Simplified Predictive Instrument to Rule Out Acute Coronary Syndromes in a High-Risk Population.
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ABSTRACT:
SUBMITTER: Fanaroff AC
PROVIDER: S-EPMC4845272 | biostudies-other | 2015 Dec
REPOSITORIES: biostudies-other
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Project description:BackgroundA challenge for emergency medical service (EMS) is accurate identification of acute coronary syndromes (ACS) and ST-segment elevation myocardial infarction (STEMI) for immediate treatment and transport. The electrocardiograph-based acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) and the thrombolytic predictive instrument (TPI) have been shown to improve diagnosis and treatment in emergency departments (EDs), but their use by paramedics in the community has been less studied.ObjectiveTo identify candidates for participation in the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency Care (IMMEDIATE) Trial, we implemented EMS use of the ACI-TIPI and the TPI in out-of-hospital electrocardiographs and evaluated its impact on paramedic on-site identification of ACS and STEMI as a community-based approach to improving emergency cardiac care.MethodsAmbulances in the study municipalities were outfitted with electrocardiographs with ACI-TIPI and TPI software. Using a before-after quasi-experimental design, in Phase 1, for seven months, paramedics were provided with the ACI-TIPI/TPI continuous 0-100% predictions automatically printed on electrocardiogram (ECG) text headers to supplement their identification of ACS; in Phase 2, for 11 months, paramedics were told to identify ACS based on an ACI-TIPI cutoff probability of ACS ≥ 75% and/or TPI detection of STEMI. In Phase 3, this cutoff approach was used in seven additional municipalities. Confirmed diagnoses of ACS, acute myocardial infarction (AMI), and STEMI were made by blinded physician review for 100% of patients.ResultsIn Phase 1, paramedics identified 107 patients as having ACS; in Phase 2, 104. In Phase 1, 45.8% (49) of patients so identified had ACS confirmed, which increased to 76.0% (79) in Phase 2 (p < 0.001). Of those with ACS, 59.2% (29) had AMI in Phase 1 versus 84.8% (67) with AMI in Phase 2 (p < 0.01), and STEMI was confirmed in 40.8% (20) versus 68.4% (54), respectively (p < 0.01). In Phase 3, of 226 patients identified by paramedics as having ACS, 74.3% (168) had ACS confirmed, of whom 81.0% (136) had AMI and 65.5% (110) had STEMI. Among patients with ACS, the proportion who received percutaneous coronary intervention (PCI) was 30.6% (15) in Phase 1, increasing to 57.0% (45) in Phase 2 (p < 0.004) and 50.6% (85) in Phase 3, and the proportions of patients with STEMI receiving PCI rose from 75.0% (15) to 83.3% (45) (p < 0.4) and 82.7% (91).ConclusionsIn a wide range of EMS systems, use of electrocardiographs with ACI-TIPI and TPI decision support using a 75% ACI-TIPI cutoff improves paramedic diagnostic performance for ACS, AMI, and STEMI and increases the proportions of patients who receive PCI.
| S-EPMC4104416 | biostudies-literature
Project description:ObjectivesThe Stroke-Thrombolytic Predictive Instrument (Stroke-TPI) predicts the probability of good and bad outcomes with and without recombinant tissue plasminogen activator (rtPA). We sought to rebuild and externally validate a simpler Stroke-TPI to support implementation in routine clinical care.MethodsUsing the original derivation cohort of 1,983 patients from a combined database of randomized clinical trials (NINDS [National Institute of Neurological Disorders and Stroke] 1 and 2; ATLANTIS [Alteplase Thrombolysis for Acute Noninterventional Therapy in Ischemic Stroke] A and B; and ECASS [European Cooperative Acute Stroke Study] II), we simplified the Stroke-TPI by reducing variables and interaction terms and by exploring simpler (3- and 8-item) stroke severity scores. External validation was performed in the ECASS III trial (n = 821).ResultsThe following 6 variables were most predictive of good outcomes: age, systolic blood pressure, diabetes, stroke severity, symptom onset to treatment time, and rtPA therapy. Treatment effect modifiers included onset to treatment time and systolic blood pressure. For the models predicting a bad outcome (modified Rankin Scale [mRS] score ≥5), significant variables included age, stroke severity, and serum glucose. rtPA therapy did not change the risk of a poor outcome. Compared with models using the full NIH Stroke Scale, models using the 3-item severity score showed similar discrimination and excellent calibration. External validation on ECASS III showed similar performance (C statistics 0.75 [mRS score ≤1] and 0.80 [mRS score ≤2]).ConclusionA simpler model using a 3-item stroke severity score, instead of the 15-item NIH Stroke Scale, has similar prognostic value and may be easier to use in routine care. Future studies are needed to test whether it can improve process and clinical outcomes.
