RISK OF ACUTE KIDNEY INJURY IN SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS WITH CORONAVIRUS DISEASE 2019: A NATIONAL INPATIENT ANALYSIS
Bibliographic record
Abstract
PV090 / #421 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose While studies have shown increased adverse outcomes in Systemic Lupus Erythematosus (SLE) patients with Coronavirus Disease 2019 (COVID-19), detailed analysis of acute kidney injury (AKI) risk factors remains limited. We aimed to assess AKI risk in hospitalized SLE patients with COVID-19 using 2021 nationally representative data. Methods Using the 2021 National Inpatient Sample, we identified adult SLE patients (International Classification of Diseases, 10th Revision code M32) stratified by COVID-19 status. The primary outcome was AKI. We employed survey-weighted logistic regression to calculate adjusted odds ratios (aOR), controlling for demographics, comorbidities, and substance use. Results Among 170,085 hospitalized SLE patients, 12,710 (7.47%) had COVID-19. AKI occurred more frequently in SLE patients with COVID-19 compared to those without (3725/12,710 [29.31%] vs 33,640/157,375 [21.38%], p < 0.001). COVID-19 independently predicted AKI (aOR 1.61, 95% CI 1.46-1.77, p < 0.001). Substance use was lower in COVID-19 patients: nicotine (1120/12,710 [8.81%] vs 24,299/157,375 [15.44%], aOR 0.71, 95% CI 0.64-0.78, p < 0.001) and alcohol (145/12,710 [1.14%] vs 4768/157,375 [3.03%], aOR 0.59, 95% CI 0.47-0.74, p < 0.001). Each year increase in age increased risk (aOR 1.01 per year, 95% CI 1.01-1.01, p < 0.001). African American patients had higher risk compared to Caucasian patients (aOR 1.18, 95% CI 1.09-1.28, p < 0.001), while females had lower risk than males (11,215/12,710 [88.24%] vs 138,905/157,375 [88.33%], aOR 0.76, 95% CI 0.70-0.82, p < 0.001). Compared to low comorbidity burden, Elixhauser categories strongly predicted risk: moderate (aOR 2.59, 95% CI 2.24-3.00, p < 0.001) and severe (aOR 4.32, 95% CI 3.73-4.99, p < 0.001). Prior cardiovascular conditions showed lower risk: myocardial infarction (aOR 0.79, 95% CI 0.71-0.88, p < 0.001) and stroke (aOR 0.85, 95% CI 0.73-0.98, p = 0.029). Conclusions This study demonstrates that COVID-19 significantly increases AKI risk in SLE patients, with 61% higher odds compared to non-COVID SLE patients. Our findings reveal complex interactions between COVID-19 status, demographics, comorbidities, and substance use. The unexpected protective associations of cardiovascular conditions and substance use patterns suggest potential preemptive medical management effects. These insights can inform targeted preventive strategies and heightened monitoring protocols for this vulnerable population during the ongoing pandemic, particularly for identified high-risk subgroups such as older and African American patients.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".