After-hours colorectal surgery: a risk factor for anastomotic leakage

__Purpose:__ This study aims to increase knowledge of colorectal anastomotic leakage by performing an incidence study and risk factor analysis with new potential risk factors in a Dutch tertiary referral center. __Methods:__ All patients whom received a primary colorectal anastomosis between 1997 and 2007 were selected by means of operation codes. Patient records were studied for population description and risk factor analysis. __Results:__ In total 739 patients were included. Anastomotic leakage (AL) occurred in 64 (8.7%) patients of whom nine (14.1%) died. Median interval between operation and diagnosis was 8 days. The risk for AL was higher as the anastomoses were constructed more distally (p = 0.019). Univariate analysis showed duration of surgery (p = 0.038), BMI (p = 0.001), time of surgery (p = 0.029), prophylactic drainage (p = 0.006) and time under anesthesia (p = 0.012) to be associated to AL. Multivariate analysis showed BMI greater than 30 kg/m2(p = 0.006; OR 2.6 CI 1.3-5.2) and "after hours" construction of an anastomosis (p = 0.030; OR 2.2 CI 1.1-4.5) to be independent risk factors. __Conclusion:__ BMI greater than 30 kg/m2and "after hours" construction of an anastomosis were independent risk factors for colorectal anastomotic leakage

Time spent outside of target glucose range for young children with type 1 diabetes: a continuous glucose monitor study

AimTo assess the associations between demographic and clinical characteristics and sensor glucose metrics in young children with type 1 diabetes, using masked, continuous glucose monitoring data from children aged 2 to < 8 years.Research design and methodsThe analysis included 143 children across 14 sites in the USA, enrolled in a separate clinical trial. Eligibility criteria were: age 2 to <8 years; type 1 diabetes duration ≥3 months; no continuous glucose monitoring use for past 30 days; and HbA1c concentration 53 to <86 mmol/mol (7.0 to <10.0%). All participants wore masked continuous glucose monitors up to 14 days.ResultsOn average, participants spent the majority (13 h) of the day in hyperglycaemia (>10.0 mmol/l) and a median of ~1 h/day in hypoglycaemia (<3.9 mmol/l). Participants with minority race/ethnicity and higher parent education levels spent more time in target range, 3.9-10.0 mmol/l, and less time in hyperglycaemia. More time in hypoglycaemia was associated with minority race/ethnicity and younger age at diagnosis. Continuous glucose monitoring metrics were similar in pump and injection users.ConclusionsGiven that both hypo- and hyperglycaemia negatively impact neurocognitive development, strategies to increase time in target glucose range for young children are needed

Relação entre o perfil antropométrico e bioquímico em crianças e adolescentes com diabetes melito tipo 1 Relación entre perfiles antropométrico y bioquímico en niños y adolescentes con diabetes mellitus tipo 1 Relationship between anthropometric and biochemical profiles in children and adolescents with type 1 diabetes

