In a recent article published within the journal Sleep, researchers generated a harmonized evaluation investigating the impact of preexisting obstructive sleep apnea (OSA) as a risk factor for post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [PASC] in children and adults. They used electronic health record (EHR) data from three research networks throughout the REsearching COVID to Enhance Recovery (RECOVER) initiative funded by the National Institutes of Health (NIH).

Study: Risk of post-acute sequelae of SARS-CoV-2 infection related to pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based evaluation from the RECOVER initiative. Image Credit: p.in poor health.i / Shutterstock

Background

Previous studies have identified a positive relationship between OSA and acute coronavirus disease 2019 (COVID-19) outcomes. OSA, characterised by repeated obstruction of airways during sleep, is very prevalent in the USA (US), affecting nearly 20% of adults; thus, this warrants further research as a possible risk factor for PASC. Per recent estimates, PASC affects 7% to 54% of COVID-19 patients even after complete recovery.

PASC risk varies by gender, age, and specific preexisting health conditions like hypertension and diabetes, raising the likelihood that OSA may very well be a risk factor for PASC. Nevertheless, studies have barely investigated and elucidated the impact of preexisting conditions like OSA on the chance of developing PASC. As well as, studies should look beyond acute outcomes amongst COVID-19 survivors having preexisting comorbid OSA.

In regards to the study

The current study is the primary real-world data evaluation conducted between March 1, 2018, and March 1, 2020, across multiple data sources, using different Long COVID definitions and employing various approaches to discover COVID-19 patients at the next risk of developing PASC resulting from preexisting OSA. Specifically, the researchers considered evidence of OSA diagnosed inside two years before the study duration.

The National COVID Cohort Collaborative (N3C) and the Patient-Centered Clinical Research Network (PCORnet) encompassed adult populations aged ≥18 years; the latter’s PEDSnet arm also covered the pediatric population. N3C analyzed data of >15 million patients from 77 sites, while PCORnet drew analyses from 11M patients from 19 sites. Likewise, PEDSnet chosen 8.5M patients from a network of eight pediatric health systems.

A clinical science core (CSC) at Recent York University Langone Health coordinated all three RECOVER research networks, albeit each network created distinct diagnosis-based computable phenotype (CP) definitions to seek out probable PASC patients by itself. Notably, algorithms designed to discover patients with an OSA diagnosis from EHRs have excellent validity. Also, N3C and PCORnet limited their analyses to adults aged ≥21 years, while PEDSnet to children below 21 years because it facilitated delineating results for adults and kids.

The team trained all CPs on patients who visited a Long COVID clinic and definitions rooted in rules involving labs, clinical diagnoses, and medications. The eligibility criteria for inclusion was that a patient showed proof of a COVID-19 infection between March 1, 2020, and February 28, 2022, normally a positive SARS-CoV-2 reverse transcription-polymerase chain response (RT-PCR) or antigen test.

Further, the researchers used the International Statistical Classification of Diseases and Related Health Problems – Clinical Modification (ICD-10-CM) and ICD-9-CM diagnostic codes or the Systematized Nomenclature of Medicine – Clinical Terms (SNOMED-CT) codes to discover patients with preexisting OSA.

Lastly, the researchers used logistic regression models to estimate unadjusted and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for the association between a preexisting OSA diagnosis and the likelihood of developing PASC.

Study findings

Whatever the approach used to discover probable PASC patients, the present evaluation showed preexisting OSA increased risk of PASC-like conditions amongst adult patients. Even after adjusting for other comorbidities, this positive association remained significant though it attenuated barely. Sensitivity evaluation adjusting for preexisting hypertension and diabetes instead of comorbidity rating didn’t alter the findings for adults.

Conversely, the apparent positive associations between preexisting OSA and probable PASC amongst children became insignificant after adjusting for comorbidities. Moreover, sensitivity analyses adjusting for asthma,  hypertension, and diabetes for youngsters altered the observed associations and fetched different effect estimates.

Obesity was most prevalent in PCORnet and accounted for some visible differences in OSA-related PASC outcomes across all three networks. Partly, obesity and similar comorbidities confounded and diminished the strength of association with PASC.

Conclusions

PASC will not be a cohesive condition and has no accepted case definition yet, and its patients have highly heterogeneous symptoms. So, the study authors used a variety of PASC definitions to beat these challenges while examining associations between OSA and PASC risk amongst adults and kids. Finally, they found positive associations between OSA and PASC risk consistently, no matter the info source, approach, and PASC definition applied.

Nevertheless, the authors didn’t explore symptoms most prevalent in OSA patients at high risk of probable PASC. Thus, future research should examine the association of OSA and other preexisting conditions with specific PASC variations and the trajectory of impacted COVID-19 patients.