[Epidemiological study on the impact of influenza vaccination on the clinical course of patients with COVID-19 and co-infection by both viruses in Gran Canaria, Spain]. / Estudio epidemiológico sobre el impacto de la vacunación antigripal en la evolución clínica de pacientes con COVID-19 y la coinfección por ambos virus en Gran Canaria, España.

OBJECTIVE: To analyze the frequency of influenza and SARS-CoV-2 co-infections, as well as the differences in the course of disease (risk of mortality, hospital and intensive care admissions) in patients infected with the SARS-CoV-2 virus in relation to flu vaccination status in the 2021-2022 season. METHODS: Population-based observational retrospective study in a cohort of 19,850 patients diagnosed with COVID-19 between June 1, 2021 and February 28, 2022 on the island of Gran Canaria. RESULTS: A total of 1,789 patients (9%) diagnosed with COVID-19 had received flu vaccinations. 13,676 people (68.9%) had a full course of COVID-19 vaccinations. In the period between June 1, 2021 and February 28, 2022, 8 cases of flu and COVID-19 coinfection were recorded. Hypertension (18.5%), asthma (12.8%) and diabetes (7.2%) were the most frequent comorbidities. There were 147 deaths (0.7%). Older patients ([OR] 1.11 95% CI 1.09-1.13) and people with cancer ([OR] 4.21 95% CI 2.58-6.89) had a higher risk of dying from COVID-19 (p<0.05). Female sex was noted as a protective factor ([OR] 0.61 95% CI 0.40-0.92). CONCLUSIONS: Old age, male sex and cancer were independent prognostic factors for mortality. Three doses of SARS-CoV-2 vaccines and influenza vaccines were highly effective in preventing COVID-19-related deaths and hospital admissions. These findings suggest that flu vaccination can help control the pandemic.

Predicting the onset of major depression in primary care: international validation of a risk prediction algorithm from Spain.

BACKGROUND: The different incidence rates of, and risk factors for, depression in different countries argue for the need to have a specific risk algorithm for each country or a supranational risk algorithm. We aimed to develop and validate a predictD-Spain risk algorithm (PSRA) for the onset of major depression and to compare the performance of the PSRA with the predictD-Europe risk algorithm (PERA) in Spanish primary care. METHOD: A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multi-level logistic regression and inverse probability weighting to build the PSRA. In Spain (4574), Chile (2133) and another five European countries (5184), 11 891 non-depressed adult primary care attendees formed our at-risk population. The main outcome was DSM-IV major depression (CIDI). RESULTS: Six variables were patient characteristics or past events (sex, age, sex×age interaction, education, physical child abuse, and lifetime depression) and six were current status [Short Form 12 (SF-12) physical score, SF-12 mental score, dissatisfaction with unpaid work, number of serious problems in very close persons, dissatisfaction with living together at home, and taking medication for stress, anxiety or depression]. The C-index of the PSRA was 0.82 [95% confidence interval (CI) 0.79-0.84]. The Integrated Discrimination Improvement (IDI) was 0.0558 [standard error (s.e.)=0.0071, Zexp=7.88, p<0.0001] mainly due to the increase in sensitivity. Both the IDI and calibration plots showed that the PSRA functioned better than the PERA in Spain. CONCLUSIONS: The PSRA included new variables and afforded an improved performance over the PERA for predicting the onset of major depression in Spain. However, the PERA is still the best option in other European countries.