ABSTRACT
BACKGROUND: Post-viral respiratory symptoms are common among patients with asthma. Respiratory symptoms after acute COVID-19 are widely reported in the general population, but large-scale studies identifying symptom risk for patients with asthma are lacking. OBJECTIVE: To identify and compare risk for post-acute COVID-19 respiratory symptoms in patients with and without asthma. METHODS: This retrospective, observational cohort study included COVID-19-positive patients between March 4, 2020, and January 20, 2021, with up to 180 days of health care follow-up in a health care system in the Northeastern United States. Respiratory symptoms recorded in clinical notes from days 28 to 180 after COVID-19 diagnosis were extracted using natural language processing. Cohorts were stratified by hospitalization status during the acute COVID-19 period. Univariable and multivariable analyses were used to compare symptoms among patients with and without asthma adjusting for demographic and clinical confounders. RESULTS: Among 31,084 eligible patients with COVID-19, 2863 (9.2%) had hospitalization during the acute COVID-19 period; 4049 (13.0%) had a history of asthma, accounting for 13.8% of hospitalized and 12.9% of nonhospitalized patients. In the post-acute COVID-19 period, patients with asthma had significantly higher risk of shortness of breath, cough, bronchospasm, and wheezing than patients without an asthma history. Incident respiratory symptoms of bronchospasm and wheezing were also higher in patients with asthma. Patients with asthma who had not been hospitalized during acute COVID-19 had additionally higher risk of cough, abnormal breathing, sputum changes, and a wider range of incident respiratory symptoms. CONCLUSION: Patients with asthma may have an under-recognized burden of respiratory symptoms after COVID-19 warranting increased awareness and monitoring in this population.
Subject(s)
Asthma , Bronchial Spasm , COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , COVID-19 Testing , Retrospective Studies , Electronic Health Records , Cough , Respiratory Sounds , Asthma/epidemiology , HospitalizationABSTRACT
OBJECTIVE: To develop a comprehensive post-acute sequelae of COVID-19 (PASC) symptom lexicon (PASCLex) from clinical notes to support PASC symptom identification and research. METHODS: We identified 26,117 COVID-19 positive patients from the Mass General Brigham's electronic health records (EHR) and extracted 328,879 clinical notes from their post-acute infection period (day 51-110 from first positive COVID-19 test). PASCLex incorporated Unified Medical Language System® (UMLS) Metathesaurus concepts and synonyms based on selected semantic types. The MTERMS natural language processing (NLP) tool was used to automatically extract symptoms from a development dataset. The lexicon was iteratively revised with manual chart review, keyword search, concept consolidation, and evaluation of NLP output. We assessed the comprehensiveness of PASCLex and the NLP performance using a validation dataset and reported the symptom prevalence across the entire corpus. RESULTS: PASCLex included 355 symptoms consolidated from 1520 UMLS concepts of 16,466 synonyms. NLP achieved an averaged precision of 0.94 and an estimated recall of 0.84. Symptoms with the highest frequency included pain (43.1%), anxiety (25.8%), depression (24.0%), fatigue (23.4%), joint pain (21.0%), shortness of breath (20.8%), headache (20.0%), nausea and/or vomiting (19.9%), myalgia (19.0%), and gastroesophageal reflux (18.6%). DISCUSSION AND CONCLUSION: PASC symptoms are diverse. A comprehensive lexicon of PASC symptoms can be derived using an ontology-driven, EHR-guided and NLP-assisted approach. By using unstructured data, this approach may improve identification and analysis of patient symptoms in the EHR, and inform prospective study design, preventative care strategies, and therapeutic interventions for patient care.