The Assessment of Risk in Cardiothoracic Intensive Care (ARCtIC): prediction of hospital mortality after admission to cardiothoracic critical care

Perioperative care in cardiac surgery

As mortality is now low for many cardiac surgical procedures, there has been an increasing focus on patient centered outcomes such as recovery and quality of life. The Enhanced Recovery After Surgery (ERAS) cardiac society recently published the first set of guidelines for cardiac surgery which will be useful as a starting point to help translate this philosophy for the benefit of those undergoing cardiac surgery. At the same time there are many advances in other areas such as mechanical circulation, diagnostics and quality metrics. We intend here to present a balanced and evidenced based review of selected aspects of current practice, encompassing both UK and international perioperative care with a focus on recent advances. For the convenience of the reader we will adopt the conventional perioperative preoperative, intraoperative and postoperative phases of care. The focus of cardiac surgical practice needs to evolve from mortality to recovery. Those specialists who work in cardiac anaesthesia and critical care are well placed to contribute to these changes. Accompanying this work is the development of technologies to improve recognition of and intervention to prevent early organ dysfunction. Measuring, benchmarking and publishing quality outcomes from cardiac surgical centres is likely to improve services and benefit our patients.

Mortality Prediction After Cardiac Surgery: Higgins' Intensive Care Unit Admission Score Revisited

BACKGROUND

This study was performed to develop and validate a cardiac surgical intensive care risk adjustment model for mixed cardiac surgery based on a few preoperative laboratory tests, extracorporeal circulation time, and measurements at arrival to the intensive care unit.

METHODS

This was a retrospective study of admissions to 5 cardiac surgical intensive care units in Sweden that submitted data to the Swedish Intensive Care Registry. Admissions from 2008 to 2014 (n = 21,450) were used for model development, whereas admissions from 2015 to 2016 (n = 6463) were used for validation. Models were built using logistic regression with transformation of raw values or categorization into groups.

RESULTS

The final model showed good performance, with an area under the receiver operating characteristics curve of 0.86 (95% confidence interval, 0.83-0.89), a Cox calibration intercept of -0.16 (95% confidence interval, -0.47 to 0.19), and a slope of 1.01 (95% confidence interval, 0.89-1.13) in the validation cohort.

CONCLUSIONS

Eleven variables available on admission to the intensive care unit can be used to predict 30-day mortality after cardiac surgery. The model performance was better than those of general intensive care risk adjustment models used in cardiac surgical intensive care and also avoided the subjective assessment of the cause of admission. The standardized mortality ratio improves over time in Swedish cardiac surgical intensive care.

Acute Risk Change: An Innovative Measure of Operative Adverse Events and Perioperative Team Performance

OBJECTIVES

Cardiac surgical risk models predict mortality preoperatively, whereas intensive care unit (ICU) models predict mortality postoperatively. Finding a large difference between the 2 (an acute risk change [ARC]) may reflect an alteration in the status of the patient related to the surgery. An adverse ARC was associated with morbidity and mortality in an Australian population. The aims of this study were to validate ARC in a UK population and to investigate the possible mechanisms behind ARC.

DESIGN

This was a retrospective case-control study.

SETTING

Single, high-volume cardiothoracic hospital.

PARTICIPANTS

Data from 4,842 cardiac surgical patients were collected between 2013 and 2015.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

EuroSCORE was recalibrated to each preceding year's data. ARC was defined as postoperative minus preoperative percentage mortality risk. Association among ARC, morbidity, and mortality was tested. Cases with large adverse ARC (greater than +15%) were compared with cases with large favorable ARC (less than -10%) with regard to intraoperative adverse events, unmeasured patient risk factors, and postoperative events. Adverse ARC was associated with hospital mortality, ICU stay, ICU readmission, renal support, prolonged intubation and return to the operating room (p < 0.001). Intraoperative adverse events occurred in 23 of 33 patients with adverse ARC; however, only 2 of 17 patients with favorable ARC reported adverse events (p < 0.001). Unmeasured risk factors were present in 48% of patients in the adverse ARC group.

CONCLUSION

ARC is a readily available and sensitive marker that correlates strongly with morbidity and mortality. The use of ARC in local and national quality monitoring could identify areas for improvement of the quality of cardiac surgical care.