An observational retrospective study was conducted on patients diagnosed with COVID-19 living in Spain, specifically in the Catalan Central Region, from March 1 to August 17, 2020. The population in the region over the age of 15 years was included in the study, with 348,596 patients. Patients older than 15 years are cared for by family and community specialists in primary care in Spain. The population of the area, including patients younger than 16 years, was 415,000 at the time of the study. Among the patients included in the study, 6.8% (23,844/348,596) had been diagnosed with COVID-19.

The data were extracted from the computerized medical records of the Primary Care Services Information Technologies (IT) System of the Catalan Institute of Health in Barcelona, Spain. The Primary Care Services IT System contains primary care electronic health records (EHRs) for over 6 million people in Catalonia, covering more than 80% of the Catalan population [26]. This system applies an anonymization process to maintain complete confidentiality and privacy of these data, following the European General Data Protection Regulation 2016/679 of April 27 and the Spanish Organic Law 3/2018 on Data Protection and Guarantee of Digital Rights. Variables such as demographic characteristics (ie, age and sex) and diverse comorbidities, such as hypertension, diabetes, obesity, dyslipidemia, COPD, being a current smoker, heart failure, cerebrovascular disease, and ischemic heart disease, were studied. Patients being treated with ACEIs or ARBs were also considered. The different diagnoses of risk factors and COVID-19 were based on the International Statistical Classification of Diseases and Related Health Problems 10th Edition (ICD-10); the codes related to these diseases are registered in the EHR database. Specifically, the codes used were based on the WHO and the Spanish Ministry of Health codification recommendations: U07.1 COVID-19; B97.29: Other coronavirus as the cause of diseases classified elsewhere and B34.2: Coronavirus infection, unspecified. The complete list of codes used in the study is included in Multimedia Appendix 1. The death events of the patients were also obtained from this database, which records the exact moment a patient dies.

The study protocol was approved by the University Institute for Primary Care Research Jordi Gol Health Care Ethics Committee (Code 20/066-PCV).

Categorical variables are described using frequencies and percentages. Continuous variables are described with means and standard deviation. Proportions of categorical variables were compared using the Fisher exact test, and the sample t test or Wilcoxon rank-sum test were used in the case of continuous variables. Multiple logistic regression analysis for predicting binary outcomes from continuous and categorical variables was applied. Multivariate logistic regression models were applied for the comparison between groups (patients with and without COVID-19, and deceased and living patients with COVID-19), in which risk factors were adjusted for age and sex. The level of significance used was P<.05. The statistical analysis was conducted using R version 3.6.3 (R Project) and Jamovi version 1.2.24.0.

We report the clinical characteristics and mortality rates of 23,844 patients diagnosed with COVID-19 in primary care, who constituted 6.84% of the population studied in the Central Catalan Region aged ≥16 years. This is one of only a few larger studies of COVID-19 patients conducted in primary care settings [25,27,28] and the only one to compare the characteristics and risk factors of patients diagnosed with COVID-19 with those of other patients without COVID-19 in the same health care area. Although there is no significant difference in age between patients with and without COVID-19, age is the main factor associated with mortality in patients with COVID-19, along with male sex, diabetes, dyslipidemia and heart failure. On the other hand, although obesity is more frequent among patients with COVID-19, it did not show an increase in the risk of mortality in this study. Moreover, ACEI or ARB treatment did not show an increase in the risk of mortality.

In our study, we report lower rates of comorbidity among patients diagnosed with COVID-19 compared to another study carried out in Catalonia in primary care, with rates of 33.9% for hypertension, 14.3% for diabetes, 5.9% for COPD, and 11.5% for cancer. In contrast, they reported lower rates of dyslipidemia (13.7%) and obesity (14.3%) [25]. In this study, they reported a mean age of 56.7 years, more than 7 years older than the mean age in our study; this aspect could explain the differences in the frequency of the mentioned comorbidities.

