Preoperative Cardiac Risk Assessment

Raslau, David; Bierle, Dennis M.; Stephenson, Christopher R.; Mikhail, Michael A.; Kebede, Esayas; Mauck, Karen F.

doi:10.1016/j.mayocp.2019.08.013

Cited by 19 publications

(13 citation statements)

References 44 publications

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“…For example, an early systematic review and our recent preliminary study with meta-analysis identified pre-existing cardiac disease and comorbidity such as hypertension as significant risk factors for higher risk of cardiotoxicity when cancer patients underwent fluoropyrimidine-based treatments [34,35]. Two other review studies reported a > 5% surgical cardiac risk of bowel-related surgery, as well as a > 3% high cardiovascular risk for general abdominal or intraperitoneal surgery, with an even higher risk of myocardial infarction and major adverse cardiovascular events in adults aged 75 years or older (9.5% vs. 4.8% for younger adults) [36,37]. Older age and hypertension were also reported as significant risk factors in the clinical practice guidelines on the primary prevention of cardiovascular disease [38].…”

Section: Discussionmentioning

confidence: 99%

Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy

Chen

Chou

et al. 2021

Cardiovasc Toxicol

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Cardiotoxicity is a severe side effect for colorectal cancer (CRC) patients undergoing fluoropyrimidine-based chemotherapy. To develop and compare machine learning algorithms to predict cardiotoxicity risk among nationally representative CRC patients receiving fluoropyrimidine, CRC Patients with at least one claim of fluoropyrimidine after their cancer diagnosis were included. The outcome was the 30-day cardiotoxicity from the first day of starting fluoropyrimidine. The machine learning models including extreme gradient boosting (XGBoost), random forest (RF), and logistic regression (LR) were developed using 2006-2011 SEER-Medicare data, and model performances were evaluated using 2012-2014 data. Precision, F1 score, and area under the receiver operating characteristics curve (AUC) were measured to evaluate model performances. Feature importance plots were obtained to quantify the predictor importance. Among 36,030 CRC patients, 18.74% of them developed cardiotoxicity within 30 days since the first fluoropyrimidine. The XGBoost approach had better prediction performance with higher precision (0.619) and F1 score (0.406) in predicting the 30-day cardiotoxicity, compared to the RF (precision, 0.607 and F1 score, 0.395) and LR (precision, 0.610 and F1 score, 0.398). According to the DeLong's test for AUC difference, the XGBoost significantly outperformed the RF and LR (XGBoost, 0.816 vs. RF, 0.804, P < 0.001; XGBoost vs. LR, 0.812, P = 0.003, respectively). Feature importance plots identified pre-existing cardiac conditions, surgery, older age as top significant risk factors for cardiotoxicity events among CRC patients after receiving fluoropyrimidine. In summary, the developed machine learning models can accurately predict the occurrence of 30-day cardiotoxicity among CRC patients receiving fluoropyrimidine-based chemotherapy.

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Section: Discussionmentioning

confidence: 99%

Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy

Chen

Chou

et al. 2021

Cardiovasc Toxicol

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“…Brain natriuretic peptide (BNP) or its N-terminal prohormone, for example, were shown to be validly associated with the incidence of myocardial injury, as well as with major adverse cardiac events after non-cardiac surgery [ 23 , 24 ]. Therefore, preoperative BNP assessment for perioperative cardiac risk stratification is recommended by recent national guidelines [ 25 , 26 ]. It was demonstrated that the predictive power of score-based screening tools for perioperative risk assessment was significantly improved when combined with biomarkers [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Perioperative Vascular Biomarker Profiling in Elective Surgery Patients Developing Postoperative Delirium: A Prospective Cohort Study

