Associations Between Inflammatory and Catecholamine Markers and Clinical Outcomes in People with Post-Acute SARS-CoV-2 Infection
Bibliographic record
Abstract
Lynn H Gerber,1,2,* Micahel Estep,1,* Leyla De Avila,1,* Jillian K Price,1,* Ali A Weinstein,3,* Maria Stepanova,1,2,* Aybike Birerdinc,4,* Zobair Younossi1,2,* 1Betty and Guy Beatty Center for Integrated Research, Inova Health System, Falls Church, VA, USA; 2Department of Medicine, Inova Health System, Falls Church, VA, USA; 3Department of Global and Community Health, George Mason University, Fairfax, VA, USA; 4School of Systems Biology, College of Science, George Mason University, Fairfax, VA, USA*These authors contributed equally to this workCorrespondence: Lynn H Gerber, Betty and Guy Beatty Center for Integrated Research, Inova Health System, 3300 Gallows Road, Falls Church, VA, 22042, USA, Email ngerber1@gmu.eduPurpose: The diagnosis of post-acute SARS-CoV-2 infection (PASC) is broad, referring to new or persistent health problems >four weeks after being infected with SARSCoV-2. The aim of this study was to determine whether cytokines, chemokines or catecholamine levels could specify the clinical condition.Patients and Methods: Seventy-nine participants participated in person to study PASC. They were average 51 years (mean), 52% female, 62% Caucasian, 11% African American and 37% Hispanic with a mean BMI of 30.5. Most prevalent symptoms were fatigue, memory loss and shortness of breath. We extracted co-morbid conditions, length of hospital stay and course and laboratory values; medications, history of regular exercise (total of 150 minutes/week), measures of cognition (PCCOG), including Color Word Interference Test (CWIT), Coding, Arithmetic, Matrix Reasoning), clinical assessment of health behavior change, and several patient reported outcomes (PROs) (Edmonton Symptom Assessment System (ESAS), health-related quality of life instrument (EQ5D), anxiety and depression (GAD7, PHQ9) and fatigue (Functional Assessment of Chronic Illness Therapy – Fatigue (FACIT-F).Results: These data suggest that people with PASC are more likely to report lower levels of physical well-being, emotional well-being and higher fatigue levels than the non-PASC population. Epinephrine levels correlate statistically significantly with PROs (p< 0.05), for overall FACIT-F, as well as the physical and functional subscales. The fatigue severity self-report, PHQ9 and number of symptoms were also significantly correlated. Interleukin-1 beta (IL1b) was inversely correlated with the Physical Well Being (PWB) and Emotional Well Being (EWB) FACIT-F subscales, the GAD7 and the PCCOG scale (p< 0.05).Conclusion: Participants in this observational study of PASC report lower levels of emotional, physical well-being, more fatigue, anxiety and depression than are reported in population norms. Epinephrine and IL1b correlate with these findings and may offer a biological measurement, providing clinically useful information for tracking persistence or recovery. These findings may encourage further study to develop newer treatment approaches.Keywords: post acute SARS-CoV-2, PASC, patient reported outcomes, cytokines, catecholamines, chemokines
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".