Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add more filters











Database
Language
Publication year range
1.
Diabetes Care ; 45(12): 2918-2925, 2022 12 01.
Article in English | MEDLINE | ID: mdl-36749868

ABSTRACT

OBJECTIVE: The relationship between diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes and long-term glycemic control varies between studies. We aimed, firstly, to characterize the association of DKA and its severity with long-term HbA1c in a large contemporary cohort, and secondly, to identify other independent determinants of long-term HbA1c. RESEARCH DESIGN AND METHODS: Participants were 7,961 children and young adults diagnosed with type 1 diabetes by age 30 years from 2000 to 2019 and followed prospectively in the Australasian Diabetes Data Network (ADDN) until 31 December 2020. Linear mixed-effect models related variables to HbA1c. RESULTS: DKA at diagnosis was present in 2,647 participants (33.2%). Over a median 5.6 (interquartile range 3.2, 9.4) years of follow-up, participants with severe, but not moderate or mild, DKA at diagnosis had a higher mean HbA1c (+0.23%, 95% CI 0.11,0.28; [+2.5 mmol/mol, 95% CI 1.4,3.6]; P < 0.001) compared with those without DKA. Use of continuous subcutaneous insulin infusion (CSII) was independently associated with a lower HbA1c (-0.28%, 95% CI -0.31, -0.25; [-3.1 mmol/mol, 95% CI -3.4, -2.8]; P < 0.001) than multiple daily injections, and CSII use interacted with severe DKA to lower predicted HbA1c. Indigenous status was associated with higher HbA1c (+1.37%, 95% CI 1.15, 1.59; [+15.0 mmol/mol, 95% CI 12.6, 17.4]; P < 0.001), as was residing in postcodes of lower socioeconomic status (most vs. least disadvantaged quintile +0.43%, 95% CI 0.34, 0.52; [+4.7 mmol/mol, 95% CI 3.4, 5.6]; P < 0.001). CONCLUSIONS: Severe, but not mild or moderate, DKA at diagnosis was associated with a marginally higher HbA1c over time, an effect that was modified by use of CSII. Indigenous status and lower socioeconomic status were independently associated with higher long-term HbA1c.


Subject(s)
Diabetes Mellitus, Type 1 , Diabetic Ketoacidosis , Glycated Hemoglobin , Adult , Child , Humans , Young Adult , Diabetes Mellitus, Type 1/blood , Diabetes Mellitus, Type 1/complications , Diabetes Mellitus, Type 1/diagnosis , Diabetes Mellitus, Type 1/epidemiology , Diabetic Ketoacidosis/diagnosis , Diabetic Ketoacidosis/epidemiology , Diabetic Ketoacidosis/etiology , Glycated Hemoglobin/analysis , Hypoglycemic Agents/administration & dosage , Hypoglycemic Agents/therapeutic use , Injections , Insulin/administration & dosage , Insulin/therapeutic use , Insulin Infusion Systems , Australasia/epidemiology , Low Socioeconomic Status , Australian Aboriginal and Torres Strait Islander Peoples/statistics & numerical data
2.
J Clin Endocrinol Metab ; 106(1): 133-142, 2021 01 01.
Article in English | MEDLINE | ID: mdl-33120421

