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Coll-Planas L, Carbó-Cardeña A, Jansson A, Dostálová V, Bartova A, Rautiainen L, Kolster A, Masó-Aguado M, Briones-Buixassa L, Blancafort-Alias S, Roqué-Figuls M, Sachs AL, Casajuana C, Siebert U, Rochau U, Puntscher S, Holmerová I, Pitkala KH, Litt JS. Nature-based social interventions to address loneliness among vulnerable populations: a common study protocol for three related randomized controlled trials in Barcelona, Helsinki, and Prague within the RECETAS European project. BMC Public Health 2024; 24:172. [PMID: 38218784 PMCID: PMC10787456 DOI: 10.1186/s12889-023-17547-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/20/2023] [Indexed: 01/15/2024] Open
Abstract
BACKGROUND The negative effects of loneliness on population health and wellbeing requires interventions that transcend the medical system and leverage social, cultural, and public health system resources. Group-based social interventions are a potential method to alleviate loneliness. Moreover, nature, as part of our social and health infrastructure, may be an important part of the solutions that are needed to address loneliness. The RECETAS European project H2020 (Re-imagining Environments for Connection and Engagement: Testing Actions for Social Prescribing in Natural Spaces) is an international research project aiming to develop and test the effectiveness of nature-based social interventions to reduce loneliness and increase health-related quality of life. METHODS This article describes the three related randomized controlled trials (RCTs) that will be implemented: the RECETAS-BCN Trial in Barcelona (Spain) is targeting people 18+ from low socio-economic urban areas; the RECETAS-PRG Trial in Prague (Czech Republic) is addressing community-dwelling older adults over 60 years of age, and the RECETAS-HLSNK trial is reaching older people in assisted living facilities. Each trial will recruit 316 adults suffering from loneliness at least sometimes and randomize them to nature-based social interventions called "Friends in Nature" or to the control group. "Friends in Nature" uses modifications of the "Circle of Friends" methodology based on group processes of peer support and empowerment but including activities in nature. Participants will be assessed at baseline, at post-intervention (3 months), and at 6- and 12-month follow-up after baseline. Primary outcomes are the health-related quality-of-life according to 15D measure and The De Jong Gierveld 11-item loneliness scale. Secondary outcomes are health and psychosocial variables tailored to the specific target population. Nature exposure will be collected throughout the intervention period. Process evaluation will explore context, implementation, and mechanism of impact. Additionally, health economic evaluations will be performed. DISCUSSION The three RECETAS trials will explore the effectiveness of nature-based social interventions among lonely people from various ages, social, economic, and cultural backgrounds. RECETAS meets the growing need of solid evidence for programs addressing loneliness by harnessing the beneficial impact of nature on enhancing wellbeing and social connections. TRIAL REGISTRATION Barcelona (Spain) trial: ClinicalTrials.gov, ID: NCT05488496. Registered 29 July 2022. Prague (Czech Republic) trial: ClinicalTrials.gov, ID: NCT05522140. Registered August 25, 2022. Helsinki (Finland) trial: ClinicalTrials.gov, ID: NCT05507684. Registered August 12, 2022.
