Using machine learning in the prediction of symptomatic venous thromboembolism following ankle fracture.

BACKGROUND: Venous thromboembolism (VTE) is a major cause of morbidity and mortality in the trauma setting, and both prediction and prevention of VTE have long been a concern for healthcare providers in orthopedic surgery. The purpose of this study was to evaluate the use of novel statistical analysis and machine-learning in predicting the risk of VTE and the usefulness of prophylaxis following ankle fractures. METHODS: The medical profiles of 16,421 patients with ankle fractures were screened retrospectively for symptomatic VTE. In total, 238 patients sustaining either surgical or nonsurgical treatment for ankle fracture with subsequently confirmed VTE within 180 days following the injury were placed in the case group. Alternatively, 937 patients who sustained ankle fractures managed similarly but had no documented evidence of VTE were randomly chosen as the control group. Individuals from both the case and control populations were also divided into those who had received VTE prophylaxis and those who had not. Over 110 variables were included. Conventional statistics and machine learning methods were used for data analysis. RESULTS: Patients who had a motor vehicle accident, surgical treatment, increased hospital stay, and were on warfarin were shown to have a higher incidence of VTE, whereas patients who were on statins had a lower incidence of VTE. The highest Area Under the Receiver Operating Characteristic Curves (AUROC) showing the performance of our machine learning approach was 0.88 with 0.94 sensitivity and 0.36 specificity. The most balanced performance was seen in a model that was trained using selected variables with 0.86 AUROC, 0.75 sensitivity, and 0.85 specificity. CONCLUSION: By using machine learning, this study successfully pinpointed several predictive factors linked to the occurrence or absence of VTE in patients who experienced an ankle fracture. Training these algorithms using larger, more granular, and multicentric data will further increase their validity and reliability and should be considered the standard for the development of such algorithms. LEVEL OF EVIDENCE: Case-Control study - 3.

Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.

BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and positively influence decision-making regarding prophylaxis. In this study, we aimed to investigate the correlation between statin consumption and the incidence of VTE in patients who sustained an ankle fracture. METHODS: In this retrospective, case-controlled study, cases were those who developed VTE and controls were those who had no VTE, and the ratio was 1:4. Patients' demographics, history of hyperlipidemia, and reported statins use were obtained. A random forest classifier (RFC) model was used to predict whether statin consumers were at risk of VTE after ankle fracture regardless of VTE prophylaxis administration based on statin consumption, body mass index (BMI), age, and biological sex. RESULTS: Of the 1175 patients with ankle fractures, 238 had confirmed VTE (case group), and 937 had no symptomatic VTE (control group; ratio 1:4). Fifty (21%) cases and 407 (43%) controls were on a statin. Statin users had a significantly lower incidence of VTE after ankle fracture, odds ratio (OR) = 0.35, 95% CI: 0.25, 0.49, P < .001. Our model showed an area under the receiving operator curve (AUROC) of 78%, a sensitivity of 73%, and a specificity of 83% in predicting the risk of VTE. The importance of the predictors of VTE, other than the use of statins (model importance = 0.1), were age (model importance of 0.72), BMI (model importance of 0.24), and biological sex (model importance of 0.02). CONCLUSION: Statins were significantly associated with a lower rate of VTE in our population of patients who sustained an ankle fracture. LEVELS OF EVIDENCE: 3.

Disparity in sex in ankle fracture treatment.

BACKGROUND: Literature has shown implicit bias in the treatment between non-operative and surgical treatment in patients with certain types of ankle fractures, which comprise 7.6% of all adult fractures. An understanding of any bias across all ankle fracture management may prove to be critical for the understanding of potential correlations between treatment methods and outcomes of patients with ankle fractures. Therefore, this study aimed to determine whether there is a sex-based bias in the operative and non-operative treatment of all ankle fractures. METHODS: A retrospective study of 1175 adult patients with ankle fractures was conducted. Data extracted included sex, race, age, type of treatment (non-operative/operative), fracture type (displaced/non-displaced), fracture class, BMI, and length of hospital stay. Odds ratio (OR), Chi-squared, t-test, and Pearson's correlation tests were used with p < 0.05 considered significant. RESULTS: The study population consisted of 750 females (63.8%) and 425 males (36.2%). The study demonstrated a sex-based disparity in operative and non-operative treatment revealing that women are less likely than men to receive operative treatment for displaced ankle fractures (OR = 0.7, 95% CI: 0.5-0.9, p = 0.01). Of the 750 females, 417 (55.6%) underwent non-operative treatment, while 333 (44.4%) females had an operation. Of the 425 males, 204 (48%) had non-operative treatment, while 221 (52%) underwent operative treatment. The distribution of ankle fracture classes between both sexes was similar, suggesting fracture class did not influence the observed disparity. CONCLUSION: Our results suggest sex correlates with the treatment type for ankle fractures, with women more likely to receive non-operative treatment for displaced fractures. As post-treatment outcomes often reflect the chosen form of treatment, it is imperative to determine if a disparity in sex explicates differences in clinical outcomes.

Outcomes of Closed versus Open Rhinoplasty: A Systematic Review.

Open and closed rhinoplasty are two main approaches to perform nasal modifications. According to current literature, there is no current consensus among plastic surgeons and otolaryngologists on which technique is preferred in terms of aesthetic result, complications, and patient satisfaction. This study uses published research to determine whether open or closed rhinoplasty leads to superior patient outcomes. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed and a literature search was conducted in four databases based on our search strategy. Articles were then imported into COVIDENCE where they underwent primary screening and full-text review. Twenty articles were selected in this study after 243 articles were screened. There were 4 case series, 12 retrospective cohort studies, 1 prospective cohort study, 1 case-control, and 2 outcomes research. There were three cosmetic studies, eight functional studies, and nine studies that included both cosmetic and functional components. Sixteen studies utilized both open and closed rhinoplasty and four utilized open rhinoplasty. Both techniques demonstrated high patient and provider satisfaction and no advantage was found between techniques. Based on available studies, we cannot conclude if there is a preference between open or closed rhinoplasty in terms of which technique leads to better patient outcomes. Several studies determined that open rhinoplasty and closed rhinoplasty leads to comparative patient satisfaction. To make outcome reporting more reliable and uniform among studies, authors should look to utilize the Nasal Obstruction and Septoplasty Effectiveness scale and the Rhinoplasty Outcome Evaluation.