Background
Current benzodiazepine (BZD) prescription guidelines recommend short-term use to minimize the risk of dependence, cognitive impairment, and falls and fractures. However, many clinicians overprescribe BZDs and chronic use by patients is common. There is limited evidence on the effectiveness of interventions delivered by general practitioners (GPs) on reducing prescriptions and long-term use of BZDs. We aimed to evaluate the effectiveness of a multicomponent intervention for GPs that seeks to reduce BZD prescriptions and the prevalence of long-term users.
Methods and findings
We conducted a multicenter two-arm, cluster randomized controlled trial in 3 health districts in Spain (primary health centers [PHCs] in Balearic Islands, Catalonia, and Valencian Community) from September 2016 to May 2018. The 81 PHCs were randomly allocated to the intervention group (n = 41; 372 GPs) or the control group (n = 40; 377 GPs). GPs were not blinded to the allocation; however, pharmacists, researchers, and trial statisticians were blinded to the allocation arm. The intervention consisted of a workshop about the appropriate prescribing of BZDs and tapering-off long-term BZD use using a tailored stepped dose reduction with monthly BZD prescription feedback and access to a support web page. The primary outcome, based on 700 GPs (351 in the control group and 349 in the intervention group), compared changes in BZD prescriptions in defined daily doses (DDDs) per 1,000 inhabitants per day after 12 months. The 2 secondary outcomes were the proportion of long-term users (>= 6 months) and the proportion of long-term users over age 65 years.
Intention-to-treat (ITT) analysis was used to assess all clinical outcomes.
Forty-nine GPs (21 intervention group and 28 control group) were lost to follow-up. However, all GPs were included in the ITT analysis. After 12 months, there were a statistically significant decline in total BZD prescription in the intervention group compared to the control group (mean difference: -3.24 DDDs per 1,000 inhabitants per day, 95% confidence interval (CI): -4.96, -1.53, p < 0.001). The intervention group also had a smaller number of long-term users. The adjusted absolute difference overall was -0.36 (95% CI: -0.55, -0.16, p > 0.001), and the adjusted absolute difference in long-term users over age 65 years was -0.87 (95% CI: -1.44, -0.30, p = 0.003). A key limitation of this clustered design clinical trial is the imbalance of some baseline characteristics. The control groups have a higher rate of baseline BZD prescription, and more GPs in the intervention group were women, GPs with a doctorate degree, and trainers of GP residents.
Conclusions
A multicomponent intervention that targeted GPs and included educational meeting, feedback about BZD prescriptions, and a support web page led to a statistically significant reduction of BZD prescriptions and fewer long-term users. Although the effect size was small, the high prevalence of BZD use in the general population suggests that large-scale implementation of this intervention could have positive effects on the health of many patients.

Healthcare workers (HCW) are at high risk for suicide, yet little is known about the onset of suicidal thoughts and behaviors (STB) in this important segment of the population in conjunction with the COVID-19 pandemic. We conducted a multicenter, prospective cohort study of Spanish HCW active during the COVID-9 pandemic. A total of n = 4809 HCW participated at baseline (May-September 2020; i.e., just after the first wave of the pandemic) and at a four-month follow-up assessment (October-December 2020) using web-based surveys. Logistic regression assessed the individual-and population-level associations of separate proximal (pandemic) risk factors with four-month STB incidence (i.e., 30-day STB among HCW negative for 30-day STB at baseline), each time adjusting for distal (pre-pandemic) factors. STB incidence was estimated at 4.2% (SE = 0.5; n = 1 suicide attempt). Adjusted for distal factors, proximal risk factors most strongly associated with STB incidence were various sources of interpersonal stress (scaled 0-4; odds ratio [OR] range = 1.23-1.57) followed by personal health-related stress and stress related to the health of loved ones (scaled 0-4; OR range 1.30-1.32), and the perceived lack of healthcare center preparedness (scaled 0-4; OR = 1.34). Population-attributable risk proportions for these proximal risk factors were in the range 45.3-57.6%. Other significant risk factors were financial stressors (OR range 1.26-1.81), isolation/quarantine due to COVID-19 (OR = 1.53) and having changed to a specific COVID-19 related work location (OR = 1.72). Among other interventions, our findings call for healthcare systems to implement adequate conflict communication and resolution strategies and to improve family-work balance embedded in organizational justice strategies.

