ABSTRACT
ObjectiveMany healthcare staff work in high-risk settings for contracting and transmitting Severe Acute Respiratory Syndrome Coronavirus 2. Their risk of hospitalisation for coronavirus disease 2019 (COVID-19), and that of their households, is poorly understood. Design and settings and participantsDuring the peak period for COVID-19 infection in Scotland (1st March 2020 to 6th June 2020) we conducted a national record linkage study to compare the risk of COVID-19 hospitalisation among healthcare workers (age: 18-65 years), their households and other members of the general population. Main outcomeHospitalisation with COVID-19 ResultsThe cohort comprised 158,445 healthcare workers, the majority being patient facing (90,733 / 158,445; 57.3%), and 229,905 household members. Of all COVID-19 hospitalisations in the working age population (18-65-year-old), 17.2% (360 / 2,097) were in healthcare workers or their households. Adjusting for age, sex, ethnicity, socio-economic deprivation and comorbidity, the risk of COVID-19 hospitalisation in non-patient facing healthcare workers and their households was similar to the risk in the general population (hazards ratio [HR] 0.81; 95%CI 0.52-1.26 and 0.86; 95%CI 0.49-1.51 respectively). In models adjusting for the same covariates however, patient facing healthcare workers, compared to non-patient facing healthcare workers, were at higher risk (HR 3.30; 95%CI 2.13-5.13); so too were household members of patient facing healthcare workers (HR 1.79; 95%CI 1.10-2.91). On sub-dividing patient-facing healthcare workers into those who worked in front-door, intensive care and non-intensive care aerosol generating settings and other, those in front door roles were at higher risk (HR 2.09; 95%CI 1.49-2.94). For most patient facing healthcare workers and their households, the estimated absolute risk of COVID-19 hospitalisation was less than 0.5% but was 1% and above in older men with comorbidity. ConclusionsHealthcare workers and their households contribute a sixth of hospitalised COVID-19 cases. Whilst the absolute risk of hospitalisation was low overall, patient facing healthcare workers and their households had 3- and 2-fold increased risks of COVID-19 hospitalisation.
ABSTRACT
ObjectivesTo investigate the relation of severe COVID-19 to prior drug prescribing. DesignMatched case-control study (REACT-SCOT) based on record linkage to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. SettingScottish population. Main outcome measureSevere COVID-19, defined by entry to critical care or fatal outcome. ParticipantsAll 4272 cases of severe COVID-19 in Scotland since the start of the epidemic, with 36948 controls matched for age, sex and primary care practice. ResultsSevere COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in care homes, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.7, 13.2), and was not accounted for by treatment of conditions designated as conferring increased risk. Of 17 drug classes postulated at the start of the epidemic to be "medications compromising COVID", all were associated with increased risk of severe COVID-19. The largest effect was for antipsychotic agents: rate ratio 4.14 (3.39, 5.07). Other drug classes with large effects included proton pump inhibitors (rate rato 2.19 (1.70, 2.80) for >= 2 defined daily doses/day), opioids (3.62 (2.65, 4.94) for >= 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates, and were stronger with recent than with non-recent exposure. ConclusionsSevere COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression or dyskinesia, have anticholinergic effects or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Although the evidence for causality is not conclusive, these results support existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy as a potential means of reducing COVID-19 risk. RegistrationENCEPP number EUPAS35558 What is already known on this topicTwo previous studies have examined the relationship of severe COVID-19 to drugs for the cardiovascular system. This is the first systematic study of the relationship of severe COVID-19 to prior drug prescribing. What this study addsSevere COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression or dyskinesia, have anticholinergic effects or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. These results support earlier warnings that these drug classes that these drugs might increase susceptibility to COVID-19, and reinforce existing guidance on reducing overprescribing of these drug classes.
ABSTRACT
BackgroundThe objectives of this study were to identify risk factors for severe COVID-19 and to lay the basis for risk stratification based on demographic data and health records. Methods and FindingsThe design was a matched case-control study. Severe COVID-19 was defined as either a positive nucleic acid test for SARS-CoV-2 in the national database followed by entry to a critical care unit or death within 28 days, or a death certificate with COVID-19 as underlying cause. Up to ten controls per case matched for sex, age and primary care practice were selected from the population register. All diagnostic codes from the past five years of hospitalisation records and all drug codes from prescriptions dispensed during the past nine months were extracted. Rate ratios for severe COVID-19 were estimated by conditional logistic regression. There were 4272 severe cases. In a logistic regression using the age-sex distribution of the national population, the odds ratios for severe disease were 2.87 for a 10-year increase in age and 1.63 for male sex. In the case-control analysis, the strongest risk factor was residence in a care home, with rate ratio (95% CI) 21.4 (19.1, 23.9). Univariate rate ratios (95% CIs) for conditions listed by public health agencies as conferring high risk were 2.75 (1.96, 3.88) for Type 1 diabetes, 1.60 (1.48, 1.74) for Type 2 diabetes, 1.49 (1.37, 1.61) for ischemic heart disease, 2.23 (2.08, 2.39) for other heart disease, 1.96 (1.83, 2.10) for chronic lower respiratory tract disease, 4.06 (3.15, 5.23) for chronic kidney disease, 5.4 (4.9, 5.8) for neurological disease, 3.61 (2.60, 5.00) for chronic liver disease and 2.66 (1.86, 3.79) for immune deficiency or suppression. 78% of cases and 52% of controls had at least one listed condition (NA of cases and NA of controls under age 40). Severe disease was associated with encashment of at least one prescription in the past nine months and with at least one hospital admission in the past five years [rate ratios 3.10 (2.59, 3.71)] and 2.75 (2.53, 2.99) respectively] even after adjusting for the listed conditions. In those without listed conditions significant associations with severe disease were seen across many hospital diagnoses and drug categories. Age and sex provided 2.58 bits of information for discrimination. A model based on demographic variables, listed conditions, hospital diagnoses and prescriptions provided an additional 1.25 bits (C-statistic 0.825). A limitation of this study is that records from primary care were not available. ConclusionsAlong with older age and male sex, severe COVID-19 is strongly associated with past medical history across all age groups. Many comorbidities beyond the risk conditions designated by public health agencies contribute to this. A risk classifier that uses all the information available in health records, rather than only a limited set of conditions, will more accurately discriminate between low-risk and high-risk individuals who may require shielding until the epidemic is over. Author summaryMost people infected with the SARS-CoV-2 coronavirus do not become seriously ill. It is The risk of severe or fatal illness is higher in older than in younger people, and is higher in people with conditions such as asthma and diabetes than in people without these conditions. Using Scotlands capability for linking electronic health records, we report the first systematic study of the relation of severe or fatal COVID-19 to pre-existing health conditions and other risk factors. We show that the strongest risk factor, apart from age, is residence in a care home. The conditions associated with increased risk include not only those already designated by public health agencies - asthma, diabetes, heart disease, disabling neurological disease, kidney disease - but many other diagnoses, associated with frailty and poor health. This lays a basis for constructing risk scores based on electronic health records that can be used to advise people at high risk of severe disease to shield themselves when there cases in their neighbourhood.