OBJETIVO: Avaliar a relação entre o perfil antropométrico e bioquímico de crianças e adolescentes com diabetes melito tipo 1 (DM1). MÉTODOS: Estudo transversal com 11 crianças e 43 adolescentes com DM1. Coletaram-se dados socioeconômicos e demográficos (idade, sexo, escolaridade, renda), clínicos (insulinoterapia), antropométricos (peso, estatura, dobras cutâneas, circunferência da cintura - CC) e bioquímicos (hemoglobina glicada - HbA, glicemias casual - GLC, pós-prandial - GLPP, e perfil lipídico). Foram utilizados o teste t de Student (p<0,05) e a correlação de Pearson (p<0,05). RESULTADOS: A renda média per capita foi de 0,58±0,39 salário-mínimo e predominou o esquema de três aplicações de insulina/dia em 72,2% da amostra. A maioria apresentou estatura (92,6%) e IMC (87%) adequados para a idade. Aqueles com índice da HbA (inHbA) adequado apresentaram menores GLC (p=0,002) e GLPP (p<0,001). O inHbA correlacionou-se positivamente com CC (p=0,013), GLC (p=0,014), GLPP (p<0,001), TG e VLDL (p<0,001). CONCLUSÕES: O pior controle glicêmico relaciona-se a maiores níveis de lipídeos séricos e CC mais elevada.<br>OBJETIVO: Evaluar la relación entre perfil antropométrico y bioquímico de niños y adolescentes con diabetes mellitus tipo 1 (DM1). MÉTODOS: Estudio transversal con 11 niños y 43 adolescentes con DM1. Se recogieron datos socioeconómicos y demográficos (edad, sexo, escolaridad, ingresos), clínicos (insulinoterapia), antropométricos (peso, estatura, pliegues cutáneos, circunferencia de la cintura-CC) y bioquímicos (hemoglobina glicada - HbA, glucemias casual - GLC, postprandial - GLPP y perfil lipídico). Se utilizaron la prueba t de Student y la correlación de Pearson (p<0,05). RESULTADOS: El ingreso mediano per capita fue de 0,58±0,39 salario mínimo y predominó el esquema de tres aplicaciones de insulina/día en el 72,2% de la muestra. La mayoría presentó estatura (92,6%) e IMC (87%) adecuados a la edad. Aquellos con índice de HbA (inHbA) adecuado presentaron menores GLC (p=0,002) y GLPP (p<0,001). El inHbA se correlacionó positivamente con CC (p=0,013), GLC (p=0,014), GLPP (p<0,001), TG y VLDL (p<0,001). CONCLUSIONES: El peor control glucémico se relaciona a mayores niveles de lípidos séricos y CC más elevada.<br>OBJECTIVE: To evaluate the relationship between anthropometric and biochemical variables in children and adolescents with type 1 diabetes mellitus (DM1). METHODS: This was a cross-sectional study of 11 children and 43 adolescents with DM1. The following data were collected: socioeconomic and demographic (age, sex, education, income), clinical (insulin therapy), anthropometric (weight, height, skinfolds, waist circumference - WC) and biochemical variables (glycated hemoglobin - HbA, casual blood glucose - CBG, post-prandial blood glucose - PPBG, and lipid profile). Statistical analysis included Student's t test (p<0.05) and Pearson's correlation (p<0.05). RESULTS: The average income per capita was 0.58±0.39 times the monthly minimum wage and 72.2% of the sample were on insulin therapy consisting of three doses per day. Most individuals had adequate height (92.6%) and BMI (87.0%) for their ages. Subjects with an adequate HbA index (inHbA) had lower CBG (p=0.002) and PPBG (p<0.001). There were positive correlations between inHbA and WC (p=0.013), CBG (p=0.014), PPBG (p<0.001), triglycerides and VLDL-cholesterol (p<0.001). CONCLUSIONS: Poorer glycemic control is related to higher serum lipids levels and larger WC

Associations of dietary intake patterns identified using reduced rank regression with markers of arterial stiffness among youth with type 1 diabetes

BACKGROUND/OBJECTIVES: Youth with type 1 diabetes (T1DM) are at substantially increased risk for adverse vascular outcomes, but little is known about the influence of dietary behavior on cardiovascular disease (CVD) risk profile. We aimed to identify dietary intake patterns associated with CVD risk factors and evaluate their impact on arterial stiffness (AS) measures collected thereafter in a cohort of youth with T1DM. SUBJECTS/METHODS: Baseline diet data from a food frequency questionnaire and CVD risk factors (triglycerides, LDL-cholesterol, systolic BP, HbA1c, C-reactive protein and waist circumference) were available for 1,153 youth aged ≥10 years with T1DM from the SEARCH for Diabetes in Youth Study. A dietary intake pattern was identified using 33 food-groups as predictors and six CVD risk factors as responses in reduced rank regression (RRR) analysis. Associations of this RRR-derived dietary pattern with AS measures [augmentation index(AIx75), n=229; pulse wave velocity(PWV), n=237; and brachial distensibility(BrachD), n=228] were then assessed using linear regression. RESULTS: The RRR-derived pattern was characterized by high intakes of sugar-sweetened beverages (SSB) and diet soda, eggs, potatoes and high-fat meats, and low intakes of sweets/desserts and low-fat dairy; major contributors were SSB and diet soda. This pattern captured the largest variability in adverse CVD risk profile and was subsequently associated with AIx75 (β=0.47; p<0.01). The mean difference in AIx75 concentration between the highest and the lowest dietary pattern quartiles was 4.3% in fully adjusted model. CONCLUSIONS: Intervention strategies to reduce consumption of unhealthful foods and beverages among youth with T1DM may significantly improve CVD risk profile and ultimately reduce the risk for AS