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Affiliation(s)
- Laura Coll-Planas
- Research group on Methodology, Methods, Models and Outcomes of Health and Social Sciences (M3O). Faculty of Health Sciences and Welfare. Centre for Health and Social Care Research (CESS), University of Vic-Central University of Catalonia (UVic-UCC). Institute for Research and Innovation in Life Sciences and Health in Central Catalonia (IRIS-CC), Vic, Spain
| | - Aina Carbó-Cardeña
- Research group on Methodology, Methods, Models and Outcomes of Health and Social Sciences (M3O). Faculty of Health Sciences and Welfare. Centre for Health and Social Care Research (CESS), University of Vic-Central University of Catalonia (UVic-UCC). Institute for Research and Innovation in Life Sciences and Health in Central Catalonia (IRIS-CC), Vic, Spain
| | - Anu Jansson
- Department of General Practice, University of Helsinki, PO BOX 20, 00014, Helsinki, Finland
| | - Vladimira Dostálová
- Charles University, Faculty of Humanities - Centre of Expertise in Longevity and Long-Term Care, Pátkova 2137/5, 182 00, Prague, Czech Republic
| | - Alzbeta Bartova
- Charles University, Faculty of Humanities - Centre of Expertise in Longevity and Long-Term Care, Pátkova 2137/5, 182 00, Prague, Czech Republic
| | - Laura Rautiainen
- Department of General Practice, University of Helsinki, PO BOX 20, 00014, Helsinki, Finland
| | - Annika Kolster
- Department of General Practice, University of Helsinki, PO BOX 20, 00014, Helsinki, Finland
- Western Uusimaa Wellbeing Services, Health Services, Espoo, Finland
| | - Montse Masó-Aguado
- Research group on Methodology, Methods, Models and Outcomes of Health and Social Sciences (M3O). Faculty of Health Sciences and Welfare. Centre for Health and Social Care Research (CESS), University of Vic-Central University of Catalonia (UVic-UCC). Institute for Research and Innovation in Life Sciences and Health in Central Catalonia (IRIS-CC), Vic, Spain
| | - Laia Briones-Buixassa
- Innovation in Mental Health and Social Wellbeing Research group (ISAMBES), Faculty of Health Sciences and Welfare. Centre for Health and Social Care Research (CESS), University of Vic-Central University of Catalonia (UVic-UCC). Institute for Research and Innovation in Life Sciences and Health in Central Catalonia (IRIS-CC), Vic, Spain
| | - Sergi Blancafort-Alias
- Fundació Salut i Envelliment UAB, Casa Convalescència UAB C/ Sant Antoni M. Claret, 171, 4a planta, Barcelona, Spain
| | - Marta Roqué-Figuls
- Fundació Salut i Envelliment UAB, Casa Convalescència UAB C/ Sant Antoni M. Claret, 171, 4a planta, Barcelona, Spain
| | - Ashby Lavelle Sachs
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB) Doctor Aiguader, 88 08003, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Cristina Casajuana
- Subdirecció General d'Addiccions, VIH, ITS i Hepatitis Víriques. Agència de Salut Pública de Catalunya, Carrer de Roc Boronat, 81-95, 08005, Barcelona, Spain
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria
- Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Institute for Technology Assessment, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Ursula Rochau
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria
| | - Sibylle Puntscher
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria
| | - Iva Holmerová
- Charles University, Faculty of Humanities - Centre of Expertise in Longevity and Long-Term Care, Pátkova 2137/5, 182 00, Prague, Czech Republic
| | - Kaisu H Pitkala
- Department of General Practice, University of Helsinki, PO BOX 20, 00014, Helsinki, Finland
- Helsinki University Hospital, Unit of Primary Health Care, Helsinki, Finland
| | - Jill S Litt
- Fundació Salut i Envelliment UAB, Casa Convalescència UAB C/ Sant Antoni M. Claret, 171, 4a planta, Barcelona, Spain.
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB) Doctor Aiguader, 88 08003, Barcelona, Spain.
