Patients’ Opinions about Knowing Their Risk for Depression and What to Do about It. The PredictD-Qualitative Study

[Background] The predictD study developed and validated a risk algorithm for predicting the onset of major depression in primary care. We aimed to explore the opinion of patients about knowing their risk for depression and the values and criteria upon which these opinions are based. [Methods] A maximum variation sample of patients was taken, stratified by city, age, gender, immigrant status, socio-economic status and lifetime depression. The study participants were 52 patients belonging to 13 urban health centres in seven different cities around Spain. Seven Focus Groups (FGs) were given held with primary care patients, one for each of the seven participating cities. [Results] The results showed that patients generally welcomed knowing their risk for depression. Furthermore, in light of available evidence several patients proposed potential changes in their lifestyles to prevent depression. Patients generally preferred to ask their General Practitioners (GPs) for advice, though mental health specialists were also mentioned. They suggested that GPs undertake interventions tailored to each patient, from a “patient-centred” approach, with certain communication skills, and giving advice to help patients cope with the knowledge that they are at risk of becoming depressed. [Conclusions] Patients are pleased to be informed about their risk for depression. We detected certain beliefs, attitudes, values, expectations and behaviour among the patients that were potentially useful for future primary prevention programmes on depression.This work was supported by grants from the Andalusian Council of Health [grant reference: 2008/0195][www.juntadeandalucia.es/fundacionprogres​oysalud]; the Department of Health of the Basque Government [grant reference: 2008/111021][www.osakidetza.euskadi.net]; the Spanish Network of Primary Care Research “redIAPP” (RD06/0018), the “Aragón group” (RD06/0018/0020), the “Sant Joan de Deu group” (RD07/0018/0017), “Bizkaya group” (RD07/0018/0018), “Castilla-León group” (RD07/0018/0027) and the “SAMSERAP group” (RD06/0018/0039 and CTS-587) [www.rediapp.org]

Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals

Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals

A personalized intervention to prevent depression in primary care: cost-effectiveness study nested into a clustered randomized trial

Abstract Background: Depression is viewed as a major and increasing public health issue, as it causes high distress in the people experiencing it and considerable financial costs to society. Efforts are being made to reduce this burden by preventing depression. A critical component of this strategy is the ability to assess the individual level and profile of risk for the development of major depression. This paper presents the cost-effectiveness of a personalized intervention based on the risk of developing depression carried out in primary care, compared with usual care. Methods: Cost-effectiveness analyses are nested within a multicentre, clustered, randomized controlled trial of a personalized intervention to prevent depression. The study was carried out in 70 primary care centres from seven cities in Spain. Two general practitioners (GPs) were randomly sampled from those prepared to participate in each centre (i.e. 140 GPs), and 3326 participants consented and were eligible to participate. The intervention included the GP communicating to the patient his/her individual risk for depression and personal risk factors and the construction by both GPs and patients of a psychosocial programme tailored to prevent depression. In addition, GPs carried out measures to activate and empower the patients, who also received a leaflet about preventing depression. GPs were trained in a 10- to 15-h workshop. Costs were measured from a societal and National Health care perspective. Qualityadjustedlife years were assessed using the EuroQOL five dimensions questionnaire. The time horizon was 18 months.This work was supported by grants from the Spanish Ministry of Health, the Institute of Health Carlos III (ISCIII) and the European Regional Development Fund (ERDF) ’A way to build Europe’(grant references PS09/02272, PS09/02147, PS09/01095, PS09/00849 and PS09/00461); the Andalusian Council of Health (grant reference PI-0569-2010); the Spanish Network of Primary Care Research ’redIAPP’ (RD06/0018, RD12/0005/0001); the ’Aragón group’ (RD06/0018/0020, RD12/0005/0006); the ’Bizkaya group’ (RD06/0018/0018, RD12/0005/0010); the Castilla-León Group (RD06/0018/0027); the Mental Health (SJD) Barcelona Group (RD06/0018/0017, RD12/0005/0008); and the Mental-Health, Services and Primary Care (SAMSERAP) MálagaGroup (RD06/0018/0039, RD12/0005/0005)

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Relationship between olive oil consumption and ankle-brachial pressure index in a population at high cardiovascular risk

