Search Results (11)

Background: Preparing patients for surgery considers assessing the patient’s somatic health, for example by the American Society of Anesthesiology (ASA) scale or the Revised Cardiac Risk Index (RCRI), known as the Lee index. This process usually ignores mental functioning (personality and anxiety), which is known to influence health. The purpose of this study is to analyze the existence of a relationship between personality traits (the Big Five model and trait-anxiety) and anesthesia scales (ASA scale, Lee index) used for the preoperative evaluation of patients. Methods: The study group comprised 102 patients (59 women, 43 men) scheduled for hip replacement surgery. Patients completed two psychological questionnaires: the NEO-FFI (NEO Five Factors Inventory) and the X-2 STAI (State-Trait Anxiety Inventory) sheet. Next, the presence and possible strength of the relationship between personality traits and demographic and medical variables were analyzed using Spearman’s rho rank correlation coefficient. Results: Patients with a high severity of trait anxiety are classified higher on the ASA scale (rs = 0.359; p < 0.001). Neuroticism, defined according to the Big Five model, significantly correlates with scales of preoperative patient assessment: the ASA classification (rs = 0.264; p < 0.001) and the Lee index (rs = 0.202; p = 0.044). A hierarchical regression model was created to test the possibility of predicting ASA scores based on personality. It explained more than 34% of the variance and was a good fit to the data (p < 0.05). The controlled variables of age and gender accounted for more than 23% of the variance. Personality indicators (trait anxiety, neuroticism) additionally accounted for slightly more than 11% of the variance. Trait anxiety (Beta = 0.293) proved to be a better predictor than neuroticism (Beta = 0.054). Conclusions: These results indicate that inclusion of personality screening in the preoperative patient evaluation might help to introduce a more individualized approach to patients, which could result in better surgical outcomes. Full article

The rate of major surgery is constantly increasing worldwide, and approximately 85% are non-cardiac surgery. More than half of patients over 45 years presenting for non-cardiac surgical interventions have cardiovascular risk factors, and the most common: chronic coronary syndrome and history of stroke. The preoperative cardiovascular risk is determined by the comorbidities, the clinical condition before the intervention, the urgency, duration or type. Cardiovascular risk scores are necessary tools to prevent perioperative cardiovascular morbidity and mortality and the most frequently used are Lee/RCRI (Revised Cardiac Risk Index), APACHE II (Acute Physiology and Chronic Health Evaluation), POSSUM (Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity), The American University of Beirut (AUB)-HAS2. To reduce the perioperative risk, there is a need for an appropriate preoperative risk assessment, as well as the choice of the type and timing of surgical intervention. Quantification of surgical risk as low, intermediate, and high is useful in identifying the group of patients who are at risk of complications such as myocardial infarction, thrombosis, arrhythmias, heart failure, stroke or even death. Currently there are not enough studies that can differentiate the risk according to gender, race, elective versus emergency procedure, the value of cardiac biomarkers. Full article

Background: Currently, recommended pre-operative risk assessment models including the revised cardiac risk index (RCRI) are not very effective in predicting postoperative myocardial damage after non-elective surgery, especially for elderly patients. Aims: This study aimed to create a new risk prediction model to assess myocardial injury after non-cardiac surgery (MINS) in elderly patients and compare it with the RCRI, a well-known pre-operative risk prediction model. Materials and Methods: This retrospective study included 370 elderly patients who were over 65 years of age and had non-elective surgery in a tertiary hospital. Each patient underwent detailed physical evaluations before the surgery. The study cohort was divided into two groups: patients who had MINS and those who did not. Results: In total, 13% (48 out of 370 patients) of the patients developed MINS. Multivariable analysis revealed that creatinine, lymphocyte, aortic regurgitation (moderate-severe), stroke, hemoglobin, ejection fraction, and D-dimer were independent determinants of MINS. By using these parameters, a model called “CLASHED” was developed to predict postoperative MINS. The ROC analysis comparison demonstrated that the new risk prediction model was significantly superior to the RCRI in predicting MINS in elderly patients undergoing non-elective surgery (AUC: 0.788 vs. AUC: 0.611, p < 0.05). Conclusions: Our study shows that the new risk preoperative model successfully predicts MINS in elderly patients undergoing non-elective surgery. In addition, this new model is found to be superior to the RCRI in predicting MINS. Full article

