ACUTE CARE UTILIZATION IN PATIENTS WITH ANTIPHOSPHOLIPID SYNDROME AND/OR SYSTEMIC LUPUS ERYTHEMATOSUS
Bibliographic record
Abstract
PV078 / #557 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose Little is known about acute care utilization in patients with antiphospholipid antibodies (aPL) or antiphospholipid syndrome (APS) and systemic lupus erythematosus (SLE). This study focuses on hospitalizations, intensive care unit (ICU) admissions and emergency department (ED) visits, in patients with APS and/or SLE, both 1 year prior to and after diagnosis with SLE or identification of positive aPLs, compared to a control population in Alberta, Canada. Methods Patients from our observational aPL/APS and SLE registries were included. Patients had persistently positive aPL (medium positive [40-80 GPU] or high positive [80-160 GPU] anticardiolipin or anti-beta-2 glycoprotein 1 or a positive lupus anticoagulant test, measured at least 12 weeks apart) and/or fulfilled ACR or SLICC SLE classification criteria. Patients diagnosed with APS met revised Sapporo Criteria. The index date was defined as the date that persistently positive aPL were first identified or that SLE classification criteria were met, whichever came first. If the index date was prior to 2002, the date of registry enrollment was used instead, as administrative data was not available. Acute care utilization 1 year prior to and after the index date (between April 1st 2007 and March 31st 2024) was determined. Data were sourced from several Albertan health-related databases, including the Discharge Abstract Database, National Ambulatory Care Reporting System, and Alberta Provincial Registry, linking participants via their Alberta Personal Health Number. Acute care utilization was compared to age- and sex-matched controls, matched to cases 5:1, excluding any individuals with results for aPLs, ANA, ENA or anti dsDNA or those with any practitioner claim codes or inpatient/outpatient ICD codes for SLE or APS. Controls were assigned the index date of their matched case. Results 466 patients participated, aPL positive only (n=7), APS only (n=19), SLE only (n=339), SLE and aPL positive (n=55), and SLE and APS (n=46) (Table 1). A total of 1,857,127 potential control candidates were identified, from which 2,330 controls were randomly selected. One year prior to the index date, the proportion of participants with inpatient hospitalizations were as follows: APS only (5.56%), SLE only (10.07%), SLE and aPL positive (4.17%), SLE and APS (14.63%), and control (3.79%), with no hospitalizations recorded among the aPL-positive only group. Patients who had SLE and APS experienced the highest ED visit rate (36.59%). The lowest ED visit rate was observed in the control group (11.84%) (Table 2). One year after the index date, the highest hospitalization rates were observed in patients with SLE and APS (44.44%) and APS (42.11%) groups, while the control group had the lowest rate (3.81%). SLE and APS participants had the longest average hospital length of stay (18.45 days). ICU admissions were rare, peaking at 5.26% in the APS group. ED visits were most frequent in SLE and APS (66.67%) and APS (52.63%) groups, compared to 12.25% in controls (Table 2). Table 1: Baseline characteristics at index date* Table 2 Acute care utilization one year prior to, and one year after index date* Conclusions Patients with APS and/or SLE have a high number of hospitalizations and ED presentations compared to a control population, both 1 year prior to and after the first identification of positive aPLs or diagnosis of SLE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".