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1. Temporal changes in fecal microbiota of patients infected with COVID-19: a longitudinal cohort

Author

Tatiana Galperine, Yangji Choi, Jean-Luc Pagani, Antonios Kritikos, Matthaios Papadimitriou-Olivgeris, Marie Méan, Valentin Scherz, Onya Opota, Gilbert Greub, Benoit Guery, Claire Bertelli, and the RegCOVID Study Group

Subjects
COVID-19, SARS-CoV-2, Gut microbiota, Microbiota profiling, Gut-lung axis, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a multifaceted disease potentially responsible for various clinical manifestations including gastro-intestinal symptoms. Several evidences suggest that the intestine is a critical site of immune cell development, gut microbiota could therefore play a key role in lung immune response. We designed a monocentric longitudinal observational study to describe the gut microbiota profile in COVID-19 patients and compare it to a pre-existing cohort of ventilated non-COVID-19 patients. Methods From March to December 2020, we included patients admitted for COVID-19 in medicine (43 not ventilated) or intensive care unit (ICU) (14 ventilated) with a positive SARS-CoV-2 RT-PCR assay in a respiratory tract sample. 16S metagenomics was performed on rectal swabs from these 57 COVID-19 patients, 35 with one and 22 with multiple stool collections. Nineteen non-COVID-19 ICU controls were also enrolled, among which 14 developed ventilator-associated pneumonia (pneumonia group) and five remained without infection (control group). SARS-CoV-2 viral loads in fecal samples were measured by qPCR. Results Although similar at inclusion, Shannon alpha diversity appeared significantly lower in COVID-19 and pneumonia groups than in the control group at day 7. Furthermore, the microbiota composition became distinct between COVID-19 and non-COVID-19 groups. The fecal microbiota of COVID-19 patients was characterized by increased Bacteroides and the pneumonia group by Prevotella. In a distance-based redundancy analysis, only COVID-19 presented significant effects on the microbiota composition. Moreover, patients in ICU harbored increased Campylobacter and decreased butyrate-producing bacteria, such as Lachnospiraceae, Roseburia and Faecalibacterium as compared to patients in medicine. Both the stay in ICU and patient were significant factors affecting the microbiota composition. SARS-CoV-2 viral loads were higher in ICU than in non-ICU patients. Conclusions Overall, we identified distinct characteristics of the gut microbiota in COVID-19 patients compared to control groups. COVID-19 patients were primarily characterized by increased Bacteroides and decreased Prevotella. Moreover, disease severity showed a negative correlation with butyrate-producing bacteria. These features could offer valuable insights into potential targets for modulating the host response through the microbiota and contribute to a better understanding of the disease's pathophysiology. Trial registration CER-VD 2020–00755 (05.05.2020) & 2017–01820 (08.06.2018).

Published
2023
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3. Operational integration in primary health care: patient encounters and workflows

Author

Dimitra Sifaki-Pistolla, Vasiliki-Eirini Chatzea, Adelais Markaki, Kyriakos Kritikos, Elena Petelos, and Christos Lionis

Subjects
Primary health care, Operational integration, Integrated care, Clinical pathways, Structure, Outcome, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Despite several countrywide attempts to strengthen and standardise the primary healthcare (PHC) system, Greece is still lacking a sustainable, policy-based model of integrated services. The aim of our study was to identify operational integration levels through existing patient care pathways and to recommend an alternative PHC model for optimum integration. Methods The study was part of a large state-funded project, which included 22 randomly selected PHC units located across two health regions of Greece. Dimensions of operational integration in PHC were selected based on the work of Kringos and colleagues. A five-point Likert-type scale, coupled with an algorithm, was used to capture and transform theoretical framework features into measurable attributes. PHC services were grouped under the main categories of chronic care, urgent/acute care, preventive care, and home care. A web-based platform was used to assess patient pathways, evaluate integration levels and propose improvement actions. Analysis relied on a comparison of actual pathways versus optimal, the latter ones having been identified through literature review. Results Overall integration varied among units. The majority (57%) of units corresponded to a basic level. Integration by type of PHC service ranged as follows: basic (86%) or poor (14%) for chronic care units, poor (78%) or basic (22%) for urgent/acute care units, basic (50%) for preventive care units, and partial or basic (50%) for home care units. The actual pathways across all four categories of PHC services differed from those captured in the optimum integration model. Certain similarities were observed in the operational flows between chronic care management and urgent/acute care management. Such similarities were present at the highest level of abstraction, but also in common steps along the operational flows. Conclusions Existing patient care pathways were mapped and analysed, and recommendations for an optimum integration PHC model were made. The developed web platform, based on a strong theoretical framework, can serve as a robust integration evaluation tool. This could be a first step towards restructuring and improving PHC services within a financially restrained environment.