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
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Stojkov I, Conrads-Frank A, Rochau U, Arvandi M, Koinig KA, Schomaker M, Mittelman M, Fenaux P, Bowen D, Sanz GF, Malcovati L, Langemeijer S, Germing U, Madry K, Guerci-Bresler A, Culligan DJ, Kotsianidis I, Sanhes L, Mills J, Puntscher S, Schmid D, van Marrewijk C, Smith A, Efficace F, de Witte T, Stauder R, Siebert U. Determinants of low health-related quality of life in patients with myelodysplastic syndromes: EUMDS Registry study. Blood Adv 2023; 7:2772-2783. [PMID: 36607832 PMCID: PMC10275700 DOI: 10.1182/bloodadvances.2022008360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 12/02/2022] [Accepted: 12/15/2022] [Indexed: 01/07/2023] Open
Abstract
Patients with myelodysplastic syndromes (MDS) frequently experience a significant symptom burden, which reduces health-related quality of life (HRQoL). We aimed to identify determinants of low HRQoL in patients recently diagnosed with MDS, for guiding early intervention strategies. We evaluated longitudinal data in 2205 patients with MDS during their first year after diagnosis. Median values of EQ-5D 3-level (EQ-5D-3L) index (0.78) and visual analog scale (VAS) score (0.70) were used as thresholds for low HRQoL. In addition, the 5 dimensions of EQ-5D-3L were analyzed for impairments (any level vs "no problem" category). After multiple imputation of missing values, we used generalized estimating equations (GEE) to estimate odds ratios (OR) for univariable determinant screening (P < .15), and to subsequently derive multivariable models for low HRQoL with 95% confidence intervals (CI). Multivariable GEE analysis showed the following independent determinants (OR, 95% CI) for low EQ-5D index: increased age (60-75 years: 1.33, 1.01-1.75; >75: 1.84, 1.39-2.45), female sex (1.70, 1.43-2.03), high serum ferritin level (≥1000 vs ≤300 μg/L: 1.41, 1.06-1.87), comorbidity burden (per unit: 1.11, 1.02-1.20), and reduced Karnofsky performance status (KPS, per 10 units: 0.62, 0.58-0.67). For low VAS score, additional determinants were transfusion dependence (1.53, 1.03-2.29), low hemoglobin <10 g/dL (1.34, 1.12-1.61), and high body mass index (≥30 vs 23-29.9 kg/m2: 1.26, 1.02-1.57). Sex, KPS, comorbidity burden, hemoglobin count, and transfusion burden were determinants for all EQ-5D dimensions. Low HRQoL is determined by multiple factors, which should be considered in the management and shared decision making of patients with MDS. This trial was registered at www.clinicaltrials.gov as #NCT00600860.
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Affiliation(s)
- Igor Stojkov
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Annette Conrads-Frank
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Ursula Rochau
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Marjan Arvandi
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Karin A. Koinig
- Department of Internal Medicine V (Hematology and Oncology), Innsbruck Medical University, Innsbruck, Austria
| | - Michael Schomaker
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
| | - Moshe Mittelman
- Department of Medicine A, Tel Aviv Sourasky (Ichilov) Medical Center and Sackler Medical Faculty, Tel Aviv University, Tel Aviv, Israel
| | - Pierre Fenaux
- Service d’Hématologie Séniors, Hôpital Saint-Louis, Assistance Publique des Hôpitaux de Paris and Université Paris 7, Paris, France
| | - David Bowen
- St. James’s Institute of Oncology, Leeds Teaching Hospitals, Leeds, United Kingdom
| | - Guillermo F. Sanz
- Department of Haematology, Hospital Universitario y Politécnico La Fe, Valencia, Spain
- Centro de Investigación Biomédica en Red de Cáncer, CIBERONC, Instituto de Salud Carlos III, Madrid, Spain
| | - Luca Malcovati
- Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, University of Pavia, Pavia, Italy
| | - Saskia Langemeijer
- Department of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ulrich Germing
- Department of Haematology, Oncology and Clinical Immunology, Universitätsklinik Düsseldorf, Düsseldorf, Germany
| | - Krzysztof Madry
- Department of Haematology, Oncology and Internal Medicine, Warszawa Medical University, Warsaw, Poland
| | - Agnès Guerci-Bresler
- Service d'Hématologie Clinique, Centre Hospitalier Universitaire Brabois, Nancy, France
| | - Dominic J. Culligan
- Department of Haematology, Aberdeen Royal Infirmary, Aberdeen, United Kingdom
| | - Ioannis Kotsianidis
- Department of Hematology, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece
| | - Laurence Sanhes
- Haematology Department of Perpignan, Saint Jean Hospital, Perpignan, France
| | - Juliet Mills
- Worcestershire Acute Hospitals NHS Trust and University Hospitals Birmingham NHS Foundation Trust, Worcester, United Kingdom
| | - Sibylle Puntscher
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Daniela Schmid
- Division for Quantitative Methods in Public Health and Health Services Research, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
| | - Corine van Marrewijk
- Department of Hematology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Alexandra Smith
- Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, United Kingdom
| | - Fabio Efficace
