Materiały źródłowe

• #1 An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes | Scientific Reports

  https://www.nature.com/articles/s41598-024-53459-5

  Abdominal aortic aneurysms (AAA) have been rigorously investigated to understand when their clinically-estimated risk of rupturean event that is the 13th leading cause of death in the USexceeds the risk associated with repair. […] In this study, we train and assess machine learning models using clinical, biomechanical, and morphological indices from 381 patients to develop an aneurysm prognosis classifier to predict one of three outcomes for a given AAA patient: their AAA will remain stable, their AAA will require repair based as currently indicated from the maximum diameter criterion, or their AAA will rupture. […] The APC model therefore represents a potential clinical tool to striate specific patient outcomes using machine learning models and patient-specific image-based (biomechanical and morphological) and clinical data as input.

• #2 Current Prognostic Biomarkers for Abdominal Aortic Aneurysm: A Comprehensive Scoping Review of the Literature

  https://www.mdpi.com/2218-273X/14/6/661

  Abdominal aortic aneurysm (AAA) is a progressive dilatation of the aorta that can lead to aortic rupture. […] A total of 45 proteins were found to be potential prognostic biomarkers for AAA, predicting incidence of AAA, AAA rupture, AAA growth, endoleak, and post-surgical mortality. […] This review outlines the wide pathophysiological processes that are implicated in AAA disease progression. […] Patients with smaller AAAs (<5.5 cm) must be counselled for lifestyle changes, such as smoking cessation, and should begin medical management to control hypertension and hyperlipidemia to prevent the progression of the disease. [...] Therefore, finding predictive biomarkers for the prognosis of AAA at the time of diagnosis may be beneficial to risk stratify patients and monitor more closely those who are at a greater risk of complications and provide them with less invasive surgical strategies if required.

• #3 Abdominal Aortic Aneurysm: Practice Essentials, Anatomy, Pathophysiology

  https://emedicine.medscape.com/article/1979501-overview

  For patients who suffer rupture of an AAA before hospital arrival, the prognosis is guarded. More than 50% do not survive to reach the emergency department (ED); for those who do, the survival rate drops by about 1% per minute. However, in the subset of patients who are not in severe shock and who receive expert surgical intervention in a timely manner, the survival rate is more favorable. […] In 1988, 40,000 surgical reconstructions for AAA were performed in the United States, and substantial mortality differences between elective and emergency operations were noted. Because the mortality associated with elective aneurysm repair is drastically lower than that associated with repair of a ruptured AAA, the emphasis must be on early detection and repair free from complications. […] The long-term prognosis is related to associated comorbidities. Long-term survival is shortened by chronic heart failure and COPD. Rupture of associated TAAs is also an important cause of late death. Overall, AAA repair is very durable, with few long-term complications (5% false aneurysm). In general, the survival rate of patients with successful AAA repair is comparable to that of people in the age-matched population at large who have never had an aneurysm.

• #4 An artificial intelligence based abdominal aortic aneurysm prognosis classifier to predict patient outcomes | Scientific Reports

  https://www.nature.com/articles/s41598-024-53459-5

  Such a tool could greatly assist clinicians in their management decisions for patients with AAA. […] The survival curve shows that no patients in our study had surgical repair or rupture within the first year of aneurysm discovery, where the number of patients at risk was 17% or 65 patients over a 10-year period. […] Additionally, the survival curve reveals that 4 years after aneurysm discovery, the rate of repair or rupture stabilizes (i.e., levels-off without further events), and 83% of the studied patients made it 10 years without either rupture or need for repair. […] The APC model demonstrated the ability to striate AAA patients according to outcomes and represents a potentially important step towards the creation of a reliable, noninvasive, objective clinical decision support tool for aneurysm management. […] Throughout training of the hierarchical levels targeting every combination of categories, it was found that clinical indices alone are insufficient to striate patient outcomes and that imaging-based biomechanical and morphological quantification contributes significantly to ML approaches.