Karst rocky desertification (KRD) is a significant issue that affects the ecological and economic sustainability of southwest China. Obtaining the accurate distribution of different levels of KRD can provide decision-making support for the effective management of KRD. The Sustainable Development Goals Science Satellite 1 (SDGSAT-1) is the world’s first scientific satellite serving the 2030 Agenda for Sustainable Development of the United Nations, and is dedicated to developing high-resolution, multi-scale, global public datasets to support policy and decision-making support systems for sustainable development. SDGSAT-1 multispectral data provide detailed ground information with a spatial resolution of 10 m and a rich spectral resolution. In this study, we combined the red-modified carbonate rock index (RCRI, an index that characterizes the degree of carbonate rock exposure) and the normalized difference red edge index (NDRE, an index that characterizes the degree of vegetation coverage) to propose a novel feature space method based on SDGSAT-1 multispectral data to classify the different levels of KRD in the Jinsha County of Guizhou Province, a representative region with significant KRD in southwest China. This method effectively identified different levels of KRD with an overall classification accuracy of 87%. This was 20% higher than that of the grading index method, indicating that SDGSAT-1 multispectral data have promising potential for KRD classification. In this study, we offer a new insight into the classification of KRD and a greater quantity of remote-sensing data to monitor KRD over a wider area and for a longer period of time, contributing to the economic development and environmental protection of KRD areas. Full article

Objectives: The role of inflammation in the pathophysiology of atherosclerosis is extensive. Our study aims to assess the predictive role of inflammatory indexes regarding in-hospital mortality in major vascular surgery of Leriche syndrome as a convenient, low-cost, and noninvasive prognostic marker to optimize the patient’s perioperative course. Methods: Our retrospective single-center study enrolled consecutive patients diagnosed with aortoiliac occlusive disease, Leriche syndrome, who underwent elective major vascular surgery between 2017 and 2023 in a tertiary cardiovascular center. Preoperative, postoperative, and day-one after-surgery data, including systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio, and monocyte–lymphocyte ratio, were studied to the endpoint, in-hospital death. We also tested the delta values of the indexes to the endpoint. The indexes were compared to the Revised Cardiac Risk Index (RCRI) and Vascular Surgery Group Cardiac Risk Index (VSG-CRI) for outcome prediction. Results: The tested inflammatory indexes significantly increased from the preoperative to postoperative and, further, to the day-one settings. Preoperative AISI (p = 0.040) emerged as the only independent risk factor regarding in-hospital death occurrence in Leriche patients who underwent major revascularization surgery. While RCRI did not significantly predict the endpoint (AUC = 0.698, p = 0.057), VSG-CRI (AUC = 0.864, p = 0.001) presented the best result in ROC analysis. Postoperative NLR (AUC = 0.758, p = 0.006) was next, followed by NLR postoperative–preoperative (_Preop-_Postop) delta value (AUC = 0.725, p = 0.004), postoperative SIRI (AUC = 0.716, p = 0.016), SIRI_Preop-_Postop delta value (AUC = 0.712, p = 0.016), postoperative SII (AUC = 0.692, p = 0.032), and SII_Preop-_Postop delta value (AUC = 0.631, p = 0.030). Conclusions: Inflammatory indexes are valuable tools for assessing perioperative risk in major vascular surgery, enhancing the value of the already validated risk scores. Full article

