In a recent study published in BMC Medicine, researchers determined the nature and magnitude of changes in healthcare utilization attributable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections.
Study: Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK. Image Credit: DCStudio/Shutterstock.com
Background
Post-coronavirus disease 2019 (COVID-19) illnesses and infections remain a significant concern for healthcare systems, as the morbidities and use of healthcare resources by SARS-CoV-2-positive individuals remain unclear.
A minority of individuals develop persistent symptoms, resulting in various post-COVID-19 conditions. Care provision to COVID-19 convalescents is important.
Studies have reported that individuals who are not hospitalized might experience severe longer-term COVID-19 consequences, including respiratory distress and chronic fatigue. The burden of unseen symptoms in the population is unclear, and health systems worldwide are under extreme pressure due to the pandemic.
Limited data on the scale of demand and services sought remains essential to inform health systems about the potential impact of long COVID on healthcare systems.
About the study
The present study evaluated healthcare facilities’ usage after one to four and five to 24 weeks of SARS-CoV-2 infections.
The electronic medical records (EMRs) of 249,390 Welsh individuals obtained from the Secure Anonymized Information Linkage (SAIL) database were analyzed between February 28, 2020, and August 26, 2021. Compared to propensity score-matched (PSM) controls, the study investigated healthcare contact one to four and five to 24.0 weeks after a SARS-CoV-2 infection diagnosis.
The participants had SARS-CoV-2-positive reverse transcription-polymerase chain reaction (RT-PCR) reports. After eligibility criteria were met, 98,600 SARS-CoV-2-positive participants were PS-matched to RT-PCR-negative individuals (the test-negative group) and those who had never undergone RT-PCR testing (the never-tested group).
The tests were conducted in community as well as hospital settings. The team performed a survival analysis for the first clinical (primary and secondary) outcomes.
The primary study outcomes included post-COVID-19 fatigue and illness as long COVID indicators. The secondary study outcomes included pulmonary disorders, mental health disorders, embolism, hospital attendance, and fit notes.
Cox regression modeling was performed to calculate the hazard ratios (HRs) and quantify the instantaneous risks for COVID-19 patients. A life table analysis was performed to quantify the relative and absolute risks (AR).
Variables included were participant age, sex, region, testing location, local area deprivation, comorbidities, number of individuals in each household, and previous COVID-19 test reports. The following datasets were linked: the Welsh Demographic Service, primary care general practitioner (GP) datasets, the Patient Episode Database, the Office for National Statistics (ONS) Mortality dataset, and the laboratory management information system (LMIS) reports.
The participants were followed for six months after the index date (i.e., the initial SARS-CoV-2-positive or negative report date or allocated pseudo dates for test-positive, test-negative, and never-tested individuals, respectively).
Results and discussion
Among the study participants, 5,431, 17,584, and 75,585 individuals tested in hospitals, communities, and unknown locations, respectively. 23,015 and 69,566 individuals were identified as SARS-CoV-2-infected and uninfected, respectively.
There was an increased likelihood of fatigue and embolism among test-positive participants within the initial 28 days, with HR values of 1.8 and 1.5, respectively, and a lower likelihood of depression and anxiety (HR, 0.8) among infected individuals.
The increased risk of embolism and fatigue persisted among the SARS-CoV-2-positive individuals even after four weeks of infection, with HR values of 1.5 and 1.5, respectively. In addition, the test-positive group was at a heightened post-COVID-19 illness risk (HR, 4.6).
In spite of the statistically significant relationship between showing positivity for SARS-CoV-2 and various other conditions, only a minor proportion of individuals were affected, as indicated by the life table analysis findings.
The mortality risk was higher for SARS-CoV-2-positive individuals in the initial four weeks, but the team did not observe any excess mortality risk after four weeks.
The finding that individuals surviving SARS-CoV-2 infections had higher cardiovascular disease (CVD) risks was consistent with earlier research. However, the observation of no overall rise in mental health diagnoses contradicts previous findings.
The disparities in the results might be attributed to changes in the statistical variables used for PSM. Alternatively, mental health issues might have been associated with SARS-CoV-2 infections but not reported by the patients to healthcare facilities, or they might have been documented as post-COVID-19 conditions or long COVID symptoms such as fatigue.
SARS-CoV-2-negative individuals showed an increased likelihood of reporting altered mental health, which might have been linked to depression.
Conclusions
The study findings showed that SARS-CoV-2 infections in community settings increase the risks of post-acute COVID-19 illness, embolism, fatigue, and pulmonary conditions. Despite these increased risks, the COVID-19 burden on healthcare facilities is low, indicating that a small proportion of individuals develop severe outcomes or do not seek healthcare.
The findings must be interpreted cautiously, as only the first occurrence of the disease was investigated, and diagnoses like brain or memory fog were not identified. Healthcare professionals should evaluate post-COVID-19 mental illness and provide appropriate care.
Further research is required to determine the COVID-19 burden on patients who do not seek healthcare.
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