et al. 2021

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Background: Postoperative delirium (POD) ranks among the most common complications in surgical patients. Blood-based biomarkers might help identify the patient at risk. This study aimed to assess how serum biomarkers with specificity for vascular and endothelial function and for inflammation are altered, prior to or following surgery in patients who subsequently develop POD. Methods: This was a study on a subcohort of consecutively recruited elective non-cardiac as well as cardiac surgery patients (age > 60 years) of the single-center PROPDESC trial at a German tertiary care hospital. Serum was sampled prior to and following surgery, and the samples were subjected to bead-based multiplex analysis of 17 serum proteins (IL-3, IL-8, IL-10, Cripto, CCL2, RAGE, Resistin, ANGPT2, TIE2, Thrombomodulin, Syndecan-1, E-Selectin, VCAM-1, ICAM-1, CXCL5, NSE, and uPAR). Development of POD was assessed during the first five days after surgery, using the Confusion Assessment Method for ICU (CAM-ICU), the CAM, the 4-’A’s test (4AT), and the Delirium Observation Scale (DOS). Patients were considered positive if POD was detected at least once during the visitation period by any of the applied methods. Non-parametric testing, as well as propensity score matching were used for statistical analysis. Results: A total of 118 patients were included in the final analysis; 69% underwent non-cardiac surgery, median overall patient age was 71 years, and 59% of patients were male. In the whole cohort, incidence of POD was 28%. The male gender was significantly associated with the development of POD (p = 0.0004), as well as a higher ASA status III (p = 0.04). Incidence of POD was furthermore significantly increased in cardiac surgery patients (p = 0.002). Surgery induced highly significant changes in serum levels of almost all biomarkers except uPAR. In preoperative serum samples, none of the analyzed parameters was significantly altered in subsequent POD patients. In postoperative samples, CCL2 was significantly increased by a factor of 1.75 in POD patients (p = 0.03), as compared to the no-POD cohort. Following propensity score matching, CCL2 remained the only biomarker that showed significant differences in postoperative values (p = 0.01). In cardiac surgery patients, postoperative CCL2 serum levels were more than 3.5 times higher than those following non-cardiac surgery (p < 0.0001). Moreover, after cardiac surgery, Syndecan-1 serum levels were significantly increased in POD patients, as compared to no-POD cardiac surgery patients (p = 0.04). Conclusion: In a mixed cohort of elective non-cardiac as well as cardiac surgery patients, preoperative serum biomarker profiling with specificity for vascular dysfunction and for systemic inflammation was not indicative of subsequent POD development. Surgery-induced systemic inflammation—as evidenced by the significant increase in CCL2 release—was associated with POD, particularly following cardiac surgery. In those patients, postoperative glycocalyx injury might furthermore contribute to POD development.

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“…Patients with cirrhosis are at increased risk of perioperative complications, including Compiled from resources in the reference list. [16][17][18][19][20][21]23,24 bleeding, thromboembolism, poor wound healing, pulmonary complications, delirium, hepatic failure, renal dysfunction, and death. 7 General perioperative risk assessment principles discussed in previous entries in this series should be applied.…”

Section: Perioperative Management Of Cirrhotic Liver Diseasementioning

confidence: 99%

“…7 General perioperative risk assessment principles discussed in previous entries in this series should be applied. 23 Early evaluation by a multispecialty team may be beneficial for patients being considered for elective or semi-urgent surgery. Patients being considered for urgent or emergency surgery may benefit from the expertise at a facility experienced in cirrhosis management, such as a transplant-based medical center.…”

Section: Perioperative Management Of Cirrhotic Liver Diseasementioning

confidence: 99%

Preoperative Evaluation and Management of Patients With Select Chronic Gastrointestinal, Liver, and Renal Diseases

Bierle

Wight

Ganesh

et al. 2022

Mayo Clinic Proceedings

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Preoperative Cardiac Risk Assessment

Cited by 19 publications

References 44 publications

Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy

Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy

Perioperative Vascular Biomarker Profiling in Elective Surgery Patients Developing Postoperative Delirium: A Prospective Cohort Study

Preoperative Evaluation and Management of Patients With Select Chronic Gastrointestinal, Liver, and Renal Diseases

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