- Health Outcomes Research Unit, Gruppo Italiano Malattie Ematologiche dell’Adulto (GIMEMA), Rome, Italy
| | - Theo de Witte
- Department of Tumor Immunology - Nijmegen Center for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Reinhard Stauder
- Department of Internal Medicine V (Hematology and Oncology), Innsbruck Medical University, Innsbruck, Austria
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
- Division of Health Technology Assessment, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
- Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard Chan School of Public Health, Boston, MA
- Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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Kühne F, Schomaker M, Stojkov I, Jahn B, Conrads-Frank A, Siebert S, Sroczynski G, Puntscher S, Schmid D, Schnell-Inderst P, Siebert U. Causal evidence in health decision making: methodological approaches of causal inference and health decision science. Ger Med Sci 2022; 20:Doc12. [PMID: 36742460 PMCID: PMC9869404 DOI: 10.3205/000314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Indexed: 02/07/2023]
Abstract
Objectives Public health decision making is a complex process based on thorough and comprehensive health technology assessments involving the comparison of different strategies, values and tradeoffs under uncertainty. This process must be based on best available evidence and plausible assumptions. Causal inference and health decision science are two methodological approaches providing information to help guide decision making in health care. Both approaches are quantitative methods that use statistical and modeling techniques and simplifying assumptions to mimic the complexity of the real world. We intend to review and lay out both disciplines with their aims, strengths and limitations based on a combination of textbook knowledge and expert experience. Methods To help understanding and differentiating the methodological approaches of causal inference and health decision science, we reviewed both methods with the focus on aims, research questions, methods, assumptions, limitations and challenges, and software. For each methodological approach, we established a group of four experts from our own working group to carefully review and summarize each method, followed by structured discussion rounds and written reviews, in which the experts from all disciplines including HTA and medicine were involved. The entire expert group discussed objectives, strengths and limitations of both methodological areas, and potential synergies. Finally, we derived recommendations for further research and provide a brief outlook on future trends. Results Causal inference methods aim for drawing causal conclusions from empirical data on the relationship of pre-specified interventions on a specific target outcome and apply a counterfactual framework and statistical techniques to derive causal effects of exposures or interventions from these data. Causal inference is based on a causal diagram, more specifically, a directed acyclic graph (DAG), which encodes the assumptions regarding the causal relations between variables. Depending on the type of confounding and selection bias, traditional statistical methods or more complex g-methods are needed to derive valid causal effects. Besides the correct specification of the DAG and the statistical model, assumptions such as consistency, positivity, and exchangeability must be checked when aiming at causal inference. Health decision science aims for guiding policy decision making regarding health interventions considering and balancing multiple competing objectives of a decision based on data from multiple sources and studies, for example prevalence studies, clinical trials and long-term observational routine effectiveness studies, and studies on preferences and costs. It involves decision analysis, a systematic, explicit and quantitative framework to guide decisions under uncertainty. Decision analyses are based on decision-analytic models to mimic the course of disease as well as aspects and consequences of the intervention in order to quantitatively optimize the decision. Depending on the type of decision problem, decision trees, state-transition models, discrete event simulation models, dynamic transmission models, or other model types are applied. Models must be validated against observed data, and comprehensive sensitivity analyses must be performed to assess uncertainty. Besides the appropriate choice of the model type and the valid specification of the model structure, it must be checked if input parameters of effects can be interpreted as causal parameters in the model. Otherwise results will be biased. Conclusions Both causal inference and health decision science aim for providing best causal evidence for informed health decision making. The strengths and limitations of both methods differ and a good understanding of both methods is essential for correct application but also for correct interpretation of findings from the described methods. Importantly, decision-analytic modeling should be combined with causal inference when developing guidance and recommendations regarding decisions on health care interventions.