Published
2017
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4. Identifying the hidden burden of allergic rhinitis (AR) in community pharmacy: a global phenomenon

Author

Rachel Tan, Biljana Cvetkovski, Vicky Kritikos, David Price, Kwok Yan, Pete Smith, and Sinthia Bosnic-Anticevich

Subjects
Allergic rhinitis, Consult pharmacists, Self-manage, Suboptimal management, Diseases of the respiratory system, RC705-779
Abstract

Abstract Background Patients with allergic rhinitis often trivialise their condition, self-manage inappropriately, and would benefit from health care intervention. The primary point of health care contact for these self-managing allergic rhinitis patients is the community pharmacy. With the majority of allergic rhinitis treatments being available for purchase over the counter, without health care professional contact, we know little about how the patients self-manage. This study aims to identify the burden of allergic rhinitis in the community pharmacy and to identify key opportunity for intervention. Methods Pharmacy customers, who purchased nasal treatment in a community pharmacy, were approached with a research-administered questionnaire that collected data on medical history, symptoms and products purchased for the treatment of nasal symptoms. Results Of the 296 participants, 69.9% self-managed with over-the-counter medications; with 68% experiencing allergic rhinitis symptoms and only 44.3% of this subgroup had a doctor’s diagnosis. Nasal congestion (73.6%) was most commonly experienced and oral antihistamines were most commonly purchased (44.3%), indicating a pattern of suboptimal management. A third of participants (36.5%) experienced moderate-severe symptoms, persistently, which impacted on their daily living. Medication selection was mainly based on pharmacy customers’ perceptions of medication effectiveness (47.6%). Conclusion A majority of participants that self-selected over-the-counter medications have symptoms consistent with allergic rhinitis, with almost half not having received a diagnosis. Medication purchasing patterns suggest that sub-optimal therapeutic decisions made by participants, even when they are experiencing significant symptoms. This study uncovers the hidden burden of allergic rhinitis in the community pharmacy and a missed opportunity to intervene and refer if necessary. Patients need to be guided through appropriate treatment as this study showed that many should be referred to a medical practitioner.

Published
2017
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5. Identifying the hidden burden of allergic rhinitis (AR) in community pharmacy: a global phenomenon

Author

Kwok Yan, Biljana Cvetkovski, Peter Smith, Sinthia Bosnic-Anticevich, David Price, Rachel Tan, and Vicky Kritikos

Subjects
Consult pharmacists, Allergy, medicine.medical_specialty, Alternative medicine, Pharmacy, Nasal congestion, Biochemistry, Allergic rhinitis, 03 medical and health sciences, 0302 clinical medicine, Self-manage, Intervention (counseling), Health care, medicine, Medical history, 030212 general & internal medicine, lcsh:RC705-779, business.industry, Research, Organic Chemistry, lcsh:Diseases of the respiratory system, medicine.disease, Suboptimal management, 030228 respiratory system, Family medicine, Physical therapy, Over-the-counter, medicine.symptom, business
Abstract

