Up and down waves of glycemic control and lower-extremity amputation in diabetes

Caruso, Paola; Scappaticcio, Lorenzo; Maiorino, Maria Ida; Esposito, Katherine; Giugliano, Dario

doi:10.1186/s12933-021-01325-3

Cited by 9 publications

(16 citation statements)

References 20 publications

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“… 60 Lower socioeconomic status, which can barely be altered, is associated with an elevated amputation risk in diabetics. 61 Optimal glucose control and diabetes medication like glucagon‐like peptide‐1 receptor agonists have shown beneficial effects on prevention of limb amputation, 62 , 63 whereas sodium glucose cotransporter 2 inhibitors are suspected of increasing the risk for amputation in PAD patients. 64 , 65 Emphasizing the high value of continuous monitoring, a UK study revealed a significant reduction of amputation rates after improving diabetic foot care.…”

Section: Discussionmentioning

confidence: 99%

Temporal trends in patients with peripheral artery disease influenced by diabetes mellitus in Germany

Schmitt

Hobohm

Vosseler

et al. 2022

Journal of Diabetes

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Introduction In patients with peripheral artery disease (PAD) the presence of diabetes mellitus (DM) is associated with higher morbidity and mortality. Because huge efforts are made to improve medical care of patients with DM including chronic disease programs, the aim of the present study was to investigate temporal trends regarding the clinical burden of DM on PAD patients within a 15‐year observational period. Methods We analyzed all patients hospitalized because of PAD between 2005 and 2019 in Germany stratified regarding DM. Results Overall, 2 654 871 hospitalizations of PAD patients (865 823 with DM) were included. Hospitalizations based on PAD inclined from 142 778 in 2005 to 190 135 in 2019 ( β 3956 per year; 95% confidence interval [CI] 3034–4878, p < .001) with simultaneous increase of hospitalizations of PAD patients with DM (2005: 41609 (29.1%) versus 2019: 65 302 (34.3%); β 2019 per year [95% CI 1593–2446], p < .001). Amputation rates ( β −0.42 [95% CI −0.44 to −0.40]; p < .001) as well as in‐hospital case‐fatality rate (2005: 4.7%, 2019: 2.8%; β −0.64 [95% CI −0.69 to −0.59]; p < .001) decreased in diabetic PAD patients during the observational time. In spite of improved morbidity and mortality in the last years of the observational period, patients with DM still suffered from an increased risk for morbidity and mortality during the observational period compared to nondiabetic PAD patients. Conclusions Despite the progress in DM treatments, DM still was associated with an unfavorable clinical patient profile and remained a substantial risk factor for morbidity and mortality in hospitalized patients with PAD and DM in Germany between 2005 and 2019.

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Section: Discussionmentioning

confidence: 99%

Temporal trends in patients with peripheral artery disease influenced by diabetes mellitus in Germany

Schmitt

Hobohm

Vosseler

et al. 2022

Journal of Diabetes

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“…Some studies have shown that intensive blood glucose control may lead to hypoglycemia [44][45][46][47]. Nevertheless, the relaxation of blood glucose control has contributed to the return of LEA based on an analysis of adult participants in the National Health and Nutrition Survey (NHANES) from 2010 to 2015 [48]. The Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial collected 10251 randomly selected type 2 diabetic patients at 77 locations in the United States and Canada.…”

Section: Plos Onementioning

confidence: 99%

Machine learning for the prediction of minor amputation in University of Texas grade 3 diabetic foot ulcers

