Thirty-day readmission rates after PCI in a metropolitan center in Europe: incidence and impact on prognosis

Thirty-Day Unplanned Readmissions Following Elective and Acute Percutaneous Coronary Intervention

BACKGROUND

Prior studies have reported a high rate of unplanned readmissions following acute percutaneous coronary intervention (PCI). Data outside the USA comparing 30-day unplanned readmissions following elective PCI to those who undergo acute PCI remain limited.

METHODS

Patients who underwent a PCI procedure in Australia and New Zealand between 2010 and 2015 were included. We determined the rates, causes and predictors of 30-day unplanned readmissions, as well as rates of repeat revascularisation procedures, for patients who underwent an elective or acute PCI. Predictors of readmissions were identified using logistic regression.

RESULTS

A total of 199,686 PCI encounters were included, of which 74,890 (37.5%) were elective and 124,796 (62.5%) were acute procedures. Overall, 10.6% of patients had at least one unplanned readmission within 30 days of discharge with lower rates following elective PCI (7.0%) compared to acute PCI (12.7%) (p<0.01). Non-specific chest pain was the commonest cause of readmission after elective and acute PCI, accounting for 20.7% and 21.5% of readmission diagnoses, respectively. Readmissions for acute myocardial infarction (13.0% vs 4.6%, p<0.01) and heart failure (6.5% vs 3.3%, p<0.01) were higher following acute PCI compared to elective PCI. Among readmitted patients, 16.7% had a coronary catheterisation, 12.2% had a PCI and 0.7% had coronary artery bypass surgery. Multivariable predictors of 30-day unplanned readmission included female sex and comorbidities such as heart failure, metastatic disease, chronic lung disease and renal failure (p<0.0001 for all).

CONCLUSIONS

Unplanned readmissions following elective or acute PCI are high. Clinical and quality-control measures are required to prevent avoidable readmissions in both settings.

Early vs. Late Readmission following Percutaneous Coronary Intervention: Predictors and Impact on Long-Term Outcomes

BACKGROUND

Readmissions within 1 year after percutaneous coronary intervention (PCI) are common (18.6-50.4% in international series) and a burden to patients and health services, however their long-term implications are not well characterised. We compared predictors of 30-day (early) and 31-day to 1-year (late) unplanned readmission and the impact of unplanned readmission on long-term clinical outcomes post-PCI.

METHODS

Patients enrolled in the GenesisCare Cardiovascular Outcomes Registry (GCOR-PCI) from 2008 to 2020 were included in the study. Multivariate logistic regression analysis was performed to identify predictors of early and late unplanned readmission. A Cox proportion hazards regression model was used to explore the impact of any unplanned readmission during the first year post-PCI on the clinical outcomes at 3 years. Finally, patients with early and late unplanned readmission were compared to determine which group was at the highest risk of adverse long-term outcomes.

RESULTS

The study comprised 16,911 consecutively enrolled patients who underwent PCI between 2009-2020. Of these, 1422 patients (8.5%) experienced unplanned readmission within 1-year post-PCI. Overall, the mean age was 68.9 ± 10.5 years, 76.4% were male and 45.9% presented with acute coronary syndromes. Predictors of unplanned readmission included increasing age, female gender, previous CABG, renal impairment and PCI for acute coronary syndromes. Unplanned readmission within 1 year of PCI was associated with an increased risk of MACE (adjusted HR 1.84 (1.42-2.37), p < 0.001) and death over a 3-year follow-up (adjusted HR 1.864 (1.34-2.59), p < 0.001) compared with those without readmission within 1-year post-PCI. Late compared with early unplanned readmission within the first year of PCI was more frequently associated with subsequent unplanned readmission, MACE and death between 1 and 3 years post-PCI.

CONCLUSIONS

Unplanned readmissions in the first year following PCI, particularly those occurring more than 30 days after discharge, were associated with a significantly higher risk of adverse outcomes, such as MACE and death at 3 years. Strategies to identify patients at high risk of readmission and interventions to reduce their greater risk of adverse events should be implemented post-PCI.

Impact of diabetes on long-term all-cause re-hospitalization after revascularization with percutaneous coronary intervention

PURPOSE

The purpose of the study was to investigate the incidence, cause and probability of re-hospitalization within 30 and 365 days after percutaneous coronary intervention (PCI) in patients with diabetes.

