Systemic lupus erythematosus in North American Indians: a population based study.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the prevalence, disease course, and survival of patients with systemic lupus erythematosus (SLE) in a population of over 120,000 North American Indians (NAI), and contrast the results to those in the non-Indian population. METHODS: The regional arthritis center database and the medical records of all rheumatologists, hematologists, nephrologists, and general internists with > 1 patient with SLE were searched for cases of SLE diagnosed between 1980 and 1996. A random survey of 20% of family physicians serving this population suggested that > 85% of all SLE cases were identified. Demographics, SLE Disease Activity Index (SLEDAI) scores, Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) damage scores. clinical manifestations, and therapy for NAI were contrasted with the results in Caucasians (CAUC). RESULTS: We identified 257 cases meeting the ACR criteria for SLE diagnosed between 1980 and 1996. There were 49 NAI cases, resulting in a prevalence of 42.3/100,000, compared to a prevalence of 20.6/100,000 for the remainder of the population. NAI patients were younger at diagnosis, had higher SLEDAI scores at diagnosis, and had more frequent vasculitis, proteinuria and cellular casts. There were no treatment differences at diagnosis or at 2 years, but NAI patients were significantly more likely to receive treatment with prednisone or immunosuppressives at the last clinic visit. The NAI patients had similar damage scores at diagnosis, but significantly higher scores at 2 years and at the last clinic visit. NAI ethnicity increased the likelihood of death more than 4-fold. CONCLUSION: The prevalence of SLE was increased 2-fold in the NAI population. NAI patients had higher SLEDAI scores at diagnosis and more frequent vasculitis and renal involvement, required more treatment later in the disease course, accumulated more damage following diagnosis, and had increased fatality.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".