• #5 Prediction of in-hospital mortality after ruptured abdominal aortic aneurysm repair using an artificial neural network

  https://pmc.ncbi.nlm.nih.gov/articles/PMC4484301/

  Ruptured abdominal aortic aneurysm (rAAA) carries a high mortality rate, even with prompt transfer to a medical center. […] The goal of this study was to effectively use ANN modeling to provide vascular surgeons a discriminant adjunct to assess the likelihood of in-hospital mortality on a pending rAAA admission using easily obtainable patient information from the field. […] Five preoperative factors were significant (P .05) independent predictors of in-hospital mortality in multivariate analysis: advanced age, renal disease, loss of consciousness, cardiac arrest and shock, though renal disease was excluded from the models. […] The sequential accumulation of zero to four of these risk factors progressively increased overall mortality rate, from 11% to 16% to 44% to 76% to 89% (Age 70 considered a risk factor).

• #6 Risk factors for predicting survival after abdominal aortic aneurysm rupture – NCBI Bookshelf

  https://www.ncbi.nlm.nih.gov/books/NBK556908/

  Moderate-quality evidence from 1 retrospective cohort study, including 309 people with ruptured AAA, indicated that increasing age increased the odds of death within 48 hours of open surgical repair. […] Low- to moderate-quality evidence from 1 prospective and 10 retrospective cohort studies, including 178,994 people with ruptured AAA, indicated that the following risk factors increased the odds of death within 30 days (or within hospital) after EVAR or open surgical repair: […] Moderate- to high-quality evidence from 1 prospective and 1 retrospective cohort study, including 551 people with ruptured AAA, indicated that loss of consciousness and hypotension longer than 60 minutes increased the odds of death within 30 days (or in-hospital) of open surgical repair. […] Very low- to moderate-quality evidence from 2 retrospective cohort studies, including up to 2,567 people with ruptured AAA, indicated that increasing age, congestive heart disease, a history of cerebrovascular disease, cardiac arrest, loss of consciousness and a systolic blood pressure below 90 mmHg increased the odds of death within 5 years of EVAR or open surgical repair.

• #7 Predicting outcomes following open abdominal aortic aneurysm repair using machine learning | Scientific Reports

  https://www.nature.com/articles/s41598-025-98573-0

  Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post-operative complications. […] However, there are no widely used tools to predict surgical risk in this population. […] Currently, there are no standardized tools to predict adverse outcomes following open AAA repair. […] Therefore, there is an important need to develop better and more practical risk prediction tools for patients being considered for open AAA repair. […] Our automated ML algorithm can help guide risk-mitigation strategies for patients being considered for open AAA repair to improve outcomes. […] The primary outcome was 30-day post-procedural MACE, defined as a composite of myocardial infarction (MI), stroke, or death. […] Thirty-day post-procedural secondary outcomes included individual components of the primary outcome, any re-intervention, other morbidity, non-home discharge, and unplanned readmission.

• #8 Predicting outcomes following open abdominal aortic aneurysm repair using machine learning | Scientific Reports

  https://www.nature.com/articles/s41598-025-98573-0

  Our algorithms also predicted 30-day MI, stroke, death, re-intervention, other morbidity, non-home discharge, and unplanned readmission with AUROCs ranging from 0.81 to 0.91. […] Our model achieved good calibration with a Brier score of 0.03, indicating excellent agreement between predicted and observed event probabilities. […] We have developed robust ML-based prognostic models with excellent predictive ability for perioperative outcomes following open AAA repair, which may help guide clinical decision-making to improve outcomes and reduce costs from complications, reinterventions, and readmissions.