Background Patients with allergic rhinitis often trivialise their condition, self-manage inappropriately, and would benefit from health care intervention. The primary point of health care contact for these self-managing allergic rhinitis patients is the community pharmacy. With the majority of allergic rhinitis treatments being available for purchase over the counter, without health care professional contact, we know little about how the patients self-manage. This study aims to identify the burden of allergic rhinitis in the community pharmacy and to identify key opportunity for intervention. Methods Pharmacy customers, who purchased nasal treatment in a community pharmacy, were approached with a research-administered questionnaire that collected data on medical history, symptoms and products purchased for the treatment of nasal symptoms. Results Of the 296 participants, 69.9% self-managed with over-the-counter medications; with 68% experiencing allergic rhinitis symptoms and only 44.3% of this subgroup had a doctor’s diagnosis. Nasal congestion (73.6%) was most commonly experienced and oral antihistamines were most commonly purchased (44.3%), indicating a pattern of suboptimal management. A third of participants (36.5%) experienced moderate-severe symptoms, persistently, which impacted on their daily living. Medication selection was mainly based on pharmacy customers’ perceptions of medication effectiveness (47.6%). Conclusion A majority of participants that self-selected over-the-counter medications have symptoms consistent with allergic rhinitis, with almost half not having received a diagnosis. Medication purchasing patterns suggest that sub-optimal therapeutic decisions made by participants, even when they are experiencing significant symptoms. This study uncovers the hidden burden of allergic rhinitis in the community pharmacy and a missed opportunity to intervene and refer if necessary. Patients need to be guided through appropriate treatment as this study showed that many should be referred to a medical practitioner. Electronic supplementary material The online version of this article (10.1186/s40733-017-0036-z) contains supplementary material, which is available to authorized users.

Published
2017

6. Operational integration in primary health care: patient encounters and workflows

Author

Christos Lionis, Vasiliki Eirini Chatzea, Elena Petelos, Kyriakos Kritikos, Adelais Markaki, and Dimitra Sifaki-Pistolla

Subjects
medicine.medical_specialty, Integrated services, Chronic care management, education, Process assessment (healthcare), Health informatics, Patient Care Planning, Workflow, Health administration, Operational integration, 03 medical and health sciences, 0302 clinical medicine, Clinical pathways, Surveys and Questionnaires, Acute care, medicine, Humans, Operations management, 030212 general & internal medicine, Quality indicators (healthcare), Primary health care, Outcome, Chronic care, Greece, business.industry, 030503 health policy & services, Health Policy, Nursing research, lcsh:Public aspects of medicine, Integrated care, Structure, lcsh:RA1-1270, Home Care Services, Patient Care Management, 0305 other medical science, business, Delivery of Health Care, Research Article
Abstract

Background Despite several countrywide attempts to strengthen and standardise the primary healthcare (PHC) system, Greece is still lacking a sustainable, policy-based model of integrated services. The aim of our study was to identify operational integration levels through existing patient care pathways and to recommend an alternative PHC model for optimum integration. Methods The study was part of a large state-funded project, which included 22 randomly selected PHC units located across two health regions of Greece. Dimensions of operational integration in PHC were selected based on the work of Kringos and colleagues. A five-point Likert-type scale, coupled with an algorithm, was used to capture and transform theoretical framework features into measurable attributes. PHC services were grouped under the main categories of chronic care, urgent/acute care, preventive care, and home care. A web-based platform was used to assess patient pathways, evaluate integration levels and propose improvement actions. Analysis relied on a comparison of actual pathways versus optimal, the latter ones having been identified through literature review. Results Overall integration varied among units. The majority (57%) of units corresponded to a basic level. Integration by type of PHC service ranged as follows: basic (86%) or poor (14%) for chronic care units, poor (78%) or basic (22%) for urgent/acute care units, basic (50%) for preventive care units, and partial or basic (50%) for home care units. The actual pathways across all four categories of PHC services differed from those captured in the optimum integration model. Certain similarities were observed in the operational flows between chronic care management and urgent/acute care management. Such similarities were present at the highest level of abstraction, but also in common steps along the operational flows. Conclusions Existing patient care pathways were mapped and analysed, and recommendations for an optimum integration PHC model were made. The developed web platform, based on a strong theoretical framework, can serve as a robust integration evaluation tool. This could be a first step towards restructuring and improving PHC services within a financially restrained environment. Electronic supplementary material The online version of this article (10.1186/s12913-017-2702-5) contains supplementary material, which is available to authorized users.

