Derivation and validation of a clinical prediction model for assessing the risk of lower extremity amputation in patients with type 2 diabetes

Prediction model for lower limb amputation in hospitalized diabetic foot patients using classification and regression trees

BACKGROUND

The decision to perform amputation of a limb in a patient with diabetic foot ulcer (DFU) is not an easy task. Prediction models aim to help the surgeon in decision making scenarios. Currently there are no prediction model to determine lower limb amputation during the first 30 days of hospitalization for patients with DFU.

METHODS

Classification And Regression Tree analysis was applied on data from a retrospective cohort of patients hospitalized for the management of diabetic foot ulcer, using an existing database from two Orthopaedics and Traumatology departments. The secondary analysis identified independent variables that can predict lower limb amputation (mayor or minor) during the first 30 days of hospitalization.

RESULTS

Of the 573 patients in the database, 290 feet underwent a lower limb amputation during the first 30 days of hospitalization. Six different models were developed using a loss matrix to evaluate the error of not detecting false negatives. The selected tree produced 13 terminal nodes and after the pruning process, only one division remained in the optimal tree (Sensitivity: 69%, Specificity: 75%, Area Under the Curve: 0.76, Complexity Parameter: 0.01, Error: 0.85). Among the studied variables, the Wagner classification with a cut-off grade of 3 exceeded others in its predicting capacity.

CONCLUSIONS

Wagner classification was the variable with the best capacity for predicting amputation within 30 days. Infectious state and vascular occlusion described indirectly by this classification reflects the importance of taking quick decisions in those patients with a higher compromise of these two conditions. Finally, an external validation of the model is still required.

LEVEL OF EVIDENCE

III.

Risk of amputation under diuretics in patients with or at risk of lower extremity arterial disease: A systematic review and meta-analysis

BACKGROUND

Recently, increased risk of amputation under sodium glucose cotransporter-2 inhibitors has been debated. Similar concerns have been raised with other "traditional" diuretics, more particularly in patients with or at risk of lower extremity arterial disease (LEAD).

AIM

To collect all available data on any potential risk of amputation associated with diuretics in patients with or at risk of LEAD. Additionally, we looked for other limb-related events in these patients.

METHODS

We searched in PubMed, Embase and Scopus databases up to February 2021 for references, using peripheral or lower extremity arterial disease, diuretics and amputation keywords, excluding case reports, experimental animal studies and non-English reports.

RESULTS

Among the 1376 hits identified in the databases, six studies were finally included in this review, including one cross-sectional and five longitudinal studies (total of 47,612 participants). One study was limited to thiazide diuretics, one focused on loop diuretics and the remainder mixed all diuretics. All studies reported a significant association between diuretic use and amputation risk in patients with or at high risk of LEAD. Despite some limitations in several studies, the meta-analysis showed an increased risk of amputation associated with diuretics (odds ratio: 1.75, 95% confidence interval: 1.53-1.99; P<0.001). Beyond amputation, patients with or at risk of LEAD under diuretics appeared to be at increased risk of other lower limb events, mostly in the presence of other comorbidities, including diabetes.

CONCLUSIONS

Although the amount of data in the literature is scarce, this first systematic review and meta-analysis favours an increased risk of amputation in patients with or at risk of LEAD under diuretics. Further prospective studies must be conducted to provide a better understanding of the mechanisms. Meanwhile, the use of diuretics in these patients should be parsimonious, considering alternatives whenever possible.

Precision prognostics for the development of complications in diabetes

Individuals with diabetes face higher risks for macro- and microvascular complications than their non-diabetic counterparts. The concept of precision medicine in diabetes aims to optimise treatment decisions for individual patients to reduce the risk of major diabetic complications, including cardiovascular outcomes, retinopathy, nephropathy, neuropathy and overall mortality. In this context, prognostic models can be used to estimate an individual's risk for relevant complications based on individual risk profiles. This review aims to place the concept of prediction modelling into the context of precision prognostics. As opposed to identification of diabetes subsets, the development of prediction models, including the selection of predictors based on their longitudinal association with the outcome of interest and their discriminatory ability, allows estimation of an individual's absolute risk of complications. As a consequence, such models provide information about potential patient subgroups and their treatment needs. This review provides insight into the methodological issues specifically related to the development and validation of prediction models for diabetes complications. We summarise existing prediction models for macro- and microvascular complications, commonly included predictors, and examples of available validation studies. The review also discusses the potential of non-classical risk markers and omics-based predictors. Finally, it gives insight into the requirements and challenges related to the clinical applications and implementation of developed predictions models to optimise medical decision making.

