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. 2000 Jan 13;342(2):83-9.
doi: 10.1056/NEJM200001133420203.

Prediction of adverse outcomes in children with sickle cell disease

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Free article

Prediction of adverse outcomes in children with sickle cell disease

S T Miller et al. N Engl J Med. .
Free article

Abstract

Background: The ability to identify infants with sickle cell anemia who are likely to have severe complications later in life would permit accurate prognostication and tailoring of therapy to match disease-related risks and facilitate planning of clinical trials. We attempted to define the features of such babies by following the clinical course of 392 children with sickle cell disease from infancy to about the age of 10 years.

Methods: We analyzed the records of 392 infants who received the diagnosis of homozygous sickle cell anemia or sickle cell-Beta(0)-thalassemia before the age of six months and for whom comprehensive clinical and laboratory data were recorded prospectively; data were available for a mean (+/-SD) of 10.0+/-4.8 years. Results obtained before the age of two years were evaluated to determine whether they predicted the outcome later in life.

Results: Of the 392 infants in the cohort, 70 (18 percent) subsequently had an adverse outcome, defined as death (18 patients [26 percent]), stroke (25 [36 percent]) frequent pain (17 [24 percent]), or recurrent acute chest syndrome (10 [14 percent]). Using multivariate analysis, we found three statistically significant predictors of an adverse outcome: an episode of dactylitis before the age of one year (relative risk of an adverse outcome, 2.55; 95 percent confidence interval, 1.39 to 4.67), a hemoglobin level of less than 7 g per deciliter (relative risk, 2.47; 95 percent confidence interval, 1.14 to 5.33), and leukocytosis in the absence of infection (relative risk, 1.80; 95 percent confidence interval, 1.05 to 3.09).

Conclusions: Three easily identifiable manifestations of sickle cell disease that may appear in the first two years of life (dactylitis, severe anemia, and leukocytosis) can help to predict the possibility of severe sickle cell disease later in life.

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