennaro Daniele
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Unità di Medicina Traslazionale per la Salute della Donna e del Bambino, Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Maria Tredicine
- Department of Translational Medicine and Surgery, Section of General Pathology, Università Cattolica del Sacro Cuore, 00168 Rome, Italy or (R.D.M.M.); (M.T.)
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
| | - Alfredo Cesario
- Scientific Direction, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (A.C.); (M.D.); or (G.S.)
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
| | - Vincenzo Valentini
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Department of Radiology, Radiation Oncology and Hematology, UOC Radioterapia Oncologica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
- Institute of di Radiology, Università Cattolica Del Sacro Cuore, 00168 Rome, Italy
| | - Daniela Gallo
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Unità di Medicina Traslazionale per la Salute della Donna e del Bambino, Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
- Dipartimento Universitario Scienze della Vita e Sanità Pubblica, Sezione di Ginecologia ed Ostetricia, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Gabriele Babini
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Unità di Medicina Traslazionale per la Salute della Donna e del Bambino, Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Marika D’Oria
- Scientific Direction, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (A.C.); (M.D.); or (G.S.)
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
| | - Giovanni Scambia
- Scientific Direction, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (A.C.); (M.D.); or (G.S.)
- Comprehensive Cancer Center—Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (G.P.); (C.C.); or (G.T.); (L.B.); (A.P.); (G.D.); or (V.V.); or (D.G.); (G.B.)
- Unità di Medicina Traslazionale per la Salute della Donna e del Bambino, Dipartimento Scienze della Salute della Donna, del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
- Dipartimento Universitario Scienze della Vita e Sanità Pubblica, Sezione di Ginecologia ed Ostetricia, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
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5
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Chen Y, Liu X, Yu Y, Yu C, Yang L, Lin Y, Xi T, Ye Z, Feng Z, Shen B. PCaLiStDB: a lifestyle database for precision prevention of prostate cancer. Database (Oxford) 2020; 2020:baz154. [PMID: 31950190 PMCID: PMC6966110 DOI: 10.1093/database/baz154] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 11/30/2019] [Accepted: 12/13/2019] [Indexed: 02/05/2023]
Abstract
The interaction between genes, lifestyles and environmental factors makes the genesis and progress of prostate cancer (PCa) very heterogeneous. Positive lifestyle is important to the prevention and controlling of PCa. To investigate the relationship between PCa and lifestyle at systems level, we established a PCa related lifestyle database (PCaLiStDB) and collected the PCa-related lifestyles including foods, nutrients, life habits and social and environmental factors as well as associated genes and physiological and biochemical indexes together with the disease phenotypes and drugs. Data format standardization was implemented for the future Lifestyle-Wide Association Studies of PCa (PCa_LWAS). Currently, 2290 single-factor lifestyles and 856 joint effects of two or more lifestyles were collected. Among these, 394 are protective factors, 556 are risk factors, 45 are no-influencing factors, 52 are factors with contradictory views and 1977 factors are lacking effective literatures support. PCaLiStDB is expected to facilitate the prevention and control of PCa, as well as the promotion of mechanistic study of lifestyles on PCa. Database URL: http://www.sysbio.org.cn/pcalistdb/.
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Affiliation(s)
- Yalan Chen
- Center for Systems Biology, Soochow University, Suzhou 215006, China
- Department of Medical Informatics, School of Medicine, Nantong University, Nantong 226001, China
| | - Xingyun Liu
- Center for Systems Biology, Soochow University, Suzhou 215006, China
- Institutes for Systems Genetics, West China Hospital, Sichuan University, No.17 Gaopeng Avenue, Chengdu 610041, China
| | - Yijun Yu
- Department of Medical Informatics, School of Medicine, Nantong University, Nantong 226001, China
| | - Chunjiang Yu
- Center for Systems Biology, Soochow University, Suzhou 215006, China
- School of Nanotechnology, Suzhou Industrial Park Institute of Services Outsourcing, Suzhou 215123, China
| | - Lan Yang
- Center for Systems Biology, Soochow University, Suzhou 215006, China
| | - Yuxin Lin
- Center for Systems Biology, Soochow University, Suzhou 215006, China
- Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou 215006, China
| | - Ting Xi
- Department of Medical Informatics, School of Medicine, Nantong University, Nantong 226001, China
| | - Ziyun Ye
- Department of Medical Informatics, School of Medicine, Nantong University, Nantong 226001, China
| | - Zhe Feng
- Department of Medical Informatics, School of Medicine, Nantong University, Nantong 226001, China
| | - Bairong Shen
- Institutes for Systems Genetics, West China Hospital, Sichuan University, No.17 Gaopeng Avenue, Chengdu 610041, China
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6
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Riba M, Sala C, Toniolo D, Tonon G. Big Data in Medicine, the Present and Hopefully the Future. Front Med (Lausanne) 2019; 6:263. [PMID: 31803746 PMCID: PMC6873822 DOI: 10.3389/fmed.2019.00263] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 10/29/2019] [Indexed: 01/01/2023] Open
Abstract
The emergence of data coming from different venues, as several “omic” approaches, is providing already compelling evidence that the smart use of this information could provide invaluable information to prevent, diagnose and treat human diseases. However, the most daunting challenges remain ahead, as the explosive accumulation of data from additional perspectives, including social graphs, biosensors, and imaging, promise to deliver crucial information that could be exploited for the improvement of the entire human race, both in developed, and developing countries, optimizing health expenses and reaching also the less fortunate sections of the societies. And yet, formidable challenges remain, that pertain for the most part to the collection of the data, their organization, and most relevantly their integration. Here we provide few, pointed examples to the present relevance of these big data approaches in human health as well potential road maps toward the implementation of broader data collections and analyses.