A nationwide cohort investigation on pay-for-performance and major adverse limb events in patients with diabetes

A retrospective cohort study was conducted using claims data from Taiwan's National Health Insurance program to assess the effect of diabetic pay-for-performance (P4P) program on major adverse limb events (MALE) and major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). This study included patients with T2DM who had completed or not completed a 1-year P4P program from 2002 to 2013. Propensity-score matching was used to balance the baseline characteristics between groups. The Cox proportional-hazard model and Fine and Gray subdistribution hazard model were used to examine the association between P4P and the risks of MALE, MACE, systemic thromboembolism (ST), heart failure (HF) hospitalization, and all-cause mortality. Patients who underwent the P4P program had a significantly decreased incidence of MALE (2.0% vs. 2.6%, subdistribution hazard ratio [SHR] 0.73, 95% CI 0.71-0.76). Regarding the individual components, the P4P group demonstrated lower risks for foot ulcer (1.1% vs 1.3%, SHR 0.80, 95% CI 0.77-0.84), gangrene (0.57% vs 0.93%, SHR 0.59, 95% CI 0.56-0.63), percutaneous transluminal angioplasty (0.61% vs 0.79%, SHR 0.72, 95% CI 0.68-0.77), and amputation (0.46% vs 0.75%, SHR 0.58, 95% CI 0.55-0.62). In addition, the risks of MACE, ST, HF hospitalization, and all-cause mortality were remarkably lower in the P4P group. The P4P program might significantly reduce critical events of MALE, MACE, ST, HF, and mortality in the diabetic population.

Development and validation of a risk score model for prediction of lower extremity arterial disease in Chinese with type 2 diabetes aged over 50 years

BACKGROUND

Lower extremity arterial disease (LEAD) is highly prevalent in people with diabetes in China, but half of cases are underdiagnosed due to diversities of clinical presentations and complexities of diagnosis approaches. The purpose of this study was to develop a risk score model for LEAD to facilitate early screening among type 2 diabetes (T2DM) patients.

METHODS

A total of 8313 participants with T2DM from the China DIA-LEAD study, a multicenter, cross-sectional epidemiological study, were selected as the training dataset to develop a risk score model for LEAD by logistic regression. The area under receiver operating characteristic curve (AUC) and bootstrapping were utilized for internal validation. A dataset of 287 participants consecutively enrolled from a teaching hospital between July 2017 and November 2017 was used as external validation for the risk score model.

RESULTS

A total of 931 (11.2%) participants were diagnosed as LEAD in the training dataset. Factors including age, current smoking, duration of diabetes, blood pressure control, low density lipoprotein cholesterol, estimated glomerular filtration rate, and coexistence of cardio and/or cerebrovascular disease correlated with LEAD in logistic regression analysis and resulted in a weighed risk score model of 0-13. A score of ≥5 was found to be the optimal cut-off for discriminating moderate-high risk participants with AUC of 0.786 (95% CI: 0.778-0.795). The bootstrapping validation showed that the AUC was 0.784. Similar performance of the risk score model was observed in the validation dataset with AUC of 0.731 (95% CI: 0.651-0.811). The prevalence of LEAD was 3.4, 12.1, and 27.6% in the low risk (total score 0-4), moderate risk (total score 5-8), and high risk (total score 9-13) groups of LEAD in the training dataset, respectively, which were 4.3, 19.6, and 30.2% in the validation dataset.

CONCLUSION

The weighed risk score model for LEAD could reliably discriminate the presence of LEAD in Chinese with T2DM aged over 50 years, which may be helpful for a precise risk assessment and early diagnosis of LEAD.

Prognostic models for predicting the risk of foot ulcer or amputation in people with type 2 diabetes: a systematic review and external validation study

AIMS/HYPOTHESIS

Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic models can aid in targeted monitoring but an overview of their performance is lacking. This study aimed to systematically review prognostic models for the risk of foot ulcer or amputation and quantify their predictive performance in an independent cohort.

METHODS

A systematic review identified studies developing prognostic models for foot ulcer or amputation over minimal 1 year follow-up applicable to people with type 2 diabetes. After data extraction and risk of bias assessment (both in duplicate), selected models were externally validated in a prospective cohort with a 5 year follow-up in terms of discrimination (C statistics) and calibration (calibration plots).