ABSTRACT

CONTEXT: Cardiovascular disease occurs prematurely in type 1 diabetes. The additional risk of overweight is not well characterized. OBJECTIVE: The primary aim was to measure the impact of body mass index (BMI) in youth with type 1 diabetes on cardiovascular risk factors. The secondary aim was to identify other determinants of cardiovascular risk. DESIGN: Observational longitudinal study of 7061 youth with type 1 diabetes followed for median 7.3 (interquartile range [IQR] 4-11) years over 41 (IQR 29-56) visits until March 2019. SETTING: 15 tertiary care diabetes centers in the Australasian Diabetes Data Network.Participants were aged 2 to 25 years at baseline, with at least 2 measurements of BMI and blood pressure. MAIN OUTCOME MEASURE: Standardized systolic and diastolic blood pressure scores and non-high-density lipoprotein (HDL) cholesterol were co-primary outcomes. Urinary albumin/creatinine ratio was the secondary outcome. RESULTS: BMI z-score related independently to standardized blood pressure z- scores and non-HDL cholesterol. An increase in 1 BMI z-score related to an average increase in systolic/diastolic blood pressure of 3.8/1.4 mmHg and an increase in non-HDL cholesterol (coefficient + 0.16 mmol/L, 95% confidence interval [CI], 0.13-0.18; P < 0.001) and in low-density lipoprotein (LDL) cholesterol. Females had higher blood pressure z-scores, higher non-HDL and LDL cholesterol, and higher urinary albumin/creatinine than males. Indigenous youth had markedly higher urinary albumin/creatinine (coefficient + 2.15 mg/mmol, 95% CI, 1.27-3.03; P < 0.001) and higher non-HDL cholesterol than non-Indigenous youth. Continuous subcutaneous insulin infusion was associated independently with lower non-HDL cholesterol and lower urinary albumin/creatinine. CONCLUSIONS: BMI had a modest independent effect on cardiovascular risk. Females and Indigenous Australians in particular had a more adverse risk profile.


Subject(s)
Diabetes Mellitus, Type 1/complications , Heart Disease Risk Factors , Adolescent , Adult , Age Factors , Australasia/epidemiology , Body Mass Index , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/etiology , Child , Child, Preschool , Community Networks , Databases, Factual , Diabetes Mellitus, Type 1/diagnosis , Diabetes Mellitus, Type 1/epidemiology , Diabetic Angiopathies/diagnosis , Diabetic Angiopathies/epidemiology , Diabetic Angiopathies/etiology , Female , Humans , Longitudinal Studies , Male , Risk Factors , Young Adult
3.
Injury ; 44(6): 834-41, 2013 Jun.
Article in English | MEDLINE | ID: mdl-23265787

ABSTRACT

INTRODUCTION: Trauma registries are central to the implementation of effective trauma systems. However, differences between trauma registry datasets make comparisons between trauma systems difficult. In 2005, the collaborative Australian and New Zealand National Trauma Registry Consortium began a process to develop a bi-national minimum dataset (BMDS) for use in Australasian trauma registries. This study aims to describe the steps taken in the development and preliminary evaluation of the BMDS. METHODS: A working party comprising sixteen representatives from across Australasia identified and discussed the collectability and utility of potential BMDS fields. This included evaluating existing national and international trauma registry datasets, as well as reviewing all quality indicators and audit filters in use in Australasian trauma centres. After the working party activities concluded, this process was continued by a number of interested individuals, with broader feedback sought from the Australasian trauma community on a number of occasions. Once the BMDS had reached a suitable stage of development, an email survey was conducted across Australasian trauma centres to assess whether BMDS fields met an ideal minimum standard of field collectability. The BMDS was also compared with three prominent international datasets to assess the extent of dataset overlap. Following this, the BMDS was encapsulated in a data dictionary, which was introduced in late 2010. RESULTS: The finalised BMDS contained 67 data fields. Forty-seven of these fields met a previously published criterion of 80% collectability across respondent trauma institutions; the majority of the remaining fields either could be collected without any change in resources, or could be calculated from other data fields in the BMDS. However, comparability with international registry datasets was poor. Only nine BMDS fields had corresponding, directly comparable fields in all the national and international-level registry datasets evaluated. CONCLUSION: A draft BMDS has been developed for use in trauma registries across Australia and New Zealand. The email survey provided strong indications of the utility of the fields contained in the BMDS. The BMDS has been adopted as the dataset to be used by an ongoing Australian Trauma Quality Improvement Program.


Subject(s)
Registries/standards , Trauma Centers/standards , Wounds and Injuries/epidemiology , Australia/epidemiology , Benchmarking , Female , Humans , Male , New Zealand/epidemiology , Outcome Assessment, Health Care , Quality Improvement , Quality Indicators, Health Care , Reference Standards , Registries/statistics & numerical data , Trauma Centers/statistics & numerical data
SELECTION OF CITATIONS
SEARCH DETAIL