The aim of this study was to ascertain the association between the consumption of different categories of edible olive oils (virgin olive oils and olive oil) and olive pomace oil and ankle-brachial pressure index (ABI) in participants in the PREDIMED-Plus study, a trial of lifestyle modification for weight and cardiovascular event reduction in individuals with overweight/obesity harboring the metabolic syndrome. Methods: We performed a cross-sectional analysis of the PREDIMED-Plus trial. Consumption of any category of olive oil and olive pomace oil was assessed through a validated food-frequency questionnaire. Multivariable linear regression models were fitted to assess associations between olive oil consumption and ABI. Additionally, ABI ≤1 was considered as the outcome in logistic models with different categories of olive oil and olive pomace oil as exposure. Results: Among 4330 participants, the highest quintile of total olive oil consumption (sum of all categories of olive oil and olive pomace oil) was associated with higher mean values of ABI (beta coefficient: 0.014, 95% confidence interval [CI]: 0.002, 0.027) (p for trend = 0.010). Logistic models comparing the consumption of different categories of olive oils, olive pomace oil and ABI ≤1 values revealed an inverse association between virgin olive oils consumption and the likelihood of a low ABI (odds ratio [OR] 0.73, 95% CI [0.56, 0.97]), while consumption of olive pomace oil was positively associated with a low ABI (OR 1.22 95% CI [1.00, 1.48]). Conclusions: In a Mediterranean population at high cardiovascular risk, total olive oil consumption was associated with a higher mean ABI. These results suggest that olive oil consumption may be beneficial for peripheral artery disease prevention, but longitudinal studies are needed

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Respuesta emocional de los médicos de familia en los encuentros médico-pacientes difíciles

Tesis Univ. Granada. Departamento de Medicina Legal, Toxicología y Psiquiatría. Leída el 31 de mayo de 201

Common mental disorders in primary care: diagnostic and therapeutic difficulties, and new challenges in prediction and prevention. SESPAS Report 2020

In primary health care only chronic pain surpass depression and anxiety in loss of quality-adjusted life years. More than 70% of people suffering from common mental disorders consulted their GPs for this reason. However, 'the declining halves rule' is a reality: less than 50% of primary care attendees with common mental disorders were correctly diagnosed, of these less than 50% received adequate treatment (pharmacological or psychological) and of these less than 50% patients were adherent. Collaborative models of common mental disorders care in primary health care have demonstrated their effectiveness through clinical trials; however, its implementation in a more general and real context is difficult and its effectiveness remains unclear. Risk algorithms have been developed and validated in primary health care to predict the onset and prognosis of common mental disorders; which are useful for their treatment and prevention. There is evidence that psychological and psychoeducational interventions (and possibly those of physical exercise) are effective for the primary prevention of common mental disorders, even in primary health care; although their effects are small or moderate. These interventions have a high potential to be scalable in schools, workplace and primary health care; in addition, when they are administered through information and communication technologies (e.g. by App), in self-guided or minimally guided programs, they have demonstrated their effectiveness for the treatment and prevention of common mental disorders. They are also very accessible, have low cost and contribute to the massive implementation of these interventions in different settings.YesEn atención primaria solo el dolor crónico supera a la depresión y la ansiedad en la pérdida de años de vida ajustados por calidad. Más del 70% de las personas que sufrían enfermedades mentales comunes consultaron por ello a su médico/a de familia. Sin embargo, «la regla de las mitades decrecientes» es una realidad: menos del 50% de las personas consultantes de atención primaria con enfermedades mentales comunes fueron diagnosticadas correctamente, y de ellas, menos del 50% recibieron un tratamiento (farmacológico o psicológico) adecuado, y de estas, menos del 50% fueron adherentes. Los modelos colaborativos de atención a las enfermedades mentales comunes en atención primaria han demostrado su efectividad en ensayos clínicos, pero su implementación en un contexto más general y real es difícil y su efectividad todavía es poco conocida. Se han desarrollado y validado algoritmos de riesgo para predecir el inicio y el pronóstico de las enfermedades mentales comunes en atención primaria que son útiles para su tratamiento y prevención. Existen evidencias de que las intervenciones psicológicas, psicoeducativas y de ejercicio físico son efectivas en prevención primaria, incluso en atención primaria, aunque su efecto es pequeño o moderado. Estas intervenciones tienen un gran potencial para ser escalables en las escuelas, el ámbito laboral y la atención primaria; además, cuando se administran mediante tecnologías de la información y la comunicación (p. ej., App), en programas autoguiados o mínimamente guiados, han demostrado su efectividad para el tratamiento y la prevención de las enfermedades mentales comunes. También son muy accesibles y de bajo coste, y contribuyen a la implementación masiva de estas intervenciones en diferentes contextos