scholarly journals The risk-treatment paradox in acute coronary syndrome patients: insights from the FORCE-ACS registry

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
J Azzahhafi ◽  
N M R Van Der Sangen ◽  
D R P P Chan Pin Yin ◽  
J P Simao Henriques ◽  
W J Kikkert ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Mortality Risk ◽  
Recommended Care ◽  
High Risk Patients ◽  
Grace Risk Score ◽  
Risk Patients ◽  
Risk Treatment ◽  
One Year ◽  
Risk Categories

Abstract Background Acute coronary syndrome (ACS) patients at high risk might benefit most from guideline-recommended interventions. However, it is well recognized that the delivery of guideline-directed care is inversely related to the estimated mortality risk, the so called risk-treatment paradox. Purpose To assess the existence of the risk-treatment paradox in a contemporary cohort of ACS patients and its possible association with one-year mortality. Methods The study population consisted patients enrolled in the FORCE-ACS registry who survived their initial admission. All ACS patients were stratified into low, intermediate or high mortality risk based on the Global Registry of Acute Coronary Events (GRACE) risk score. Optimal guideline-recommended care was defined as undergoing coronary angiography during initial hospital admission and receiving all outpatient medications with a class I guideline recommendation (i.e. aspirin, P2Y12-inhibitor, beta-blocker, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker and cholesterol-lowering drug). Aspirin and/or a P2Y12-inhibitor on top of an oral anticoagulant was also considered as optimal guideline-recommended care. The cumulative incidence of one-year mortality between optimal and suboptimal managed patients, within each GRACE risk score stratum, was estimated. Results In total, 2,524 patients who were enrolled between January 2015 and June 2018 were included. Based on the GRACE risk score, 46.9% of patients were classified as low-risk, 37.6% as intermediate-risk and 15.5% as high-risk. Overall, 49.8% of patients received optimal guideline-recommended care. Among the different risk strata, 54.9% of the low-risk, 49.1% of the intermediate-risk and 36.1% of the high-risk patients received optimal guideline-recommended care (Table 1). DAPT or DAT treatment (95.3% overall) did not differ between the risk categories. Beta-blockers were prescribed less frequently (69.6% overall), butprescription rates did not differ between the risk categories. ACE-inhibitors/ARBs were prescribed in 74.1% of all patients, but less often in high risk patients. Cholesterol lowering-drugs were prescribed in almost all patients (94.9% overall), but less frequently in high risk patients. Overall, 93.9% of patients underwent coronary angiography (CAG), high-risk patients had a statistically significant lower likelihood of undergoing CAG. In all risk categories, optimal guideline-recommended care was associated with a lower one-year mortality as compared to sub-optimal treatment (5.7% vs. 15.6% in high-risk) (Fig. 1). Conclusion Patients at higher estimated mortality risk, based on the GRACE-risk score, are less likely to receive guideline-recommended care. Although, the absolute benefit from guideline-recommended care appears to be greater in high-risk patients. Receiving guideline-recommended care was associated with a statistically significant better prognosis in intermediate- and high-risk patients. FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): ZonMW Netherlands TopZorgSt. Antonius Research funds Figure 1. All-cause mortality

scholarly journals Validation study of grace risk score for prognosis in Indian patients with non-STEMI

2017 ◽  
Vol 4 (4) ◽  
pp. 1036
Author(s):  
Rangamanikandan M. ◽  
Shivcharan Jelia ◽  
Meena S. R. ◽  
Shyam Bihari Meena ◽  
Devendra Ajmera ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Predictive Value ◽  
Statistical Significance ◽  
Cardiac Biomarkers ◽  
Female Ratio ◽  
High Risk Patients ◽  
Grace Risk Score ◽  
Risk Patients ◽  
Grace Score

