Demographic and Clinical Factors Associated With Functional Changes in Long-Covid
Bibliographic record
Abstract
ABSTRACT: Many people experience symptoms months or years after COVID-19 infection. The impact of these symptoms on daily functioning and factors associated with functional decline are not well understood. This study aimed to describe functional changes among persons with long-Covid and explore associated sociodemographic and clinical factors. A total of 2764 adults who tested positive for COVID-19 were recruited at ≥12 wks after diagnosis. Participants responded to an electronic survey ( Newcastle Post-COVID Syndrome Questionnaire (symptoms); COVID-19 Yorkshire Rehabilitation Screen (activities; perceived global health, mobility, personal care, daily activities). A total of 37.8% were classified as having long-Covid based on the positive response to " Are you still troubled by symptoms?" The majority reported a decline in global health, mobility, and participation in daily activities. Common changes in function included fatigue, breathlessness upon climbing stairs and when dressing, decline in participation in usual activities, anxiety, pain/discomfort, and reduced concentration. Having COVID-19 ≥ 1 yr prior was associated with change in perceived global health (odds ratio = 1.5). Being infected ≥12 mos prior (odds ratio = 1.5), hospitalized for COVID-19 (odds ratio = 2.2-2.4), ≥1 chronic comorbid conditions (odds ratio = 1.6), and obesity (odds ratio = 1.6) were associated with functional decline. Many of those infected with COVID-19 experience long-lasting symptoms impacting daily functioning. Multidisciplinary medical and rehabilitation services are needed to help improve recovery and maximize functioning.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".