RESULTS

We identified 21 studies with 34 models predicting polyneuropathy, foot ulcer or amputation. Eleven models were validated in 7624 participants, of whom 485 developed an ulcer and 70 underwent amputation. The models for foot ulcer showed C statistics (95% CI) ranging from 0.54 (0.54, 0.54) to 0.81 (0.75, 0.86) and models for amputation showed C statistics (95% CI) ranging from 0.63 (0.55, 0.71) to 0.86 (0.78, 0.94). Most models underestimated the ulcer or amputation risk in the highest risk quintiles. Three models performed well to predict a combined endpoint of amputation and foot ulcer (C statistics >0.75).

CONCLUSIONS/INTERPRETATION

Thirty-four prognostic models for the risk of foot ulcer or amputation were identified. Although the performance of the models varied considerably, three models performed well to predict foot ulcer or amputation and may be applicable to clinical practice.

Hypoglycaemia and Cardiovascular Disease Risk in Patients with Diabetes

Hypoglycaemia represents an important side effect of insulin therapy and insulin secretagogues. It can occur in both type 1 and type 2 diabetes mellitus patients. Also, some associations between hypoglycaemia and cardiovascular (CV) risk have been reported. Several mechanisms may be involved, including the sympathoadrenal system, hypokalaemia, endothelial dysfunction, coagulation, platelets, inflammation, atherothrombosis and impaired autonomic cardiac reflexes. This narrative review discusses the associations of hypoglycaemia with CV diseases, including coronary heart disease (CHD), cardiac arrhythmias, stroke, carotid disease and peripheral artery disease (PAD), as well as with dementia. Severe hypoglycaemia has been related to CHD, CV and all-cause mortality. Furthermore, there is evidence supporting an association between hypoglycaemia and cardiac arrhythmias, potentially predisposing to sudden death. The data linking hypoglycaemia with stroke, carotid disease and PAD is limited. Several factors may affect the hypoglycaemia-CV relationships, such as the definition of hypoglycaemia, patient characteristics, co-morbidities (including chronic kidney disease) and antidiabetic drug therapy. However, the association between hypoglycaemia and dementia is bilateral. Both the disorders are more common in the elderly; thus, glycaemic goals should be carefully selected in older patients. Further research is needed to elucidate the impact of hypoglycaemia on CV disease.

Associations between attainment of incentivized primary care indicators and incident lower limb amputation among those with type 2 diabetes: a population-based historical cohort study

INTRODUCTION

England has invested considerably in diabetes care through such programs as the Quality and Outcomes Framework (QOF) and National Diabetes Audit (NDA). Associations between program indicators and clinical endpoints, such as amputation, remain unclear. We examined associations between primary care indicators and incident lower limb amputation.

RESEARCH DESIGN AND METHODS

This population-based retrospective cohort study, spanning 2010-2017, was comprised of adults in England with type 2 diabetes and no history of lower limb amputation. Exposures at baseline (2010-2011) were attainment of QOF glycated hemoglobin (HbA1c), blood pressure and total cholesterol indicators, and number of NDA processes completed. Propensity score matching was performed and multivariable Cox proportional hazards models, adjusting for disease-related, comorbidity, lifestyle, and sociodemographic factors, were fitted using matched samples for each exposure.

RESULTS

83 688 individuals from 330 English primary care practices were included. Mean follow-up was 3.9 (SD 2.0) years, and 521 (0.6%) minor or major amputations were observed (1.62 per 1000 person-years). HbA1c and cholesterol indicator attainment were associated with considerably lower risks of minor or major amputation (adjusted HRs; 95% CIs) 0.61 (0.49 to 0.74; p<0.0001) and 0.67 (0.53 to 0.86; p=0.0017), respectively). No evidence of association between blood pressure indicator attainment and amputation was observed (adjusted HR 0.88 (0.73 to 1.06; p=0.1891)). Substantially lower amputation rates were observed among those completing a greater number of NDA care processes (adjusted HRs 0.45 (0.24 to 0.83; p=0.0106), 0.67 (0.47 to 0.97; p=0.0319), and 0.38 (0.20 to 0.70; p=0.0022) for comparisons of 4-6 vs 0-3, 7-9 vs 0-3, and 7-9 vs 4-6 processes, respectively). Results for major-only amputations were similar for HbA1c and blood pressure, though cholesterol indicator attainment was non-significant.

CONCLUSIONS

Comprehensive primary care-based secondary prevention may offer considerable protection against diabetes-related amputation. This has important implications for diabetes management and medical decision-making for patients, as well as type 2 diabetes quality improvement programs.