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Background & Aim: The resistance profile of anti-hepatitis C virus (HCV) agents used in combination is important to guide optimal treatment regimens. We evaluated baseline and treatment-emergent NS3/4A and NS5B amino-acid variants among HCV genotype (GT)-1a and -1b-infected patients treated with faldaprevir (HCV protease inhibitor), deleobuvir (HCV polymerase non-nucleoside inhibitor), and ribavirin in multiple clinical studies.
Methods: HCV NS3/4A and NS5B population sequencing (Sanger method) was performed on all baseline plasma samples (n = 1425 NS3; n = 1556 NS5B) and on post-baseline plasma samples from patients with virologic failure (n = 113 GT-1a; n = 221 GT-1b). Persistence and time to loss of resistance-associated variants (RAVs) was estimated using Kaplan–Meier analysis.
Results: Faldaprevir RAVs (NS3 R155 and D168) and deleobuvir RAVs (NS5B 495 and 496) were rare (<1%) at baseline. Virologic response to faldaprevir/deleobuvir/ribavirin was not compromised by common baseline NS3 polymorphisms (e.g. Q80K in 17.5% of GT-1a) or by NS5B A421V, present in 20% of GT-1a. In GT-1b, alanine at NS5B codon 499 (present in 15% of baseline sequences) was associated with reduced response. Treatment-emergent RAVs consolidated previous findings: NS3 R155 and D168 were key faldaprevir RAVs; NS5B A421 and P495 were key deleobuvir RAVs. Among on-treatment virologic breakthroughs, RAVs emerged in both NS3 and NS5B (>90%). Virologic relapse was associated with RAVs in both NS3 and NS5B (53% GT-1b; 52% GT-1b); some virologic relapses had NS3 RAVs only (47% GT-1a; 17% GT-1b). Median time to loss of GT-1b NS5B P495 RAVs post-treatment (5 months) was less than that of GT-1b NS3 D168 (8.5 months) and GT-1a R155 RAVs (11.5 months).
Conclusion: Faldaprevir and deleobuvir RAVs are more prevalent among virologic failures than at baseline. Treatment response was not compromised by common NS3 polymorphisms; however, alanine at NS5B amino acid 499 at baseline (wild-type in GT-1a, polymorphism in GT-1b) may reduce response to this deleobuvir-based regimen.
Multimorbidity is a health issue mostly dealt with in primary care practice. As a result of their generalist and patient-centered approach, long-lasting relationships with patients, and responsibility for continuity and coordination of care, family physicians are particularly well placed to manage patients with multimorbidity. However, conflicts arising from the application of multiple disease oriented guidelines and the burden of diseases and treatments often make consultations challenging. To provide orientation in decision making in multimorbidity during primary care consultations, we developed guiding principles and named them after the Greek mythological figure Ariadne. For this purpose, we convened a two-day expert workshop accompanied by an international symposium in October 2012 in Frankfurt, Germany. Against the background of the current state of knowledge presented and discussed at the symposium, 19 experts from North America, Europe, and Australia identified the key issues of concern in the management of multimorbidity in primary care in panel and small group sessions and agreed upon making use of formal and informal consensus methods. The proposed preliminary principles were refined during a multistage feedback process and discussed using a case example. The sharing of realistic treatment goals by physicians and patients is at the core of the Ariadne principles. These result from i) a thorough interaction assessment of the patient’s conditions, treatments, constitution, and context; ii) the prioritization of health problems that take into account the patient's preferences – his or her most and least desired outcomes; and iii) individualized management realizes the best options of care in diagnostics, treatment, and prevention to achieve the goals. Goal attainment is followed-up in accordance with a re-assessment in planned visits. The occurrence of new or changed conditions, such as an increase in severity, or a changed context may trigger the (re-)start of the process. Further work is needed on the implementation of the formulated principles, but they were recognized and appreciated as important by family physicians and primary care researchers.
Purpose: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization.
Methods: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16).
Results: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface.
Conclusion: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.