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Affiliation(s)
- Felicitas Kühne
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Michael Schomaker
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
- Centre for Infectious Disease Epidemiology & Research, University of Cape Town, South Africa
| | - Igor Stojkov
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Beate Jahn
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
- Division of Health Technology Assessment, ONCOTYROL – Center for Personalized Cancer Medicine, Innsbruck, Austria
| | - Annette Conrads-Frank
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Silke Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Gaby Sroczynski
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Sibylle Puntscher
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Daniela Schmid
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Petra Schnell-Inderst
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT TIROL – University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria
- Division of Health Technology Assessment, ONCOTYROL – Center for Personalized Cancer Medicine, Innsbruck, Austria
- Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program on Cardiovascular Research, Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Laimer J, Hechenberger M, Lercher JM, Born E, Schomaker M, Puntscher S, Siebert U, Bruckmoser E. New Perspective for Soft Tissue Closure in Medication-Related Osteonecrosis of the Jaw (MRONJ) Using Barbed Sutures. J Clin Med 2021; 10:jcm10081677. [PMID: 33919696 PMCID: PMC8069803 DOI: 10.3390/jcm10081677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/03/2021] [Accepted: 04/11/2021] [Indexed: 12/19/2022] Open
Abstract
The aim of this study was to compare the effectiveness of barbed versus smooth sutures for soft tissue closure of exposed jawbone sites in medication-related osteonecrosis of the jaw (MRONJ) patients. Exposed necrotic jawbone sites surgically managed by intraoral soft tissue closure were evaluated. Either barbed sutures (Stratafix™ or V-Loc™) together with Prolene® or Vicryl® sutures were used. We estimated the effect of barbed sutures (BS) with Prolene® compared to smooth sutures (Vicryl®) on the hazard rate of intraoral soft tissue dehiscence using a multivariate Cox regression model within a target trial framework, adjusting for relevant confounders. In total, 306 operations were performed in 188 sites. In the primary analysis 182 sites without prior surgery were included. Of these, 113 sites developed a dehiscence during follow-up. 84 sites were operated using BS and Prolene®. A total of 222 sites were operated with Vicryl® (control group). In the BS group, the median time to event (i.e., dehiscence) was 148 days (interquartile range (IQR), 42–449 days) compared to 15 days (IQR, 12–52 days) in the control group. The hazard rate of developing intraoral dehiscence was 0.03 times (95%-confidence interval (CI): 0.01; 0.14, p < 0.001) lower for BS patients compared to the control group. Within the limits of a retrospective study, BS showed a high success rate and are therefore recommended for soft tissue closure of exposed jawbone sites in MRONJ patients. Additional studies are warranted to further evaluate this novel application of BS.
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Affiliation(s)
- Johannes Laimer
- University Hospital for Craniomaxillofacial and Oral Surgery, Medical University Innsbruck, A-6020 Innsbruck, Austria; (J.L.); (M.H.); (J.M.L.); (E.B.)
| | - Martin Hechenberger
- University Hospital for Craniomaxillofacial and Oral Surgery, Medical University Innsbruck, A-6020 Innsbruck, Austria; (J.L.); (M.H.); (J.M.L.); (E.B.)
| | - Johanna Maria Lercher
- University Hospital for Craniomaxillofacial and Oral Surgery, Medical University Innsbruck, A-6020 Innsbruck, Austria; (J.L.); (M.H.); (J.M.L.); (E.B.)
| | - Eva Born
- University Hospital for Craniomaxillofacial and Oral Surgery, Medical University Innsbruck, A-6020 Innsbruck, Austria; (J.L.); (M.H.); (J.M.L.); (E.B.)
| | - Michael Schomaker
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, A-6060 Hall in Tirol, Austria; (M.S.); (S.P.); (U.S.)
