Prediction models for amputation after diabetic foot: systematic review and critical appraisal

BACKGROUND

Numerous studies have developed or validated prediction models aimed at estimating the likelihood of amputation in diabetic foot (DF) patients. However, the quality and applicability of these models in clinical practice and future research remain uncertain. This study conducts a systematic review and assessment of the risk of bias and applicability of amputation prediction models among individuals with DF.

METHODS

A comprehensive search was conducted across multiple databases, including PubMed, Web of Science, EBSCO CINAHL Plus, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, Chinese Biomedical Literature Database (CBM), and Weipu (VIP) from their inception to December 24, 2023. Two investigators independently screened the literature and extracted data using the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability.

RESULTS

A total of 20 studies were included in this analysis, comprising 17 development studies and three validation studies, encompassing 20 prediction models and 11 classification systems. The incidence of amputation in patients with DF ranged from 5.9 to 58.5%. Machine learning-based methods were employed in more than half of the studies. The reported area under the curve (AUC) varied from 0.560 to 0.939. Independent predictors consistently identified by multivariate models included age, gender, HbA1c, hemoglobin, white blood cell count, low-density lipoprotein cholesterol, diabetes duration, and Wagner's Classification. All studies were found to exhibit a high risk of bias, primarily attributed to inadequate handling of outcome events and missing data, lack of model performance assessment, and overfitting.

CONCLUSIONS

The assessment using PROBAST revealed a notable risk of bias in the existing prediction models for amputation in patients with DF. It is imperative for future studies to concentrate on enhancing the robustness of current prediction models or constructing new models with stringent methodologies.

Predicting amputation using machine learning: A systematic review

Amputation is an irreversible, last-line treatment indicated for a multitude of medical problems. Delaying amputation in favor of limb-sparing treatment may lead to increased risk of morbidity and mortality. This systematic review aims to synthesize the literature on how ML is being applied to predict amputation as an outcome. OVID Embase, OVID Medline, ACM Digital Library, Scopus, Web of Science, and IEEE Xplore were searched from inception to March 5, 2023. 1376 studies were screened; 15 articles were included. In the diabetic population, models ranged from sub-optimal to excellent performance (AUC: 0.6-0.94). In trauma patients, models had strong to excellent performance (AUC: 0.88-0.95). In patients who received amputation secondary to other etiologies (e.g.: burns and peripheral vascular disease), models had similar performance (AUC: 0.81-1.0). Many studies were found to have a high PROBAST risk of bias, most often due to small sample sizes. In conclusion, multiple machine learning models have been successfully developed that have the potential to be superior to traditional modeling techniques and prospective clinical judgment in predicting amputation. Further research is needed to overcome the limitations of current studies and to bring applicability to a clinical setting.

A Data-Driven Method to Discriminate Limb Salvage from Other Combat-Related Extremity Trauma

INTRODUCTION

The aim of this study was to address and enhance our ability to study the clinical outcome of limb salvage (LS), a commonly referenced but ill-defined clinical care pathway, by developing a data-driven approach for the identification of LS cases using existing medical code data to identify characteristic diagnoses and procedures, and to use that information to describe a cohort of US Service members (SMs) for further study.

METHODS

Diagnosis code families and inpatient procedure codes were compiled and analyzed to identify medical codes that are disparately associated with a LS surrogate population of SMs who underwent secondary amputation within a broader cohort of 3390 SMs with lower extremity trauma (AIS > 1). Subsequently, the identified codes were used to define a cohort of all SMs who underwent lower extremity LS which was compared with the opinion of a panel of military trauma surgeons.

RESULTS

The data-driven approach identified a population of n = 2018 SMs who underwent LS, representing 59.5% of the combat-related lower extremity (LE) trauma population. Validation analysis revealed 70% agreement between the data-driven approach and gold standard SME panel for the test cases studied. The Kappa statistic (κ = 0.55) indicates a moderate agreement between the data-driven approach and the expert opinion of the SME panel. The sensitivity and specificity were identified as 55.6% (expert range of 51.8-66.7%) and 87% (expert range of 73.9-91.3%), respectively.

CONCLUSIONS

This approach for identifying LS cases can be utilized to enable future high-throughput retrospective analyses for studying both short- and long-term outcomes of this underserved patient population.

