Dataset Information

A Decision Tree Analysis of Diabetic Foot Amputation Risk in Indian Patients.

ABSTRACT:

Aim

The aim of this study is to create an evidence-based tool that guides the risk of amputation in diabetic foot patients.

Materials and methods

Hospital records of 301 diabetic foot patients were examined retrospectively for explanatory variables of foot amputation decisions. The study included all patients with a lower limb ulcer with a known history of diabetes mellitus or those diagnosed post-admission. The dataset was analyzed, and a risk scoring system was constructed using the decision tree algorithm, C5.0. Two classifiers, one simple and another complex, were constructed for predicting amputation outcome.

Results and discussion

Based on our evaluation, the most influential predictors for a decision to amputate are Doppler flow measurements and the Wagner grading of the ulceration. The simple classifier uses just these two parameters in determining risk. The results obtained show an accuracy of 96.4% in the primary group and an accuracy of 94% in the test group. The second classifier is a more complex computer-derived construct that showed 100% accuracy in the principle group and an accuracy of 96% during testing.

Conclusion

In the present era of precision medicine, these two classifiers act as an accurate guide to the prognosis of the limb in patients with diabetic foot and can predict the risk of future amputation.

SUBMITTER: Kasbekar PU

PROVIDER: S-EPMC5313600 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

A Decision Tree Analysis of Diabetic Foot Amputation Risk in Indian Patients.

Kasbekar Prasad Umesh PU Goel Pranay P Jadhav Shailaja Prakash SP

Frontiers in endocrinology 20170217

<h4>Aim</h4>The aim of this study is to create an evidence-based tool that guides the risk of amputation in diabetic foot patients.<h4>Materials and methods</h4>Hospital records of 301 diabetic foot patients were examined retrospectively for explanatory variables of foot amputation decisions. The study included all patients with a lower limb ulcer with a known history of diabetes mellitus or those diagnosed post-admission. The dataset was analyzed, and a risk scoring system was constructed using ...[more]

PMID: 28261156

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Project description:BACKGROUND:Diabetes mellitus is a major global health issue with a growing prevalence. In this context, the number of diabetic complications is also on the rise, such as diabetic foot ulcers (DFU), which are closely linked to the risk of lower extremity amputation (LEA). Statistical prediction tools may support clinicians to initiate early tertiary LEA prevention for DFU patients. Thus, we designed Bayesian prediction models, as they produce transparent decision rules, quantify uncertainty intuitively and acknowledge prior available scientific knowledge. METHOD:A logistic regression using observational collected according to the standardised PEDIS classification was utilised to compute the six-month amputation risk of DFU patients for two types of LEA: 1.) any-amputation and 2.) major-amputation. Being able to incorporate information which is available before the analysis, the Bayesian models were fitted following a twofold strategy. First, the designed prediction models waive the available information and, second, we incorporated the a priori available scientific knowledge into our models. Then, we evaluated each model with respect to the effect of the predictors and validity of the models. Next, we compared the performance of both models with respect to the incorporation of prior knowledge. RESULTS:This study included 237 patients. The mean age was 65.9 (SD 12.3), and 83.5% were male. Concerning the outcome, 31.6% underwent any- and 12.2% underwent a major-amputation procedure. The risk factors of perfusion, ulcer extent and depth revealed an impact on the outcomes, whereas the infection status and sensation did not. The major-amputation model using prior information outperformed the uninformed counterpart (AUC 0.765 vs AUC 0.790, Cohen's d 2.21). In contrast, the models predicting any-amputation performed similarly (0.793 vs 0.790, Cohen's d 0.22). CONCLUSIONS:Both of the Bayesian amputation risk models showed acceptable prognostic values, and the major-amputation model benefitted from incorporating a priori information from a previous study. Thus, PEDIS serves as a valid foundation for a clinical decision support tool for the prediction of the amputation risk in DFU patients. Furthermore, we demonstrated the use of the available prior scientific information within a Bayesian framework to establish chains of knowledge.

Project description:To examine the association between use of statin and nonstatin cholesterol-lowering medications and risk of nontraumatic major lower extremity amputations (LEAs) and treatment failure (LEA or death).A retrospective cohort of patients with Type I and Type 2 diabetes mellitus (diabetes) was followed for 5 years between 2004 and 2008. The follow-up exposure duration was divided into 90-day periods. Use of cholesterol-lowering agents, diabetic medications, hemoglobin A1c, body mass index, and systolic and diastolic blood pressures were observed in each period. Demographic factors were observed at baseline. Major risk factors of LEA including peripheral neuropathy, peripheral artery disease, and foot ulcers were observed at baseline and were updated for each period. LEA and deaths were assessed in each period and their hazard ratios (HRs) were estimated. The study took place in the U.S. Department of Veterans Affairs Healthcare system, and the subjects consisted of cholesterol drug-naïve patients with Type I or II diabetes who were treated in the U.S. Department of Veterans Affairs Healthcare system in 2003 and were <65 years old at the end of follow-up.Of 83,953 patients in the study cohort, 217 (0.3%) patients experienced a major LEA and 11,716 (14.0%) patients experienced an LEA or death (treatment failure) after a mean follow-up of 4.6 years. Compared with patients who did not use cholesterol-lowering agents, statin users were 35% to 43% less likely to experience an LEA (HR, 0.65; 95% confidence interval [CI], 0.42-0.99) and a treatment failure (HR, 0.57; 95% CI, 0.54-0.60). Users of other cholesterol-lowering medications were not significantly different in LEA risk (HR, 0.95; 95% CI, 0.35-2.60) but had a 41% lower risk of treatment failure (HR, 0.59; 95% CI, 0.51-0.68).This is the first study to report a significant association between statin use and diminished amputation risk among patients with diabetes. In this nonrandomized cohort, beneficial effects of statin therapy were similar to that seen in large-scale clinical trial experience. For LEA risk, those given nonstatins did not have a statistically significant benefit and its effect on LEA risk was much smaller compared with statins. Unanswered questions to be explored in future studies include a comparison of statins of moderate vs high potency in those with high risk of coronary heart disease and an exploration of whether the effects seen in this study are simply effects of cholesterol-lowering or possibly pleiotropic effects.

Dataset Information

A Decision Tree Analysis of Diabetic Foot Amputation Risk in Indian Patients.

Aim

Materials and methods

Results and discussion

Conclusion

Publications

A Decision Tree Analysis of Diabetic Foot Amputation Risk in Indian Patients.

Similar Datasets

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