Using the Revised Cardiac Risk Index to Predict Major Postoperative Events for People With Kidney Failure: An External Validation and Update

Cardiac Troponin as a Prognostic Indicator for Major Adverse Cardiac Events in Non-Cardiac Surgery: A Narrative Review

A major adverse cardiac event (MACE) following non-cardiac surgery encompasses critical postoperative cardiovascular complications such as myocardial infarction or injury, cardiac arrest, or stroke that are associated with increased perioperative morbidity, mortality, and healthcare resource utilisation. Cardiac troponin (cTn), particularly high-sensitivity cardiac troponin (hs-cTn), has emerged as a key biomarker for prediction of MACE. Despite its recognised utility, there is no consensus on how cTn levels should be used for standardised postoperative surveillance. Interpretation of the cTn levels may vary depending on sex-specific reference values and baseline comorbidities such as chronic kidney disease, sepsis, critical illness, and non-ischaemic conditions. The balance between cost-effectiveness and clinical benefit in implementing universal versus targeted postoperative hs-cTn screening remains to be fully explored. This review examines the prognostic value of cardiac troponin (cTn) levels in predicting major adverse cardiovascular events (MACEs) in patients undergoing non-cardiac surgery, with a focus on perioperative cTn elevations-particularly those associated with myocardial injury after non-cardiac surgery (MINS)-as potential early indicators of increased cardiovascular risk.

A New Risk Prediction Model for the Assessment of Myocardial Injury in Elderly Patients Undergoing Non-Elective Surgery

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.

Revised cardiac risk index in predicting cardiovascular complications in patients receiving chronic kidney replacement therapy undergoing elective general surgery

INTRODUCTION

The Revised Cardiac Risk Index (RCRI) is a six-parameter model that is commonly used in assessing individual 30-day perioperative cardiovascular risk before general surgery, but its use in patients on chronic kidney replacement therapy (KRT) is unvalidated. This study aimed to externally validate RCRI in this patient group over a 15-year period.

METHODS

Data linkage was used between the the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry and jurisdictional hospital admisisons data across Australia and New Zealand to identify all incident and prevalent patients on chronic KRT between 2000 and 2015 who underwent elective abdominal surgery. Chronic KRT was categorised as haemodialysis (HD), peritoneal dialysis (PD), home haemodialysis (HHD) and kidney transplant. The outcome of interest was major adverse cardiovascular event (MACE) which was defined as nonfatal myocardial infarction, nonfatal stroke, non-fatal cardiac arrest and cardiovascular mortality at 30 days. Logistic regression was used with the RCRI score included as a continuous variable to estimate discrimination by area under the receiver operating curve (AUROC). Calibration was evaluated using a calibration plot. Clinical utility was assessed using a decision curve analysis to determine the net benefit.

RESULTS

A total of 5094 elective surgeries were undertaken, and MACE occurred in 153 individuals (3.0%). Overall, RCRI had poor discrimination in patients on chronic KRT undergoing elective surgery (AUROC 0.67), particularly in patients aged greater than 65 years (AUROC 0.591). A calibration plot showed that RCRI overestimated risk of MACE. The expected-to-observed outcome ratio was 6.0, 5.1 and 2.5 for those with RCRI scores of 1, 2 and ≥ 3, respectively. Discrimination was moderate in patients under 65 years and in kidney transplant recipients, with AUROC values of 0.740 and 0.718, respectively. Overestimation was common but less so for kidney transplant recipients. Decision curve analysis showed that there was no net benefit of using the tool in neither the overall cohort nor patients under 65 years, but a slight benefit associated with threshold probability > 5.5% in kidney transplant recipients.

CONCLUSIONS

The RCRI tool performed poorly and overestimated risk in patients on chronic dialysis, potentially misinforming patients and clinicians about the risk of elective surgery. Further research is needed to define a more comprehensive means of estimating risk in this unique population.

Postoperative Outcomes After Gastrointestinal Surgery in Patients Receiving Chronic Kidney Replacement Therapy: A Population-based Cohort Study

OBJECTIVE

This study evaluated the postoperative mortality and morbidity outcomes following the different subtypes of gastrointestinal (GI) surgery over a 15-year period.