Outcomes Following Below Knee Arterial Trauma

INTRODUCTION

Lower extremity vascular injuries have significant implications for trauma patients with regards to morbidity from limb loss. There is limited evidence on outcomes for patients with injuries to tibial arteries. Our study focuses on defining outcomes of traumatic vascular injury to vessels below the knee.

METHODS

A retrospective review using ICD-9 and 10 codes of all patients with below knee vascular injuries was performed at a Level 1 trauma center from November 2014 to June 2022. Interventions, outcomes, and complications were assessed.

RESULTS

Seventy-six patients were identified fitting inclusion criteria. The mean age was 35.3 +/- 15.2 years and 67 (88%) patients were male. Thirty-nine suffered penetrating trauma, 37 suffered blunt trauma. The most injured artery was posterior tibial artery (40%) followed by anterior tibial artery (36%). Injuries included 51 transections, 22 occlusions and 4 pseudoaneurysms. Forty-five (59%) patients underwent operative intervention. Thirty (67%) operations were performed by trauma surgery. Arterial ligation was performed in 30 cases (67%), arterial bypass in 12 (27%), and 2 (4%) primary amputations. Vascular surgery performed all bypasses. Overall amputation rate was 8% (n = 6) with 3 for mangled extremity and 3 due to failed bypass graft. All amputations were associated with open fracture and amputations for failed bypass had multiple arterial injuries.

CONCLUSION

The management of below knee vascular trauma requires a multidisciplinary approach. Patients requiring reconstruction are more likely to have multiple vessel injuries and may have significant risk of graft failure. These patients as well as those with extensive soft tissue injury and/or multi-vessel injuries are at increased risk for amputation.

THE MANAGEMENT OF THE VICTIMS WITH GUNSHOT WOUNDS OF THE EXTREMITIES WITH EXTENSIVE DEFECTS OF THE SOFT TISSUES AT THE LEVEL OF QUALIFIED MEDICAL CARE. CASE-SERIES

OBJECTIVE

The aim: To highlight the original experience of diagnosis and treatment of patients with gunshot wounds of the extremities with extensive defects of the soft tissues.

PATIENTS AND METHODS

Materials and methods: The total number of treated patients with massive gunshot wounds from February 2022 to March 2023 was 60 males. Basic labo¬ratory tests, X-rays of the affected limbs were performed to all patients. USS of the vessels with color Doppler was performed to those casualties who had no peripheral pulses on the wounded extremity. All injured persons underwent wound debridement and fasciotomy on the day of admission, 8 more casualties underwent surgical interventions on the major vessels and nerves.

RESULTS

Results: Good treatment outcomes for patients with extensive soft tissue injury were achieved by early surgical intervention to remove non-viable tissue. Limb preservation was achieved in 98.3% of cases.

CONCLUSION

Conclusions: The study's conclusion emphasizes the importance of a multidisciplinary approach to treating patients with gunshot wounds to the limbs with extensive soft tissue injury. Early surgical interventions with the removal of non-viable tissues are necessary for good outcomes. Revascularization of the affected limb is essential in case of major vessel injury if there is no thread to the life.

Pattern of upper limb amputation associated with lower limb amputation: the UK military experience from Iraq and Afghanistan

INTRODUCTION

The conflicts in Iraq and Afghanistan resulted in large numbers of personnel sustaining extremity injuries. In the context of polytrauma, partial hand amputation is often unrecorded. The aim of this work was to quantify the burden of upper limb (UL) amputation at any level occurring concurrently with a major (ankle and proximal) lower limb (LL) amputation. Knowledge of this cohort could aid in prosthetic modification to further improve quality of life outcomes in a population with dexterity loss.

METHOD

A trauma database search was undertaken for all UK military LL amputees from the conflicts in Iraq and Afghanistan. A manual search method was employed to identify from the major LL amputees those who had a concurrent UL amputation at any level (including isolated finger amputation). Demographics, level of amputation, and injury profile data were recorded.

RESULTS

Sixty-eight individuals were identified; the most prevalent population was bilateral LL with a unilateral UL amputation (60%). Most UL amputations were partial hand (75%). The was no statistically significant difference between left or right side (p=0.13). On the left side, correlation was found between amputation of the thumb and third digit (rho=0.34; p=0.005) not seen on the right.

CONCLUSION

We have determined the rate of UL amputation at any level, in combination with LL amputation as a result of blast injury. Knowledge of these combinations enables further research to support anecdotal evidence that there is a need for tailored prosthetics in the context of potential dexterity loss making donning and doffing problematic.