Numerous studies have shown that male sex and older age are associated with higher COVID-19–related mortality, a conclusion which our study strongly supports [14,29,30]. Although studies based on hospital data have found that the frequency of SARS-CoV-2 infection was higher in men [2,31-35], we found that women more frequently contracted COVID-19. Regarding mortality and age, we report that the death rate among patients aged ≥60 years with COVID-19 was 8.36 times higher than that among patients aged ≥60 years without COVID-19, with age being a strong predictor of mortality among people diagnosed with COVID-19, in particular those older than a certain age (≥60 years).

In our study, diabetes was more common in patients with COVID-19 and was associated with an increased risk of death. This finding is in accordance with a meta-analysis that analyzed the association between comorbid diabetes and disease severity or death [35,36]. As shown in our study, diabetes is one of the most prevalent comorbidities in patients with COVID-19, and there is a significant association with a greater severity of the illness or death in primary care; this association is in line with in-hospital mortality for patients with COVID-19, for which up to a 3-fold increased risk has been found [37]. Likewise, in our study, heart failure was more frequent among patients with COVID-19 and was associated with an increased risk of mortality. Other studies have reported similar results [30]. Although we found that patients with obesity were more common among those diagnosed with COVID-19, contrary to other studies, we did not find an increased risk of mortality in these patients [38]. In addition, surprisingly, hypertension, one of the most important factors reported as a mortality risk factor [31], and ischemic heart disease were neither more frequent nor associated with a higher mortality risk in our study.

As for smoking, we found that smokers were more frequently infected with COVID-19, although with no increased risk of mortality. Regarding risk factors such as cancer and cerebrovascular disease, patients diagnosed with COVID-19 were not at a higher risk of mortality. In addition, our results are in keeping with those showing that ACEIs and ARBs are not significantly associated with an increased risk of death among patients with COVID-19 [2,35,39] when adjusting for age and sex. Although the frequency of the different risk factors analyzed, except in the case of dyslipidemia, was higher among patients with COVID-19, this aspect should be considered as important to take into account in the management of these patients; we have seen that mortality is linked to some of these factors, such as diabetes, dyslipidemia, and heart failure. In addition, the health characteristics of the population followed up in primary care settings can be useful to have a better knowledge of

The study has several limitations. The diagnostics of COVID-19 registered in the Primary Care Services IT System during the early months of the pandemic were based on both clinical and polymerase chain reaction (PCR) testing. This is a pragmatic approach due to the fact that PCR testing was not fully available in primary care during the first few weeks of the pandemic. After the first months of pandemic the number of PCR tests performed increased, and for this reason the number of COVID-19 diagnoses may be underestimated during the period of our study. Although we included the majority of relevant risk factors and comorbidities associated with COVID-19 in the study, additional conditions should be considered, which may have an impact on the analysis and its interpretation. Although the coverage of patients followed up by primary care physicians is approximately 80% of the population in Catalonia, including this health care area studied, it is unlikely but possible that the remaining 20% of patients have other demographic or health characteristics that could affect the results. In addition, as can occur in other diseases, the registration and mortality of cases can be underestimated or can be affected by factors such as gender; this may modify some of the results presented.

At the beginning of the COVID-19 outbreak, attention was focused on the characteristics of patients diagnosed with COVID-19 who were admitted to hospital. However, after the period of our study, the attention shifted to community and primary care services, coinciding with the work overload in primary care settings and the possibility of more extensive SARS-CoV-2 testing. Our study is focused on patients in primary care with COVID-19, unlike most previous studies on COVID-19, which are based on hospital data. As we observed in our study, hypertension, one of the risk factors associated with COVID-19, was neither more frequent nor associated with higher mortality in patients with COVID-19 in primary care. We observed that women were more affected by COVID-19, unlike the majority of studies, which reported that men more frequently contracted the disease. In addition, our study did not find an associated risk between obesity and COVID-19, another risk factor associated with increased COVID-19–related mortality. Furthermore, treatment with ACEIs or ARBs was not associated with a higher mortality rate among patients infected with SARS-CoV-2. Age was the most important factor associated with mortality in patients with COVID-19.

Further studies focused on community and primary care are needed to provide new insights into SARS-CoV-2 infection and how to address outbreaks and improve health care strategies in pandemic situations.