Feeding type and development drive the ingestion of microplastics by freshwater invertebrates
(2017)
Microscopic plastic items (microplastics) are ubiquitously present in aquatic ecosystems. With decreasing size their availability and potential to accumulate throughout food webs increase. However, little is known on the uptake of microplastics by freshwater invertebrates. To address this, we exposed species with different feeding strategies to 1, 10 and 90 µm fluorescent polystyrene spheres (3–3 000 particles mL−1). Additionally, we investigated how developmental stages and a co-exposure to natural particles (e.g., food) modulate microplastic ingestion. All species ingested microplastics in a concentration-dependent manner with Daphnia magna consuming up to 6 180 particles h−1, followed by Chironomus riparius (226 particles h−1), Physella acuta (118 particles h−1), Gammarus pulex (10 particles h−1) and Lumbriculus variegatus (8 particles h−1). D. magna did not ingest 90 µm microplastics whereas the other species preferred larger microplastics over 1 µm in size. In C. riparius and D. magna, size preference depended on the life stage with larger specimens ingesting more and larger microplastics. The presence of natural particles generally reduced the microplastics uptake. Our results demonstrate that freshwater invertebrates have the capacity to ingest microplastics. However, the quantity of uptake depends on their feeding type and morphology as well as on the availability of microplastics.
Background: While the use of plastic materials has generated huge societal benefits, the "plastic age" comes with downsides: One issue of emerging concern is the accumulation of plastics in the aquatic environment. Here, so-called microplastics (MP), fragments smaller than 5 mm, are of special concern because they can be ingested throughout the food web more readily than larger particles. Focusing on freshwater MP, we briefly review the state of the science to identify gaps of knowledge and deduce research needs.
State of the science: Environmental scientists started investigating marine (micro)plastics in the early 2000s. Today, a wealth of studies demonstrates that MP have ubiquitously permeated the marine ecosystem, including the polar regions and the deep sea. MP ingestion has been documented for an increasing number of marine species. However, to date, only few studies investigate their biological effects. The majority of marine plastics are considered to originate from land-based sources, including surface waters. Although they may be important transport pathways of MP, data from freshwater ecosystems is scarce. So far, only few studies provide evidence for the presence of MP in rivers and lakes. Data on MP uptake by freshwater invertebrates and fish is very limited.
Knowledge gaps: While the research on marine MP is more advanced, there are immense gaps of knowledge regarding freshwater MP. Data on their abundance is fragmentary for large and absent for small surface waters. Likewise, relevant sources and the environmental fate remain to be investigated. Data on the biological effects of MP in freshwater species is completely lacking. The accumulation of other freshwater contaminants on MP is of special interest because ingestion might increase the chemical exposure. Again, data is unavailable on this important issue.
Conclusions: MP represent freshwater contaminants of emerging concern. However, to assess the environmental risk associated with MP, comprehensive data on their abundance, fate, sources, and biological effects in freshwater ecosystems are needed. Establishing such data critically depends on a collaborative effort by environmental scientists from diverse disciplines (chemistry, hydrology, ecotoxicology, etc.) and, unsurprisingly, on the allocation of sufficient public funding.
Microplastics (MP) are contaminants of emerging concern in aquatic ecosystems. While the number of studies is rapidly increasing, a comparison of the toxicity of MP and natural particulate matter is largely missing. In addition, research focusses on the impacts of hydrophobic chemicals sorbed to plastics. However, the interactive effects of MP and hydrophilic, dissolved chemicals remain largely unknown. Therefore, we conducted chronic toxicity studies with larvae of the freshwater dipteran Chironomus riparius exposed to unplasticised polyvinyl chloride MP (PVC-MP) as well as kaolin and diatomite as reference materials for 28 days. In addition, we investigated the effects of particles in combination with the neonicotinoid imidacloprid in a multiple-stressor experiment. High concentrations of kaolin positively affected the chironomids. In contrast, exposure to diatomite and PVC-MP reduced the emergence and mass of C. riparius. Likewise, the toxicity of imidacloprid was enhanced in the presence of PVC-MP and slightly decreased in the co-exposure with kaolin. Overall, parallel experiments and chemical analysis indicate that the toxicity of PVC-MP was not caused by leached or sorbed chemicals. Our study demonstrates that PVC-MP induce more severe effects than both natural particulate materials. However, the latter are not benign per se, as the case of diatomite highlights. Considering the high, environmentally irrelevant concentrations needed to induce adverse effects, C. riparius is insensitive to exposures to PVC-MP.
Background: Multimorbidity is a common phenomenon in primary care. Until now, no clinical guidelines for multimorbidity exist. For the development of these guidelines, it is necessary to know whether or not patients are aware of their diseases and to what extent they agree with their doctor. The objectives of this paper are to analyze the agreement of self-reported and general practitioner-reported chronic conditions among multimorbid patients in primary care, and to discover which patient characteristics are associated with positive agreement.
Methods: The MultiCare Cohort Study is a multicenter, prospective, observational cohort study of 3,189 multimorbid patients, ages 65 to 85. Data was collected in personal interviews with patients and GPs. The prevalence proportions for 32 diagnosis groups, kappa coefficients and proportions of specific agreement were calculated in order to examine the agreement of patient self-reported and general practitioner-reported chronic conditions. Logistic regression models were calculated to analyze which patient characteristics can be associated with positive agreement.