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, 7550 Cape Town, South Africa
| | - Sibylle Puntscher
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, A-6060 Hall in Tirol, Austria; (M.S.); (S.P.); (U.S.)
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT—University for Health Sciences, Medical Informatics and Technology, A-6060 Hall in Tirol, Austria; (M.S.); (S.P.); (U.S.)
- Center for Health Decision Science, Departments of Epidemiology and Health Policy & Management, T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
- Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Emanuel Bruckmoser
- Private Practice for Oral and Maxillofacial Surgery, A-5020 Salzburg, Austria
- Correspondence: ; Tel.: +43-677-63846310
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Kreider N, Remp T, Puntscher S, Koenig A, Siebert U, Stempfle H. Comparison of endovascular infrapopliteal revascularization strategies based on the angiosome model in diabetic patients within critical limb ischemia. Eur Heart J 2020. [DOI: 10.1093/ehjci/ehaa946.2382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
The relevance of an angiosome model for infrapopliteal endovascular interventions (EVT) in diabetic patients is still in debate because the lesions are more likely to be diffuse with a different pattern of collateral arteries ranging from reduced to normal caliber. The aim of this study was to analyse the outcome of two different endovascular infrapopliteal interventional strategies (Group I: angiosome-based direct revascularization -DR- vs. Group II: complete (direct + indirect) revascularization strategy -CR-) in diabetic patients with critical limb ischemia. Furthermore we analyzed the outcome if DR or CR failed and only indirect revascularization (IR) or no revascularization was possible. Both groups were differentiated in patients with collaterals, defined as an intact pedal arch (immediate or after pedal PTA).
Patients and methods
We performed a prospective cohort study in routine angiologic patients. The database includes 91 consecutive EVT with two intrapopliteal interventional strategies performed in 68 diabetic patients (pts.; 24 female, 44 male, mean age 73±10 years) between 2013–2015 and 2016–2019. The study included only patients with CLI (Rutherford class 4 or greater) with a critical subtotal stenosis or occlusion of at least one artery below the knee. EVT were performed mainly by an antegrade approach and with the use of 5F sheaths. In case of failure to recanalise, a retrograde approach was attempted. Positive clinical outcome was defined as wound healing without amputation or wound healing after minor amputation, combined with a symptom improvement to Rutherford category 0 or 1 after 6 months. The clinical outcome proportions were compared using the Fisher's exact test.
Results
An angiosome-based direct reperfusion (DR) of the artery supplying the ischemic tissue and a complete (both direct and indirect, CR) revascularization strategy demonstrated a similar positive clinical outcome (92,6% vs. 90,5%; p=0.594). Indirect revascularization showed a significantly lower positive outcome in comparison to a successful DR as well as CR strategy (33,3% vs 92,6%, p=0.0003; 40% vs 90,5%, p=0.001). IR outcome improved by the presence of collaterals (66,7% vs. 30,8%).
Conclusions
In case of successful intervention, both strategies (DR and CR) yielded a similarly high proportion of positive clinical outcome. The role of collaterals and the pedal arch are important for the clinical outcome in patients in whom only indirect revascularization was possible, because of unsuccessful CR or DR. The time of the procedure/radiation, the risk to reopen more than one vessel, the necessary amount of contrast medium and final the costs of the procedure should also be considered for an individually based decision process to perform an angiosome-based direct or a complete revascularization.