• #9 Prediction of in-hospital mortality after ruptured abdominal aortic aneurysm repair using an artificial neural network

  https://pmc.ncbi.nlm.nih.gov/articles/PMC4484301/

  An ANN-based predictive model may represent a simple, useful and highly discriminant adjunct to the vascular surgeon in accurately identifying those patients who may carry a high mortality risk from attempted repair of rAAA, using only easily definable preoperative variables. […] The goal of our study was to utilize an ANN model to accurately determine which patients are prone to in-hospital mortality after rAAA repair, using easily obtainable preoperative variables. […] The data from our ANN allow prediction of in-hospital mortality for surgical rAAA patients with greater discriminant ability than a multiple logistic regression model or the established GAS score. […] Using the ANN-4 training algorithm, postoperative in-hospital mortality was predicted with a high degree of accuracy (84%), and with 79% sensitivity and 88% specificity using an arbitrary output score of 0.5 as a cutoff for death.

• #10

  https://journals.lww.com/annalsofsurgery/fulltext/2023/01000/prediction_of_abdominal_aortic_aneurysm_growth.51.aspx

  We investigated the utility of geometric features for future AAA growth prediction. […] Novel methods for growth prediction of AAA are recognized as a research priority. […] Geometric features of an AAA can predict its future growth. This method can be applied to routine clinical CT scans acquired from patients during their AAA surveillance pathway. […] Methods for the prediction of AAA growth is considered as a priority for research in the opinions of vascular and endovascular surgeons. […] Accurate prediction of AAA growth in patients can allow for the optimization of surveillance intervals and better inform the timing for surgery. […] Using APD, UI, and RC as 3 input variables, the area under receiver operating characteristics curve for predicting slow growth (2.5 mm/yr) or fast growth (5 mm/yr) at 12 months are 0.80 and 0.79, respectively.

• #11

  https://journals.lww.com/annalsofsurgery/fulltext/2023/01000/prediction_of_abdominal_aortic_aneurysm_growth.51.aspx

  The prediction or growth rate is within 2 mm error in 87% of cases. […] There were significant positive correlations between AAA size (Spearman r = 0.25, P 0.05) and UI (Spearman r = 0.38, P 0.001) with annual AAA growth rate. […] A significant negative correlation between minimum RC and annual AAA growth rate was observed. (Spearman r=-0.53, P 0.001). […] Different combinations of input features (APD, UI, and RC) were used to train multiple logistic regression models. […] The area under receiver operation curve for predicting slow growth (2.5 mm/yr) and prediction fast growth (5mm/yr) is 0.80 and 0.79, respectively. […] This model comprising of 3 variables significantly outperforms the use of AAA diameter alone as the predictor (P 0.01). […] Predictions from this model were significantly correlated (r = 0.61, P 0.001) and closer (RMSE: 1.32 1.44 mm) to that of observed measurements than that of the other models. […] This model is able to predict annual AAA growth to within 2 mm error in 87% of cases.

• #12 Current Prognostic Biomarkers for Abdominal Aortic Aneurysm: A Comprehensive Scoping Review of the Literature

  https://www.mdpi.com/2218-273X/14/6/661

  By identifying prognostic biomarkers for AAA, we hope to further understand the mechanisms behind the initiation of this disease, as well as set the groundwork for future research which may allow for further validation of these markers to be used in a clinical setting. […] This review has outlined some of the single proteins and their ability to predict outcomes. […] There is a need for a marker or a panel of markers that can be used to risk stratify patients with AAA to determine those who may progress faster or are at a higher risk of AAA.

• #13 Prognostic prediction models for endovascular abdominal aortic aneurysm repair: protocol for a scoping review | BMJ Open

  https://bmjopen.bmj.com/content/12/10/e061420

  Endovascular aneurysm repair (EVAR) has a marked short-term advantage over open surgical repair in managing abdominal aortic aneurysms (AAA); however, this benefit is lost in the long term. […] The current trend towards stratified medicine has given rise to diverse prognostic prediction models and scoring systems for EVAR. […] These models could act as decision support tools that employ patient and operative factors, to improve long-term outcomes. […] The proposed study will use a scoping review approach to capture literature on prognostic modelling in EVAR for all predictable outcomes. […] The results are anticipated to inform future research, identify knowledge gaps, and assist in determining the potential of models for clinical use. […] There has been a growing interest in the development of prediction models to address these challenges.