Wang

Zhu

et al. 2022

PLoS ONE

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Minor amputations are performed in a large proportion of patients with diabetic foot ulcers (DFU) and early identification of the outcome of minor amputations facilitates medical decision-making and ultimately reduces major amputations and deaths. However, there are currently no clinical predictive tools for minor amputations in patients with DFU. We aim to establish a predictive model based on machine learning to quickly identify patients requiring minor amputation among newly admitted patients with DFU. Overall, 362 cases with University of Texas grade (UT) 3 DFU were screened from tertiary care hospitals in East China. We utilized the synthetic minority oversampling strategy to compensate for the disparity in the initial dataset. A univariable analysis revealed nine variables to be included in the model: random blood glucose, years with diabetes, cardiovascular diseases, peripheral arterial diseases, DFU history, smoking history, albumin, creatinine, and C-reactive protein. Then, risk prediction models based on five machine learning algorithms: decision tree, random forest, logistic regression, support vector machine, and extreme gradient boosting (XGBoost) were independently developed with these variables. After evaluation, XGBoost earned the highest score (accuracy 0.814, precision 0.846, recall 0.767, F1-score 0.805, and AUC 0.881). For convenience, a web-based calculator based on our data and the XGBoost algorithm was established (https://dfuprediction.azurewebsites.net/). These findings imply that XGBoost can be used to develop a reliable prediction model for minor amputations in patients with UT3 DFU, and that our online calculator will make it easier for clinicians to assess the risk of minor amputations and make proactive decisions.

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“…Diabetes-related complications, including acute myocardial infarctions, strokes and lower extremity amputations, increased by 25% between 2010 and 2015 among young adults (aged 18–44 years) and middle-aged adults (aged 45–64 years) in the USA 1. Accordingly, diabetes is associated with high rates of morbidity and disability due to chronic complications, particularly in the working-age population 1 2. Between 1995 and 2017, Global Burden of Diseases data showed that diabetes moved from seventh to fourth place in Italy in terms of disability-adjusted life years, which represent the number of years lost to disease, disability and premature death 3…”

Section: Introductionmentioning

confidence: 99%

Applications for social security benefits related to diabetes in the working age in Italy between 2009 and 2019: a nationwide retrospective cohort study

et al. 2022

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ObjectivesThe aim of this study is to estimate the average number of claims for social security benefits from workers with diabetes-related disability.DesignNationwide retrospective cohort study.SettingThe database of the Italian Social Security Institute (INPS) was used to analyse the trends and the breakdown of all claims for social security benefit with diabetes as primary diagnosis from 2009 to 2019.ParticipantsWe selected all the applications with the 250.xx International Classification of Diseases, Ninth Revision-CM diagnosis code from 2009 to 2019.Primary and secondary outcome measuresThe ratio between accepted or rejected claims for both ordinary incapacity benefit (OIB) and disability pension (DP) and total submitted claims over a 10-year period was computed.ResultsFrom 2009 to 2019, 40 800 applications for social security benefits were filed with diabetes as the principal diagnosis, with an annual increase of 30% per year. Throughout the study decade, there was a higher rate of rejected (67.2%) than accepted (32.8%) applications. Among the accepted requests, most of them (30.7%) were recognised as OIB and the remaining 2.1% were recognised as DP. When related to the total number of claims presented per year, there was a 8.8% decrease of rejected applications, associated with a 20.6% increase of overall acceptance rate. In terms of time trends, the overall rise of submitted requests from 2009 to 2019 resulted in an increase in both rejected (+18%) and accepted (+61% for OIB, +11% for DP) applications. The higher rate of accepted requests was for workers aged 51–60 years, with 52% of admitted applications.ConclusionsBetween 2009 and 2019, the number of applications for social security benefits due to diabetes in Italy increased significantly, and so did the number of applications approved, mainly represented by the OIBs.

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Up and down waves of glycemic control and lower-extremity amputation in diabetes

Cited by 9 publications

References 20 publications

Temporal trends in patients with peripheral artery disease influenced by diabetes mellitus in Germany

Temporal trends in patients with peripheral artery disease influenced by diabetes mellitus in Germany

Machine learning for the prediction of minor amputation in University of Texas grade 3 diabetic foot ulcers

Applications for social security benefits related to diabetes in the working age in Italy between 2009 and 2019: a nationwide retrospective cohort study

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