RESUMO
BackgroundFew datasets have been established that capture the full breadth of COVID-19 patient interactions with a health system. Our first objective was to create a COVID-19 dataset that linked primary care data to COVID-19 testing, hospitalisation, and mortality data at a patient level. Our second objective was to provide a descriptive analysis of COVID-19 outcomes among the general population and describe the characteristics of the affected individuals. MethodsWe mapped patient-level data from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). More than 3,000 data quality checks were performed to assess the readiness of the database for research. Subsequently, to summarise the COVID-19 population captured, we established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or positive test results for SARS-CoV-2, hospitalisations with COVID-19, and COVID-19 deaths during follow-up, which went up until 30th June 2021. FindingsMapping data to the OMOP CDM was performed and high data quality was observed. The mapped database was used to identify a total of 5,870,274 individuals, who were included in the general population cohort as of 1st March 2020. Over follow up, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation with COVID-19, 5,642 had an ICU admission with COVID-19, and 11,233 had a COVID-19 death. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised in general and those who died. InterpretationWe have established a comprehensive dataset that captures COVID-19 diagnoses, test results, hospitalisations, and deaths in Catalonia, Spain. Extensive data checks have shown the data to be fit for use. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19 outcomes over time were described. FundingGeneralitat de Catalunya and European Health Data and Evidence Network (EHDEN).
RESUMO
ObjectivesTo investigate how incidence trends of anxiety and depressive disorders have been affected by the COVID-19 pandemic. DesignPopulation-based cohort study. SettingObservational cohort study from 2018 to 2021 using the Information System for Research in Primary Care (SIDIAP) database in Catalonia, Spain. Participants4,255,847 individuals aged 18 or older in SIDIAP on 1 March, 2018 with no prior history of anxiety and depressive disorders. Primary and secondary outcomes measuresIncidence of anxiety and depressive disorders prior to COVID-19 (March, 2018 to February, 2020), during the COVID-19 lockdown (March to June, 2020) and post-lockdown periods (from July, 2020 to March, 2021) were calculated. Forecasted rates over COVID-19 periods were estimated using negative binomial regression models based on previous data. The percentage reduction was estimated by comparing forecasted versus observed events, overall and by age, sex and socioeconomic status. ResultsThe incidence rates per 100,000 person-months of anxiety and depressive disorders were 171.0 (95%CI: 170.2-171.8) and 46.6 (46.2-47.0), respectively, during the pre-lockdown period. We observed an increase of 39.7% (95%PI: 26.5 to 53.3) in incident anxiety diagnoses compared to the expected in March, 2020, followed by a reduction of 16.9% (8.6 to 24.5) during the post-lockdown periods. A reduction of incident depressive disorders occurred during the lockdown and post-lockdown periods (46.6% [38.9 to 53.1] and 23.2% [12.0 to 32.7], respectively). Reductions were higher among adults aged 18 to 34 and individuals living in most deprived areas. ConclusionsThe COVID-19 pandemic in Catalonia was associated with an initial increase in anxiety disorders diagnosed in primary care, but a reduction in cases as the pandemic continued. Diagnoses of depressive disorders were lower than expected throughout the pandemic. Summary boxO_ST_ABSWhat is already known on this topicC_ST_ABS- While previous self-reported studies have provided evidence of increased mental health burden during the initial phase of the COVID-19 pandemic, a number of studies observed that fewer diagnoses were made in primary care settings than would have been expected during the initial stages of the pandemic. - Population data that examine the impact of COVID-19 on temporal trends of incident cases of common mental health disorders are lacking in Catalonia, Spain. What this study adds- This study has quantified the impact of the COVID-19 pandemic on trends of incidence of anxiety and depressive disorders among adults living in Catalonia. - Reductions in incident cases of anxiety and depressive disorders were higher for young adults and people living in most deprived areas. - Incident diagnoses of anxiety and depressive disorders have not been fully recovered to what would have been expected.
RESUMO
ObjectiveTo develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones. DesignCohort study SettingThe Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. ParticipantsConsecutive symptomatic patients ([≥]18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay. Main outcome measuresIn-hospital mortality ResultsMedian (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). ConclusionsWe designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19. Summary boxesWhat is already known on this topic? O_LIRapid scoring systems may be very useful for fast and effective assessment of COVID-19 patients in the emergency department. C_LIO_LIThe majority of available scores have high risk of bias and lack benefit to clinical decision making. C_LIO_LIDerivation and validation studies in low- and middle-income countries, including Latin America, are scarce. C_LI What this study adds O_LIABC2-SPH employs seven well defined variables, routinely assessed upon hospital presentation: age, number of comorbidities, blood urea nitrogen, C reactive protein, Spo2/FiO2 ratio, platelets and heart rate. C_LIO_LIThis easy-to-use risk score identified four categories at increasing risk of death with a high level of accuracy, and displayed better discrimination ability than other existing scores. C_LIO_LIA free web-based calculator is available and may help healthcare practitioners to estimate the expected risk of mortality for patients at hospital presentation. C_LI
