Prediction Model of Cardiac Risk for Dental Extraction in Elderly Patients with Cardiovascular Diseases.

BACKGROUND: With the rapidly increasing population of elderly people, dental extraction in elderly individuals with cardiovascular diseases (CVDs) has become quite common. The issue of how to assure the safety of elderly patients with CVDs undergoing dental extraction has perplexed dentists and internists for many years. And it is important to derive an appropriate risk prediction tool for this population. OBJECTIVES: The aim of this retrospective, observational study was to establish and validate a prediction model based on the random forest (RF) algorithm for the risk of cardiac complications of dental extraction in elderly patients with CVDs. METHODS: Between August 2017 and May 2018, a total of 603 patients who fulfilled the inclusion criteria were used to create a training set. An independent test set contained 230 patients between June 2018 and July 2018. Data regarding clinical parameters, laboratory tests, clinical examinations before dental extraction, and 1-week follow-up were retrieved. Predictors were identified by using logistic regression (LR) with penalized LASSO (least absolute shrinkage and selection operator) variable selection. Then, a prediction model was constructed based on the RF algorithm by using a 5-fold cross-validation method. RESULTS: The training set, based on 603 participants, including 282 men and 321 women, had an average participant age of 72.38 ± 8.31 years. Using feature selection methods, 11 predictors for risk of cardiac complications were screened out. When the RF model was constructed, its overall classification accuracy was 0.82 at the optimal cutoff value of 18.5%. In comparison to the LR model, the RF model showed a superior predictive performance. The AUROC (area under the receiver operating characteristic curve) scores of the RF and LR models were 0.83 and 0.80, respectively, in the independent test set. The AUPRC (area under the precision-recall curve) scores of the RF and LR models were 0.56 and 0.35, respectively, in the independent test set. CONCLUSION: The RF-based prediction model is expected to be applicable for preoperative clinical assessment for preventing cardiac complications in elderly patients with CVDs undergoing dental extraction. The findings may aid physicians and dentists in making more informed recommendations to prevent cardiac complications in this patient population.

[Changes in tissue plasminogen activator and plasminogen activator inhibitor during administration of nitroglycerine into internal thoracic artery in dogs with acute myocardial ischemia].

OBJECTIVE: To study the changes in tissue plasminogen activator (t-PA) and plasminogen activator inhibitor (PAI) in a model of acute myocardial infarction reproduced in the dog with administration of nitroglycerin into internal thoracic artery under pressure. METHODS: Sixty healthy cross-breed dogs were randomly divided into experimental and control group with 30 dogs in each group. The animal model of acute myocardial ischemia was reproduced by ligating the left anterior descending coronary artery. Internal thoracic artery in the experimental group was ligated, and a tube was introduced into the proximal end. Nitroglycerine was infused under pressure into the internal thoracic artery in experimental group. The drug was given intravenously in control group. t-PA and PAI were measured before anterior coronary artery ligation and at 0.5, 2 and 6 hours after coronary artery ligation. RESULTS: The t-PA levels in two groups were increased at 0.5 hour after coronary artery ligation, and gradually declined in control group, while no obvious change was found in experimental group. There was significant difference between experimental group and control group at 6 hours after coronary artery ligation(P<0.05). PAI levels were increased after coronary artery ligation, peaking at 6 and 2 hours after coronary artery ligation in both groups. Significant difference in PAI level was observed between two groups at 6 hours after coronary artery ligation(P<0.05). CONCLUSION: Introduction of nitroglycerine through internal thoracic artery under pressure is effective to accelerate release of t-PA from the endothelium while inhibit secretion of PAI, therefore it is useful to modulate the balance of fibrinolysis.