Published
2017

7. Next-generation ARIA care pathways for rhinitis and asthma : a model for multimorbid chronic diseases

Author

Bousquet, J. Jean, Schunemann, Holger J., Togias, Alkis, Erhola, Marina, Hellings, Peter W., Zuberbier, Torsten, Agache, Ioana, Ansotegui, Ignacio J., Anto, Josep M., Bachert, Claus, Becker, Sven, Bedolla-Barajas, Martin, Bewick, Michael, Bosnic-Anticevich, Sinthia, Bosse, Isabelle, Boulet, Louis P., Bourrez, Jean Marc, Brusselle, Guy, Chavannes, Niels, Costa, Elisio, Cruz, Alvaro A., Czarlewski, Wienczyslawa, Fokkens, Wytske J., Fonseca, Joao A., Gaga, Mina, Haahtela, Tari, Illario, Maddalena, Klimek, Ludger, Kuna, Piotr, Kvedariene, Violeta, Le, L. T. T., Larenas-Linnemann, Desiree, Laune, Daniel, Lourenco, Olga M., Menditto, Enrica, Mullo, Joaquin, Okamoto, Yashitaka, Papadopoulos, Nikos, Pham-Thi, Nhan, Picard, Robert, Pinnock, Hilary, Roche, Nicolas, Roller-Wirnsberger, Regina E., Rolland, Christine, Samolinski, Boleslaw, Sheikh, Aziz, Toppila-Salmi, Sanna, Tsiligianni, Ioanna, Valiulis, Arunas, Valovirta, Erkka, Vasankari, Tuula, Ventura, Maria-Teresa, Walker, Samantha, Williams, Sian, Akdis, Cezmi A., Annesi-Maesano, Isabella, Arnavielhe, Sylvie, Basagana, Xavier, Bateman, Eric, Bedbrook, Anna, Bennoor, K. S., Benveniste, Samuel, Bergmann, Karl C., Bia, Slawomir, Billo, Nils, Bindslev-Jensen, Carsten, Bjermer, Leif, Blain, Hubert, Bonini, Mateo, Bonniaud, Philippe, Bouchard, Jacques, Briedis, Vitalis, Brightling, Christofer E., Brozek, Jan, Buhl, Roland, Buonaiuto, Roland, Canonica, Giorgo W., Cardona, Victoria, Carriazo, Ana M., Carr, Warner, Cartier, Christine, Casale, Thomas, Cecchi, Lorenzo, Cepeda Sarabia, Alfonso M., Chkhartishvili, Eka, Chu, Derek K., Cingi, Cemal, Colgan, Elaine, de Sousa, Jaime Correia, Courbis, Anne Lise, Custovic, Adnan, Cvetkosvki, Biljana, D'Amato, Gennaro, da Silva, Jane, Dantas, Carina, Dokic, Dejand, Dauvilliers, Yves, Dedeu, Antoni, De Feo, Giulia, Devillier, Philippe, Di Capua, Stefania, Dykewickz, Marc, Dubakiene, Ruta, Ebisawa, Motohiro, El-Gamal, Yaya, Eller, Esben, Emuzyte, Regina, Farrell, John, Fink-Wagner, Antjie, Fiocchi, Alessandro, Fontaine, Jean F., Gemicioglu, Bilun, Schmid-Grendelmeir, Peter, Gamkrelidze, Amiran, Garcia-Aymerich, Judith, Gomez, Maximiliano, Gonzalez Diaz, Sandra, Gotua, Maia, Guldemond, Nick A., Guzman, Maria-Antonieta, Hajjam, Jawad, Hourihane, John O'B, Humbert, Marc, Iaccarino, Guido, Ierodiakonou, Despo, Ivancevich, Juan C., Joos, Guy, Jung, Ki-Suck, Jutel, Marek, Kaidashev, Igor, Kalayci, Omer, Kardas, Przemyslaw, Keil, Thomas, Khaitov, Mussa, Khaltaev, Nikolai, Kleine-Tebbe, Jorg, Kowalski, Marek L., Kritikos, Vicky, Kull, Inger, Leonardini, Lisa, Lieberman, Philip, Lipworth, Brian, Carlsen, Karin C. Lodrup, Loureiro, Claudia C., Louis, Renaud, Mair, Alpana, Marien, Gert, Mahboub, Bassam, Malva, Joao, Manning, Patrick, Keenoy, Esteban De Manuel, Marshall, Gallen D., Masjedi, Mohamed R., Maspero, Jorge F., Mathieu-Dupas, Eve, Matricardi, Poalo M., Melen, Eric, Melo-Gomes, Elisabete, Meltzer, Eli