Background: Cardiovascular disease has emerged as the single most important cause of death worldwide. Every patient of MI has to be stratified according to the risk factors, so that high risk patients can be identified and can be managed effectively GRACE risk score is one of the score used to calculate the risk in MI. Present study was undertaken to correlate GRACE risk score and mortality in non-STEMI.Methods: 200 patients of non-STEMI fulfilling the inclusion criteria admitted in wards of NMCH, Kota were recruited. GRACE risk score was calculated for all patients. Each patient monitored closely throughout their hospitalization. Each component of GRACE risk score was studied for statistical significance. Statistical analysis of correlation was done with chi square test and statistical significance was taken p < 0.05.Results: Mean age is 59.45±8.66 years, with male preponderance, male to female ratio 3:1. Maximum GRACE score is 300 and the minimum score is 86. Patients were categorized into low (74 patients), intermediate (60 patients), high risk (66 patients) according to GRACE score. 14 patients were expired and all of them are in high risk category. GRACE score had sensitivity (100%), specificity (72.04%), positive predictive value (21.2%) and negative predictive value (100%). Serum creatinine (p<0.001), heart rate (p<0.001), blood pressure (p<0.001), Killip class (p<0.001), cardiac biomarkers (p<0.001), ST segment changes (p<0.001) were significantly associated with adverse events. Age>50 (p<0.110) is not significant. Overall grace score demonstrated excellent discrimination (p<0.001), C statistics 0.99, 95% CI 115.742-151.221 for in hospital mortality.Conclusions: This study has shown GRACE risk score is highly accurate in predicting in hospital mortality in patients of non-STEMI. We should routinely use GRACE risk score in our hospital settings to identify the high-risk patients to decrease mortality. 

Abstract 334: Potential Risk Factors for Recurrent Coronary Revascularization and Hospitalization for Unstable Angina Following Acute Myocardial Infarction

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Kim Smolderen ◽  
Yan Li ◽  
David Cohen ◽  
Suzanne V Arnold ◽  
Phil G Jones ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
High Risk ◽  
Unstable Angina ◽  
Risk Score ◽  
Coronary Revascularization ◽  
High Risk Patients ◽  
Grace Risk Score ◽  
Increased Risk ◽  
Risk Patients

Background: Subsequent hospitalizations after acute myocardial infarction (AMI) for unstable angina (UA) and coronary revascularization represent common and important clinical events. While numerous studies sought to predict survival, AMI, and all-cause rehospitalization after AMI, there are limited data about how to best risk-stratify patients for UA and subsequent revascularization. Understanding these factors can support the development of more efficient AMI care. Methods: In the multi-center TRIUMPH registry, we used 3,283 patients with detailed baseline and 1-year follow-up information, including adjudicated hospitalizations, following initial AMI admission. An initial prediction model was derived after examining > 60 demographic, socio-economic, comorbidity, AMI severity, treatment, psychosocial and health status characteristics using hierarchical Cox Proportional Hazards for UA or revascularization. Staged PCIs and elective CABGs performed ≤1 month were excluded. Results: A total of 140 (4.3%) patients were readmitted ≤1 year for UA and 158 (4.8%) for revascularization. Independent predictors of UA were female sex (HR=1.88; 95%CI: 1.33, 2.65), prior PCI (HR=1.64; 95%CI: 1.12, 2.39), prior CABG (HR=2.06; 95%CI: 1.28, 3.32), and GRACE risk score (HR per 1 point increase=0.99; 95%CI: 0.98, 0.99). Independent predictors of revascularization were diseased vessels >1 (HR=2.50; 95%CI: 1.74, 3.60), and GRACE risk score (HR=0.99; 95%CI: 0.99, 1.00). While high-risk patients (those with diabetes, peripheral artery and cerebrovascular disease) were at increased risk of being readmitted for UA (HR=1.48; 95%CI 1.04, 2.10) or revascularization (HR=1.35; 95%CI: 0.97, 1.88), there was no interaction between these associations and risk status, suggesting equal prognostic significance in those with and without high-risk characteristics. Conclusion: Unique characteristics are associated with admissions for UA and revascularization. Creating multivariable models, risk scores and prospective risk stratification can support tailoring treatment to those at highest risk, although prospective studies are needed to establish the best management for high-risk patients.