The Revised Cardiac Risk Index (RCRI) and the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) preoperative risk assessment tools are the most widely used methods for quantifying the risk of major negative perioperative cardiac outcomes that a patient may face during and after noncardiac surgery. However, these tools were created to include as wide a range of surgical factors as possible; thus, some predictive accuracy is sacrificed when it comes to certain surgical subpopulations. In this review, we explore the various surgical oncology patient populations for whom these assessment tools can be reliably applied and for whom they demonstrate poor reliability. Full article

Background: Long-term survival after emergency colorectal cancer surgery is low, and its estimation is most frequently neglected, with priority given to the immediate prognosis. This study aimed to propose an effective nomogram to predict overall survival in these patients. Materials and methods: We retrospectively studied 437 patients who underwent emergency surgery for colorectal cancer between 2008 and 2019, in whom we analyzed the clinical, paraclinical, and surgical parameters. Results: Only 30 patients (6.86%) survived until the end of the study. We identified the risk factors through the univariate Cox regression analysis and a multivariate Cox regression model. The model included the following eight independent prognostic factors: age > 63 years, Charlson score > 4, revised cardiac risk index (RCRI), LMR (lymphocytes/neutrophils ratio), tumor site, macroscopic tumoral invasion, surgery type, and lymph node dissection (p < 0.05 for all), with an AUC (area under the curve) of 0.831, with an ideal agreement between the predicted and observed probabilities. On this basis, we constructed a nomogram for prediction of overall survival. Conclusions: The nomogram created, on the basis of a multivariate logistic regression model, has a good individual prediction of overall survival for patients with emergency surgery for colon cancer and may support clinicians when informing patients about prognosis. Full article

Background: The goal of cardiac evaluation of patients awaiting orthotopic liver transplantation (OLT) is to identify the patients at risk for cardiovascular events (CVEs) in the peri- and postoperative periods by opportunistic evaluation of coronary artery calcium (CAC) in non-gated abdominal computed tomographs (CT). Methods: We hypothesized that in patients with OLT, a combination of Lee’s revised cardiac index (RCRI) and CAC scoring would improve diagnostic accuracy and prognostic impact compared to non-invasive cardiac testing. Therefore, we retrospectively evaluated 169 patients and compared prediction of CVEs by both methods. Results: Standard workup identified 22 patients with a high risk for CVEs during the transplant period, leading to coronary interventions. Eighteen patients had a CVE after transplant and a CAC score > 0. The combination of CAC and RCRI ≥ 2 had better negative (NPV) and positive predictive values (PPV) for CVEs (NPV 95.7%, PPV 81.6%) than standard non-invasive stress tests (NPV 92.0%, PPV 54.5%). Conclusion: The cutoff value of CAC > 0 by non-gated CTs combined with RCRI ≥ 2 is highly sensitive for identifying patients at risk for CVEs in the OLT population. Full article

Major adverse cardiac events, defined as death or myocardial infarction, are common causes of perioperative mortality and major morbidity in patients undergoing non-cardiac surgery. Reduction of perioperative cardiovascular risk in relation to non-cardiac surgery requires a stepwise patient evaluation that integrates clinical risk factors, functional status and the estimated stress of the planned surgical procedure. Major guidelines on preoperative cardiovascular risk assessment recommend to establish, firstly, the risk of surgery per se (low, moderate, high) and the related timing (elective vs. urgent/emergent), evaluate the presence of unstable cardiac conditions or a recent coronary revascularization (percutaneous coronary intervention or coronary artery bypass grafting), assess the functional capacity of the patient (usually expressed in metabolic equivalents), determine the value of non-invasive and/or invasive cardiovascular testing and then combine these data in estimating perioperative risk for major cardiac adverse events using validated scores (Revised Cardiac Risk Index (RCRI) or National Surgical Quality Improvement Program (NSQIP)). This stepwise approach has the potential to guide clinicians in determining which patients could benefit from cardiovascular therapy and/or coronary artery revascularization before non-cardiac surgery towards decreasing the incidence of perioperative morbidity and mortality. Finally, it should be highlighted that there is a need to implement specific strategies in the 2019 Coronavirus disease (COVID-19) pandemic to minimize the risk of transmission of COVID-19 infection during the preoperative risk assessment process. Full article

