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- Franks, P. W., et al.
(författare)
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Technological readiness and implementation of genomic-driven precision medicine for complex diseases
- 2021
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Ingår i: Journal of Internal Medicine. - : Wiley. - 0954-6820 .- 1365-2796. ; 290:3, s. 602-620
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Forskningsöversikt (refereegranskat)abstract
- The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.
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| 3. |
- Kjellberg, A, et al.
(författare)
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Hyperbaric oxygen for treatment of long COVID-19 syndrome (HOT-LoCO): protocol for a randomised, placebo-controlled, double-blind, phase II clinical trial
- 2022
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Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 12:11, s. e061870-
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Tidskriftsartikel (refereegranskat)abstract
- Long COVID-19, where symptoms persist 12 weeks after the initial SARS-CoV-2-infection, is a substantial problem for individuals and society in the surge of the pandemic. Common symptoms are fatigue, postexertional malaise and cognitive dysfunction. There is currently no effective treatment and the underlying mechanisms are unknown, although several hypotheses exist, with chronic inflammation as a common denominator. In prospective studies, hyperbaric oxygen therapy (HBOT) has been suggested to be effective for the treatment of similar syndromes such as chronic fatigue syndrome and fibromyalgia. A case series has suggested positive effects of HBOT in long COVID-19. This randomised, placebo-controlled clinical trial will explore HBOT as a potential treatment for long COVID-19. The primary objective is to evaluate if HBOT improves health-related quality of life (HRQoL) for patients with long COVID-19 compared with placebo/sham. The main secondary objective is to evaluate whether HBOT improves endothelial function, objective physical performance and short-term HRQoL.Methods and analysisA randomised, placebo-controlled, double-blind, phase II clinical trial in 80 previously healthy subjects debilitated due to long COVID-19, with low HRQoL. Clinical data, HRQoL questionnaires, blood samples, objective tests and activity metre data will be collected at baseline. Subjects will be randomised to a maximum of 10 treatments with hyperbaric oxygen or sham treatment over 6 weeks. Assessments for safety and efficacy will be performed at 6, 13, 26 and 52 weeks, with the primary endpoint (physical domains in RAND 36-Item Health Survey) and main secondary endpoints defined at 13 weeks after baseline. Data will be reviewed by an independent data safety monitoring board.Ethics and disseminationThe trial is approved by the Swedish National Institutional Review Board (2021–02634) and the Swedish Medical Products Agency (5.1-2020-36673). Positive, negative and inconclusive results will be published in peer-reviewed scientific journals with open access.Trial registration numberNCT04842448.
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| 6. |
- Kjellberg, A., et al.
(författare)
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Randomised, controlled, open label, multicentre clinical trial to explore safety and efficacy of hyperbaric oxygen for preventing ICU admission, morbidity and mortality in adult patients with COVID-19
- 2021
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Ingår i: BMJ Open. - : BMJ. - 2044-6055. ; 11:7
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Tidskriftsartikel (refereegranskat)abstract
- Introduction COVID-19 may cause severe pneumonitis and trigger a massive inflammatory response that requires ventilatory support. The intensive care unit (ICU)-mortality has been reported to be as high as 62%. Dexamethasone is the only of all anti-inflammatory drugs that have been tested to date that has shown a positive effect on mortality. We aim to explore if treatment with hyperbaric oxygen (HBO) is safe and effective for patients with severe COVID-19. Our hypothesis is that HBO can prevent ICU admission, morbidity and mortality by attenuating the inflammatory response. The primary objective is to evaluate if HBO reduces the number of ICU admissions compared with best practice treatment for COVID-19, main secondary objectives are to evaluate if HBO reduces the load on ICU resources, morbidity and mortality and to evaluate if HBO mitigates the inflammatory reaction in COVID-19. Methods and analysis A randomised, controlled, phase II, open label, multicentre trial. 200 subjects with severe COVID-19 and at least two risk factors for mortality will be included. Baseline clinical data and blood samples will be collected before randomisation and repeated daily for 7 days, at days 14 and 30. Subjects will be randomised with a computer-based system to HBO, maximum five times during the first 7 days plus best practice treatment or only best practice treatment. The primary endpoint, ICU admission, is defined by criteria for selection for ICU. We will evaluate if HBO mitigates the inflammatory reaction in COVID-19 using molecular analyses. All parameters are recorded in an electronic case report form. An independent Data Safety Monitoring Board will review the safety parameters. Ethics and dissemination The trial is approved by The National Institutional Review Board in Sweden (2020-01705) and the Swedish Medical Product Agency (5.1-2020-36673). Positive, negative and any inconclusive results will be published in peer-reviewed scientific journals with open access.
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| 7. |
- Knevel, R, et al.
(författare)
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Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study
- 2022
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Ingår i: Frontiers in medicine. - : Frontiers Media SA. - 2296-858X. ; 9, s. 774945-
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Tidskriftsartikel (refereegranskat)abstract
- Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.Materials and MethodsThe performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold.ResultsThe total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively.ConclusionRheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized.
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| 8. |
- Knevel, R, et al.
(författare)
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Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study
- 2022
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Ingår i: Frontiers in medicine. - : Frontiers Media SA. - 2296-858X. ; 9, s. 774945-
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Tidskriftsartikel (refereegranskat)abstract
- Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.Materials and MethodsThe performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold.ResultsThe total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively.ConclusionRheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized.
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| 9. |
- Knevel, R, et al.
(författare)
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RHEUMATIC? - A DIGITAL DIAGNOSTIC DECISION SUPPORT TOOL FOR INDIVIDUALS SUSPECTING RHEUMATIC DISEASES: A MULTICENTER VALIDATION STUDY
- 2021
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 80, s. 87-88
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations for individuals suspecting a rheumatic disease.1,2 The tool can be used by people suspicious for rheumatic diseases resulting in individual advise on eventually seeking further health care.Objectives:We tested Rheumatic? for its ability to differentiate symptoms from immune-mediated diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.Methods:The performance of Rheumatic? was tested using data from 175 patients from three university rheumatology centers covering two different settings:A.Risk-RA phase setting. Here, we tested whether Rheumatic? could predict the development of arthritis in 50 at risk-individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity from the KI (Karolinska Institutet)B.Early arthritis setting. Here, we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic disease in i) EUMC (Erlangen) n=52 patients and ii) LUMC (Leiden) n=73 patients.In each setting, we examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC).Results:In setting A, the total test score clearly differentiated between individuals developing arthritis or not, median 245 versus 163, P < 0.0001, AUC-ROC = 75.3 (Figure 1). Also within patients with arthritis the Rheumatic? total score was significantly higher in patients developing an immune-mediated arthritic disease versus those who did not: median score EUMC 191 versus 107, P < 0.0001, AUC-ROC = 79.0, and LUMC 262 versus 212, P < 0.0001, AUC-ROC = 53.6.Figure 1.(Area under) the receiver operating curve for the total Rheumatic? scoreConclusion:Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. A following subject of research is how the tool performs in a population-wide setting.References:[1]Knitza J. et al. Mobile Health in Rheumatology: A Patient Survey Study Exploring Usage, Preferences, Barriers and eHealth Literacy. JMIR mHealth and uHealth. 2020.[2]https://rheumatic.elsa.science/en/Acknowledgements:This project has received funding from EIT Health. EIT Health is supported by the European Institute of Innovation and Technology (EIT), a body of the European Union that receives support from the European Union’s Horizon 2020 Research and Innovation program.This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777357, RTCure.Disclosure of Interests:Rachel Knevel: None declared, Johannes Knitza: None declared, Aase Hensvold: None declared, Alexandra Circiumaru: None declared, Tor Bruce Employee of: Ocean Observations, Sebastian Evans Employee of: Elsa Science, Tjardo Maarseveen: None declared, Marc Maurits: None declared, Liesbeth Beaart- van de Voorde: None declared, David Simon: None declared, Arnd Kleyer: None declared, Martina Johannesson: None declared, Georg Schett: None declared, Thomas Huizinga: None declared, Sofia Svanteson Employee of: Elsa Science, Alexandra Lindfors Employee of: Ocean Observations, Lars Klareskog: None declared, Anca Catrina: None declared
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| 10. |
- Lind, Marcus, 1976, et al.
(författare)
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Fast-Acting Insulin Aspart in Patients with Type 1 Diabetes in Real-World Clinical Practice: A Noninterventional, Retrospective Chart and Database Study
- 2023
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Ingår i: Diabetes Therapy. - : Springer. - 1869-6953 .- 1869-6961. ; 14, s. 1563-1575
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionThis study utilized continuous glucose monitoring data to analyze the effects of switching to treatment with fast-acting insulin aspart (faster aspart) in adults with type 1 diabetes (T1D) in clinical practice.MethodsA noninterventional database review was conducted in Sweden among adults with T1D using multiple daily injection (MDI) regimens who had switched to treatment with faster aspart as part of basal-bolus treatment. Glycemic data were retrospectively collected during the 26 weeks before switching (baseline) and up to 32 weeks after switching (follow-up) to assess changes in time in glycemic range (TIR; 70-180 mg/dL), mean sensor glucose, glycated hemoglobin (HbA1c) levels, coefficient of variation, time in hyperglycemia (level 1, > 180 to & LE; 250 mg/dL; level 2, > 250 mg/dL), and time in hypoglycemia (level 1, & GE; 54 to < 70 mg/dL; level 2, < 54 mg/dL) (ClinicalTrials.gov Identifier NCT03895515).ResultsOverall, 178 participants were included in the study cohort. The analysis population included 82 individuals (mean age 48.5 years) with adequate glucose sensor data. From baseline to follow-up, statistically significant improvements were reported for TIR (mean increase 3.3%-points [approximately 48 min/day]; p = 0.006) with clinically relevant improvement (& GE; 5%) in 43% of participants. Statistically significant improvements from baseline were observed for mean sensor glucose levels, HbA1c levels, and time in hyperglycemia (levels 1 and 2), with no statistically significant changes in time spent in hypoglycemia.ConclusionsSwitching to faster aspart was associated with improvements in glycemic control without increasing hypoglycemia in adults with T1D using MDI in this real-world setting.
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