Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/17323
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dc.contributor.authorYong, Priscilla H-
dc.contributor.authorWeinberg, Laurence-
dc.contributor.authorTorkamani, Niloufar-
dc.contributor.authorChurilov, Leonid-
dc.contributor.authorRobbins, Raymond J-
dc.contributor.authorMa, Ronald-
dc.contributor.authorBellomo, Rinaldo-
dc.contributor.authorLam, Que T-
dc.contributor.authorBurns, James D-
dc.contributor.authorHart, Graeme K-
dc.contributor.authorLew, Jeremy F-
dc.contributor.authorMårtensson, Johan-
dc.contributor.authorStory, David A-
dc.contributor.authorMotley, Andrew N-
dc.contributor.authorJohnson, Douglas F-
dc.contributor.authorZajac, Jeffrey D-
dc.contributor.authorEkinci, Elif I-
dc.date2018-03-26-
dc.date.accessioned2018-04-03T00:37:32Z-
dc.date.available2018-04-03T00:37:32Z-
dc.date.issued2018-06-
dc.identifier.citationDiabetes Care 2018; 41(6): 1172-1179en_US
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/17323-
dc.description.abstractLimited studies have examined the association between diabetes and HbA1cwith postoperative outcomes. We investigated the association of diabetes, defined categorically and HbA1cas a continuous measure, with postoperative outcomes. In this prospective, observational study, we measured the HbA1cof surgical inpatients age ≥54 years at a tertiary hospital between May 2013 and January 2016. Patients were diagnosed with diabetes if they had preexisting diabetes or an HbA1c≥6.5% (48 mmol/mol) or with prediabetes if they had an HbA1cbetween 5.7-6.4% (39-48 mmol/mol). Patients with an HbA1c<5.7% (39 mmol/mol) were categorized as having normoglycemia. Baseline demographic and clinical data were obtained from hospital records, and patients were followed for 6 months. Random-effects logistic and negative binomial regression models were used for analysis, treating surgical units as random effects. We undertook classification and regression tree (CART) analysis to design a 6-month mortality risk model. Of 7,565 inpatients, 30% had diabetes, and 37% had prediabetes. After adjusting for age, Charlson comorbidity index (excluding diabetes and age), estimated glomerular filtration rate, and length of surgery, diabetes was associated with increased 6-month mortality (adjusted odds ratio [aOR] 1.29 [95% CI 1.05-1.58];P= 0.014), major complications (1.32 [1.14-1.52];P< 0.001), intensive care unit (ICU) admission (1.50 [1.28-1.75];P< 0.001), mechanical ventilation (1.67 [1.32-2.10];P< 0.001), and hospital length of stay (LOS) (adjusted incidence rate ratio [aIRR] 1.08 [95% CI 1.04-1.12];P< 0.001). Each percentage increase in HbA1cwas associated with increased major complications (aOR 1.07 [1.01-1.14];P= 0.030), ICU admission (aOR 1.14 [1.07-1.21];P< 0.001), and hospital LOS (aIRR 1.05 [1.03-1.06];P< 0.001). CART analysis confirmed a higher risk of 6-month mortality with diabetes in conjunction with other risk factors. Almost one-third of surgical inpatients age ≥54 years had diabetes. Diabetes and higher HbA1cwere independently associated with a higher risk of adverse outcomes after surgery.en_US
dc.language.isoeng-
dc.titleThe Presence of Diabetes and Higher HbA1cAre Independently Associated With Adverse Outcomes After Surgery.en_US
dc.typeJournal Articleen_US
dc.identifier.journaltitleDiabetes Careen_US
dc.identifier.affiliationMedicine (University of Melbourne)en_US
dc.identifier.affiliationAnaesthesiaen_US
dc.identifier.affiliationEndocrinologyen_US
dc.identifier.affiliationThe Florey Institute of Neuroscience & Mental Health, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationDepartment of Administrative Informatics, Austin Health, Heidelberg, Victoria, Australiaen_US
dc.identifier.affiliationClinical Costing Finance, Austin Health, Heidelberg, Victoria, Australiaen_US
dc.identifier.affiliationCentre for Integrated Critical Care, University of Melbourne, Parkville, Victoria, Australiaen_US
dc.identifier.affiliationPathologyen_US
dc.identifier.affiliationClinical Informatics Unit, Austin Health, Heidelberg, Victoria, Australiaen_US
dc.identifier.affiliationIntensive Careen_US
dc.identifier.affiliationSection of Anesthesia and Intensive Care Medicine, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Swedenen_US
dc.identifier.affiliationQuality and Patient Safetyen_US
dc.identifier.affiliationGeneral Medicineen_US
dc.identifier.affiliationAustralian and New Zealand Intensive Care Society Research Centre, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australiaen_US
dc.identifier.doi10.2337/dc17-2304en_US
dc.type.contentTexten_US
dc.identifier.orcid0000-0001-8739-7896en_US
dc.identifier.orcid0000-0003-2372-395Xen_US
dc.identifier.orcid0000-0001-7403-7680en_US
dc.identifier.orcid0000-0002-9807-6606en_US
dc.identifier.orcid0000-0002-1650-8939en_US
dc.identifier.orcid0000-0002-6479-1310en_US
dc.identifier.pubmedid29581095-
dc.type.austinJournal Article-
local.name.researcherBellomo, Rinaldo
item.fulltextNo Fulltext-
item.openairetypeJournal Article-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.deptAnaesthesia-
crisitem.author.deptEndocrinology-
crisitem.author.deptMedicine (University of Melbourne)-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
crisitem.author.deptClinical Analytics and Reporting-
crisitem.author.deptClinical Analytics and Reporting-
crisitem.author.deptIntensive Care-
crisitem.author.deptData Analytics Research and Evaluation (DARE) Centre-
crisitem.author.deptPathology-
crisitem.author.deptIntensive Care-
crisitem.author.deptMedicine (University of Melbourne)-
crisitem.author.deptAnaesthesia-
crisitem.author.deptQuality and Patient Safety-
crisitem.author.deptEndocrinology-
crisitem.author.deptMedicine (University of Melbourne)-
crisitem.author.deptEndocrinology-
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