METHOD

Between January 2010 and September 2014, 2763 patients with diabetes were treated with PCI at two Hospitals in Western Denmark. Reasons for readmission within 30 and 365 days were identified.

RESULTS

Readmission risks for patients with diabetes were 58% within 365 days and 18% within 30 days. Reason for readmission was ischemic heart disease (IHD) in 725 patients (27%), and non-IHD-related reasons in 826 patients (31%). IHD-related readmission within 365 days was associated with female gender (OR 1.3, 95% CI: 1.1-1.5), and non-ST-segment elevation myocardial infarction, compared to stable angina at the index hospitalization (OR 1.3, 95% CI: 1.1-1.6). Among patients with diabetes, increased risk of readmission due to other reasons were age (OR 1.3, 95% CI: 1.2-1.5) and higher scores of modified Charlson Comorbidity index (CCI): CCI ≥3 (OR 3.6, 95% CI: 2.8-4.6).

CONCLUSION

More than half of the patients with diabetes mellitus undergoing PCI were readmitted within 1 year. Comorbidities were the strongest predictor for non-IHD-related readmission, but did not increase the risk for IHD-related readmissions.

Prediction of All-Cause Mortality Following Percutaneous Coronary Intervention in Bifurcation Lesions Using Machine Learning Algorithms

Stratifying prognosis following coronary bifurcation percutaneous coronary intervention (PCI) is an unmet clinical need that may be fulfilled through the adoption of machine learning (ML) algorithms to refine outcome predictions. We sought to develop an ML-based risk stratification model built on clinical, anatomical, and procedural features to predict all-cause mortality following contemporary bifurcation PCI. Multiple ML models to predict all-cause mortality were tested on a cohort of 2393 patients (training, n = 1795; internal validation, n = 598) undergoing bifurcation PCI with contemporary stents from the real-world RAIN registry. Twenty-five commonly available patient-/lesion-related features were selected to train ML models. The best model was validated in an external cohort of 1701 patients undergoing bifurcation PCI from the DUTCH PEERS and BIO-RESORT trial cohorts. At ROC curves, the AUC for the prediction of 2-year mortality was 0.79 (0.74–0.83) in the overall population, 0.74 (0.62–0.85) at internal validation and 0.71 (0.62–0.79) at external validation. Performance at risk ranking analysis, k-center cross-validation, and continual learning confirmed the generalizability of the models, also available as an online interface. The RAIN-ML prediction model represents the first tool combining clinical, anatomical, and procedural features to predict all-cause mortality among patients undergoing contemporary bifurcation PCI with reliable performance.

Prediction models for hospital readmissions in patients with heart disease: a systematic review and meta-analysis

OBJECTIVE

To describe the discrimination and calibration of clinical prediction models, identify characteristics that contribute to better predictions and investigate predictors that are associated with unplanned hospital readmissions.

DESIGN

Systematic review and meta-analysis.

DATA SOURCE

Medline, EMBASE, ICTPR (for study protocols) and Web of Science (for conference proceedings) were searched up to 25 August 2020.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies were eligible if they reported on (1) hospitalised adult patients with acute heart disease; (2) a clinical presentation of prediction models with c-statistic; (3) unplanned hospital readmission within 6 months.

PRIMARY AND SECONDARY OUTCOME MEASURES

Model discrimination for unplanned hospital readmission within 6 months measured using concordance (c) statistics and model calibration. Meta-regression and subgroup analyses were performed to investigate predefined sources of heterogeneity. Outcome measures from models reported in multiple independent cohorts and similarly defined risk predictors were pooled.

RESULTS

Sixty studies describing 81 models were included: 43 models were newly developed, and 38 were externally validated. Included populations were mainly patients with heart failure (HF) (n=29). The average age ranged between 56.5 and 84 years. The incidence of readmission ranged from 3% to 43%. Risk of bias (RoB) was high in almost all studies. The c-statistic was <0.7 in 72 models, between 0.7 and 0.8 in 16 models and >0.8 in 5 models. The study population, data source and number of predictors were significant moderators for the discrimination. Calibration was reported for 27 models. Only the GRACE (Global Registration of Acute Coronary Events) score had adequate discrimination in independent cohorts (0.78, 95% CI 0.63 to 0.86). Eighteen predictors were pooled.

