Risk of thrombotic events and other complications in anticoagulant users infected with SARS-CoV-2: an observational cohort study in primary health care in SIDIAP (Catalonia, Spain).

BACKGROUND: The risk of thromboembolic events and COVID-19 complications in anticoagulated patients once hospitalized has been widely analyzed. We aim to assess these outcomes in primary health care (PHC) patients chronically treated with oral anticoagulants (OAC) in comparison with non-treated. METHODS: Cohort study including adults with COVID-19 diagnosis in the PHC records in Catalonia, Spain; from March to June 2020. Patients were matched between exposed and non-exposed to OAC based on age and gender in a 1:2 design. Data source is the Information System for Research in Primary Care (SIDIAP). RESULTS: We included 311,542 individuals with COVID-19. After propensity score matching, we obtained a cohort of 20,360 people, 10,180 exposed and 10,180 non-exposed to OAC. Their mean age was 79.9 and 52.1% were women. Patients exposed to OAC had a higher frequency of comorbidities than non-exposed. Anticoagulated patients had a higher risk of hospital admission (IRR 1.16, 95% CI 1.03-1.29), and of stroke and pulmonary embolism than non-anticoagulated (IRR 1,80, 95% CI 1.06-3.06). The risk of pneumonia was not different between groups (IRR 1.04, 95% CI 0.84-1.30). We found a lower risk of death in patients exposed to OAC (IRR 0.60, 95% CI 0.55-0.65). CONCLUSIONS: OAC users in our study had more comorbidities and were older than non-users, well known risks for hospitalization being confirmed with our results. We also found in our study that OAC exposure was not associated to an increased risk in the mortality rate, and it was associated with higher risks of hospital admission and thromboembolic events, although we cannot assess the effect of the interventions applied during hospital admission on the outcomes studied, as our database is a PHC database. TRIAL REGISTRATION: EUPAS register: EUPAS37205 .

COVIDApp as an Innovative Strategy for the Management and Follow-Up of COVID-19 Cases in Long-Term Care Facilities in Catalonia: Implementation Study.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has caused an unprecedented worldwide public health crisis that requires new management approaches. COVIDApp is a mobile app that was adapted for the management of institutionalized individuals in long-term care facilities. OBJECTIVE: The aim of this paper is to report the implementation of this innovative tool for the management of long-term care facility residents as a high-risk population, specifically for early identification and self-isolation of suspected cases, remote monitoring of mild cases, and real-time monitoring of the progression of the infection. METHODS: COVIDApp was implemented in 196 care centers in collaboration with 64 primary care teams. The following parameters of COVID-19 were reported daily: signs/symptoms; diagnosis by reverse transcriptase-polymerase chain reaction; absence of symptoms for ≥14 days; total deaths; and number of health care workers isolated with suspected COVID-19. The number of at-risk centers was also described. RESULTS: Data were recorded from 10,347 institutionalized individuals and up to 4000 health care workers between April 1 and 30, 2020. A rapid increase in suspected cases was seen until day 6 but decreased during the last two weeks (from 1084 to 282 cases). The number of confirmed cases increased from 419 (day 6) to 1293 (day 22) and remained stable during the last week. Of the 10,347 institutionalized individuals, 5,090 (49,2%) remained asymptomatic for ≥14 days. A total of 854/10,347 deaths (8.3%) were reported; 383 of these deaths (44.8%) were suspected/confirmed cases. The number of isolated health care workers remained high over the 30 days, while the number of suspected cases decreased during the last 2 weeks. The number of high-risk long-term care facilities decreased from 19/196 (9.5%) to 3/196 (1.5%). CONCLUSIONS: COVIDApp can help clinicians rapidly detect and remotely monitor suspected and confirmed cases of COVID-19 among institutionalized individuals, thus limiting the risk of spreading the virus. The platform shows the progression of infection in real time and can aid in designing new monitoring strategies.