Literature DB >> 28285428

A Novel Model for Predicting Incident Moderate to Severe Anemia and Iron Deficiency in Patients with Newly Diagnosed Ulcerative Colitis.

Nabeel Khan1,2, Dhruvan Patel3, Yash Shah4, Yu-Xiao Yang5.   

Abstract

BACKGROUND: Anemia and iron deficiency are common complications of ulcerative colitis (UC). We aimed to develop and internally validate a prediction model for the incidence of moderate to severe anemia and iron deficiency anemia (IDA) in newly diagnosed patients with UC.
METHODS: Multivariable logistic regression was performed among a nationwide cohort of patients who were newly diagnosed with UC in the VA health-care system. Model development was performed in a random two-third of the total cohort and then validated in the remaining one-third of the cohort. As candidate predictors, we examined routinely available data at the time of UC diagnosis including demographics, medications, laboratory results, and endoscopy findings.
RESULTS: A total of 789 patients met the inclusion criteria. For the outcome of moderate to severe anemia, age, albumin level and mild anemia at UC diagnosis were predictors selected for the model. The AUC for this model was 0.69 (95% CI 0.64-0.74). For the outcome of moderate to severe anemia with evidence of iron deficiency, the predictors included African-American ethnicity, mild anemia, age, and albumin level at UC diagnosis. The AUC was 0.76, (95% CI 0.69-0.82). Calibration was consistently good in all models (Hosmer-Lemeshow goodness of fit p > 0.05). The models performed similarly in the internal validation cohort.
CONCLUSIONS: We developed and internally validated a prognostic model for predicting the risk of moderate to severe anemia and IDA among newly diagnosed patients with UC. This will help identify patients at high risk of these complications, who could benefit from surveillance and preventive measures.

Entities:  

Keywords:  Anemia; Iron deficiency; Prediction model; Ulcerative colitis; Web-based application

Mesh:

Year:  2017        PMID: 28285428     DOI: 10.1007/s10620-017-4512-3

Source DB:  PubMed          Journal:  Dig Dis Sci        ISSN: 0163-2116            Impact factor:   3.199


  31 in total

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