scholarly journals Risk factors and incidence over time for lower extremity amputations in people with type 1 diabetes: an observational cohort study of 46,088 patients from the Swedish National Diabetes Registry

Diabetologia ◽  
2021 ◽  
Author(s):  
Sara Hallström ◽  
Ann-Marie Svensson ◽  
Aldina Pivodic ◽  
Arndís F. Ólafsdóttir ◽  
Magnus Löndahl ◽  
...  

Abstract Aims/hypothesis The aim of this work was to study the incidence over time of lower extremity amputations and determine variables associated with increased risk of amputations in people with type 1 diabetes. Methods Individuals with type 1 diabetes registered in the Swedish National Diabetes Registry with no previous amputation from 1 January 1998 and followed to 2 October 2019 were included. Time-updated Cox regression and gradient of risk per SD were used to evaluate the impact of risk factors on the incidence of amputation. Age- and sex-adjusted incidences were estimated over time. Results Of 46,088 people with type 1 diabetes with no previous amputation (mean age 32.5 years [SD 14.5], 25,354 [55%] male sex), 1519 (3.3%) underwent amputation. Median follow-up was 12.4 years. The standardised incidence for any amputation in 1998–2001 was 2.84 (95% CI 2.32, 3.36) per 1000 person-years and decreased to 1.64 (95% CI 1.38, 1.90) per 1000 person-years in 2017–2019. The incidence for minor and major amputations showed a similar pattern. Hyperglycaemia and renal dysfunction were the strongest risk factors for amputation, followed by older age, male sex, cardiovascular comorbidities, smoking and hypertension. Glycaemic control and age- and sex-adjusted renal function improved during the corresponding time period as amputations decreased. Conclusions/interpretation The incidence of amputation and of the most prominent risk factors for amputation, including renal dysfunction and hyperglycaemia, has improved considerably during recent years for people with type 1 diabetes. This finding has important implications for quality of life, health economics and prognosis regarding CVD, indicating a trend shift in the treatment of type 1 diabetes. Graphical abstract

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 52-OR
Author(s):  
SARA HALLSTRÖM ◽  
ANN-MARIE SVENSSON ◽  
ALDINA PIVODIC ◽  
ARNDIS F. OLAFSDOTTIR ◽  
MAGNUS LONDAHL ◽  
...  

2019 ◽  
Vol 160 (5) ◽  
pp. 810-817 ◽  
Author(s):  
Ashley M. Nassiri ◽  
James W. Pichert ◽  
Henry J. Domenico ◽  
Mitchell B. Galloway ◽  
William O. Cooper ◽  
...  

Objectives To analyze unsolicited patient complaints (UPCs) among otolaryngologists, identify risk factors for UPCs, and determine the impact of physician feedback on subsequent UPCs. Methods This retrospective study reviewed UPCs associated with US otolaryngologists from 140 medical practices from 2014 to 2017. A subset of otolaryngologists with high UPCs received peer-comparative feedback and was monitored for changes. Results The study included 29,778 physicians, of whom 548 were otolaryngologists. UPCs described concerns with treatment (45%), communication (19%), accessibility (18%), concern for patients and families (10%), and billing (8%). Twenty-nine (5.3%) otolaryngologists were associated with 848 of 3659 (23.2%) total UPCs. Male sex and graduation from a US medical school were statistically significantly associated with an increased number of UPCs ( P = .0070 and P = .0036, respectively). Twenty-nine otolaryngologists with UPCs at or above the 95th percentile received peer-comparative feedback. The intervention led to an overall decrease in the number of UPCs following intervention ( P = .049). Twenty otolaryngologists (69%) categorized as “responders” reduced the number of complaints an average of 45% in the first 2 years following intervention. Discussion Physician demographic data can be used to identify otolaryngologists with a greater number of UPCs. Most commonly, UPCs expressed concern regarding treatment. Peer-delivered, comparative feedback can be effective in reducing UPCs in high-risk otolaryngologists. Implications for Practice Systematic monitoring and respectful sharing of peer-comparative patient complaint data offers an intervention associated with UPCs and concomitant malpractice risk reduction. Collegial feedback over time increases the response rate, but a small proportion of physicians will require directive interventions.


2020 ◽  
Vol 105 (5) ◽  
pp. e2032-e2038 ◽  
Author(s):  
Viral N Shah ◽  
Ryan Bailey ◽  
Mengdi Wu ◽  
Nicole C Foster ◽  
Rodica Pop-Busui ◽  
...  