Prognostic implications of pre-ablation stimulated Tg: a retrospective analysis of 2500 thyroid cancer patients

2021 ◽  
Author(s):  
Tian Tian ◽  
Yangmengyuan Xu ◽  
Xinyue Zhang ◽  
Bin Liu
Keyword(s):  
Thyroid Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Clinical Outcomes ◽  
Recurrent Disease ◽  
Clinicopathological Parameters ◽  
Characteristic Analysis ◽  
High Risk Patients ◽  
Risk Patients ◽  
Risk Categories

Abstract Context The risk of persistent and recurrent disease in patients with differentiated thyroid cancer (DTC) is a continuum that ranges from very low to very high, even within the three primary risk categories. It is important to identify independent clinicopathological parameters to accurately predict clinical outcomes. Objective To examine the association between pre-ablation stimulated thyroglobulin (ps-Tg) and persistent and recurrent disease in DTC patients and investigate whether incorporation of ps-Tg could provide a more individualized estimate of clinical outcomes. Design, Setting, and Participants Medical records of 2524 DTC patients who underwent total thyroidectomy and radioiodine ablation between 2006 and 2018 were retrospectively reviewed. Main Outcome Measure Ps-Tg was measured under thyroid hormone withdrawal before remnant ablation. Association of ps-Tg and clinical outcomes. Results In multivariate analysis, age, ATA risk stratification, M1, ps-Tg and cumulative administered activities were the independent predictive factors for persistent/ recurrent disease. Receiver operating characteristic analysis identified ps-Tg cutoff (≤ 10.1 ng/mL) to predict disease free status with a negative predictive value of 95%, and validated for all ATA categories. Integration of ps-Tg into ATA risk categories indicated that the presence of ps-Tg ≤ 10.1 ng/mL was associated with a significantly decreased chance of having persistent/recurrent disease in intermediate- and high-risk patients (9.9 to 4.1% in intermediate-risk patients, and 33.1 to 8.5% in high-risk patients). Conclusion Ps-Tg (≤ 10.1 ng/mL) was a key predictor of clinical outcomes in DTC patients. Its incorporation as a variable in the ATA risk stratification system could more accurately predict clinical outcomes.

Effect of a Real-Time Risk Score on 30-day Readmission Reduction in Singapore

2021 ◽  
Vol 12 (02) ◽  
pp. 372-382
Author(s):  
Christine Xia Wu ◽  
Ernest Suresh ◽  
Francis Wei Loong Phng ◽  
Kai Pik Tai ◽  
Janthorn Pakdeethai ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Real Time ◽  
Risk Score ◽  
Patient Specific ◽  
Learning Models ◽  
Medicine Department ◽  
High Risk Patients ◽  
Risk Patients ◽  
Machine Learning Models

Abstract Objective To develop a risk score for the real-time prediction of readmissions for patients using patient specific information captured in electronic medical records (EMR) in Singapore to enable the prospective identification of high-risk patients for enrolment in timely interventions. Methods Machine-learning models were built to estimate the probability of a patient being readmitted within 30 days of discharge. EMR of 25,472 patients discharged from the medicine department at Ng Teng Fong General Hospital between January 2016 and December 2016 were extracted retrospectively for training and internal validation of the models. We developed and implemented a real-time 30-day readmission risk score generation in the EMR system, which enabled the flagging of high-risk patients to care providers in the hospital. Based on the daily high-risk patient list, the various interfaces and flow sheets in the EMR were configured according to the information needs of the various stakeholders such as the inpatient medical, nursing, case management, emergency department, and postdischarge care teams. Results Overall, the machine-learning models achieved good performance with area under the receiver operating characteristic ranging from 0.77 to 0.81. The models were used to proactively identify and attend to patients who are at risk of readmission before an actual readmission occurs. This approach successfully reduced the 30-day readmission rate for patients admitted to the medicine department from 11.7% in 2017 to 10.1% in 2019 (p < 0.01) after risk adjustment. Conclusion Machine-learning models can be deployed in the EMR system to provide real-time forecasts for a more comprehensive outlook in the aspects of decision-making and care provision.

scholarly journals Does the implementation of a novel intensive care discharge risk score and nurse-led inpatient review tool improve outcome? A prospective cohort study in two intensive care units in the UK

