GRACE Score Validation in Predicting Hospital Mortality: Analysis of the Role of Sex

Accuracy of death risk prediction models for acute coronary syndrome patients: a systematic review and meta-analysis

INTRODUCTION

This study systematically evaluates the accuracy of several death risk prediction models for patients with acute coronary syndrome (ACS) through evidence-based methods. We identify the most accurate and effective ACS death risk prediction model and provide an evidence-based basis for clinical healthcare personnel to evaluate their choice of death risk prediction model for ACS patients.

EVIDENCE ACQUISITION

An evidence-based approach was used to study the current death risk prediction model for ACS. First, a literature search was carried out using computer-based and manual searching. The literature databases searched include Cochrane Library, MEDLINE, EMBASE, PubMed, Web of Science, WanFang Data, CNKI, VPCS, and SinoMed. The search period was limited to 2009 to 2022. Screening, quality evaluation and data extraction were carried out for the included articles. The PROBAST was used to conduct a migration risk assessment. RevMan 5.3 and Meta-DiSc 1.4 were used in combination to determine the model effect sizes. A descriptive analysis was conducted for the data that could not be meta-analyzed.

EVIDENCE SYNTHESIS

A total of 8277 articles were initially included in this study. After screening, 25 articles were finally included, involving 11 different risk prediction models. A total of 306,390 patients with ACS were included of which 158,080 (51.6%) were male and 147,793 (48.4%) were female. The patients stemmed from 11 different countries (e.g., China, the USA, Spain, the UK, etc.). The total number of deaths was 23,601. The sensitivity of the GRACE risk prediction model was 0.78, with a specificity of 0.76 and an AUC value of 0.86. The sensitivity of the CAMI risk prediction model was 0.78, with a specificity of 0.70 and an AUC value of 0.85. The sensitivity of the TIMI risk prediction model was 0.51, with a specificity of 0.81, and an AUC value of 0.64. The sensitivity of the REMS risk prediction model was 0.78, with a specificity of 0.46 and an AUC value of 0.41. Eight different risk prediction models (EPICOR, CRUSADE, SAMI, GWTG, LNS, SYNTAX II, APACHE II) that could not be combined with the effect size were also included, with sensitivities ranging from 0.77-0.95, specificities ranging from 0.22-0.99, and AUC values ranging from 0.71-0.92.

CONCLUSIONS

The GRACE and CAMI risk prediction models demonstrate good accuracy for evaluating the death risk of ACS patients. The accuracy of the TIMI risk prediction model is similar to that of the REMS risk prediction model. The APACHE II, SYNTAX II, EPICOR, and CAMI risk prediction models also show good accuracy for estimating the risk of death in ACS patients, although further validation is needed due to limited evidence. For improved predictive accuracy and to help advance medical interventions, the author recommends that clinical medical staff use the GRACE model to predict the death risk of ACS patients.

Sex-specific evaluation and redevelopment of the GRACE score in non-ST-segment elevation acute coronary syndromes in populations from the UK and Switzerland: a multinational analysis with external cohort validation

BACKGROUND

The Global Registry of Acute Coronary Events (GRACE) 2.0 score was developed and validated in predominantly male patient populations. We aimed to assess its sex-specific performance in non-ST-segment elevation acute coronary syndromes (NSTE-ACS) and to develop an improved score (GRACE 3.0) that accounts for sex differences in disease characteristics.

METHODS

We evaluated the GRACE 2.0 score in 420 781 consecutive patients with NSTE-ACS in contemporary nationwide cohorts from the UK and Switzerland. Machine learning models to predict in-hospital mortality were informed by the GRACE variables and developed in sex-disaggregated data from 386 591 patients from England, Wales, and Northern Ireland (split into a training cohort of 309 083 [80·0%] patients and a validation cohort of 77 508 [20·0%] patients). External validation of the GRACE 3.0 score was done in 20 727 patients from Switzerland.

