RESUMO
Acute myeloid leukemia (AML) patients with t(8;16)(p11.2;p13) constitute a small subgroup with a distinct genetic and clinical profile. We present a unique case of a female infant with monocytic AML associated with t(8;19)(p11.2;q13.3), a rarely reported variation of t(8;16)(p11.2;p13). The patient presented with leukemia cutis and demonstrated erythrophagocytosis in the diagnostic bone marrow. She responded well to standard AML chemotherapy and is currently in remission. Here, we highlight her case as the youngest AML patient with t(8;19) described in the literature, discuss the significance and prognostic implications of this genetic variant, and review 8p11.2 fusion proteins in AML.
RESUMO
OBJECTIVE: To characterize pediatrician and family physician (FP) screening practices for type 2 diabetes among adolescents and to examine the impact of the 2010 American Diabetes Association (ADA) guidelines, recommending use of Hemoglobin A1c (HbA1c). METHODS: We conducted a cross-sectional mail survey of a random sample of 1,400 U.S. pediatricians and FPs and we received 604 eligible responses. Our main outcome measure was the types of tests ordered by physicians, particularly HbA1c, when presented with a hypothetical scenario. RESULTS: The overall response rate was 52% (57% for pediatricians and 48% for FPs). Fasting glucose and HbA1c were the most commonly ordered tests. Overall, at least 58% of physicians ordered HbA1c; 35% ordered HbA1c in conjunction with fasting tests; and 22% ordered HbA1c alone or with nonfasting tests. Only 38% of providers were aware of the new ADA recommended HbA1c screening guidelines. However, a majority (67%) said they would change their screening practices. In the context of the guidelines, 84% of physicians would now order HbA1c. Furthermore, there was a large increase in the proportion of physicians who would shift to using HbA1c only or with other nonfasting tests. CONCLUSIONS: When screening adolescents for type 2 diabetes, providers are more likely to order HbA1c and order fewer fasting tests in response to the new ADA guidelines. HbA1c has lower sensitivity and higher costs than other testing modalities in children, therefore increasing uptake of this test (HbA1c) in children may have implications for both detection rates and healthcare costs.
Assuntos
Glicemia/análise , Diabetes Mellitus Tipo 2/diagnóstico , Hemoglobinas Glicadas/análise , Padrões de Prática Médica/estatística & dados numéricos , Adolescente , Adulto , Estudos Transversais , Medicina de Família e Comunidade , Jejum , Feminino , Teste de Tolerância a Glucose/estatística & dados numéricos , Hemoglobinas Glicadas/economia , Fidelidade a Diretrizes , Humanos , Masculino , Pessoa de Meia-Idade , Pediatria , Guias de Prática Clínica como Assunto , Sensibilidade e EspecificidadeRESUMO
OBJECTIVE: To develop a clinical risk scoring system for identifying adolescents with dysglycemia (prediabetes or diabetes) who need further confirmatory testing and to determine whether the addition of non-fasting tests would improve the prediction of dysglycemia. STUDY DESIGN: A sample of 176 overweight and obese adolescents (10-17 years) had a history/physical exam, a 2-h oral glucose tolerance test, and non-fasting tests [hemoglobin A1c, 1-h glucose challenge test (GCT), and random glucose test] performed. Given the low number of children with diabetes, we created several risk scoring systems combining the clinical characteristics with non-fasting tests for identifying adolescents with dysglycemia and compared the test performance. RESULTS: Sixty percent of participants were white and 32% were black; 39.2% had prediabetes and 1.1% had diabetes. A basic model including demographics, body mass index percentile, family history of diabetes, and acanthosis nigricans had reasonable test performance [area under the curve (AUC), 0.75; 95% confidence interval (95% CI), 0.68-0.82]. The addition of random glucose (AUC, 0.81; 95% CI, 0.75-0.87) or 1-h GCT (AUC, 0.82; 95% CI, 0.75-0.88) to the basic model significantly improved the predictive capacity, but the addition of hemoglobin A1c did not (AUC, 0.76; 95% CI, 0.68-0.83). The clinical score thresholds to consider for the basic plus random glucose model are total score cutoffs of 60 or 65 (sensitivity 86% and 65% and specificity 60% and 78%, respectively) and for the basic plus 1-h GCT model are total score cutoffs of 50 or 55 (sensitivity 87% and 73% and specificity 59% and 76%, respectively). CONCLUSIONS: Pending a validation in additional populations, a risk score combining the clinical characteristics with non-fasting test results may be a useful tool for identifying children with dysglycemia in the primary care setting.