CONCLUSION

Some promising models require updating and validation before use in clinical practice. The lack of independent validation studies, high RoB and low consistency in measured predictors limit their applicability.

PROSPERO REGISTRATION NUMBER

CRD42020159839.

Accuracy of the PARIS score and PCI complexity to predict ischemic events in patients treated with very thin stents in unprotected left main or coronary bifurcations

BACKGROUND

The PARIS risk score (PARIS-rs) and percutaneous coronary intervention complexity (PCI-c) predict clinical and procedural residual ischemic risk following PCI. Their accuracy in patients undergoing unprotected left main (ULM) or bifurcation PCI has not been assessed.

METHODS

The predictive performances of the PARIS-rs (categorized as low, intermediate, and high) and PCI-c (according to guideline-endorsed criteria) were evaluated in 3,002 patients undergoing ULM/bifurcation PCI with very thin strut stents.

RESULTS

After 16 (12-22) months, increasing PARIS-rs (8.8% vs. 14.1% vs. 27.4%, p < .001) and PCI-c (15.2% vs. 11%, p = .025) were associated with higher rates of major adverse cardiac events ([MACE], a composite of death, myocardial infarction [MI], and target vessel revascularization), driven by MI/death for PARIS-rs and target lesion revascularization/stent thrombosis for PCI-c (area under the curves for MACE: PARIS-rs 0.60 vs. PCI-c 0.52, p-for-difference < .001). PCI-c accuracy for MACE was higher in low-clinical-risk patients; while PARIS-rs was more accurate in low-procedural-risk patients. ≥12-month dual antiplatelet therapy (DAPT) was associated with a lower MACE rate in high PARIS-rs patients, (adjusted-hazard ratio 0.42 [95% CI: 0.22-0.83], p = .012), with no benefit in low to intermediate PARIS-rs patients. No incremental benefit with longer DAPT was observed in complex PCI.

CONCLUSIONS

In the setting of ULM/bifurcation PCI, the residual ischemic risk is better predicted by a clinical risk estimator than by PCI complexity, which rather appears to reflect stent/procedure-related events. Careful procedural risk estimation is warranted in patients at low clinical risk, where PCI complexity may substantially contribute to the overall residual ischemic risk.

Incidence and Predictors of Unplanned Hospital Readmission after Percutaneous Coronary Intervention

Unplanned readmissions to hospital after percutaneous coronary intervention (PCI) pose a significant burden to the healthcare system and are potentially preventable. In this study, we sought to determine the incidence of, and risk factors for, unplanned hospital readmissions within 30 days following PCI. We prospectively collected data on 28,488 patients undergoing PCI between 2013 and 2019, who were enrolled in the state-wide multi-centre Victorian Cardiac Outcomes Registry. Patients’ data were then linked to data from the Victorian Department of Health administrative database that records statewide hospital admissions. Disease diagnosis codes were used to identify cause of readmission. Patients who had an unplanned readmission were further divided into those who had a cardiac vs. non-cardiac cause for readmission. Overall, 3059 patients (10.7%) had an unplanned hospital readmission within 30 days of PCI, of which 1848 patients (60.4%) were readmitted for primarily cardiac diagnoses. Independent predictors of both 30-day unplanned cardiac and non-cardiac readmissions post-PCI were female sex, having ≥1 admission in the 12 months prior to PCI, acute coronary syndrome presentation, having any in-hospital complication and being discharged on an oral anticoagulant (all p < 0.05). A stepwise increase in readmission risk was observed with increasing number of admissions from 1 to ≥4 admissions in the 12 months prior to PCI. In conclusion, a substantial proportion of patients undergoing PCI have unexpected readmissions to hospital in the 30 days following PCI. Targeted strategies for patients with risk factors for readmission may be useful to reduce this significant burden to the healthcare system.

Validation of the Elderly Risk Assessment Index in the Emergency Department

OBJECTIVES

The Elderly Risk Assessment (ERA) score is a validated index for primary care patients that predict hospitalizations, mortality, and Emergency Department (ED) visits. The score incorporates age, prior hospital days, marital status, and comorbidities. Our aim was to validate the ERA score in ED patients.

METHODS

Observational cohort study of patients age ≥ 60 presenting to an academic ED over a 1-year period. Regression analyses were performed for associations with outcomes (hospitalization, return visits and death). Medians, interquartile range (IQR), odds ratios (OR) and 95% confidence intervals (CI) were calculated.