FINDINGS

Between Jan 1, 2005, and Aug 27, 2020, 400 054 patients with NSTE-ACS in the UK and 20 727 patients with NSTE-ACS in Switzerland were included in the study. Discrimination of in-hospital death by the GRACE 2.0 score was good in male patients (area under the receiver operating characteristic curve [AUC] 0·86, 95% CI 0·86-0·86) and notably lower in female patients (0·82, 95% CI 0·81-0·82; p<0·0001). The GRACE 2.0 score underestimated in-hospital mortality risk in female patients, favouring their incorrect stratification to the low-to-intermediate risk group, for which the score does not indicate early invasive treatment. Accounting for sex differences, GRACE 3.0 showed superior discrimination and good calibration with an AUC of 0·91 (95% CI 0·89-0·92) in male patients and 0·87 (95% CI 0·84-0·89) in female patients in an external cohort validation. GRACE 3·0 led to a clinically relevant reclassification of female patients to the high-risk group.

INTERPRETATION

The GRACE 2.0 score has limited discriminatory performance and underestimates in-hospital mortality in female patients with NSTE-ACS. The GRACE 3.0 score performs better in men and women and reduces sex inequalities in risk stratification.

FUNDING

Swiss National Science Foundation, Swiss Heart Foundation, Lindenhof Foundation, Foundation for Cardiovascular Research, and Theodor-Ida-Herzog-Egli Foundation.

A Nomogram for Predicting Hospital Mortality in Intensive Care Unit Patients with Acute Myocardial Infarction

Background

This study aims to construct and validate an early-stage nomogram for predicting hospital mortality of ICU patients with acute myocardial infarction (AMI), to help clinicians determine the appropriate intervention.

Methods

The primary cohort of 2704 patients diagnosed with acute myocardial infarction in admission records from eICU-Collaborative Research Database (eICU-CRD) v2.0. Univariate logistic regression analysis and multivariate logistic regression analysis were enrolled for the construction of the predictive nomogram. Demographic factors, history of clinical cardiovascular disease, vital signs, the use of vasopressors, urine output, and serum variables in the first 24 hours were included in this analysis. The nomogram was evaluated by performance traits including Harrell's concordance index (C-index) and area under the receiver operating characteristic (AUC) analysis, calibration curve, and decision curve analysis (DCA). The nomogram was validated in a different cohort containing 1026 subjects collected from MIMIC-III Database v1.4. Finally, in order to compare the performance with other classic prediction models, AUC analysis, calibration curve, DCA and accuracy analysis (net reclassification improvement (NRI)) were conducted for three ICU scores in validated cohort.

Results

The nomogram revealed 14 predictors of the first 24 hours derived from univariate and multivariable analyses, including age, history of peripheral vascular disease, atrial fibrillation, cardiogenic shock and cardiac arrest, the use of norepinephrine, urine output, white blood cell (WBC), hemoglobin (Hb), red blood cell (RBC), red cell distribution width (RDW), glucose, bicarbonate and magnesium. The C-index of this nomogram was 0.834 (95% CI 0.812 to 0.856). Then, the result of AUC analysis, the DCA and calibration curve indicated that our nomogram was feasible for clinical prediction. The predictive ability and clinical use of the nomogram were verified in the validated cohort. The AUC analysis of ICU scores showed that the AUC of these score systems was ranged from 0.811 to 0.860 (the AUC of nomogram: 0.885). Moreover, our nomogram also showed a better performance in calibration curve and DCA NRI.

Conclusion

The study presents a prediction nomogram incorporating 14 variables that could help identify AMI patients admitted in ICU who might have a high risk of hospital mortality in the first hospitalized 24 hours. This nomogram showed a better performance than normal ICU score systems.