• #14 Prognostic prediction models for endovascular abdominal aortic aneurysm repair: protocol for a scoping review | BMJ Open

  https://bmjopen.bmj.com/content/12/10/e061420

  Prognostic prediction models could be employed as stratified medicine tools to support decision-making on suitability for endovascular repair, controlling procedural complications and post-EVAR surveillance requirements. […] Despite their potential utility, their use in practice is currently limited. […] The Society for Vascular Surgery (SVS) practice guidelines reference the Vascular Study Group of New England (VSGNE) risk model, which uses anatomical features such as aneurysm diameter, neck length and level of clamp placement to calculate perioperative mortality. […] Although the model was validated and endorsed by the Vascular Quality Initiative database, the guidelines gave it a recommendation level of 2 (weak) and graded the quality of evidence as C (low). […] A 2017 systematic review on prediction models in EVAR compared the performance of 13 prediction models for mortality after EVAR.

• #15 Prognostic prediction models for endovascular abdominal aortic aneurysm repair: protocol for a scoping review | BMJ Open

  https://bmjopen.bmj.com/content/12/10/e061420

  The authors found that the British Aneurysm Repair score and the Vascular Biochemistry and Hematology Outcome Model came out on top, even outperforming the VSGNE risk model. […] However, they reported that both these models lacked enough validation to be used in clinical practice. […] The study also highlighted that although there were many new models, the existing models were not getting updated, nor were they externally validated well enough for generalised use. […] Another recent paper systematically reviewed 29 studies on predictors of reinterventions after EVAR to guide risk-stratified surveillance for patients. […] The study reported that models had a critical weakness in their development process, in that most were based on retrospective studies rather than prospective studies.

• #16 Risk factors for predicting survival after abdominal aortic aneurysm rupture – NCBI Bookshelf

  https://www.ncbi.nlm.nih.gov/books/NBK556908/

  The committee agreed there was reasonable evidence that some symptoms, signs, risk factors and assessment tools were associated with postoperative outcomes but they could not identify specific factors that were strong enough to inform the decision on whether or how to operate on people with ruptured AAA. […] The committee agreed that the evidence identified on risk assessment tools failed to show that individual tools could be used determine how a person with a ruptured AAA should be treated.

• #17 Prognostic prediction models for endovascular abdominal aortic aneurysm repair: protocol for a scoping review | BMJ Open

  https://bmjopen.bmj.com/content/12/10/e061420

  It similarly concluded that existing models needed to be subjected to more external validation to be used for stratified surveillance. […] Due to several gaps in the existing literature, it is difficult to assess whether EVAR prognostic models can currently make the transition into clinical practice. […] Systematic reviews on the subject have been performed; however, the most recent papers were published in 2017 and only included data up until 2015. […] It is likely that advancements have been in model development, validation and study conduct over the years; an update is necessary. […] Furthermore, previous systematic reviews only evaluated models for mortality and reintervention risk prediction. […] There are no reviews on models predicting other important outcomes such as case complexity, costs and specific preoperative, perioperative or postoperative complications.

• #18 Prognostic prediction models for endovascular abdominal aortic aneurysm repair: protocol for a scoping review | BMJ Open

  https://bmjopen.bmj.com/content/12/10/e061420

  Although both the reviews and SVS guidelines highlighted a need for improvement in the quality of evidence for EVAR prognostic models, there is no current review that assessed and compared the risk of bias (RoB), applicability, or completeness of reporting for modelling studies. […] Filling these gaps requires a thorough review of the literature that captures the present state of research into prognostic modelling for EVAR. […] This will allow for a full dissection of current research practices and an indication of whether the key improvements have been made. […] Subsequently, it will assist in identifying knowledge gaps and expediting factors for bringing models into clinical practice. […] The results of the study could inform the value of performing a systematic review, developing new models or validating existing models. […] Considering the broad nature of the goals to be met, a scoping review is the most appropriate method.

Zobacz więcej