Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting

Bartkowiak, Bartlomiej; Snyder, Ashley; Benjamin, Andrew; Schneider, Andrew; Twu, Nicole M.; Churpek, Matthew M.; Roggin, Kevin K.; Edelson, Dana P.

doi:10.1097/sla.0000000000002665

Cited by 54 publications

(78 citation statements)

References 16 publications

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“…Discrimination by NEWS, as measured by the area under the ROC curve (0.75), was less in our postoperative population than typically reported in acute medical populations (> 0.85). A recent large, single‐centre North American study reported a similar area (0.76) for a general postoperative population . A continuous logistic risk score has previously been demonstrated to offer better discriminatory performance than an additive score in general ward admissions .…”

Section: Discussionmentioning

confidence: 86%

Logistic early warning scores to predict death, cardiac arrest or unplanned intensive care unit re‐admission after cardiac surgery

Chiu

Villar

Brand³

et al. 2019

Anaesthesia

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Summary NHS England recently mandated that the National Early Warning Score of vital signs be used in all acute hospital trusts in the UK despite limited validation in the postoperative setting. We undertook a multicentre UK study of 13,631 patients discharged from intensive care after risk‐stratified cardiac surgery in four centres, all of which used VitalPACTM to electronically collect postoperative National Early Warning Score vital signs. We analysed 540,127 sets of vital signs to generate a logistic score, the discrimination of which we compared with the national additive score for the composite outcome of: in‐hospital death; cardiac arrest; or unplanned intensive care admission. There were 578 patients (4.2%) with an outcome that followed 4300 sets of observations (0.8%) in the preceding 24 h: 499 out of 578 (86%) patients had unplanned re‐admissions to intensive care. Discrimination by the logistic score was significantly better than the additive score. Respective areas (95%CI) under the receiver‐operating characteristic curve with 24‐h and 6‐h vital signs were: 0.779 (0.771–0.786) vs. 0.754 (0.746–0.761), p < 0.001; and 0.841 (0.829–0.853) vs. 0.813 (0.800–0.825), p < 0.001, respectively. Our proposed logistic Early Warning Score was better than the current National Early Warning Score at discriminating patients who had an event after cardiac surgery from those who did not.

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Section: Discussionmentioning

confidence: 86%

Logistic early warning scores to predict death, cardiac arrest or unplanned intensive care unit re‐admission after cardiac surgery

Chiu

Villar

Brand³

et al. 2019

Anaesthesia

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“…Most validation of NEWS has been in acute admissions and medical in-patients, settings in which it appears to perform well; there is less validity in elective surgical settings and non-medical specialities. These findings have encouraged researchers to develop specialty-specific scores and, within these subpopulations, the predictive value of a generic EWS suffers in comparison [5,6]. The potential inference is that one standardised EWS may not apply with accuracy to all types of patients and all relevant critical illness events.…”

Section: Validationmentioning

confidence: 99%

Improving early warning scores – more data, better validation, the same response

Oglesby¹,

Sterne

Gibbison

2019

Anaesthesia

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“…We saw that cancer patients who experienced IHCA had higher alanine aminotransferase, alkaline phosphatase, and INR on admission. These parameters have been included in several scoring systems that predict cardiac arrest in general floor patients [ 5 ]. Renal and hepatic function tests are available for most patients on admission and these derangements should be given consideration when triaging patients.…”

Section: Discussionmentioning

confidence: 99%

“…Electronic-Cardiac Arrest Risk Triage (e-CART) is a scoring system that incorporates ward vital signs as well as laboratory results and demographics for combined prediction of cardiac arrest, intensive care unit (ICU) transfer, and death [ 4 ]. Multiple studies have validated their use in real-time [ 5 ]. These scoring systems predict the probability of an adverse event in the general patient population and help physicians make timely interventions to prevent cardiac arrest or death.…”

Section: Introductionmentioning

confidence: 99%

Possible Predictive Factors for In-hospital Cardiac Arrest in Patients with Cancer: A Retrospective Single Center Study

Sardar

Shaikh

Malik

et al. 2018

Cureus

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Background: Despite cancer being the second most common cause of death in the United States, more people are living longer after the diagnosis of cancer than before. Healthcare workers will be treating an increasing number of patients with cancer. Various studies have identified predictors of cardiac arrest in the general population, however, none have been done to identify such factors in cancer patients who form a more vulnerable group with lower survival rate following cardiac arrest.Methods: We retrospectively analysed charts of all patients with active cancer who experienced in-hospital cardiac arrest (IHCA) and underwent cardio-pulmonary resuscitation (CPR) from January 2015 to December 2017 at our hospital (n=44, group A). We compared this group to 44 consecutive patients with active cancer admitted to the oncology unit who did not experience cardiac arrest (n=44, group B). We excluded patients in remission.Results: Both the groups were comparable in terms of age (69 ± 14 vs 68 ± 15, p=0.776) and gender distribution (50% vs 56% males, p=0.521). Prevalence of coronary artery disease (CAD) (25% vs 11%, p=0.097), hypertension (68% vs 66%, p=0.821), hyperlipidaemia (34% in both groups, p=1.000), tobacco abuse (18% vs 27%, p=0.308), and diabetes mellitus (34% vs 23%, p=0.237) was not significantly different between the two groups. Group with cardiac arrest had significantly higher alanine aminotransferase (100 U/L ± 150 vs 47 U/L ± 87, p=0.043), alkaline phosphatase (288 U/L ± 512 vs 118 U/L ± 80, p=0.032), creatinine (1.8 mg/dl ± 1.74 vs 1.1 mg/dl ± 0.76, p=0.023), international normalised ratio (INR) (2.1 ± 1.5 vs 1.2 ± 0.5, p=0.005), and lower estimated -glomerular filtration rate (43 mL/min/1.73m2 ± 17 vs 51 mL/min/1.73m2 ± 15, p=0.022) on admission. Group A also had significantly higher incidence of sepsis during the hospital course as compared to group B (30% vs 2%, p<0.001). In group A, 11.4% survived to discharge as compared to 95.5% in group B. Significantly higher number of patients in group B were taking chemotherapy (77.27% vs 34.09%, p=0.000046) and radiation therapy (65.9% vs 22.72%, p=0.000046) as compared to group A.Conclusion: Cancer patients who experienced IHCA had worse renal and hepatic function; they were frequently diagnosed with sepsis and had similar cardiovascular risk factors as compared to cancer patients who did not experience cardiac arrest. Furthermore, a higher number of patients with active cancer who did not experience cardiac arrest were on chemotherapy, immunotherapy or radiation therapy.

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Validating the Electronic Cardiac Arrest Risk Triage (eCART) Score for Risk Stratification of Surgical Inpatients in the Postoperative Setting

Abstract: Early warning scores are predictive of severe adverse events in postoperative patients. eCART is significantly more accurate in this patient population than both NEWS and MEWS.

Cited by 54 publications

References 16 publications

Logistic early warning scores to predict death, cardiac arrest or unplanned intensive care unit re‐admission after cardiac surgery

Logistic early warning scores to predict death, cardiac arrest or unplanned intensive care unit re‐admission after cardiac surgery

Improving early warning scores – more data, better validation, the same response

Possible Predictive Factors for In-hospital Cardiac Arrest in Patients with Cancer: A Retrospective Single Center Study

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