Results: We identified four chronic conditions with good agreement (e.g. diabetes mellitus κ = 0.80;PA = 0,87), seven with moderate agreement (e.g. cerebral ischemia/chronic stroke κ = 0.55;PA = 0.60), seventeen with fair agreement (e.g. cardiac insufficiency κ = 0.24;PA = 0.36) and four with poor agreement (e.g. gynecological problems κ = 0.05;PA = 0.10).Factors associated with positive agreement concerning different chronic diseases were sex, age, education, income, disease count, depression, EQ VAS score and nursing care dependency. For example: Women had higher odds ratios for positive agreement with their GP regarding osteoporosis (OR = 7.16). The odds ratios for positive agreement increase with increasing multimorbidity in almost all of the observed chronic conditions (OR = 1.22-2.41).
Conclusions: For multimorbidity research, the knowledge of diseases with high disagreement levels between the patients' perceived illnesses and their physicians' reports is important. The analysis shows that different patient characteristics have an impact on the agreement. Findings from this study should be included in the development of clinical guidelines for multimorbidity aiming to optimize health care. Further research is needed to identify more reasons for disagreement and their consequences in health care.
Background: Multimorbidity is a phenomenon with high burden and high prevalence in the elderly. Our previous research has shown that multimorbidity can be divided into the multimorbidity patterns of 1) anxiety, depression, somatoform disorders (ADS) and pain, and 2) cardiovascular and metabolic disorders. However, it is not yet known, how these patterns are influenced by patient characteristics. The objective of this paper is to analyze the association of socio-demographic variables, and especially socio-economic status with multimorbidity in general and with each multimorbidity pattern.
Methods: The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses.
Results: Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status.
Conclusions: Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups.
Background: It is not well established how psychosocial factors like social support and depression affect health-related quality of life in multimorbid and elderly patients. We investigated whether depressive mood mediates the influence of social support on health-related quality of life.
Methods: Cross-sectional data of 3,189 multimorbid patients from the baseline assessment of the German MultiCare cohort study were used. Mediation was tested using the approach described by Baron and Kenny based on multiple linear regression, and controlling for socioeconomic variables and burden of multimorbidity.
Results: Mediation analyses confirmed that depressive mood mediates the influence of social support on health-related quality of life (Sobel's p < 0.001). Multiple linear regression showed that the influence of depressive mood (beta = -0.341, p < 0.01) on health-related quality of life is greater than the influence of multimorbidity (beta = -0.234, p < 0.01).
Conclusion: Social support influences health-related quality of life, but this association is strongly mediated by depressive mood. Depression should be taken into consideration in research on multimorbidity, and clinicians should be aware of its importance when caring for multimorbid patients.
Obesity and associated lifestyle in a large sample of multi-morbid German primary care attendees
(2014)
Background: Obesity and the accompanying increased morbidity and mortality risk is highly prevalent among older adults. As obese elderly might benefit from intentional weight reduction, it is necessary to determine associated and potentially modifiable factors on senior obesity. This cross-sectional study focuses on multi-morbid patients which make up the majority in primary care. It reports on the prevalence of senior obesity and its associations with lifestyle behaviors.
Methods: A total of 3,189 non-demented, multi-morbid participants aged 65–85 years were recruited in primary care within the German MultiCare-study. Physical activity, smoking, alcohol consumption and quantity and quality of nutritional intake were classified as relevant lifestyle factors. Body Mass Index (BMI, general obesity) and waist circumference (WC, abdominal obesity) were used as outcome measures and regression analyses were conducted.
Results: About one third of all patients were classified as obese according to BMI. The prevalence of abdominal obesity was 73.5%. Adjusted for socio-demographic variables and objective and subjective disease burden, participants with low physical activity had a 1.6 kg/m2 higher BMI as well as a higher WC (4.9 cm, p<0.001). Current smoking and high alcohol consumption were associated with a lower BMI and WC. In multivariate logistic regression, using elevated WC and BMI as categorical outcomes, the same pattern in lifestyle factors was observed. Only for WC, not current but former smoking was associated with a higher probability for elevated WC. Dietary intake in quantity and quality was not associated with BMI or WC in either model.
Conclusions: Further research is needed to clarify if the huge prevalence discrepancy between BMI and WC also reflects a difference in obesity-related morbidity and mortality. Yet, age-specific thresholds for the BMI are needed likewise. Encouraging and promoting physical activity in older adults might a starting point for weight reduction efforts.