BMJ Open ◽  
2017 ◽  
Vol 7 (12) ◽  
pp. e018322
Author(s):  
Jez Fabes ◽  
William Seligman ◽  
Carolyn Barrett ◽  
Stuart McKechnie ◽  
John Griffiths
Keyword(s):  
Intensive Care ◽  
High Risk ◽  
Risk Score ◽  
Prospective Cohort ◽  
Data Set ◽  
High Risk Patients ◽  
Poor Outcome ◽  
Icu Discharge ◽  
Risk Patients ◽  
Risk Scoring

ObjectiveTo develop a clinical prediction model for poor outcome after intensive care unit (ICU) discharge in a large observational data set and couple this to an acute post-ICU ward-based review tool (PIRT) to identify high-risk patients at the time of ICU discharge and improve their acute ward-based review and outcome.DesignRetrospective patient cohort of index ICU admissions between June 2006 and October 2011 receiving routine inpatient review. Prospective cohort between March 2012 and March 2013 underwent risk scoring (PIRT) which subsequently guided inpatient ward-based review.SettingTwo UK adult ICUs.Participants4212 eligible discharges from ICU in the retrospective development cohort and 1028 patients included in the prospective intervention cohort.InterventionsMultivariate analysis was performed to determine factors associated with poor outcome in the retrospective cohort and used to generate a discharge risk score. A discharge and daily ward-based review tool incorporating an adjusted risk score was introduced. The prospective cohort underwent risk scoring at ICU discharge and inpatient review using the PIRT.OutcomesThe primary outcome was the composite of death or readmission to ICU within 14 days of ICU discharge following the index ICU admission.ResultsPIRT review was achieved for 67.3% of all eligible discharges and improved the targeting of acute post-ICU review to high-risk patients. The presence of ward-based PIRT review in the prospective cohort did not correlate with a reduction in poor outcome overall (P=0.876) or overall readmission but did reduce early readmission (within the first 48 hours) from 4.5% to 3.6% (P=0.039), while increasing the rate of late readmission (48 hours to 14 days) from 2.7% to 5.8% (P=0.046).ConclusionPIRT facilitates the appropriate targeting of nurse-led inpatient review acutely after ICU discharge but does not reduce hospital mortality or overall readmission rates to ICU.

scholarly journals A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Fen Liu ◽  
Zongcheng Yang ◽  
Lixin Zheng ◽  
Wei Shao ◽  
Xiujie Cui ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
High Risk ◽  
Cancer Progression ◽  
Risk Score ◽  
Risk Model ◽  
Cox Regression ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
High Risk Patients ◽  
Risk Patients

BackgroundGastric cancer is a common gastrointestinal malignancy. Since it is often diagnosed in the advanced stage, its mortality rate is high. Traditional therapies (such as continuous chemotherapy) are not satisfactory for advanced gastric cancer, but immunotherapy has shown great therapeutic potential. Gastric cancer has high molecular and phenotypic heterogeneity. New strategies for accurate prognostic evaluation and patient selection for immunotherapy are urgently needed.MethodsWeighted gene coexpression network analysis (WGCNA) was used to identify hub genes related to gastric cancer progression. Based on the hub genes, the samples were divided into two subtypes by consensus clustering analysis. After obtaining the differentially expressed genes between the subtypes, a gastric cancer risk model was constructed through univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis. The differences in prognosis, clinical features, tumor microenvironment (TME) components and immune characteristics were compared between subtypes and risk groups, and the connectivity map (CMap) database was applied to identify potential treatments for high-risk patients.ResultsWGCNA and screening revealed nine hub genes closely related to gastric cancer progression. Unsupervised clustering according to hub gene expression grouped gastric cancer patients into two subtypes related to disease progression, and these patients showed significant differences in prognoses, TME immune and stromal scores, and suppressive immune checkpoint expression. Based on the different expression patterns between the subtypes, we constructed a gastric cancer risk model and divided patients into a high-risk group and a low-risk group based on the risk score. High-risk patients had a poorer prognosis, higher TME immune/stromal scores, higher inhibitory immune checkpoint expression, and more immune characteristics suitable for immunotherapy. Multivariate Cox regression analysis including the age, stage and risk score indicated that the risk score can be used as an independent prognostic factor for gastric cancer. On the basis of the risk score, we constructed a nomogram that relatively accurately predicts gastric cancer patient prognoses and screened potential drugs for high-risk patients.ConclusionsOur results suggest that the 7-gene signature related to tumor progression could predict the clinical prognosis and tumor immune characteristics of gastric cancer.