O., Mercier, Jacques, Miculinic, Neven, Mihaltan, Florin, Milenkovic, Branislava, Moda, Giuliana, Mogica-Martinezl, Maria-Dolores, Mohammad, Yousser, Montefort, Steve, Monti, Ricardo, Morais-Almeida, Mario, Moesges, Raft, Munter, Lars, Muraro, Antonella, Murray, Ruth, Naclerio, Robert, Napoli, Luigi, Namazova-Baranova, Leila, Neffen, Hugo, Nekam, Kristoff, Neou, Angelo, Novellino, Enrico, Nyembue, Dieudonne, O'Hehir, Robin, Ohta, Ken, Okubo, Kimi, Onorato, Gabrielle, Ouedraogo, Solange, Pali-Schoell, Isabella, Palkonen, Susanna, Panzner, Peter, Park, Hae-Sim, Pepin, Jean-Louis, Pereira, Ana-Maria, Pfaar, Oliver, Paulino, Ema, Phillips, Jim, Plavec, Davor, Popov, Ted A., Portejoie, Fabienne, Price, David, Prokopakis, Emmanuel P., Pugin, Benoit, Raciborski, Filip, Rajabian-Soderlund, Rojin, Reitsma, Sietze, Rodo, Xavier, Romano, Antonino, Rosario, Nelson, Rottem, Menahenm, Ryan, Dermot, Salimaki, Johanna, Sanchez-Borges, Mario M., Sisul, Juan-Carlos, Sole, Dirceu, Somekh, David, Sooronbaev, Talant, Sova, Milan, Spranger, Otto, Stellato, Cristina, Stelmach, Rafael, Ulrik, Charlotte Suppli, Thibaudon, Michel, To, Teresa, Todo-Bom, Ana, Tomazic, Peter, V, Valero, Antonio A., Valenta, Rudolph, Valentin-Rostan, Marylin, van der Kleij, Rianne, Vandenplas, Olivier, Vezzani, Giorgio, Viart, Frederic, Vieg, Giovanni, Wallace, Dana, Wagenmann, Martin, Wang, De Y., Waserman, Susan, Wickman, Magnus, Williams, Dennis M., Wong, Gary, Wroczynski, Piotr, Yiallouros, Panayiotis K., Yorgancioglu, Arzu, Yusuf, Osman M., Zar, Heahter J., Zeng, Stephane, Zernotti, Mario, Zhang, Luo, Zhong, Nan S., Zidarn, Mihaela, Bousquet, J. Jean, Schunemann, Holger J., Togias, Alkis, Erhola, Marina, Hellings, Peter W., Zuberbier, Torsten, Agache, Ioana, Ansotegui, Ignacio J., Anto, Josep M., Bachert, Claus, Becker, Sven, Bedolla-Barajas, Martin, Bewick, Michael, Bosnic-Anticevich, Sinthia, Bosse, Isabelle, Boulet, Louis P., Bourrez, Jean Marc, Brusselle, Guy, Chavannes, Niels, Costa, Elisio, Cruz, Alvaro A., Czarlewski, Wienczyslawa, Fokkens, Wytske J., Fonseca, Joao A., Gaga, Mina, Haahtela, Tari, Illario, Maddalena, Klimek, Ludger, Kuna, Piotr, Kvedariene, Violeta, Le, L. T. T., Larenas-Linnemann, Desiree, Laune, Daniel, Lourenco, Olga M., Menditto, Enrica, Mullo, Joaquin, Okamoto, Yashitaka, Papadopoulos, Nikos, Pham-Thi, Nhan, Picard, Robert, Pinnock, Hilary, Roche, Nicolas, Roller-Wirnsberger, Regina E., Rolland, Christine, Samolinski, Boleslaw, Sheikh, Aziz, Toppila-Salmi, Sanna, Tsiligianni, Ioanna, Valiulis, Arunas, Valovirta, Erkka, Vasankari, Tuula, Ventura, Maria-Teresa, Walker, Samantha, Williams, Sian, Akdis, Cezmi A., Annesi-Maesano, Isabella, Arnavielhe, Sylvie, Basagana, Xavier, Bateman, Eric, Bedbrook, Anna, Bennoor, K. S., Benveniste, Samuel, Bergmann, Karl C., Bia, Slawomir, Billo, Nils, Bindslev-Jensen, Carsten, Bjermer, Leif, Blain, Hubert, Bonini, Mateo, Bonniaud, Philippe, Bouchard, Jacques, Briedis, Vitalis, Brightling, Christofer E., Brozek, Jan, Buhl, Roland, Buonaiuto, Roland, Canonica, Giorgo W., Cardona, Victoria, Carriazo, Ana