Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

Background: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health car

Photoelectrochemical response of carbon dots (CDs) derived from chitosan and their use in electrochemical imaging

International audienceWe report a direct photoelectrochemical response from low cost carbon dots (CDs) prepared from chitosan via a solvothermal method. The carbon dots were covalently linked to an indium tin oxide (ITO) surface through a self-assembled silane monolayer. We attribute the photocurrent of the ITO–silane–CD surface to a photogenerated electron-transfer process by CDs under illumination with a wavelength of 420 nm to 450 nm. The self-assembled monolayer of CDs was used for ac-photocurrent imaging of the surface with micron scale lateral resolution. This discovery opens up new applications for CDs as biocompatible, light-addressable electrochemical sensors in bioanalytical and bioimaging applications

Suicidality in primary care patients who present with sadness and anhedonia: a prospective European study

Background: Sadness and anhedonia (loss of interest in activities) are central symptoms of major depression. However, not all people with these symptoms meet diagnostic criteria for major depression. We aimed to assess the importance of suicidality in the outcomes for primary care patients who present with sadness and anhedonia. Method: Cohort study of 2,599 unselected primary care attenders in six European countries followed up at 6 and 12 months. Results: 1) In patients with sadness and/or anhedonia who were not depressed at entry to the study, suicide plans (OR = 3.05; 95 % CI = 1.50–6.24; p = 0.0022) and suicide attempts (OR = 9.08; 95 % CI = 2.57–32.03; p = 0.0006) were significant predictors of developing new onset depression at 6 or 12 months. 2) In patients with sadness and/or anhedonia who met CIDI criteria for major depression at entry, suicidal ideation (OR = 2.93; 95 % CI = 1.70–5.07; p = 0.0001), suicide plans (OR = 3.70; 95 % CI = 2.08–6.57; p < 0.0001), and suicide attempts (OR = 3.33; 95 % CI = 1.47–7.54; p = 0.0040) were significant predictors of persistent depression at 6 or 12 months. Conclusions: Three questions on suicidality could help primary care professionals to assess such patients more closely without necessarily establishing whether they meet criteria for major depression.This research was funded by a grant from The European Commission, referencePREDICT-QL4-CT2002-00683. We are also grateful for part support in Europe from: the Estonian Scientific Foundation (grant number 5696); the Slovenian Ministry for Research (grant No.4369-1027); the Spanish Ministry of Health (grant FIS references: PI041980, PI041771, PI042450) and the Spanish Network of Primary Care Research, redIAPP (ISCIII-RETICS RD06/0018) and SAMSERAP group; and the UK NHS Research and Development office for providing service support costs in the UK. We are also grateful for the support from the University of Malaga (Spain) and to Carlos García from Loyola Andalucía University (Spain)

Predicting the onset of anxiety syndromes at 12 months in primary care attendees. The PredictA-Spain study

Background: There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. Methods: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. Results: The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval = 0.78–0.83) and the Hedges' g = 1.17 (95% confidence interval = 1.04–1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. Conclusions: The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care.This study was supported by the Spanish Ministry of Health (grant FIS references: PI041980, PI041771, PI042450 and PI06/1442) and the Andalusian Council of Health (grant references: 05/403 and 06/278); as well as the Spanish Network of Primary Care Research ‘redIAPP’ (RD06/0018), the ‘Aragón group’ (RD06/0018/0020), the ‘Baleares group’ (RD07/0018/0033), and the ‘SAMSERAP group’ (RD06/0018/0039)

Testing a global standard for quantifying species recovery and assessing conservation impact

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard