Xiaowu Sun

Background: To characterize Coronavirus disease 2019 (COVID-19) symptom severity, and recovery from pre-infection through one month, overall and by risk groups. Methods: Symptomatic adults aged ≥18 years with test-confirmed COVID-19 were enrolled from ambulatory care clinics within a national U.S. retail pharmacy network between 10/24/2024 and 08/29/2025 ( NCT05160636 ). Adjusted mixed models for repeated measures estimated least-squares mean changes (LSE) and standard errors (SE) from pre-infection and on Days 1-7, 10, 14, and Week 4 from enrollment in composite symptom scores (sum of severity ratings (0-3) across 14 symptoms), counts of mild-to-severe, moderate-to-severe, and severe symptoms, overall and by age and clinical risk status. Effect sizes (ES) were defined as small (0.2-<0.5), medium (≥0.5), and large (≥0.8). Results: The analysis included 608 adults. On Day 1, symptom severity rose sharply from pre-infection for the composite symptom score (LSE 14.2 [SE 0.3]; ES 2.22), mild-to-severe (7.6 [0.1]; 2.72), moderate-to-severe (5.0 [0.2]; 1.77); and severe (1.8 [0.1]; 0.92) (all p<0.001). By Week 4, composite score (0.7 [0.2]; 0.26), mild-to-severe (0.5 [0.1]; 0.23); moderate-to-severe symptoms (0.1 [0.1]; 0.17) and severe symptoms (0.2 [0.1]; 0.5) remained slightly above baseline (all p≤0.025). Elevated severe symptom durations varied: high-risk adults (through Day 3), adults <50 years (through Day 7), and adults ≥50 years (through Day 7). Conclusions: COVID-19 was associated with notable acute symptoms in outpatients, followed by gradual improvement over time, although symptoms still persisted at four weeks. Improvement in severe symptoms varied by individual risk profile, reinforcing the importance risk-based follow-up and ongoing monitoring.

Background: Numerous grouping and scoring methodologies have been proposed to assess long COVID symptomatology. One approach is to use symptom count as a simple, quantifiable measure of long COVID symptom burden. Methods: This was a secondary analysis of a nationwide patient-reported outcomes (PRO) study that recruited symptomatic adults testing positive for SARS-CoV-2 at a Retail Pharmacy in the spring of 2023. EQ-5D-5L ^TM , work productivity and impairment (WPAI), the Patient-Reported Outcomes Measurement Information System (PROMIS ^® ) fatigue, and a long COVID symptom questionnaire were administered at Week 4, Month 3, and Month 6 after testing. Pre-infection EQ-5D-5L, WPAI, PROMIS fatigue were collected via recall. Cronbach’s α assessed internal consistency of symptoms. Scree plots determined number of significant factors (symptoms) to retain for analysis. Spearman correlation coefficients were calculated between number of symptoms and EQ-5D-5L, WPAI, PROMIS fatigue scores and their changes from pre-COVID baseline. Categorization of long COVID burden using number of symptoms was proposed based on scores via equipercentile linking. Results: Of 505 patients, mean age was 46.3 years, 70.7% were female. Cronbach’s α was 0.865, denoting good internal consistency of the symptom survey instrument. The scree plot supported use of one factor for the composite 30-symptom list. Number of symptoms correlated strongly with EuroQol Utility Index (r = −0.53), presenteeism (r = 0.51), activity impairment (r = 0.51) and fatigue (r = 0.56). Statistically significant differences in mean number of symptoms were found between patients with versus those without problems in any of the 5 domains of the EQ-5-dimensional descriptive system. Based on linked PRO scores, subjects could be classified into low (≤2), medium (3–9), and high (≥10) symptom burden. Conclusions: Number of long COVID symptoms correlated with validated PRO measures and identified three symptom-based categories of long COVID burden. Number of symptoms is a valid and internally consistent measure to assess long COVID burden in outpatient settings.

Background: Long COVID remains a significant public health concern. This study investigated risk factors for long COVID in outpatient settings. Methods: A US-based prospective survey study (clinicaltrials.gov NCT05160636) was conducted in 2022 and replicated in 2023. Symptomatic adults testing positive for SARS-CoV-2 at CVS Pharmacies were recruited. CDC-based long COVID symptoms were collected at Week 4, Month 3, and Month 6 following SARS-CoV-2 testing. Logistic regression was used to develop a predictive model for long COVID using data from the 2022 cohort. The model was validated with data from the 2023 cohort. Model performance was evaluated with c-statistics. Results: Patients characteristics were generally similar between the 2022 (N = 328) and 2023 (N = 505) cohorts. The prevalence of long COVID defined as ≥3 symptoms at Month 6 was 35.0% and 18.2%, respectively. The risk factors associated with long COVID were older age, female sex, lack of up-to-date vaccination, number of acute symptoms on the day of SARS-CoV-2 testing, increase in symptoms at Week 1, underlying comorbidities and asthma/chronic lung disease. The c-statistic was 0.79, denoting good predictive power. Conclusions: A predictive model for long COVID was developed for an outpatient setting. This research could help differentiate at-risk groups and target interventions.

Symptoms post-SARS-CoV-2 infection may persist for months and cause significant impairment and impact to quality of life. Acute symptoms of SARS-CoV-2 infection are well studied, yet data on clusters of symptoms over time, or post-acute sequelae of SARS-CoV-2 infection (PASC), are limited. We aim to characterize PASC phenotypes by identifying symptom clusters over a six-month period following infection in individuals vaccinated (boosted and not) and those unvaccinated. Subjects with ≥1 self-reported symptom and positive RT-PCR for SARS-CoV-2 at CVS Health US test sites were recruited between January and April 2022. Patient-reported outcomes symptoms, health-related quality of life (HRQoL), work productivity and activity impairment (WPAI) were captured at 1 month, 3 months, and 6 months post-acute infection. Phenotypes of PASC were determined based on subject matter knowledge and balanced consideration of statistical criteria (lower AIC, lower BIC, and adequate entropy) and interpretability. Generalized estimation equation approach was used to investigate relationship between QoL, WPAI and number of symptoms and identified phenotypes, and relationship between phenotypes and vaccination status as well. LCA identified three phenotypes that are primarily differentiated by number of symptoms. These three phenotypes remained consistent across time periods. Subjects with more symptoms were associated with lower HRQoL, and worse WPAI scores. Vaccinated individuals were more likely to be in the low symptom burden latent classes at all time points compared to unvaccinated individuals.

Background: Long COVID has become a central public health concern. This study characterized the effectiveness of BNT162b2 BA.4/5 bivalent COVID-19 vaccine (bivalent) against long COVID symptoms. Methods: Symptomatic US adult outpatients testing positive for SARS-CoV-2 were recruited between 2 March and 18 May 2023. Symptoms were assessed longitudinally using a CDC-based symptom questionnaire at Week 4, Month 3, and Month 6 following infection. The odds ratio (OR) of long COVID between vaccination groups was assessed by using mixed-effects logistic models, adjusting for multiple covariates. Results: At Week 4, among 505 participants, 260 (51%) were vaccinated with bivalent and 245 (49%) were unvaccinated. Mean age was 46.3 years, 70.7% were female, 25.1% had ≥1 comorbidity, 43.0% prior infection, 23.0% reported Nirmatrelvir/Ritonavir use. At Month 6, the bivalent cohort had 41% lower risk of long COVID with ≥3 symptoms (OR: 0.59, 95% CI, 0.36–0.96, p = 0.034) and 37% lower risk of ≥2 symptoms (OR: 0.63, 95% CI, 0.41–0.96, p = 0.030). The bivalent cohort reported fewer and less durable symptoms throughout the six-month follow-up, driven by neurologic and general symptoms, especially fatigue. Conclusions: Compared with unvaccinated participants, participants vaccinated with the bivalent were associated with approximately 40% lower risk of long COVID and less symptom burden over the six-month study duration.

BACKGROUND: The mSToPS study (mHealth Screening to Prevent Strokes) reported screening older Americans at risk for atrial fibrillation (AF) and stroke using 2-week patch monitors was associated with increased rates of AF diagnosis and anticoagulant prescription within 1 year and improved clinical outcomes at 3 years relative to matched controls. Cost-effectiveness of this AF screening approach has not been explored. METHODS: We conducted a US-based health economic analysis of AF screening using patient-level data from mSToPS. Clinical outcomes, resource use, and costs were obtained through 3 years using claims data. Individual costs, survival, and quality-adjusted life years (QALYs) were projected over a lifetime horizon using regression modeling, US life tables, and external data where needed. Adjustment between groups was performed using propensity score bin bootstrapping. RESULTS: Screening participants (mean age, 74 years, 41% female, median CHA ₂ DS ₂ -VASC score 3) wore on average 1.7 two-week monitors at a mean cost of $614/person. Over 3 years, outpatient visits were more frequent for monitored than unmonitored individuals (difference 190 per 100 patient-years [95% CI, 82–298]), but emergency department visits (−8.3 [95% CI, −12.6 to −4.1]) and hospitalizations (−15.2 [CI, −22 to −8.6]) were less frequent. Total adjusted 3-year costs were slightly higher (mean difference, $1551 [95% CI, −$1047 to $4038]) in the monitoring group. In patient-level projections, the monitoring group had slightly greater quality-adjusted survival (8.81 versus 8.71 QALYs, difference, 0.09 [95% CI, −0.05 to 0.24]) and slightly higher lifetime costs, resulting in an incremental cost-effectiveness ratio of $36 100/QALY gained. With bootstrap resampling, the incremental cost-effectiveness ratio for monitoring was <$50 000/QALY in 64% of study replicates, and <$150 000/QALY in 91%. CONCLUSIONS: Using lifetime projections derived from the mSToPS study, we found that AF screening using 2-week patch monitors in older Americans was associated with high economic value. Confirmation of these uncertain findings in a randomized trial is warranted. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02506244.

Evidence on the impact of COVID-19 vaccination on symptoms, Health-Related Quality of Life (HRQoL) and Work Productivity and Activity Impairment (WPAI) is scarce. We analyzed associations between bivalent BA.4/5 BNT162b2 (BNT162b2) and these patient-reported outcomes (PROs). Symptomatic US adults testing positive for SARS-CoV-2 were recruited between 2 March and 18 May 2023 (CT.gov NCT05160636). PROs were assessed using four questionnaires measuring symptoms, HRQoL and WPAI (a CDC-based symptom survey, PROMIS Fatigue, EQ-5D-5L, WPAI-GH), from pre-COVID to Week 4 following infection. Multivariable analysis using mixed models for repeated measures was conducted, adjusting for several covariates. The study included 643 participants: 316 vaccinated with BNT162b2 and 327 unvaccinated/not up-to-date. Mean (SD) age was 46.5 years (15.9), 71.2% were female, 44.2% reported prior infection, 25.7% had ≥1 comorbidity. The BNT162b2 cohort reported fewer acute symptoms through Week 4, especially systemic and respiratory symptoms. All PROs were adversely affected, especially at Week 1; however, at that time point, the BNT162b2 cohort reported better work performance, driven by less absenteeism, and fewer work hours lost. No significant differences were observed for HRQoL COVID-19 negatively impacted patient outcomes. Compared with unvaccinated/not up-to-date participants, those vaccinated with bivalent BA.4/5 BNT162b2 reported fewer and less persistent symptoms and improved work performance.

Symptoms post-SARS-CoV-2 infection may persist for months and cause significant impairment and impact to quality of life. Acute symptoms of SARS-CoV-2 infection are well studied, yet data on clusters of symptoms over time, or postacute sequelae of SARS-CoV-2 infection (PASC), are limited. We aim to characterize PASC phenotypes by identifying symptom clusters over a six-month period following infection in individuals vaccinated (boosted and not) and those unvaccinated. Subjects with ≥1 self-reported symptom and positive RT-PCR for SARS-CoV-2 at CVS Health US test sites were recruited between January and April 2022. Patient-reported outcomes symptoms, heath-related quality of life (QoL), work productivity and activity impairment (WPAI) were captured at 1 month, 3 months, and 6 months post-acute infection. Logistic regression and latent class analysis (LCA) were performed on 20 symptoms using baseline socio-demographic, clinical characteristics, and vaccination status as well as EQ-5and WPAI results as covariables. Subjects with more symptoms were associated with lower health-related quality of life, and worse WPAI scores. LCA identified three phenotypes that are primarily differentiated by number of symptoms. These three phenotypes remained consistent across time periods. Vaccinated individuals were more likely to be in the low symptom burden latent classes at all time points compared to unvaccinated individuals.