| S-EPMC4567461 | biostudies-literature
Project description:Many patients evaluated in the emergency department (ED) for acute coronary syndrome (ACS) develop posttraumatic stress symptoms (PTSS), but little is known about symptom trajectories over time. We estimated longitudinal trajectories of PTSS from ED to 1 year after evaluation for suspected ACS (N = 1000), and the effect of threat perceptions and discharge diagnosis. Participants reported on threat perceptions in the ED, ongoing cardiac threat at 1 month, and PTSS at 1, 6, and 12 months. Latent growth mixture modeling identified 3 PTSS trajectories over 1 year: Resilient (81.75%), Chronic-Worsening (13.69%), and Acute-Recovering (4.56%). Chronic-Worsening and Acute-Recovering classes reported significantly higher ED and cardiac threat perceptions than Resilient class. Discharge diagnosis did not differ (χ2(2) = 2.93, p = .231). PTSS are common following evaluation for suspected ACS, and trajectories vary, but targeting threat perceptions may reduce PTSS and improve clinical course, whether or not patients are ultimately diagnosed with ACS.
| S-EPMC9255559 | biostudies-literature
Project description:Although numerous risk-prediction models exist in patients presenting with acute coronary syndromes (ACS), they are subject to important short-comings, including lack of contemporary information. Short-term models are frequently biased by in-hospital events. Accordingly, we sought to create contemporary risk-prediction models for clinical outcomes following ACS up to 1 year following discharge. Models were constructed for death at 30 days and 1 year, death/myocardial infarction (MI)/revascularization at 30 days and death/MI at 1 year in consecutive patients presenting with ACS at our institution between 2006 and 2008, and discharged alive. Logistic regression was used to model the 30 day outcomes and Cox proportional hazards were used to model the 1 year outcomes. No linearity assumptions were made for continuous variables. The final model coefficients were used to create a prediction nomogram, which was incorporated into an online risk calculator. A total of 2,681 patients were included, of which about 9.5% presented with ST-elevation MI. All-cause mortality was 2.6% at 30 days and 13% at 1 year. Demographic, past medical history, laboratory, pharmacological and angiographic parameters were identified as being predictive of adverse ischemic outcomes at 30 days and 1 year. The c-indices for these models ranged from 0.73 to 0.82. Our study thus identified risk factors that are predictive of short- and long-term ischemic and revascularization outcomes in contemporary patients with ACS, and incorporated them into an easy-to-use online calculator, with equal or better discriminatory power than currently available models.
| S-EPMC3584647 | biostudies-literature
Project description:ObjectiveAccurate, efficient and cost-effective disposition of patients presenting to emergency departments (EDs) with symptoms suggestive of acute coronary syndromes (ACS) is a growing priority. Platelet activation is an early feature in the pathogenesis of ACS; thus, we sought to obtain an insight into whether point-of-care testing of platelet function: (1) may assist in the rule-out of ACS; (2) may provide additional predictive value in identifying patients with non-cardiac symptoms versus ACS-positive patients and (3) is logistically feasible in the ED.DesignProspective cohort feasibility study.SettingTwo urban tertiary care sites, one located in the USA and the second in Argentina.Participants509 adult patients presenting with symptoms of ACS.Main outcome measuresPlatelet reactivity was quantified using the Platelet Function Analyzer-100, with closure time (seconds required for blood, aspirated under high shear, to occlude a 150 µm aperture) serving as the primary endpoint. Closure times were categorised as 'normal' or 'prolonged', defined objectively as the 90th centile of the distribution for all participants enrolled in the study. Diagnosis of ACS was made using the standard criteria. The use of antiplatelet agents was not an exclusion criterion.ResultsClosure times for the study population ranged from 47 to 300 s, with a 90th centile value of 138 s. The proportion of patients with closure times ?138 s was significantly higher in patients with non-cardiac symptoms (41/330; 12.4%) versus the ACS-positive cohort (2/105 (1.9%); p=0.0006). The specificity of 'prolonged' closure times (?138 s) for a diagnosis of non-cardiac symptoms was 98.1%, with a positive predictive value of 95.4%. Multivariate analysis revealed that the closure time provided incremental, independent predictive value in the rule-out of ACS.ConclusionsPoint-of-care assessment of platelet reactivity is feasible in the ED and may facilitate the rapid rule-out of ACS in patients with prolonged closure times.
