Airflow limitation alone is unable to capture the complexity of chronic obstructive pulmonary disease (COPD), better explained by comprehensive disease-specific indexes. Frailty is a clinical condition characterized by high vulnerability to internal and external stressors and represents a strong predictor of adverse outcomes.

Primary objective was to test the association between indexes of lung function and COPD severity with frailty index (FI), and secondary to evaluate the association between FI and comorbidities, cognitive and physical function, BODE index, and mortality.

150 stable COPD outpatients were enrolled and followed up to 4years. At baseline, participants performed a geriatric multidimensional assessment, pulmonary function tests, arterial blood gas analysis, 6-min walking test, and bioimpedance analysis. BODE and FI were calculated. Spearman’s ρ was used to assess correlations. Mortality was assessed using Kaplan-Meier curves.

Participants were followed up for a median of 39months. Mean age was 73years and median frailty index 0.15 (IQR 0.11-0.19). FI was higher in frequent exacerbators (≥ 2/year) (mean 0.18 vs 0.15, p 0.01) and dyspnoeic patients (mMRC ≥ 2) (mean 0.21 vs 0.14, p < 0.01) and correlated with lung volumes, expiratory flows, and pressure of arterial oxygen. FI was positively correlated with the number of comorbidities, depressive symptoms, cognitive decline, and BODE index. Mortality was higher in patients with BODE higher than 3 (HR 3.6, 95% CI 1.2-10.9), and not associated with FI.

FI positively correlates with all clinical drivers orienting the choice of treatment in COPD.

FI associates with lung function and COPD severity, but does not associate with mortality.

FI associates with lung function and COPD severity, but does not associate with mortality.

Enteropathy-associated T cell lymphoma (EATL) is a rare subtype of mature T cell lymphoma. The available literature about this rare type T cell lymphoma is relatively limited. This article provides a summary and review of the available literature addressing this entity in terms of risk factors, pathogenesis, diagnostic, and therapeutic options.

EATL has two distinct subtypes. Type I EATL, now known as EATL, is closely, but not exclusively linked to celiac disease (CD), and it is primarily a disease of Northern European origin. It accounts for < 5% of peripheral T cell lymphoma (PTCL). Risk factors for EATL include advanced age, male sex, and most importantly, genetic susceptibility in the form of HLA-DQ2 homozygosity. The pathogenesis of EATL is closely related to celiac disease as it shares common pathogenic features with refractory celiac disease. The gold standard of diagnosis is histological diagnosis. EATL carries an aggressive course and a poor prognosis. Treatment of EATL includes surgery, inducEATL. Early diagnosis and early referral to specialized centers would be the best way to deal with such patients. Development of new prognostic models and early surgical intervention are warranted. Prevention is where all the efforts should be spent, by counseling patients with CD regarding the importance of adherence to gluten-free diet and development of periodic surveillance programs in celiac disease patients for early detection of pre-lymphoma lesions.

Equitable health financing is crucial to attaining universal health coverage (UHC). Health financing, a major focus of the National Health Insurance in South Africa, can potentially affect income distribution.

This paper assesses the impact of financing health services on income inequality (i.e. the income redistributive effect [RE]) in South Africa.

Data come from the nationally representative Income and Expenditure Survey (2010/2011). A standard approach is used to estimate and decompose RE for the major health financing mechanisms (taxes, insurance and out-of-pocket health spending) into the sum of the vertical effect (i.e. the extent of progressivity or regressivity), horizontal inequity (i.e. the extent to which ‘equals’ are not treated equally) and reranking effect (i.e. the extent to which individuals or households change ranks after paying for health services).

Financing health services through direct taxes (RE = 0.0072, P < 0.01) and private health insurance (RE = 0.0103, P < 0.01) significantly reduce income inequality, while indirect taxes (RE = -0.0025, P < 0.01) and out-of-pocket health spending (RE = -0.0009, P < 0.01) lead to significant increases in income inequality. Although private health insurance contributions may reduce income inequality, enrolees are only a small minority, mainly the rich. Also, total taxes (RE = 0.0048, P < 0.01) and total health financing (RE = 0.0152, P < 0.01) contribute to significant reductions in income inequality, with the vertical effect dominating.

Taxes that contribute to reducing income inequality hold promise for equitable health financing in South Africa. The results are relevant for and support the current National Health Insurance policy in South Africa and the global move towards UHC.

Taxes that contribute to reducing income inequality hold promise for equitable health financing in South Africa. The results are relevant for and support the current National Health Insurance policy in South Africa and the global move towards UHC.

Studies have been published regarding the impact of major system change (MSC) on care quality and outcomes, but few evaluate implementation costs or include them in cost-effectiveness analysis (CEA). This is despite large potential costs of MSC change planning, purchasing or repurposing assets, and staff time. Implementation costs can influence implementation decisions. We describe our framework and principles for costing MSC implementation and illustrate them using a case study.

We outlined MSC implementation stages and identified components, using a framework conceived during our work on MSC in stroke services. Selleckchem Abemaciclib We present a case study of MSC of specialist surgery services for prostate, bladder, renal and oesophagogastric cancers, focusing on North Central and North East London and West Essex. Health economists collaborated with qualitative researchers, clinicians and managers, identifying key reconfiguration stages and expenditures. Data sources (n = approximately 100) included meeting minutes, interviews, and business cases.