RESULTS

The cohort included 27,397 visits among 18,607 patients. Median age 74 years (66-82), 48% were female and 59% were married. Patients from 54% of visits were admitted to the hospital, 16% returned to the ED within 30 days, and 18% died within one year. Higher ERA scores were associated with: hospital admission (score 10 [4-16] vs 5 [1-11], p < 0.0001), return visits (11 [5-17] vs 7 [2-13], p < 0.0001); and death within one year (14 [7-20] vs 6 [2-13], p < 0.0001). Patients with ERA score ≥ 16 were more likely to be admitted to the hospital, OR 2.14 (2.02-2.28, p < 0.0001), return within 30 days OR 1.99 (1.85-2.14), and to die within a year, OR 2.69 (2.54-2.85).

CONCLUSION

The ERA score can be automatically calculated within the electronic health record and helps identify patients at increased risk of death, hospitalization and return ED visits. The ERA score can be applied to ED patients, and may help prognosticate the need for advanced care planning.

Validation of the Elderly Risk Assessment Index in the Emergency Department

OBJECTIVES

The Elderly Risk Assessment (ERA) score is a validated index for primary care patients that predict hospitalizations, mortality, and Emergency Department (ED) visits. The score incorporates age, prior hospital days, marital status, and comorbidities. Our aim was to validate the ERA score in ED patients.

METHODS

Observational cohort study of patients age ≥ 60 presenting to an academic ED over a 1-year period. Regression analyses were performed for associations with outcomes (hospitalization, return visits and death). Medians, interquartile range (IQR), odds ratios (OR) and 95% confidence intervals (CI) were calculated.

RESULTS

The cohort included 27,397 visits among 18,607 patients. Median age 74 years (66-82), 48% were female and 59% were married. Patients from 54% of visits were admitted to the hospital, 16% returned to the ED within 30 days, and 18% died within one year. Higher ERA scores were associated with: hospital admission (score 10 [4-16] vs 5 [1-11], p < 0.0001), return visits (11 [5-17] vs 7 [2-13], p < 0.0001); and death within one year (14 [7-20] vs 6 [2-13], p < 0.0001). Patients with ERA score ≥ 16 were more likely to be admitted to the hospital, OR 2.14 (2.02-2.28, p < 0.0001), return within 30 days OR 1.99 (1.85-2.14), and to die within a year, OR 2.69 (2.54-2.85).

CONCLUSION

The ERA score can be automatically calculated within the electronic health record and helps identify patients at increased risk of death, hospitalization and return ED visits. The ERA score can be applied to ED patients, and may help prognosticate the need for advanced care planning.

Long-Term Survival after Acute Myocardial Infarction in Lithuania during Transitional Period (1996-2015): Data from Population-Based Kaunas Ischemic Heart Disease Register

Background and Objective: There is a lack of reliable epidemiological data on the long-term survival after acute myocardial infarction (AMI) in the Lithuanian population. The aim of the study was to evaluate the long-term (36 months) survival after AMI among persons aged 25–64 years, who had experienced AMI in four time-periods 1996, 2003–2004, 2008, and 2012. Material and Methods: The source of the data was Kaunas population-based Ischemic heart disease (IHD) register. Long-term survival after AMI (36 months) was evaluated using the Kaplan–Meier method. The survival curves significantly differed when p < 0.05. Hazard ratio for all-cause mortality and their 95% CIs, adjusted for baseline characteristics, were estimated with the Cox proportional hazards regression model. Results: The analysis of data on 36 months long-term survival among Kaunas population by sex and age groups showed that the survival rates among men and women were 83.4% and 87.6%, respectively (p < 0.05) and among 25–54 years-old and 55–64 years-old persons, 89.2% and 81.7%, respectively (p < 0.05). The rates of long-term survival of post-AMI Kaunas population were better in past periods than in first period. According to the data of the Kaplan-Meier survival analysis, long-term survival of 25 to 64-year-old post-AMI Kaunas population was without significantly difference in 1996, 2003–2004, 2008 and 2012 (Log-rank = 6.736, p = 0.081). The adjusted risk of all-cause mortality during 36 months among men and 25 to 54-year-old patients was on the average by 35% and 60% lower in 2012 than in 1996, respectively. Conclusion: It was found that 36 months survival post MI among women and younger (25–54 years) persons was significant better compared to men and older (55–64 years) persons. Long-term survival among 55 to 64-year-old post-AMI Kaunas population had a tendency to decrease during last period, while among 25–54 years old persons long-term survival was without significant changes. The results highlight the fact that AMI survivors, especially in youngest age, remain a high-risk group and reinforce the importance of primary and secondary prevention for the improvement of long-term prognosis of AMI patients.