| S-EPMC3902349 | biostudies-literature
Project description:ObjectiveWe aimed to derive and validate a clinical decision rule (CDR) for suspected cardiac chest pain in the emergency department (ED). Incorporating information available at the time of first presentation, this CDR would effectively risk-stratify patients and immediately identify: (A) patients for whom hospitalisation may be safely avoided; and (B) high-risk patients, facilitating judicious use of resources.MethodsIn two sequential prospective observational cohort studies at heterogeneous centres, we included ED patients with suspected cardiac chest pain. We recorded clinical features and drew blood on arrival. The primary outcome was major adverse cardiac events (MACE) (death, prevalent or incident acute myocardial infarction, coronary revascularisation or new coronary stenosis >50%) within 30 days. The CDR was derived by logistic regression, considering reliable (κ>0.6) univariate predictors (p<0.05) for inclusion.ResultsIn the derivation study (n=698) we derived a CDR including eight variables (high sensitivity troponin T; heart-type fatty acid binding protein; ECG ischaemia; diaphoresis observed; vomiting; pain radiation to right arm/shoulder; worsening angina; hypotension), which had a C-statistic of 0.95 (95% CI 0.93 to 0.97) implying near perfect diagnostic performance. On external validation (n=463) the CDR identified 27.0% of patients as 'very low risk' and potentially suitable for discharge from the ED. 0.0% of these patients had prevalent acute myocardial infarction and 1.6% developed MACE (n=2; both coronary stenoses without revascularisation). 9.9% of patients were classified as 'high-risk', 95.7% of whom developed MACE.ConclusionsThe Manchester Acute Coronary Syndromes (MACS) rule has the potential to safely reduce unnecessary hospital admissions and facilitate judicious use of high dependency resources.
| S-EPMC4174131 | biostudies-literature
Project description:• Population pharmacokinetics and pharmacodynamics of rivaroxaban have been characterized in healthy subjects and in patients with total venous thromboembolism, deep vein thrombosis or atrial fibrillation.• This article is the first description of the population pharmacokinetics (PK) and pharmacodynamics (PD) of rivaroxaban in patients with acute coronary syndrome (ACS). It is the largest population pharmacokinetic and pharmacodynamic study on rivaroxaban conducted to date (n= 2290). The PK and PK-PD relationship of rivaroxaban in patients with ACS were similar to those in other patient populations. In addition, model-based simulations showed that the influence of renal function and age on the exposure to rivaroxaban in the ACS population were similar to the findings from Phase 1 special population studies. These findings suggest that rivaroxaban has highly predictable PK-PD and may provide a consistent anticoagulant effect across the studied patient populations, which allows an accurate prediction of the dose to control anticoagulation optimally.The aim of this analysis was to use a population approach to facilitate the understanding of the pharmacokinetics and pharmacodynamics of rivaroxaban in patients with acute coronary syndrome (ACS) and to evaluate the influence of patient covariates on the exposure of rivaroxaban in patients with ACS. METHODS A population pharmacokinetic model was developed using pharmacokinetic samples from 2290 patients in Anti-Xa Therapy to Lower Cardiovascular Events in Addition to Standard Therapy in Subjects with Acute Coronary Syndrome Thrombolysis in Myocardial Infarction 46. The relationship between pharmacokinetics and the primary pharmacodynamic end point, prothrombin time, was evaluated.The pharmacokinetics of rivaroxaban in patients with ACS was adequately described by an oral one-compartment model. The estimated absorption rate, apparent clearance and volume of distribution were 1.24 h(-1) (interindividual variability, 139%), 6.48 l h(-1) (31%) and 57.9 l (10%), respectively. Simulations indicate that the influences of renal function, age and bodyweight on exposure in ACS patients are consistent with the findings in previous Phase 1 studies. Rivaroxaban plasma concentrations exhibit a close-to-linear relationship with prothrombin time in the ACS population, with little interindividual variability. The estimated pharmacokinetic and pharmacodynamic parameters for the ACS patients were comparable to those for venous thromboembolism prevention, deep vein thrombosis and atrial fibrillation patients.The similarity in pharmacokinetics/pharmacodynamics of rivaroxaban among different patient populations and the low interindividual variability in the exposure-prothrombin time relationship indicate that the anticoagulant effect of rivaroxaban is highly predictable and consistent across all the patient populations studied.