M., Carr, Warner, Cartier, Christine, Casale, Thomas, Cecchi, Lorenzo, Cepeda Sarabia, Alfonso M., Chkhartishvili, Eka, Chu, Derek K., Cingi, Cemal, Colgan, Elaine, de Sousa, Jaime Correia, Courbis, Anne Lise, Custovic, Adnan, Cvetkosvki, Biljana, D'Amato, Gennaro, da Silva, Jane, Dantas, Carina, Dokic, Dejand, Dauvilliers, Yves, Dedeu, Antoni, De Feo, Giulia, Devillier, Philippe, Di Capua, Stefania, Dykewickz, Marc, Dubakiene, Ruta, Ebisawa, Motohiro, El-Gamal, Yaya, Eller, Esben, Emuzyte, Regina, Farrell, John, Fink-Wagner, Antjie, Fiocchi, Alessandro, Fontaine, Jean F., Gemicioglu, Bilun, Schmid-Grendelmeir, Peter, Gamkrelidze, Amiran, Garcia-Aymerich, Judith, Gomez, Maximiliano, Gonzalez Diaz, Sandra, Gotua, Maia, Guldemond, Nick A., Guzman, Maria-Antonieta, Hajjam, Jawad, Hourihane, John O'B, Humbert, Marc, Iaccarino, Guido, Ierodiakonou, Despo, Ivancevich, Juan C., Joos, Guy, Jung, Ki-Suck, Jutel, Marek, Kaidashev, Igor, Kalayci, Omer, Kardas, Przemyslaw, Keil, Thomas, Khaitov, Mussa, Khaltaev, Nikolai, Kleine-Tebbe, Jorg, Kowalski, Marek L., Kritikos, Vicky, Kull, Inger, Leonardini, Lisa, Lieberman, Philip, Lipworth, Brian, Carlsen, Karin C. Lodrup, Loureiro, Claudia C., Louis, Renaud, Mair, Alpana, Marien, Gert, Mahboub, Bassam, Malva, Joao, Manning, Patrick, Keenoy, Esteban De Manuel, Marshall, Gallen D., Masjedi, Mohamed R., Maspero, Jorge F., Mathieu-Dupas, Eve, Matricardi, Poalo M., Melen, Eric, Melo-Gomes, Elisabete, Meltzer, Eli O., Mercier, Jacques, Miculinic, Neven, Mihaltan, Florin, Milenkovic, Branislava, Moda, Giuliana, Mogica-Martinezl, Maria-Dolores, Mohammad, Yousser, Montefort, Steve, Monti, Ricardo, Morais-Almeida, Mario, Moesges, Raft, Munter, Lars, Muraro, Antonella, Murray, Ruth, Naclerio, Robert, Napoli, Luigi, Namazova-Baranova, Leila, Neffen, Hugo, Nekam, Kristoff, Neou, Angelo, Novellino, Enrico, Nyembue, Dieudonne, O'Hehir, Robin, Ohta, Ken, Okubo, Kimi, Onorato, Gabrielle, Ouedraogo, Solange, Pali-Schoell, Isabella, Palkonen, Susanna, Panzner, Peter, Park, Hae-Sim, Pepin, Jean-Louis, Pereira, Ana-Maria, Pfaar, Oliver, Paulino, Ema, Phillips, Jim, Plavec, Davor, Popov, Ted A., Portejoie, Fabienne, Price, David, Prokopakis, Emmanuel P., Pugin, Benoit, Raciborski, Filip, Rajabian-Soderlund, Rojin, Reitsma, Sietze, Rodo, Xavier, Romano, Antonino, Rosario, Nelson, Rottem, Menahenm, Ryan, Dermot, Salimaki, Johanna, Sanchez-Borges, Mario M., Sisul, Juan-Carlos, Sole, Dirceu, Somekh, David, Sooronbaev, Talant, Sova, Milan, Spranger, Otto, Stellato, Cristina, Stelmach, Rafael, Ulrik, Charlotte Suppli, Thibaudon, Michel, To, Teresa, Todo-Bom, Ana, Tomazic, Peter, V, Valero, Antonio A., Valenta, Rudolph, Valentin-Rostan, Marylin, van der Kleij, Rianne, Vandenplas, Olivier, Vezzani, Giorgio, Viart, Frederic, Vieg, Giovanni, Wallace, Dana, Wagenmann, Martin, Wang, De Y., Waserman, Susan, Wickman, Magnus, Williams, Dennis M., Wong, Gary, Wroczynski, Piotr, Yiallouros, Panayiotis K., Yorgancioglu, Arzu, Yusuf, Osman M., Zar, Heahter J., Zeng, Stephane, Zernotti, Mario, Zhang, Luo, Zhong, Nan S., and Zidarn, Mihaela