scholarly journals Indications for an early invasive strategy in NSTE-ACS patients

2019 ◽  
Vol 28 (3) ◽  
pp. 131-135 ◽  
Author(s):  
B. Zwart ◽  
J. M. ten Berg ◽  
A. W. van ’t Hof ◽  
P. A. L. Tonino ◽  
Y. Appelman ◽  
...  
Keyword(s):  
High Risk ◽  
Coronary Angiography ◽  
Risk Score ◽  
Invasive Strategy ◽  
Coronary Syndrome ◽  
Grace Risk Score ◽  
Risk Patients ◽  
Coronary Events ◽  
Early Invasive Strategy ◽  
European Society Of Cardiology

Abstract An early invasive strategy in patients who have acute coronary syndrome without ST-elevation (NSTE-ACS) can improve clinical outcome in high-risk subgroups. According to the current guidelines of the European Society of Cardiology (ESC), the majority of NSTE-ACS patients are classified as “high-risk”. We propose to prioritise patients with a global registry of acute coronary events (GRACE) risk score >140 over patients with isolated troponin rise or electrocardiographic changes and a GRACE risk score <140. We also acknowledge that same-day transfer for all patients at a high risk is not necessary in the Netherlands since the majority of Dutch cardiology departments are equipped with a catheterisation laboratory where diagnostic coronary angiography is routinely performed in NSTE-ACS patients. Therefore, same-day transfer should be restricted to true high-risk patients (in addition to those NSTE-ACS patients with very high-risk (VHR) criteria) in centres without coronary angiography capabilities.

scholarly journals Impact of Diabetes Mellitus on Outcomes after High-Risk Interventional Coronary Procedures

2020 ◽  
Vol 9 (11) ◽  
pp. 3414
Author(s):  
Laura Johannsen ◽  
Julian Soldat ◽  
Andrea Krueger ◽  
Amir A. Mahabadi ◽  
Iryna Dykun ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Survival Rate ◽  
High Risk ◽  
High Risk Patients ◽  
Risk Patients ◽  
Insulin Dependent ◽  
Artery Disease ◽  
One Year

An increasing number of patients with coronary artery disease are at high operative risk due to advanced age, severe comorbidities, complex coronary anatomy, and reduced ejection fraction. Consequently, these high-risk patients are often offered percutaneous coronary intervention (PCI) as an alternative to coronary artery bypass grafting (CABG). We aimed to investigate the outcome of patients with diabetes mellitus (DM) undergoing high-risk PCI. We analyzed consecutive patients undergoing high-risk PCI (period 01/2016–08/2018). In-hospital major adverse cardiac and cerebrovascular events (MACCEs), defined as in-hospital stroke, myocardial infarction and death, and the one-year incidence of death from any cause were assessed in patients with and without DM. There were 276 patients (age 70 years, 74% male) who underwent high-risk PCI. Eighty-six patients (31%) presented with DM (insulin-dependent DM: n = 24; non-insulin-dependent DM: n = 62). In-hospital MACCEs occurred in 9 patients (3%) with a non-significant higher rate in patients with DM (n = 5/86, 6% vs. n = 4/190 2%; p = 0.24). In patients without DM, the survival rate was insignificantly higher than in patients with DM (93.6% vs. 87.1%; p = 0.07). One-year survival was not significantly different in DM patients with more complex coronary artery disease (SYNTAX I-score ≤ 22: 89.3% vs. > 22: 84.5%; p = 0.51). In selected high-risk patients undergoing high-risk PCI, DM was not associated with an increased incidence of in-hospital MACCEs or a decreased one-year survival rate.

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