Readmissions to Hospital After Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis of Factors Associated with Readmissions

BACKGROUND

Readmissions after PCI are a burden to patients and health services that are not well understood.

METHODS

A systematic review was performed to identify studies of readmission after PCI. Readmission rates and causes of readmission were examined and factors associated with 30-day readmissions were combined using meta-analyses.

RESULTS

A total of 39 studies evaluated readmissions after PCI (6,569,690 patients, 31 studies). The 30-day readmission rate varied from 3.3%-15.8%. Beyond 30-days, the readmission rate was 6% at 2 months, 31.5% at 6 months, 18.6-50.4% at 12 months and 26.3-71% beyond 48 months. The pooled proportion of patients with cardiac cause for readmissions ranged from 4.6%-75.3%. The range of rates of 30-day readmissions for reinfarction/stent thrombosis, heart failure, chest pain and bleeding were 2.5%-9.5%, 5.9%-12%, 6.7-38.1% and 0.7-7.5%, respectively. Meta-analysis suggests that female gender (RR 1.25(1.20-1.30), I² = 65.2%), diabetes (RR 1.22(1.20-1.25), I² = 0%), heart failure (RR 1.43(CI 1.28-1.60), I² = 92.8%), renal failure (RR 1.50(1.45-1.55), I² = 0%), chronic lung disease (RR 1.34(1.26-1.44), I² = 87.5%), peripheral artery disease (RR 1.20(1.15-1.25), I² = 46.5%) and cancer (RR 1.35(1.15-1.58), I² = 72.8%) were associated with 30-day readmissions. The average cost of unplanned and all 30-day readmissions has been reported to be $12,636 and $17,576, respectively.

CONCLUSIONS

We estimate that 1 in 7 patients who undergo PCI are readmitted within 30-days and the rate can rise to up to 3 in 4 patients beyond 3 years. Interventions should be considered to reduce readmissions such as discharge checklists, evaluation of medication compliance at follow-up and prompt management when patients re-present to emergency department.

Daily risk of adverse outcomes in patients undergoing complex lesions revascularization: A subgroup analysis from the RAIN-CARDIOGROUP VII study (veRy thin stents for patients with left mAIn or bifurcatioN in real life)

INTRODUCTION

Percutaneous coronary intervention (PCI) for complex lesions, including unprotected left main (ULM) and bifurcations, is gaining a relevant role in treating coronary artery disease with good outcomes, also thanks to new generation stents. The daily risk of adverse cardiovascular events and their temporal distribution after these procedures is not known.

METHODS

All consecutive patients presenting with a critical lesion of ULM or bifurcation treated with very thin struts stents, enrolled in the RAIN-Cardiogroup VII study, were analyzed. The daily risk of major acute cardiovascular events (MACE), target lesion revascularization (TLR) and stent thrombosis (ST) and their temporal distribution in the first year of follow-up was the primary endpoint. Differences among subgroups (ULM, patient presentation, kind of stent polymer) were the secondary endpoint.

RESULTS

2745 patients were included, mean age 68 ± 11 years, 33.3% diabetics, 54.5% had an acute coronary syndrome (ACS); 88.5% of treated lesions were bifurcations, 27.2% ULM. Average daily risk was 0.022% for MACE, 0.005% for TLR and 0.004% for ST, in the first year. Bimodal distribution of adverse events, especially TLR, with an early peak in the first 50 days and a late one after 150 days, was observed. Patients with ULM presented a significantly higher daily risk of events, and ACS patients presented higher MACE risk. No difference emerged according to the type of stent polymer.

CONCLUSIONS

The daily risk of adverse events in the first year after complex PCI in our study is acceptably low. PCI on ULM carries a higher risk of complications.

