Abstract 15110: Objective Quantification of Disease Severity in Patients With Long Covid
Bibliographic record
Abstract
Introduction: Patients with Long Covid have been described to present with over 55 subjectively reported symptoms with the most prevalent being fatigue and cardiopulmonary (e.g. chest pain, dyspnea). Objective quantification of the magnitude of disease severity in Long Covid patients using standardized validated tools is needed. Methods: This is a retrospective evaluation of patients referred to Flow Therapy for the management of Long Covid symptoms from Jan 2021 to Jan 2022. Patients were included if having complete data for 6 validated tools: PROMIS Fatigue score (range 0-20), Seattle Angina Questionnaire (SAQ) Summary Score (range 0-100), Duke Activity Status Index (DASI, range 0-58.2), 6-minute walk test (6MWT, range 0-unlimited), Rose Dyspnea Scale (RDS, range 0-4) and CCS angina class (CCS, range 1-4). The unpaired student’s t-test or the Fisher’s exact test were utilized for all analyses. Results: A total of 100 patients were included for analyses (age 54.2±14.5years, 60% female, 41% with CAD). The baseline PROMIS Fatigue, SAQ, DASI, and 6MWT were 15.8±3.6, 58.6±24.5, 12.9±12.7, and 1199.6±428.3 feet respectively. Moderate to severe dyspnea (RDS) or angina (CCS) was reported in 81% and 61% of patients respectively. When limiting to those without CAD (n=59), the PROMIS Fatigue was 15.7±3.4 compared to 16.0±3.6 in those with CAD (p=0.719). When limiting to those under the age of 41 (n=19), the PROMIS Fatigue was 15.9±4.0 compared to 15.8±3.5 in those 41 years or older (p=0.9466). No correlation was evident between age and PROMIS Fatigue score (r=0.107). SAQ and RDS were not different between the CAD and non-CAD patients (all p-values>0.111). There was no difference across all endpoints when comparing those under 41 versus 41 years or older (all p-values>0.087). Conclusion: Our data indicate a moderately high degree of disease severity using 6 validated markers assessing Long Covid symptoms. The validity of scores in patients with Long COVID applies to both patients with concurrent epicardial disease and patients without known epicardial disease. The severity of fatigue in Long Covid patients under 41 is similar to those 41 years or older. Our data provide a paradigm to more objectively diagnose Long Covid.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".