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Published on: July 24, 2013
Prediction of Hospitalizations in Systemic Lupus Erythematosus Using the Systemic Lupus International Collaborating
Alexandra Legge1, Susan Kirkland1, Kenneth Rockwood1
1Dalhousie University, Halifax, Nova Scotia, Canada.
The Systemic Lupus International Collaborating Clinics (SLICC) frailty index (FI) predicts hospitalizations in systemic lupus erythematosus (SLE) patients. Higher frailty scores indicate increased risk for more frequent and longer hospital stays.
Area of Science:
- Rheumatology
- Clinical Epidemiology
Background:
- The Systemic Lupus International Collaborating Clinics (SLICC) frailty index (FI) is established for predicting mortality and damage in systemic lupus erythematosus (SLE).
- The association between the SLICC-FI and hospitalization rates in SLE patients has not been previously described.
Purpose of the Study:
- To evaluate the association between baseline SLICC-FI values and future hospitalizations within the SLICC inception cohort.
- To determine if the SLICC-FI can predict the frequency and duration of hospitalizations in SLE patients.
Main Methods:
- Baseline SLICC-FI scores were calculated for 1,549 SLE patients.
- Inpatient hospitalizations and duration were recorded during a mean follow-up of 7.2 years.
- Negative binomial and linear regression models were used to assess the association of SLICC-FI with hospitalization rates and time spent hospitalized, adjusting for covariates.
Main Results:
- Higher baseline SLICC-FI values were significantly associated with more frequent hospitalizations (IRR 1.21, 95% CI 1.13-1.30) per 0.05 increment.
- Among hospitalized patients, higher SLICC-FI predicted a greater proportion of follow-up time spent hospitalized (RR 1.09, 95% CI 1.02-1.16).
- 39.6% of patients experienced 1,570 hospitalizations during the study period.
Conclusions:
- The SLICC-FI is a valid measure for predicting future hospitalizations in incident SLE patients.
- These findings support the utility of the SLICC-FI as a comprehensive health assessment tool in SLE management.
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