Association of Beta-Blockers with Survival on Patients Presenting with ACS Treated with PCI: A Propensity Score Analysis from the BleeMACS Registry

PURPOSE

The aim was to evaluate prognostic value of beta-blocker (BB) administration in acute coronary syndromes (ACS) patients in the percutaneous coronary intervention (PCI) era.

METHODS AND RESULTS

The BleeMACS project is a multicenter, observational, retrospective registry enrolling patients with ACS worldwide in 15 hospitals. Patients discharged with BB therapy were compared to those discharged without a BB before and after propensity score with matching. The primary endpoint was all-cause mortality at 1 year. Secondary endpoints included in-hospital reinfarction, in-hospital heart failure, 1-year myocardial infarction, 1-year bleeding and 1-year composite of death and recurrent myocardial infarction. After matching, 2935 patients for each group were enrolled. The primary endpoint of 1-year death was significantly lower in the group on BB therapy (4.5 vs 7%, p < 0.05), while only a trend was noted for recurrent acute myocardial infarction (4.5 vs 4.9%, p = 0.54). These results were consistent for patients older than 80 years of age, for ST-elevation myocardial infarction (STEMI) patients, and for those discharged with complete versus incomplete revascularization, but not for non-STEMI/unstable angina patients.

CONCLUSIONS

BB therapy was related to 1-year lower risk of all-cause mortality, independently from completeness of revascularization, admission diagnosis, age and ejection fraction. Randomized controlled trials for patients treated with PCI for ACS should be performed.

Rehospitalizations Following Primary Percutaneous Coronary Intervention in Patients With ST-Elevation Myocardial Infarction: Results From a Multi-Center Randomized Trial

Background

Rehospitalizations (RHs) after ST‐elevation myocardial infarction carry a high economic burden and may deteriorate quality of life. Characterizing patients at higher risk may allow the design of preventive measures. We studied the frequency, reasons, and predictors for unplanned cardiac and noncardiac RHs in ST‐elevation myocardial infarction patients undergoing primary percutaneous coronary intervention.

Methods and Results

In this post‐hoc analysis of the COMFORTABLE AMI (Comparison of Biolimus Eluted From an Erodible Stent Coating With Bare Metal Stents in Acute ST‐Elevation Myocardial Infarction; NCT00962416) trial including 1137 patients, unplanned cardiac and noncardiac RHs occurred in 133 (11.7%) and in 79 patients (6.9%), respectively, at 1 year. The most frequent reasons for unplanned cardiac RHs were recurrent chest pain without evidence of ischemia (20.4%), recurrent chest pain with ischemia and coronary intervention (16.9%), and ischemic events (16.9%). Unplanned noncardiac RHs occurred most frequently attributed to bleeding (24.5%), infections (14.3%), and cancer (9.1%). On multivariate analysis, left ventricular ejection fraction (22% increase in the rate of RHs per 10% decrease; P=0.03) and angiographic myocardial infarction Syntax score (34% increase per 10‐point increase; P=0.01) were independent predictors of unplanned cardiac RHs. Age emerged as the only independent predictor of unplanned noncardiac RHs. Regional differences for unplanned cardiac RHs were observed.

Conclusions

Among ST‐elevation myocardial infarction patients undergoing primary percutaneous coronary intervention in the setting of a randomized, clinical trial, unplanned cardiac RHs occurred in 12% with recurrent chest pain being the foremost reason. Unplanned noncardiac RHs occurred in 7% with bleeding as the leading cause. Left ventricular ejection fraction and Syntax score were independent predictors of unplanned cardiac RHs and identified patient subgroups in need for improved secondary prevention.

Clinical Trial Registration

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00962416.

PRotective Effect on the coronary microcirculation of patients with DIabetes by Clopidogrel or Ticagrelor (PREDICT): study rationale and design. A randomized multicenter clinical trial using intracoronary multimodal physiology

Background

In diabetic patients a predisposed coronary microcirculation along with a higher risk of distal particulate embolization during primary percutaneous intervention (PCI) increases the risk of peri-procedural microcirculatory damage. However, new antiplatelet agents, in particular Ticagrelor, may protect the microcirculation through its adenosine-mediated vasodilatory effects.

