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Combining Charlson and Elixhauser scores with varying lookback predicated mortality better than using individual scores.

OBJECTIVE To investigate variation in the presence of secondary diagnosis codes in Charlson and Elixhauser comorbidity scores and assess whether including a one-year lookback period improved prognostic adjustment by these… Click to show full abstract

OBJECTIVE To investigate variation in the presence of secondary diagnosis codes in Charlson and Elixhauser comorbidity scores and assess whether including a one-year lookback period improved prognostic adjustment by these scores individually, and combined, for 30-day mortality. STUDY DESIGN AND SETTING We analysed inpatient admissions from 01-Jan-2007 to 18-May-2018 in Oxfordshire, UK. Comorbidity scores were calculated using secondary diagnostic codes in the diagnostic-dominant episode, and primary and secondary codes from the year before. Associations between scores and 30-day mortality were investigated using Cox models with natural cubic splines for non-linearity, assessing fit using Akaike Information Criteria. RESULTS The one-year lookback improved model fit for Charlson and Elixhauser scores vs using diagnostic-dominant methods. Including both, and allowing non-linearity, improved model fit further. The diagnosis-dominant Charlson score and Elixhauser score using a 1-year lookback, and their interaction, provided the best comorbidity adjustment (reduction in AIC: 761 from best single score model). CONCLUSION The Charlson and Elixhauser score calculated using primary and secondary diagnostic codes from 1-year lookback with secondary diagnostic codes from current episode improved individual predictive ability. Ideally, comorbidities should be adjusted for using both the Charlson (diagnostic-dominant) and Elixhauser (one-year lookback) scores, incorporating non-linearity and interactions for optimal confounding control.

Keywords: year lookback; elixhauser; charlson elixhauser; mortality; charlson

Journal Title: Journal of clinical epidemiology
Year Published: 2020

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