Hip fracture patients have a high risk of mortality after surgery, with 30-day postoperative rates as high as 10%. This study aimed to explore the predictive ability of preoperative characteristics in traumatic hip fracture patients as they relate to 30-day postoperative mortality using readily available variables in clinical practice. All adult patients who underwent primary emergency hip fracture surgery in Sweden between 2008 and 2017 were included in the analysis. Associations between the possible predictors and 30-day mortality was performed using a multivariate logistic regression (LR) model; the bidirectional stepwise method was used for variable selection. An LR model and convolutional neural network (CNN) were then fitted for prediction. The relative importance of individual predictors was evaluated using the permutation importance and Gini importance. A total of 134,915 traumatic hip fracture patients were included in the study. The CNN and LR models displayed an acceptable predictive ability for predicting 30-day postoperative mortality using a test dataset, displaying an area under the ROC curve (AUC) of as high as 0.76. The variables with the highest importance in prediction were age, sex, hypertension, dementia, American Society of Anesthesiologists (ASA) classification, and the Revised Cardiac Risk Index (RCRI). Both the CNN and LR models achieved an acceptable performance in identifying patients at risk of mortality 30 days after hip fracture surgery. The most important variables for prediction, based on the variables used in the current study are age, hypertension, dementia, sex, ASA classification, and RCRI. Full article

Background and objective: The incidence of postoperative complications and death is low in the general population, but a subgroup of high-risk patients can be identified amongst whom adverse postoperative outcomes occur more frequently. The present study was undertaken to describe the incidence of postoperative complications, length of stay, and mortality after major abdominal surgery for gastrointestinal, hepatobiliary and pancreatic malignancies and to identify the risk factors for impaired outcome.
Material and methods: Data of patients, operated on for gastro-intestinal malignancies during 2009–2010 were retrieved from the clinical database of Tartu University Hospital. Major outcome data included incidence of postoperative complications, hospital-, 30-day, 90-day and 1-year mortality, and length of ICU and hospital stay. High-risk patients were defined as patients with American Society of Anesthesiologists (ASA) physical status ≥3 and revised cardiac risk index (RCRI) ≥3. Multivariate analysis was used to determine the risk factors for postoperative mortality and morbidity.
Results: A total of 507 (259 men and 248 women, mean age 68.3
11.3 years) were operated on for gastrointestinal, hepatobiliary, or pancreatic malignancies during 2009 and 2010 in Tartu University Hospital, Department of Surgical Oncology. 25% of the patients were classified as high risk patients. The lengths of intensive care and hospital stay were 4.4
7 and 14.5
10 days, respectively. The rate of postoperative complications was 33.5% in the total cohort, and 44% in high-risk patients. The most common complication was delirium, which occurred in 12.8% of patients. For patients without high risk (ASA < III; RCRI < 3) in-hospital, 30-, 90-day and 1-year mortality were 2%, 5%, 12.7% and 26.0%. Patients with ASA ≥ III and RCRI ≥ 3 had 2.3% in-hospital mortality, and at 30-, 90 days and 1 year the mortality was 8.5%, 17.8%, and 42.2%, respectively (P = 0.001, P < 0.0001 and P < 0.0001 compared to the lower risk patients). On multivariate analysis, age above 70 years, ASA ≥ III, RCRI ≥ 3, duration of surgery >130 min, and positive fluid balance >1300 mL after the 1st postoperative day, were identified as independent risk factors for the development of complications.
Conclusion: The complication rate after major gastro-intestinal surgery is high. ASA physical status and revised cardiac risk index adequately reflect increased risk for postoperative complications and worse short and long-term outcome. Full article