[Comorbidity and Gender of Patients at Risk of Hospital Mortality After Emergency Percutaneous Coronary Intervention]

Aim        To study gender aspects of comorbidity in evaluating the risk of in-hospital death for patients with acute coronary syndrome (ACS) after a percutaneous coronary intervention (PCI).Material and methods        The presented results are based on data of two ACS registries, the city of Sochi and RECORD-3. 986 patients were included into this analysis by two additional criteria, age &lt;70 years and PCI. 80% of the sample were men. Analysis of comorbidity severity was performed for all patients and included 9 indexes: type 2 diabetes mellitus, chronic kidney disease, atrial fibrillation, anemia, stroke, arterial hypertension, obesity, and peripheral atherosclerosis. Group 1 (minimum comorbidity) consisted of patients with not more than one disease (n=367); group 2 (moderate comorbidity) consisted of patients with 2 or 3 diseases (n=499), and group 3 (pronounced comorbidity) consisted of patients with 4 or more diseases (n=120). In-hospital mortality was 2.7 % (n=27).Results   Significant data on the effect of comorbidity on the in-hospital prognosis were obtained only for men of the compared groups: 0.6, 1.8, and 8.8 %, respectively (χ2=21.6; р&lt;0.0001). At the same time, among 44 women with minimum comorbidity, there were no cases of in-hospital death, and the presence of moderate (n=110) and pronounced comorbidity (n=40) was associated with a similar death rate (7.3 and 7.5 %, respectively). Noteworthy, in moderate comorbidity, the female gender was associated with a 4-fold increase in the risk of in-hospital death (odd ratio, OR 4.3 at 95 % confidence interval, CI from 1.5 to 12.1; р=0.003). In addition, both in men and women with minimum comorbidity, even a high risk by the GRACE scale (score ≥140) was not associated with increased in-hospital mortality, which was minimal (0 for women and 1 % for men). At the same time, in the patient subgroup with moderate and pronounced comorbidity, a GRACE score ≥140 resulted in a 6-fold increase in the risk of in-hospital death for men (OR 6.0 at 95 % CI from 1.7 to 21.9; р=0.002) and a 16-fold increase for women (OR 16.2 at 95 % CI from 2.0 to 130.4; р=0.0006).Conclusion            This study identified gender-related features in predicting the risk of in-hospital death for ACS patients with comorbidities after PCI, which warrants reconsideration of existing approaches to risk stratification.

Sex Difference in Risk Factors, GRACE Scores, and Management among Post-Acute Coronary Syndrome Patients in Sri Lanka

Objective

To assess sex-based differences in the prevalence of risk factor, their management, and differences in the prognosis among acute coronary syndrome (ACS) in Sri Lanka.

Methods

Patients diagnosed with ACS were recruited from hospitals throughout the island. The Joint European Societies guidelines were used to assess recommended targets for coronary heart disease risk factors, and the GRACE score was used to assess the post-ACS prognosis. Age-adjusted regression was performed to calculate odds ratios for men versus women in risk factor control.

Results

A total of 2116 patients, of whom 1242 (58.7%) were men, were included. Significant proportion of women were nonsmokers; OR = 0.11 (95% CI 0.09 to 0.13). The prevalence of hypertension (p < 0.001), diabetes (p < 0.001), and dyslipidemia (p=0.004) was higher in women. The LDL-C target was achieved in a significantly higher percentage of women (12.6%); OR = 0.33 (95% CI 0.10 to 1.05). When stratified by age, no significant differences were observed in achieving the risk factor targets or management strategies used except for fasting blood sugar (p < 0.05) where more men achieved control target in both age categories. Majority of the ACS patients had either high or intermediate risk for one-year mortality as per the GRACE score. In-hospital and 1-year mean mortality risk was significantly higher among men of less than 65 years of age (p < 0.05).

Conclusions

Smoking is significantly lower among Sri Lankan women diagnosed with ACS. However, hypertension, diabetes, and dyslipidemia were more prevalent among them. There was no difference in primary and secondary preventive strategies and management in both sexes but could be further improved in both groups.