Abstract Context Cardiovascular disease (CVD) is a major cause of mortality in adults with type 1 diabetes. Objective We prospectively evaluated CVD risk factors in a large, contemporary cohort of adults with type 1 diabetes living in the United States. Design Observational study of CVD and CVD risk factors over a median of 5.3 years. Setting The T1D Exchange clinic network. Patients Adults (age ≥ 18 years) with type 1 diabetes and without known CVD diagnosed before or at enrollment. Main Outcome Measure Associations between CVD risk factors and incident CVD were assessed by multivariable logistic regression. Results The study included 8,727 participants (53% female, 88% non-Hispanic white, median age 33 years [interquartile ratio {IQR} = 21, 48], type 1 diabetes duration 16 years [IQR = 9, 26]). At enrollment, median HbA1c was 7.6% (66 mmol/mol) (IQR = 6.9 [52], 8.6 [70]), 33% used a statin, and 37% used blood pressure medication. Over a mean follow-up of 4.6 years, 325 (3.7%) participants developed incident CVD. Ischemic heart disease was the most common CVD event. Increasing age, body mass index, HbA1c, presence of hypertension and dyslipidemia, increasing duration of diabetes, and diabetic nephropathy were associated with increased risk for CVD. There were no significant gender differences in CVD risk. Conclusion HbA1c, hypertension, dyslipidemia and diabetic nephropathy are important risk factors for CVD in adults with type 1 diabetes. A longer follow-up is likely required to assess the impact of other traditional CVD risk factors on incident CVD in the current era.


2020 ◽  
Author(s):  
An Tran-Duy ◽  
Josh Knight ◽  
Andrew J Palmer ◽  
Dennis Petrie ◽  
Tom WC Lung ◽  
...  

<b>OBJECTIVE </b> <p>To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort.</p> <p><b>RESEARCH DESIGN AND METHODS</b></p> <p>Data for model development were obtained from the <a>Swedish National Diabetes Register</a>. We derived parametric proportional hazards models predicting absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed.</p> <p><b>RESULTS </b></p> <p>The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was approximately 13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for approximately 40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycaemia and hyperglycaemia, and lowering HbA1c in reducing the risk of complications and death.</p> <p><b>CONCLUSIONS </b></p> Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes, and project events occurring over patients’ lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.


Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1606-P
Author(s):  
ANNA-MARIA LAMPOUSI ◽  
DIMITRIOS E. DELIS ◽  
MARIA XATZIPSALTI ◽  
ANDRIANI VAZEOU

Author(s):  
Anni Ylinen ◽  
◽  
Stefanie Hägg-Holmberg ◽  
Marika I. Eriksson ◽  
Carol Forsblom ◽  
...  

Abstract Background Individuals with type 1 diabetes have a markedly increased risk of stroke. In the general population, genetic predisposition has been linked to increased risk of stroke, but this has not been assessed in type 1 diabetes. Our aim was, therefore, to study how parental risk factors affect the risk of stroke in individuals with type 1 diabetes. Methods This study represents an observational follow-up of 4011 individuals from the Finnish Diabetic Nephropathy Study, mean age at baseline 37.6 ± 11.9 years. All strokes during follow-up were verified from medical records or death certificates. The strokes were classified as either ischemic or hemorrhagic. All individuals filled out questionnaires concerning their parents’ medical history of hypertension, diabetes, stroke, and/or myocardial infarction. Results During a median follow-up of 12.4 (10.9–14.2) years, 188 individuals (4.6%) were diagnosed with their first ever stroke; 134 were ischemic and 54 hemorrhagic. In Cox regression analysis, a history of maternal stroke increased the risk of hemorrhagic stroke, hazard ratio 2.86 (95% confidence interval 1.27–6.44, p = 0.011) after adjustment for sex, age, BMI, retinal photocoagulation, and diabetic kidney disease. There was, however, no association between maternal stroke and ischemic stroke. No other associations between parental risk factors and ischemic or hemorrhagic stroke were observed. Conclusion A history of maternal stroke increases the risk of hemorrhagic stroke in individuals with type 1 diabetes. Other parental risk factors seem to have limited impact on the risk of stroke.


2020 ◽  
Author(s):  
An Tran-Duy ◽  
Josh Knight ◽  
Andrew J Palmer ◽  
Dennis Petrie ◽  
Tom WC Lung ◽  
...  

<b>OBJECTIVE </b> <p>To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort.</p> <p><b>RESEARCH DESIGN AND METHODS</b></p> <p>Data for model development were obtained from the <a>Swedish National Diabetes Register</a>. We derived parametric proportional hazards models predicting absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed.</p> <p><b>RESULTS </b></p> <p>The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was approximately 13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for approximately 40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycaemia and hyperglycaemia, and lowering HbA1c in reducing the risk of complications and death.</p> <p><b>CONCLUSIONS </b></p> Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes, and project events occurring over patients’ lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.


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