Electronic health record risk score provides earlier prognostication of clinical outcomes in patients admitted to the cardiac intensive care unit

Prospective Evaluation of a Dynamic Acuity Score for Regularly Assessing a Critically Ill Patient's Risk of Mortality

OBJECTIVE

Predictive models developed for use in ICUs have been based on retrospectively collected data, which does not take into account the challenges associated with live, clinical data. This study sought to determine if a previously constructed predictive model of ICU mortality (ViSIG) is robust when using data collected prospectively in near real-time.

DESIGN

Prospectively collected data were aggregated and transformed to evaluate a previously developed rolling predictor of ICU mortality.

SETTING

Five adult ICUs at Robert Wood Johnson-Barnabas University Hospital and one adult ICU at Stamford Hospital.

PATIENTS

One thousand eight hundred and ten admissions from August to December 2020.

MEASUREMENTS AND MAIN RESULTS

The ViSIG Score, comprised of severity weights for heart rate, respiratory rate, oxygen saturation, mean arterial pressure, mechanical ventilation, and values for OBS Medical's Visensia Index. This information was collected prospectively, whereas data on discharge disposition was collected retrospectively to measure the ViSIG Score's accuracy. The distribution of patients' maximum ViSIG Score was compared with ICU mortality rate, and cut points determined where changes in mortality probability were greatest. The ViSIG Score was validated on new admissions. The ViSIG Score was able to stratify patients into three groups: 0-37 (low risk), 38-58 (moderate risk), and 59-100 (high risk), with mortality of 1.7%, 12.0%, and 39.8%, respectively ( p < 0.001). The sensitivity and specificity of the model to predict mortality for the high-risk group were 51% and 91%. Performance on the validation dataset remained high. There were similar increases across risk groups for length of stay, estimated costs, and readmission.

CONCLUSIONS

Using prospectively collected data, the ViSIG Score produced risk groups for mortality with good sensitivity and excellent specificity. A future study will evaluate making the ViSIG Score visible to clinicians to determine whether this metric can influence clinician behavior to reduce adverse outcomes.

Predictive ability of the sequential organ failure assessment score for in-hospital mortality in patients with cardiac critical illnesses: a nationwide observational study

AIMS

Several studies have reported a high predictive ability of the Sequential Organ Failure Assessment (SOFA) score for in-hospital mortality specifically for patients with cardiac critical illnesses, however, differences according to the admission classification (surgical or non-surgical) are unknown. The present study aimed to evaluate the predictive ability of the SOFA score in surgical and non-surgical patients with cardiac critical illnesses.

METHODS AND RESULTS

Using the Japanese nationwide Diagnosis Procedure Combination database, we identified patients with cardiac critical illnesses, defined as patients admitted to the intensive care unit (ICU) and treated by cardiologists or cardiovascular surgeons as their physicians in charge from April 2018 to March 2020. The discriminatory ability of the SOFA score for in-hospital mortality was assessed by calculating the area under the receiver operating characteristic curve (AUROC). Among 52 819 eligible patients with available data on their SOFA scores, 33 526 (64%) were postoperative cardiac surgeries. The median SOFA score on ICU admission was 5.0 (interquartile range, 2.0-8.0) and overall in-hospital mortality 6.8%. The AUROC of the SOFA score was 0.75 [95% confidence interval (CI), 0.75-0.76]. In the subgroup analyses, the AUROCs were 0.76 (95% CI, 0.74-0.77) in the surgical patients, 0.83 (95% CI, 0.83-0.84) in the non-surgical patients, and 0.88 (95% CI, 0.87-0.89) in the non-surgical acute coronary syndrome patients.

CONCLUSIONS

The predictive ability of the SOFA score on the day of ICU admission for in-hospital mortality was confirmed to be acceptable in the patients with cardiac critical illnesses and varied according to the admission classification and primary diagnoses.

Past, present, and future of mortality risk scores in the contemporary cardiac intensive care unit

Risk stratification dates to the dawn of the cardiac intensive care unit (CICU). As the CICU has evolved from a dedicated unit caring for patients with acute myocardial infarction to a complex healthcare environment encompassing a broad array of acute and chronic cardiovascular pathology, an expanding array of risk scores are available that can be applied to CICU patients. Most of these scores were designed for use either in patients with a specific acute cardiovascular diagnosis or unselected critically ill patients, and risk scores developed in other populations often underperform in the CICU. More recently, risk scores have been developed specific to the CICU population, demonstrating improved performance. All existing risk scores have relevant limitations, both in terms of performance and applicability to patient care. Risk scores have been predominantly developed to predict short-term mortality, either by quantifying severity of illness or by incorporating other risk factors for mortality. It is essential to distinguish mortality risk attributable to severity of illness, which may be modifiable through intervention, from mortality risk attributable to non-modifiable risk factors. This review discusses established risk scores applicable to the CICU population, details how risk score performance is characterized, describes how new risk scores can be developed, explains how the information provided by risk scores can be used in clinical practice, and highlights how novel risk stratification approaches can be developed.