A predictive value of the dynamic changes of the P-wave terminal force in lead V1 in the long-term prognosis of patients with non-ST-segment elevation acute coronary syndrome

BACKGROUND

The purpose of this study was to investigate the prognostic value of dynamic changes of P-wave terminal force in lead V1 (PtfV1 ) at electrocardiogram (ECG) in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) during the long-term major adverse cardiovascular events (MACEs) of patients.

METHODS

According to the PtfV1 value, the patients were divided into four groups: PtfV1 (-)/PtfV1 (-), PtfV1 (-)/PtfV1 (+), PtfV1 (+)/PtfV1 (-), and PtfV1 (+)/PtfV1 (+).

RESULTS

The highest incidence of MACEs was the PtfV1 (-)/(+) group with 24 patients (24.7%). The lowest incidence was the PtfV1 (-)/(-) group with 28 patients (4.9%). Compared with the PtfV1 (-)/(-) group, the risk for the occurrence of MACEs in the PtfV1 (-)/(+)group was significantly increased (24.7% vs 4.9%, P = .000). Similarly, the risk in the PtfV1 (+)/(+) group was also increased (10.1% vs 4.9%, P = .000).

CONCLUSION

The persistence of PtfV1 (+) and conversion of PtfV1 /(-) to PtfV1 /(+) at discharge significantly increased the incidence of MACEs.

Validation of a carbapenem-resistant Enterobacteriaceae colonization risk prediction model: A retrospective cohort study in Korean intensive care units

BACKGROUND

To assess the external validity of a carbapenem-resistant Enterobacteriaceae colonization risk prediction model (CREP-model).

METHODS

This retrospective cohort study included 414 patients admitted to the intensive care units of a tertiary hospital from November 1, 2017 to May 31, 2018. Data were collected via medical record review, and we analyzed the performance of the CREP-model by assessment of calibration, discrimination, clinical usefulness, and uniformity-of-fit.

RESULTS

The validation subjects showed differences in age, Acute Physiology and Chronic Health Evaluation II score, mechanical ventilation days, and carbapenem-resistant Enterobacteriaceae colonization rate from those of the CREP-model development subjects. The calibration-in-the-large was 0.069 (95% confidence interval [CI], 0.065-0.074), and calibration slope was 1.114 (95% CI, 1.091-1.136). The area under the receiver operating characteristic curve was 0.883 (95% CI, 0.838-0.928). At the predicted risk of 0.25, the sensitivity, specificity, and correct classification rates were 81.3%, 79.8%, and 80.0%, respectively, and the net benefit according to the model was 0.035 with 64 fewer false-positive results per 100 patients. The calibration, discrimination, and clinical usefulness showed similar results among subjects stratified according to sex, age group, medical department, and admission source.

CONCLUSIONS

The CREP-model showed good performance in the validation sample; therefore, we recommend introducing the CREP-model into intensive care units of tertiary hospitals to improve decision-making.

Utility of Imaging in Risk Stratification of Chest Pain in Women

OPINION STATEMENT

Recent decades have seen a growing recognition that the understanding of sex differences in cardiovascular disease (CVD) is vital to optimal diagnosis and management, particularly of women (Mosca et al. Circulation 124:2145-54, 2011). There is simultaneously an increasing appreciation of the multifactorial nature of ischemic heart disease (IHD) in many patients, in whom disease may extend beyond the epicardial coronaries. While obstructive coronary artery disease (CAD) remains underdiagnosed in women and still represents a major burden of disease, women also present with nonobstructive CAD more commonly than men (Patel et al. N Engl J Med 362:886-95, 2010). Indeed, microvascular dysfunction, coronary artery vasospasm, and coronary dissections contribute to a larger proportion of IHD in women than men (Bairey Merz et al. J Am Coll Cardiol 47:S21-9, 2006). Here, we review the symptom presentation of women with IHD and the noninvasive modalities used to risk stratify women with suspected IHD.

Predictive power of the grace score in population with diabetes

INTRODUCTION

Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score.

OBJECTIVES

The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model.

MATERIAL AND METHODS

Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement.

RESULTS

The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model.

CONCLUSIONS

The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients.