Symptom Clusters in Adult Patients with Post-Acute COVID-19
Bibliographic record
Abstract
Background: As more reports emerge that many COVID-19 survivors suffer protracted and lingering symptoms, how to define and better characterize these patients with post-acute COVID-19 is a research challenge. To understand the overall symptom burden in patients with post-acute COVID-19, we explored whether identifiable symptom clusters exist in a cohort of patients with post-acute COVID-19 and then examined whether these clusters are associated with quality of life impairments. Methods: In a prospective observational study of COVID-19 patients at a Covid-19 Recovery (CORE) clinic between June and December 2020 (eligible patients had either a positive COVID-19 PCR or IgG antibody test), we administered a modified revised Edmonton Symptom Assessment survey which assessed whether patients had 13 symptoms over the week prior to presentation to the clinic on a scale of 0 (no symptoms) to 10 (most severe symptoms). We performed exploratory factor analysis to search for clustering of symptoms into factors and examined the relationship between these clusters and quality of life measures. Results: Across 127 adult patients treated at CORE (mean (standard deviation (SD) age 51.8 (14.0);73.2% were women. We found four symptom factors: emotional factor (including depression and anxiety), activity limiting factor (fatigue, sleepiness and shortness of breath), gastrointestinal symptom factor (nausea, appetite and taste changes) and pain factor (pain, neuropathy). The Cronbach's α for the individual factors ranged from 0.64-0.84. The emotional factor was associated with an increased odds of reporting worse emotional (Odds Ratio (95% Confidence Interval (95% CI) 1.9 (1.2-3.3) and worse cognitive health status (OR 4.9 (2.5-9.5);the activity limiting factor was associated with increase odds of worse physical health status (OR 4.5 (2.1-9.7);the gastrointestinal symptom factor was associated with increase odds of worse cognitive health status (OR 2.1 (1.1-4.2). Conclusions: We found four symptom factors in adult patients with post-acute COVID-19. There was strong internal correlation between the factors and the factors were associated with quality of life measures. Routine assessment of post-acute COVID-19 patient's emotional, gastrointestinal, pain and activity limiting symptoms is important as they may be associated with impaired health related quality of life.
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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 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".