BACKGROUND

Patients receiving chronic kidney replacement therapy (KRT) experience higher rates of general surgery compared with other surgery types. Contemporary data on the types of surgeries and their outcomes are lacking. KRT was defined as patients requiring chronic dialysis (hemodialysis or peritoneal dilaysis) or having a functioning kidney transplant long-term.

METHODS

All incident and prevalent patients aged greater than 18 years identified in the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry as receiving chronic KRT were linked with jurisdictional hospital admission datasets between January 1, 2000 until December 31, 2015. Patients were categorized by their KRT modality [hemodialysis (HD), peritoneal dialysis (PD), home hemodialysis (HHD), and kidney transplant (KT)]. GI surgeries were categorized as upper gastrointestinal (UGI), bowel (small and large bowel), anorectal, hernia surgery, cholecystectomy, and appendicectomy. The primary outcome was the rates of the different surgeries, estimated using Poisson models. Secondary outcomes were risks of 30-day/in-hospital postoperative mortality risk and nonfatal outcomes and were estimated using logistic regression. Independent predictors of 30-day mortality were examined using comorbidity-adjusted Cox models.

RESULTS

Overall, 46,779 patients on chronic KRT were linked to jurisdictional hospital datasets, and 9,116 patients were identified as having undergone 14,540 GI surgeries with a combined follow-up of 76,593 years. Patients on PD had the highest rates of GI surgery (8 per 100 patient years), with hernia surgery being the most frequent. Patients on PD also had the highest risk of 30-day postoperative mortality following the different types of GI surgery, with the risk being more than 2-fold higher after emergency surgery compared with elective procedures. Infective postoperative complications were more common than cardiac complications. This study also observed a U-shaped association between body mass index (BMI) and mortality, with a nadir in the 30 to 35 kg/m 2 group.

CONCLUSIONS

Patients on chronic KRT have high rates of GI surgery and morbidity, particularly in those who receive PD, are older, or are either underweight or moderately obese.

Prediction of major postoperative events after non-cardiac surgery for people with kidney failure: derivation and internal validation of risk models

BACKGROUND

People with kidney failure often require surgery and experience worse postoperative outcomes compared to the general population, but existing risk prediction tools have excluded those with kidney failure during development or exhibit poor performance. Our objective was to derive, internally validate, and estimate the clinical utility of risk prediction models for people with kidney failure undergoing non-cardiac surgery.

DESIGN, SETTING, PARTICIPANTS, AND MEASURES

This study involved derivation and internal validation of prognostic risk prediction models using a retrospective, population-based cohort. We identified adults from Alberta, Canada with pre-existing kidney failure (estimated glomerular filtration rate [eGFR] < 15 mL/min/1.73m² or receipt of maintenance dialysis) undergoing non-cardiac surgery between 2005-2019. Three nested prognostic risk prediction models were assembled using clinical and logistical rationale. Model 1 included age, sex, dialysis modality, surgery type and setting. Model 2 added comorbidities, and Model 3 added preoperative hemoglobin and albumin. Death or major cardiac events (acute myocardial infarction or nonfatal ventricular arrhythmia) within 30 days after surgery were modelled using logistic regression models.

RESULTS

The development cohort included 38,541 surgeries, with 1,204 outcomes (after 3.1% of surgeries); 61% were performed in males, the median age was 64 years (interquartile range [IQR]: 53, 73), and 61% were receiving hemodialysis at the time of surgery. All three internally validated models performed well, with c-statistics ranging from 0.783 (95% Confidence Interval [CI]: 0.770, 0.797) for Model 1 to 0.818 (95%CI: 0.803, 0.826) for Model 3. Calibration slopes and intercepts were excellent for all models, though Models 2 and 3 demonstrated improvement in net reclassification. Decision curve analysis estimated that use of any model to guide perioperative interventions such as cardiac monitoring would result in potential net benefit over default strategies.

CONCLUSIONS

We developed and internally validated three novel models to predict major clinical events for people with kidney failure having surgery. Models including comorbidities and laboratory variables showed improved accuracy of risk stratification and provided the greatest potential net benefit for guiding perioperative decisions. Once externally validated, these models may inform perioperative shared decision making and risk-guided strategies for this population.