OBJECTIVE: To analyse susceptibility/risk of suffering COVID-19 among adults with distinct underlying medical conditions. METHODS: Population-based cohort study involving 79,083 individuals =50 years old in Tarragona (Southern Catalonia, Spain). Baseline cohort characteristics (demographic, pre-existing comorbidities, chronic medications and vaccinations history) were established at study start (01/03/2020) and primary outcome was laboratory-confirmed COVID-19 occurred among cohort members throughout 01/03/2020-30/06/2020. Risk of suffering COVID-19 was evaluated by Cox regression, estimating multivariable hazard ratios (HRs) adjusted for age/sex and pre-existing comorbidities. RESULTS: Across study period, 536 laboratory-confirmed COVID-19 cases were observed (mean incidence: 39.5 cases per 100,000 persons-week). In multivariable-analysis, increasing age/years (HR: 1.01; 95% CI: 1.00-1.02), nursing-home (HR: 20.19; 95% CI: 15.98-25.51), neurological disease (HR: 1.35; 95% CI: 1.03-1.77), taking diuretics (HR: 1.39; 95% CI: 1.10-1.75), antiplatelet (HR: 1.36; 95% CI: 1.05-1.76) and benzodiazepines (HR: 1.24; 95% CI: 1.00-1.53) increased risk; conversely, taking angiotensin-converting-enzyme inhibitors (HR: 0.78; 95% CI: 0.61-1.00), angiotensin-receptor-blockers (HR: 0.70; 95%CI: 0.51-0.96) and statins (HR: 0.75; 95% CI: 0.58-0.96) were associated with reduced risk. Among community-dwelling individuals, pre-existing cancer, renal and cardiac disease appeared also related with an increased risk, whereas influenza vaccination was associated with reduced risk. CONCLUSION: In a setting with relatively low incidence of COVID-19 across the first wave of pandemic period, increasing age, nursing-home residence and multiple comorbidities appear predisposing for COVID-19 among middle-aged/older adults. Conversely, statins, angiotensin-receptor blockers/inhibitors and influenza vaccination were related with decreased risk.

Objective: To analyse susceptibility/risk of suffering COVID-19 among adults with distinct underlying medical conditions.
Methods: Population-based cohort study involving 79,083 individuals >= 50 years old in Tarragona (Southern Catalonia, Spain). Baseline cohort characteristics (demographic, pre-existing comorbidities, chronic medications and vaccinations history) were established at study start (01/03/2020) and primary outcome was laboratory-confirmed COVID-19 occurred among cohort members throughout 01/03/2020-30/06/2020. Risk of suffering COVID-19 was evaluated by Cox regression, estimating multi -variable hazard ratios (HRs) adjusted for age/sex and pre-existing comorbidities.
Results: Across study period, 536 laboratory-confirmed COVID-19 cases were observed (mean incidence: 39.5 cases per 100,000 persons-week). In multivariable-analysis, increasing age/years (HR: 1.01; 95% CI: 1.00-1.02), nursing-home (HR: 20.19; 95% CI: 15.98-25.51), neurological disease (HR: 1.35; 95% CI: 1.03-1.77), taking diuretics (HR: 1.39; 95% CI: 1.10-1.75), antiplatelet (HR: 1.36; 95% CI: 1.05-1.76) and benzodiazepines (HR: 1.24; 95% CI: 1.00-1.53) increased risk; conversely, taking angiotensin-converting-enzyme inhibitors (HR: 0.78; 95% CI: 0.61-1.00), angiotensin-receptor-blockers (HR: 0.70; 95%CI: 0.51-0.96) and statins (HR: 0.75; 95% CI: 0.58-0.96) were associated with reduced risk. Among community-dwelling individuals, pre-existing cancer, renal and cardiac disease appeared also related with an increased risk, whereas influenza vaccination was associated with reduced risk.
Conclusion: In a setting with relatively low incidence of COVID-19 across the first wave of pandemic period, increasing age, nursing-home residence and multiple comorbidities appear predisposing for COVID-19 among middle-aged/older adults. Conversely, statins, angiotensin-receptor blockers/inhibitors and influenza vaccination were related with decreased risk. (c) 2021 Elsevier Espana, S.L.U. All rights reserved.

Objective The aim of present study was to evaluate our clinical decision support system (CDSS) for predicting risk of diabetic retinopathy (DR). We selected randomly a real population of patients with type 2 diabetes (T2DM) who were attending our screening programme.
Methods and analysis The sample size was 602 patients with T2DM randomly selected from those who attended the DR screening programme. The algorithm developed uses nine risk factors: current age, sex, body mass index (BMI), duration and treatment of diabetes mellitus (DM), arterial hypertension, Glicated hemoglobine (HbA1c), urine-albumin ratio and glomerular filtration.
Results The mean current age of 67.03 +/- 10.91, and 272 were male (53.2%), and DM duration was 10.12 +/- 6.4 years, 222 had DR (35.8%). The CDSS was employed for 1 year. The prediction algorithm that the CDSS uses included nine risk factors: current age, sex, BMI, DM duration and treatment, arterial hypertension, HbA1c, urine-albumin ratio and glomerular filtration. The area under the curve (AUC) for predicting the presence of any DR achieved a value of 0.9884, the sensitivity of 98.21%, specificity of 99.21%, positive predictive value of 98.65%, negative predictive value of 98.95%, alpha error of 0.0079 and beta error of 0.0179.
Conclusion Our CDSS for predicting DR was successful when applied to a real population.