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Affiliation(s)
- Michela Riba
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Cinzia Sala
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Daniela Toniolo
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giovanni Tonon
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Functional Genomics of Cancer Unit, Experimental Oncology Division, IRCCS San Raffaele Scientific Institute, Milan, Italy
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7
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Gavrilova A, Bandere D, Rutkovska I, Šmits D, Mauriņa B, Poplavska E, Urtāne AI. Knowledge about Disease, Medication Therapy, and Related Medication Adherence Levels among Patients with Hypertension. MEDICINA (KAUNAS, LITHUANIA) 2019; 55:E715. [PMID: 31661904 PMCID: PMC6915331 DOI: 10.3390/medicina55110715] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/07/2019] [Accepted: 10/25/2019] [Indexed: 12/19/2022]
Abstract
Background and Objectives: A particular problem in cardiology is poor adherence to pharmacological treatment among patients with hypertension. It is known that approximately half of these patients do not use their medications as prescribed by their doctor. Patients may choose not to follow the doctor's recommendations and regularly do not control their blood pressure, owing to many factors. A convenient method for measuring the level of adherence is the Morisky Medication Adherence Scale, which also provides insight into possible remedies for low adherence. We investigated their therapy, knowledge about the disease and its control, and demographic differences to assess the adherence of patients with hypertension. Materials and Methods: This was a cross-sectional observational study. Data were collected through a survey of 12 pharmacies in Latvia. The study involved 187 participants with hypertension. Results: The prevalence of non-adherence was 46.20% in Latvia. The oldest patients were the most adherent (p = 0.001, β = 0.27). The higher the self-rated extent from 0 to 10, to which the patient takes their antihypertensives exactly as instructed by their physician, the higher the level of adherence (p < 0.0001, β = 0.38), where at "0", the patient does not follow physician instructions at all, and at "10", the patient completely follows the physician's instructions. Non-adherent patients tend to assess their medication-taking behavior more critically than adherent patients. The longer the patient is known to suffer from hypertension, the more adherent he or she is (p = 0.014, β = 0.19). Conclusions: Medication non-adherence among patients with hypertension is high in Latvia. Further investigations are needed to better understand the reasons for this and to establish interventions for improving patient outcomes.
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Affiliation(s)
- Anna Gavrilova
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
| | - Dace Bandere
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
| | - Ieva Rutkovska
- Department of Dosage Form Technology, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
| | - Dins Šmits
- Department of Dosage Form Technology, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
- Department of Public Health and Epidemiology, Faculty of Public Health and Welfare, Rīga Stradiņš University, LV-1010 Riga, Latvia.
| | - Baiba Mauriņa
- Department of Dosage Form Technology, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
| | - Elita Poplavska
- Department of Dosage Form Technology, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
- Institute of Public Health, Rīga Stradiņš University, LV-1046 Riga, Latvia.
| | - And Inga Urtāne
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Rīga Stradiņš University, LV-1007 Riga, Latvia.
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8
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Qing F, Liu C. Forecasting Single Disease Cost of Cataract Based on Multivariable Regression Analysis and Backpropagation Neural Network. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2019; 56:46958019880740. [PMID: 31617426 PMCID: PMC6796205 DOI: 10.1177/0046958019880740] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
In medical services, charge according to the disease is an important way to
promote the reform of pricing mechanism, control the unreasonable growth of
medical expenses, as well as reduce the burden on patients. Single disease cost
forecasting that both identify potential influencing or driving factors and
enable better proactive estimation of costs can guide the management and control
of medical costs. This study aimed to identify the factors that affect the
medical costs of single disease cataract and compare 2 regression models for
anticipating acceptable medical cost forecasts. For this purpose, 483 patients
with cataract surgery completed in West China Hospital from May 1, 2015, to
October 1, 2015, were selected from hospital information system. For cost
forecasting, multivariable regression analysis (MRA) and backpropagation neural
network (BPNN) were used. Analysis of data was performed with SPSS21.0 and
MATLAB2014a software. Total medical costs of patients with cataract (n = 483)
ranged from 2015.00 to 13 359.00 CNY, and the mean ± standard deviation is
6292.29 ± 2639.43 CNY. Factors influencing costs of cataract in the MRA include,
in importance order, intraocular lens (IOL) implantation (|r|:
0.805, P < .01), doctor level (|r|: 0.644,
P < .01), payment source (|r|: 0.554,
P < .01), admission status (|r|: 0.326,
P < .01), additional diagnosis (|r|:
0.260, P < .01), type of surgery (|r|:
0.127, P < .05), and type of anesthesia
(|r|: 0.126, P < .05). In terms of
forecasting performance, BPNN (average error: 2.81%) outperforms, yet is less
interpretable than MRA (average error: 5.79%). Both MRA and BPNN are technically
and economically feasible in generating medical costs of cataract. And some
insights on using results of the forecasting model in controlling and reducing
disease costs are obtained.
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Affiliation(s)
- Fang Qing
- Business School, Sichuan University, Chengdu, China
| | - Chuang Liu
- Business School, Sichuan University, Chengdu, China.,Logistics Engineering School, Chengdu Vocational & Technical College of Industry, China
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Leviton A, Oppenheimer J, Chiujdea M, Antonetty A, Ojo OW, Garcia S, Weas S, Fleegler E, Chan E, Loddenkemper T. Characteristics of Future Models of Integrated Outpatient Care. Healthcare (Basel) 2019; 7:healthcare7020065. [PMID: 31035586 PMCID: PMC6627383 DOI: 10.3390/healthcare7020065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 04/23/2019] [Accepted: 04/24/2019] [Indexed: 01/01/2023] Open
Abstract
Replacement of fee-for-service with capitation arrangements, forces physicians and institutions to minimize health care costs, while maintaining high-quality care. In this report we described how patients and their families (or caregivers) can work with members of the medical care team to achieve these twin goals of maintaining-and perhaps improving-high-quality care and minimizing costs. We described how increased self-management enables patients and their families/caregivers to provide electronic patient-reported outcomes (i.e., symptoms, events) (ePROs), as frequently as the patient or the medical care team consider appropriate. These capabilities also allow ongoing assessments of physiological measurements/phenomena (mHealth). Remote surveillance of these communications allows longer intervals between (fewer) patient visits to the medical-care team, when this is appropriate, or earlier interventions, when it is appropriate. Systems are now available that alert medical care providers to situations when interventions might be needed.
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Affiliation(s)
- Alan Leviton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Julia Oppenheimer
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Madeline Chiujdea
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Annalee Antonetty
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Oluwafemi William Ojo
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Stephanie Garcia
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Sarah Weas
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Eric Fleegler
- Division of Emergency Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Eugenia Chan
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
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10
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Oppenheimer J, Leviton A, Chiujdea M, Antonetty A, Ojo OW, Garcia S, Weas S, Fleegler EW, Chan E, Loddenkemper T. Caring electronically for young outpatients who have epilepsy. Epilepsy Behav 2018; 87:226-232. [PMID: 30197227 DOI: 10.1016/j.yebeh.2018.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Revised: 06/08/2018] [Accepted: 06/11/2018] [Indexed: 01/17/2023]
Abstract
PURPOSE The purpose of this study was to review electronic tools that might improve the delivery of epilepsy care, reduce medical care costs, and empower families to improve self-management capability. METHOD We reviewed the epilepsy-specific literature about self-management, electronic patient-reported or provider-reported outcomes, on-going remote surveillance, and alerting/warning systems. CONCLUSIONS The improved care delivery system that we envision includes self-management, electronic patient (or provider)-reported outcomes, on-going remote surveillance, and alerting/warning systems. This system and variants have the potential to reduce seizure burden through improved management, keep children out of the emergency department and hospital, and even reduce the number of outpatient visits.
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Affiliation(s)
- Julia Oppenheimer
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alan Leviton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Madeline Chiujdea
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Annalee Antonetty
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Oluwafemi William Ojo
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Stephanie Garcia
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sarah Weas
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Eric W Fleegler
- Division of Emergency Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Eugenia Chan
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Tobias Loddenkemper
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
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