| S-EPMC3394132 | biostudies-literature
Project description:Undifferentiated chest pain is one of the most common reasons for emergency department attendance and admission to hospitals. Non-ST elevation acute coronary syndrome (NSTE-ACS) is an important cause of chest pain, and accurate diagnosis and risk stratification in the emergency department must be a clinical priority. In the future, the incidence of NSTE-ACS will rise further as higher sensitivity troponin assays are implemented in clinical practice. In this article, we review contemporary approaches for the diagnosis and risk stratification of NSTE-ACS during emergency care. We consider the limitations of current practices and potential improvements. Clinical guidelines recommend an early invasive strategy in higher risk NSTE-ACS. The Global Registry of Acute Coronary Events (GRACE) risk score is a validated risk stratification tool which has incremental prognostic value for risk stratification compared with clinical assessment or troponin testing alone. In emergency medicine, there has been a limited adoption of the GRACE score in some countries (e.g. United Kingdom), in part related to a delay in obtaining timely blood biochemistry results. Age makes an exponential contribution to the GRACE score, and on an individual patient basis, the risk of younger patients with a flow-limiting culprit coronary artery lesion may be underestimated. The future incorporation of novel cardiac biomarkers into this diagnostic pathway may allow for earlier treatment stratification. The cost-effectiveness of the new diagnostic pathways based on high-sensitivity troponin and copeptin must also be established. Finally, diagnostic tests and risk scores may optimize patient care but they cannot replace patient-focused good clinical judgment.
| S-EPMC4691930 | biostudies-other
Project description:BackgroundAcute coronary syndromes (ACS) are the leading cause of global death. Optimizing mortality risk prediction and early identification of high-risk patients is essential for developing targeted prevention strategies. Many researchers have built machine learning (ML) models to predict the mortality risk in ACS patients. Our meta-analysis aimed to evaluate the predictive value of various ML models in predicting death in ACS patients at different times.MethodsPubMed, Embase, Web of Science, and Cochrane Library were searched systematically from database establishment to March 12, 2022 for studies developing or validating at least one ML predictive model for death in ACS patients. We used PROBAST to assess the risk of bias in the reported predictive models and a random-effects model to assess the pooled C-index and accuracy of these models.ResultsFifty papers were included, involving 216 ML prediction models, 119 of which were externally validated. The combined C-index of the ML models in the validation cohort predicting the in-hospital mortality, 30-day mortality, 3- or 6-month mortality, and 1 year or above mortality in ACS patients were 0.8633 (95% CI 0.8467-0.8802), 0.8296 (95% CI 0.8134-0.8462), 0.8205 (95% CI 0.7881-0.8541), and 0.8197 (95% CI 0.8042-0.8354), respectively, with the corresponding combined accuracy of 0.8569 (95% CI 0.8411-0.8715), 0.8282 (95% CI 0.7922-0.8591), 0.7303 (95% CI 0.7184-0.7418), and 0.7837 (95% CI 0.7455-0.8175), indicating that the ML models were relatively excellent in predicting ACS mortality at different times. Furthermore, common predictors of death in ML models included age, sex, systolic blood pressure, serum creatinine, Killip class, heart rate, diastolic blood pressure, blood glucose, and hemoglobin.ConclusionsThe ML models had excellent predictive power for mortality in ACS, and the methodologies may need to be addressed before they can be used in clinical practice.
| S-EPMC10588162 | biostudies-literature
Project description:OBJECTIVES:Acute chest pain (ACP) is a leading cause of hospital emergency unit consultation. As there are various underlying conditions, ranging from musculoskeletal disorders to acute coronary syndrome (ACS), thorough clinical diagnostics are warranted. The aim of this prospective study was to assess whether reproducible chest wall tenderness (CWT) on palpation in patients with ACP can help to rule out ACS. METHODS:In this prospective, double-blinded diagnostic study, all consecutive patients assessed in the emergency unit at the University Hospital Zurich because of ACP between July 2012 and December 2013 were included when a member of the study team was present. Reproducible CWT on palpation was the initial step and was recorded before further examinations were initiated. The final diagnosis was adjudicated by a study-independent physician. RESULTS:121 patients (60.3% male, median age 47?years, IQR 34-66.5?years) were included. The prevalence of ACS was 11.6%. Non-reproducible CWT had a high sensitivity of 92.9% (95% CI 66.1% to 98.8%) for ACS and the presence of reproducible CWT ruled out ACS (p=0.003) with a high negative predictive value (98.1%, 95% CI 89.9% to 99.7%). Conversely non-reproducible CWT ruled in ACS with low specificity (48.6%, 95% CI 38.8% to 58.5%) and low positive predictive value (19.1%, 95% CI 10.6% to 30.5%). CONCLUSIONS:This prospective diagnostic study supports the concept that reproducible CWT helps to rule out ACS in patients with ACP in an early stage of the evaluation process. However, ACS and other diagnoses should be considered in patients with a negative CWT test. TRIAL REGISTRATION NUMBER:ClinicalTrial.gov: NCT01724996.
| S-EPMC4316553 | biostudies-literature