COVID-19 IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: A SINGLE-CENTER EXPERIENCE
Bibliographic record
Abstract
PV139 / #320 Poster Topic: AS17 - Miscellaneous Background/Purpose The COVID-19 pandemic has posed significant challenges to peoples’ life worldwide. Patients with systemic lupus erythematosus (SLE) are particularly susceptible to infections. Emerging evidence suggests that the prevalence of COVID-19 may be higher among patients with rheumatic conditions. Various factors, including comorbidities, disease state, and treatment regimens, can influence outcomes. However, the specific impact of COVID-19 on lupus patients is not yet fully understood. More evidence-based knowledge is necessary to plan effective strategies for managing these patients in the future. This study aimed to investigate the effects of COVID-19 on patients with SLE. Methods This observational study was conducted at the Green Life Center for Rheumatic Care and Research from June 2021 to May 2022. Participants included previously diagnosed SLE patients who attended follow-up or new appointments and had a confirmed history of COVID-19 infection based on positive RT-PCR results for SARS-CoV-2 from oral or nasopharyngeal swabs. Patients with suspected but unconfirmed infections, as well as those with overlap syndromes or mixed connective tissue disease (MCTD), were excluded. The sample size was of 94. Data were collected through patient interviews and medical record reviews. The severity of COVID-19 was assessed according to national guideline: mild was defined as symptomatic, meets case definition, and no evidence of pneumonia or hypoxia; moderate was defined as clinical signs of pneumonia with saturation above 90% in room air; and severe was defined as presence of signs of pneumonia with either respiratory rate above 30 breaths per minute and or saturation less than 90% in room air. Data were collected on a preformed data sheet and analyzed using SPSS. Results Among the 94 patients, 89 (94.7%) were female and 5 were male, with a mean age of 36.7 ± 12.2 years. The majority (44%) of patients were over the age of 40. Severity assessments indicated that 66% had mild disease, while 12.8% had severe disease. The most common comorbidities reported were hypertension (42%), hypothyroidism (35.1%), and asthma (29.8%). Of the 76 available HRCT chest reports, 25 (32.8%) showed lung involvement. Eighteen (19.1%) patients had a history of hospitalization, with a mean duration of 9.1 days. Treatment data indicated that most patients (96.9%) received antibiotics, while 25.5% required oxygen, 17.2% received low molecular weight heparin (LMWH), 33% were administered rivaroxaban, 38% received dexamethasone, 18% received intravenous remdesivir, and 2 patients were treated with intravenous tocilizumab. Five patients required high dependency unit (HDU) or intensive care unit (ICU) support, and 2 required mechanical ventilation. The majority of patients (86.1%) were on immunosuppressants (33% on methotrexate, 10.6% on azathioprine, and 24.5% on mycophenolate mofetil), and 81.9% were taking hydroxychloroquine. During their illness, 31.9% of patients were on steroids, with a mean dose of 8.9 mg/day. Regression analysis revealed that both mycophenolate mofetil and steroids were associated with a higher risk of developing severe disease (odds ratios of 3.2, p-value 0.005, and 2.7, p-value 0.04, respectively). Methotrexate and hydroxychloroquine were associated with a lower probability of severe disease (odds ratios of 0.96, p-value 0.04, and 0.73, p-value 0.5, respectively). Conclusions Most lupus patients experienced mild to moderate COVID-19 infections. This study had found the widespread use of antibiotics during the pandemic. Immunosuppressive medications were associated with severity of infection. Mycophenolate mofetil and steroid were associated with a higher risk of severe infection, while methotrexate and hydroxychloroquine were linked to a lower risk.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".