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. 2003 Jun;41(6):1286-92.
doi: 10.1016/s0272-6386(03)00361-5.

Medical outcomes study short form-36: a consistent and powerful predictor of morbidity and mortality in dialysis patients

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Medical outcomes study short form-36: a consistent and powerful predictor of morbidity and mortality in dialysis patients

Edmund G Lowrie et al. Am J Kidney Dis. 2003 Jun.

Abstract

Background: One of the guidelines released by the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (K/DOQI) recommends that patients with glomerular filtration rate (GFR) less than 60 mL/min/1.73 m2 undergo regular assessment of functioning and well-being (FWB) to establish baselines, monitor changes in FWB over time, and assess the effect of interventions on FWB. Although this recommendation stresses the importance of assessing and monitoring physical and mental health functioning, the Medical Outcomes Study Short Form-36 (MOS SF-36) might also be useful for predicting crucial longer-term patient outcomes. This cross-sectional study tested the hypothesis that the Physical Component Summary (PCS) and Mental Component Summary (MCS) scales of the MOS SF-36 predict morbidity (measured as hospitalization) and mortality rates among dialysis patients.

Methods: Data were collected from 13,952 prevalent dialysis patients served by Fresenius Medical Care North America including age, gender, race, diabetes, serum albumin, creatinine, bicarbonate, potassium, phosphorus, hemoglobin, iron, ferritin, white blood cell count, urea reduction ratio, serum glutamic oxaloacetic-transaminase, and systolic blood pressure. FWB was measured via the MOS SF-36 Summary scale scores, PCS, and MCS. Also collected was information about hospitalizations and patient mortality.

Results: PCS and MCS were consistent predictors of hospitalizations and mortality rates even after adjustment for clinically relevant factors.

Conclusion: Because PCS and MCS are associated with hospitalization and mortality, administering this self-report measure may serve as a valuable supplement to clinical measures traditionally relied on to predict patient outcomes. Moreover, such information may be unavailable through any other single mechanism.

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