Funding Acknowledgement
Type of funding source: None
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Affiliation(s)
- N Kreider
- Asklepios Stadtklinik Bad Toelz, Cardiology, Bad Toelz, Germany
| | - T Remp
- Asklepios Stadtklinik Bad Toelz, Cardiology, Bad Toelz, Germany
| | - S Puntscher
- Institute of Public Health, Medical Decision Making and HTA, UMIT, Hall in Tyrol, Austria
| | - A Koenig
- Asklepios Stadtklinik Bad Toelz, Cardiology, Bad Toelz, Germany
| | - U Siebert
- Institute of Public Health, Medical Decision Making and HTA, UMIT, Hall in Tyrol, Austria
| | - H.U Stempfle
- Asklepios Stadtklinik Bad Toelz, Cardiology, Bad Toelz, Germany
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6
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Jahn B, Sroczynski G, Bundo M, Mühlberger N, Puntscher S, Todorovic J, Rochau U, Oberaigner W, Koffijberg H, Fischer T, Schiller-Fruehwirth I, Öfner D, Renner F, Jonas M, Hackl M, Ferlitsch M, Siebert U. Effectiveness, benefit harm and cost effectiveness of colorectal cancer screening in Austria. BMC Gastroenterol 2019; 19:209. [PMID: 31805871 PMCID: PMC6896501 DOI: 10.1186/s12876-019-1121-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Accepted: 11/17/2019] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Clear evidence on the benefit-harm balance and cost effectiveness of population-based screening for colorectal cancer (CRC) is missing. We aim to systematically evaluate the long-term effectiveness, harms and cost effectiveness of different organized CRC screening strategies in Austria. METHODS A decision-analytic cohort simulation model for colorectal adenoma and cancer with a lifelong time horizon was developed, calibrated to the Austrian epidemiological setting and validated against observed data. We compared four strategies: 1) No Screening, 2) FIT: annual immunochemical fecal occult blood test age 40-75 years, 3) gFOBT: annual guaiac-based fecal occult blood test age 40-75 years, and 4) COL: 10-yearly colonoscopy age 50-70 years. Predicted outcomes included: benefits expressed as life-years gained [LYG], CRC-related deaths avoided and CRC cases avoided; harms as additional complications due to colonoscopy (physical harm) and positive test results (psychological harm); and lifetime costs. Tradeoffs were expressed as incremental harm-benefit ratios (IHBR, incremental positive test results per LYG) and incremental cost-effectiveness ratios [ICER]. The perspective of the Austrian public health care system was adopted. Comprehensive sensitivity analyses were performed to assess uncertainty. RESULTS The most effective strategies were FIT and COL. gFOBT was less effective and more costly than FIT. Moving from COL to FIT results in an incremental unintended psychological harm of 16 additional positive test results to gain one life-year. COL was cost saving compared to No Screening. Moving from COL to FIT has an ICER of 15,000 EUR per LYG. CONCLUSIONS Organized CRC-screening with annual FIT or 10-yearly colonoscopy is most effective. The choice between these two options depends on the individual preferences and benefit-harm tradeoffs of screening candidates.
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Affiliation(s)
- Beate Jahn
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Gaby Sroczynski
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Marvin Bundo
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Nikolai Mühlberger
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Sibylle Puntscher
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Jovan Todorovic
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Ursula Rochau
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Willi Oberaigner
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria
| | - Hendrik Koffijberg
- Health Technology and Services Research, University of Twente, Enschede, The Netherlands
| | - Timo Fischer
- Main Association of Austrian Social Security Institutions, Vienna, Austria
| | | | - Dietmar Öfner
- Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria
| | - Friedrich Renner
- Faculty of Medicine, Johannes Kepler University Linz, Linz, Austria
| | - Michael Jonas
- Medical Association of Vorarlberg, Dornbirn, Austria
| | | | - Monika Ferlitsch
- Department of Internal Medicine III; Division of Gastroenterology and Hepatology, Medical University of Vienna, Vienna, Austria.,Quality Assurance Working Group of Austrian Society of Gastroenterology and Hepatology, Vienna, Austria
| | - Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment; Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall in Tirol, Austria. .,Division of Health Technology Assessment and Bioinformatics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria. .,Center for Health Decision Science; Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA. .,Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital; Harvard Medical School, Boston, MA, USA.
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