Abstract

Background: In all societies, the burden and cost of allergic and chronic respiratory diseases are increasing rapidly. Most economies are struggling to deliver modern health care effectively. There is a need to support the transformation of the health care system into integrated care with organizational health literacy. Main body: As an example for chronic disease care, MASK (Mobile Airways Sentinel NetworK), a new project of the ARIA (Allergic Rhinitis and its Impact on Asthma) initiative, and POLLAR (Impact of Air POLLution on Asthma and Rhinitis, EIT Health), in collaboration with professional and patient organizations in the field of allergy and airway diseases, are proposing real-life ICPs centred around the patient with rhinitis, and using mHealth to monitor environmental exposure. Three aspects of care pathways are being developed: (i) Patient participation, health literacy and self-care through technology-assisted "patient activation", (ii) Implementation of care pathways by pharmacists and (iii) Next-generation guidelines assessing the recommendations of GRADE guidelines in rhinitis and asthma using real-world evidence (RWE) obtained through mobile technology. The EU and global political agendas are of great importance in supporting the digital transformation of health and care, and MASK has been recognized by DG Sante as a Good Practice in the field of digitally-enabled, integrated, person-centred care. Conclusion: In 20 years, ARIA has considerably evolved from the first multimorbidity guideline in respiratory diseases to the digital transformation of health and care with a strong political involvement.

Published
2019
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8. Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme

Author

Moschopoulos Charalampos, Kritikos George D, Vazirgiannis Michalis, and Kossida Sophia

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied. Results We adopt a two step procedure. During the first step, by applying both novel and well established protein-protein interaction (PPI) weighting methods, weights are introduced to the original interactome graph based on the confidence level that a given interaction is a true-positive one. The second step applies clustering using established algorithms in the field of graph theory, as well as two variations of Spectral clustering. The clustered interactome networks are also cross-validated against the confirmed protein complexes present in the MIPS database. Conclusions The results of our experimental work demonstrate that interactome graph weighting methods clearly improve the clustering results of several clustering algorithms. Moreover, our proposed weighting scheme outperforms other approaches of PPI graph weighting.

Published
2011
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