Methods

PREDICT is an original, prospective, randomized, multicenter controlled study designed to investigate the protective effect of Ticagrelor on the microcirculation during PCI in patient with diabetes mellitus type 2 or pre-diabetic status. The primary endpoints of this study aim to test (i) the decrease in microcirculatory resistance with antiplatelet therapy (Ticagrelor > Clopidogrel; mechanistic effect) and (ii) the relative microcirculatory protection of Ticagrelor compared to Clopidogrel during PCI (Ticagrelor < Clopidogrel; protective effect).

Conclusions

PREDICT will be the first multicentre clinical trial to test the adenosine-mediated vasodilatory effect of Ticagrelor on the microcirculation during PCI in diabetic patients. The results will provide important insights into the prospective beneficial effect of this drug in preventing microvascular impairment related to PCI (http://www.clinicaltrials.gov No. NCT02698618).

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-017-0543-5) contains supplementary material, which is available to authorized users.

Review of early hospitalisation after percutaneous coronary intervention

BACKGROUND

Percutaneous coronary intervention (PCI) is the most common modality of revascularization in patients with coronary artery disease. Understanding the readmission rates and reasons for readmission after PCI is important because readmissions are a quality of care indicator, in addition to being a burden to patients and healthcare services.

METHODS

A literature review was performed. Relevant studies are described by narrative synthesis with the use of tables to summarize study results.

RESULTS

Data suggests that 30-day readmissions are not uncommon. The rate of readmission after PCI is highly influenced by the cohort and the healthcare system studied, with 30-day readmission rates reported to be between 4.7-% and 15.6%. Studies consistently report that a majority of readmissions within 30days are due to a cardiac-related disorders or complication-related disorders. Female sex, peripheral vascular disease, diabetes mellitus, renal failure and non-elective PCI are predictive of readmission. Studies also suggest that there is greater risk of mortality among patients who are readmitted compared to those who are not readmitted.

CONCLUSION

Readmission after PCI is common and its rate is highly influenced by the type of cohort studied. There is clear evidence that majority of readmissions within 30days are cardiac related. While there are many predictors of readmission following PCI, it is not known whether targeting patients with modifiable predictors could prevent or reduce the rates of readmission.

Evidence-based interventions in primary care following acute coronary syndrome in Australia and New Zealand: a systematic scoping review

BACKGROUND

Coronary artery disease has a significant disease burden, but there are many known barriers to management of acute coronary syndrome (ACS). General practitioners (GPs) bear considerable responsibility for post-discharge management of ACS in Australia and New Zealand (NZ), but knowledge about the extent and efficacy of such management is limited. This systematic review summarises published evidence from Australia and New Zealand regarding management in primary care after discharge following ACS.

METHODS

A search of PubMed, Scopus, CINAHL-Plus and PSYCINFO databases in August 2015 was supplemented by citation screening and hand-searching. Literature was selected based on specified criteria, and assessed for quality using the Mixed Methods Appraisal Tool (MMAT). Extracted data was related to evidence-based interventions specified by published guidelines.

RESULTS

The search yielded 19 publications, most of which reported on quantitative and observational studies from Australia. The majority of studies scored at least 75 % on the MMAT. Diverse aspects of management by GPs are presented according to categories of evidence-based guidelines. Data suggests that GPs are more likely to prescribe ACS medications than to assist in lifestyle or psychological management. GP referral to cardiac rehabilitation varied, and one study showed an improvement in the number of ACS patients with documented ACS management plans. Few studies described successful interventions to improve GP management, though some quality improvement efforts through education and integration of care with hospitals were beneficial. Limited data was published about interventions effective in rural, minority, and Indigenous populations.

CONCLUSIONS

Research reflects room for improvement in GP post-discharge ACS management, but little is known about effective methods for improvement. Additional research, both observational and interventional, would assist GPs in improving the quality of post-discharge ACS care.

Effects of a home-based activation intervention on self-management adherence and readmission in rural heart failure patients: the PATCH randomized controlled trial

BACKGROUND

Heart failure (HF) patients discharged from rural hospitals have higher 30-day readmission rates. Self-management (SM) reduces readmissions, but adherence to SM guidelines is low in the rural HF population. We tested a home-based intervention to enhance patient activation and lead to improved SM adherence.

METHODS

In this two-group, repeated measures randomized control trial, the main outcomes were patient reported and clinical outcomes associated with SM adherence, and all-cause readmission at 30, 90 and 180 days.

