RESUMO
OBJECTIVE: The American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) is a widely used method for the management of adult thyroid nodules. However, its use in paediatric patients is controversial because adult fine needle aspiration biopsy (FNAB) recommendations may lead to delayed diagnoses of cancer in children. The objectives of this study were to evaluate the performance of TI-RADS in paediatric thyroid nodules and to tailor FNAB recommendations for children. METHODS: Consecutive surgically resected paediatric thyroid nodules from two tertiary care centres between 2003 and 2021 were reviewed. Ultrasounds were blindly scored by radiologists according to TI-RADS. Management recommendations based on TI-RADS were evaluated. Various modelling methodologies were used to determine the optimal cutoff for FNAB in children. RESULTS: Of the 96 patients, 79 (82%) were female and the median age at surgery was 16.1 years. Fifty (52%) nodules were malignant on surgical pathology. The area under the receiver operating characteristic curve of TI-RADS for predicting malignancy was 0.78. Adult TI-RADS recommendations would have resulted in 4% of cancerous nodules being lost to follow-up. Modifications to TI-RADS (FNAB of all TR3 nodules ≥1.5 cm, FNAB of TR4 and TR5 nodules ≥0.5 cm, surveillance of nodules ≥1 cm, consider surgery for nodules >4 cm) reduced this missed malignancy rate to 0%. CONCLUSIONS: TI-RADS can risk-stratify paediatric thyroid nodules. However, the system requires modifications to reduce the missed malignancy rate in paediatric thyroid nodules. Our data suggest that lower size thresholds for FNAB are warranted in children.
RESUMO
OBJECTIVE: Despite enthusiasm for low carbohydrate diets (LCDs) among patients with type 1 diabetes (T1DM), no prospective study has investigated outcomes in adolescent T1DM. We aimed to quantify a pragmatic LCD intervention's impact on glycemia, lipidemia, and quality of life (QOL) in adolescents with T1DM. RESEARCH DESIGN AND METHODS: At an academic center, we randomized 39 patients with T1DM aged 13-21 years to one of three 12-week interventions: an LCD, an isocaloric standard carbohydrate diet (SCD), or general diabetes education without a prescriptive diet. Glycemic outcomes included glycosylated hemoglobin (HbA1c) and continuous glucose monitoring. RESULTS: There were no significant differences in glycemic, lipidemic, or QOL parameters between groups at any timepoint. Median HbA1c was similar at baseline between groups and did not change appreciably (7.9%-8.4% in LCDs, 7.9%-7.9% in SCDs, and 8.2%-7.8% in controls). Change in carbohydrate consumption was minimal with only one participant reaching target carbohydrate intake. CONCLUSIONS: This pragmatic LCD intervention did not alter carbohydrate consumption or glycemia. Although this study was unable to evaluate a highly controlled LCD, it indicates that adolescents are unlikely to implement an educational LCD intervention in routine clinic settings. Thus, this approach is unlikely to effectively mitigate hyperglycemia in adolescents.
Assuntos
Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Adolescente , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/terapia , Dieta com Restrição de Carboidratos , Hemoglobinas Glicadas/análise , Humanos , Qualidade de Vida , Adulto JovemRESUMO
The Medtronic MiniMed 670G system delivers insulin to patients with type 1 diabetes mellitus (T1DM) using either its hybrid closed-loop (HCL) "Auto Mode" feature or an open-loop mode. In this retrospective, cross-sectional analysis, we quantified the association between time in Auto Mode and both haemoglobin A1c (HbA1c) and time in range (TIR, sensor glucose 70-180 mg/dL) among 96 paediatric and young adult patients with T1DM. The median percentage time in Auto Mode was 38.5% (interquartile range 0%-64%). The percentage time in Auto Mode significantly correlated with HbA1c after adjustment for covariables (ß = -0.008, P = 0.014). Each daily 3.4-h increase in Auto Mode time was associated with a 0.1% decrease in HbA1c. Auto Mode time was also correlated with TIR after adjustment for covariables (ß = 0.14, P = 0.02): for each daily 8.6-h increase in Auto Mode time, TIR increased by 5%. While Auto Mode use was low, increased time in Auto Mode was associated with a significantly lower HbA1c and increased TIR. These findings emphasize the importance of identifying strategies to improve the ease of use of HCL systems.
Assuntos
Diabetes Mellitus Tipo 1 , Adolescente , Glicemia , Automonitorização da Glicemia , Criança , Estudos Transversais , Diabetes Mellitus Tipo 1/tratamento farmacológico , Controle Glicêmico , Humanos , Hipoglicemiantes/uso terapêutico , Insulina/uso terapêutico , Sistemas de Infusão de Insulina , Estudos Retrospectivos , Resultado do Tratamento , Adulto JovemRESUMO
OBJECTIVE: To quantify and contextualize the risk for coronavirus disease 2019 (COVID-19)-related hospitalization and illness severity in type 1 diabetes. RESEARCH DESIGN AND METHODS: We conducted a prospective cohort study to identify case subjects with COVID-19 across a regional health care network of 137 service locations. Using an electronic health record query, chart review, and patient contact, we identified clinical factors influencing illness severity. RESULTS: We identified COVID-19 in 6,138, 40, and 273 patients without diabetes and with type 1 and type 2 diabetes, respectively. Compared with not having diabetes, people with type 1 diabetes had adjusted odds ratios of 3.90 (95% CI 1.75-8.69) for hospitalization and 3.35 (95% CI 1.53-7.33) for greater illness severity, which was similar to risk in type 2 diabetes. Among patients with type 1 diabetes, glycosylated hemoglobin (HbA1c), hypertension, race, recent diabetic ketoacidosis, health insurance status, and less diabetes technology use were significantly associated with illness severity. CONCLUSIONS: Diabetes status, both type 1 and type 2, independently increases the adverse impacts of COVID-19. Potentially modifiable factors (e.g., HbA1c) had significant but modest impact compared with comparatively static factors (e.g., race and insurance) in type 1 diabetes, indicating an urgent and continued need to mitigate severe acute respiratory syndrome coronavirus 2 infection risk in this community.