Psoriatic Arthritis and COVID-19: Patient Perspectives in a Large Psoriatic Arthritis Cohort
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence of coronavirus disease 2019 (COVID-19) infection among patients with psoriatic arthritis (PsA), understand patients' perspectives regarding their risk of COVID-19 infection, and evaluate the standard of virtual care offered during the early phases of the pandemic. METHODS: An online survey was conducted between June 2021 and September 2021 in patients with PsA who had consented to email contact. The survey was completed by 152/193 (79%) patients who had consented to the study. RESULTS: There were 86 (56.6%) men and 66 (43.4%) women with a mean age of 58 years and mean disease duration of 19 years. During the pandemic, the mean patient-reported symptom severity was 4.10, 3.24, and 3.72 for joint, skin, and overall symptom severity, respectively. Seventy-four percent of respondents would accept the effect of their PsA over the past month for the next few months. Of 79 patients who were tested for severe acute respiratory syndrome coronavirus 2, 4 tested positive. All 4 were admitted to hospital; 2 required oxygen. One hundred fifty-one patients (99%) had received at least 1 vaccine dose. Fifty-nine (38.8%) participants believed their PsA medications increased their COVID-19 infection risk. Of the 130 patients who had a telemedicine assessment, 83.1% were happy with their virtual consultations. Most were happy to continue with virtual consultations until the pandemic resolved. The average satisfaction level regarding pandemic care was 7.87 on a sliding 10-point scale. CONCLUSION: COVID-19 prevalence was low among our patients. Patients were satisfied with their care during the pandemic. Most patients would happily continue with virtual care for the duration of the pandemic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".