RESULTS

The study included 100 HF patients discharged from a rural critical access hospital. The intervention group received a 12-week SM training and coaching program delivered by telephone and tailored on subjects' activation levels. At α = .10, the PATCH intervention showed significantly greater improvement compared to usual care in patient-reported SM adherence: weighing themselves, following a low-sodium diet, taking prescribed medication, and exercising daily (all p < .0005) at 3 and 6 months after discharge. In contrast, groups did not differ in physical activity assessed by actigraphy or in clinical biomarkers. Contrary to expectation, the 30-day readmission rate was significantly higher (p = .088) in the intervention group (19.6 %) than in the control group (6.1 %), with no differences at 90 or 180 days.

CONCLUSION

It is feasible to conduct a randomized controlled trial in HF patients discharged from rural critical access hospitals. Significantly higher patient-reported SM adherence was not accompanied by lower clinical biomarkers or readmission rates. Further research is needed to understand mechanisms that influence outcomes and healthcare utilization in this population.

TRIAL REGISTRATION

CLINICAL TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov; NCT01964053 .

Prolonged and intensive medication use are associated with the obesity paradox after percutaneous coronary intervention: a systematic review and meta-analysis of 12 studies

Background

Obesity paradox is defined as the unexpected decrease in the total number of death which has been observed among patients who are overweight and obese compared to patients with normal weight after undergoing revascularization by percutaneous coronary intervention (PCI). Despite of so many recent studies which showed the existence of this phenomenon, prolonged and intensive medication use were only suggested to be among the reasons responsible for this ‘obesity paradox’ but it was never confirmed whether this hypothesis should really be considered true or not. Therefore, this study aimed to investigate whether prolonged and intensive medication use were associated with this obesity paradox after PCI.

Methods

Medline, PubMed, EMBASE and the Cochrane Library were searched for studies showing the existence of this ‘obesity paradox’ in patients who underwent coronary revascularization by PCI and only articles comprising of medication use among the patients analyzed were considered relevant for this research. Medication use among the different subgroups of patients was calculated. Mortality was considered as the clinical endpoint in this study. Risk Ratio (RR) with 95 % Confidence Interval (CI) was used to express the pooled effect on discontinuous variables and the pooled analyses were performed with RevMan 5.3.

Results

Twelve studies consisting of a total number of 91,582 patients was included in this meta-analysis. An intensive medication use after the hospital discharge and during the follow up period after PCI was observed in the subgroup of obese patients, followed by the overweight patients and the normal weight patients respectively. Our results showed that the short-term (30 days) mortality in overweight and obese patients was significantly lower compared to the normal weight patients with RR: 0.72; 95 % CI: 0.56-0.92, p = 0.008 and RR: 0.47, 95 % CI: 0.34-0.65; p < 0.00001 respectively. The long-term (≥ one year) mortality was also significantly lower in the overweight and the obese groups with RR: 0.74, 95 % CI: 0.67-0.82; p < 0.00001 and RR: 0.63, 95 % CI: 0.55-0.72; p < 0.00001 respectively.

Conclusion

Our study has confirmed to some extent, that prolonged and intensive use of medications which were more prominent in patients who were overweight and obese during the follow up period, might apparently be among the reasons responsible for this obesity paradox after PCI.

Improved treatment and prognosis after acute myocardial infarction in Estonia: cross-sectional study from a high risk country

BACKGROUND

The aim of the study was to explore trends in short- and long-term mortality after hospitalization for acute myocardial infarction (AMI) over the period 2001─2011 in Estonian secondary and tertiary care hospitals while adjusting for changes in baseline characteristics.

METHODS

In this nationwide cross-sectional study random samples of patients hospitalized due to AMI in years 2001, 2007 and 2011 were identified and followed for 1 year. Trends in 30-day and 1-year all-cause mortality were analysed using Cox proportional hazards regression model.

RESULTS

The final analysis included 423, 687 and 665 patients in years 2001, 2007 and 2011 respectively. During the study period, the prevalence of most comorbidities remained unchanged while the in-hospital and outpatient treatment improved significantly. For example, the proportion of tertiary care hospital AMI patients who underwent revascularization was almost three times higher in 2011 compared to 2001. The proportion of secondary care patients who were referred to a tertiary care centre for more advanced care increased from 5.8 to 40.1 % (p for trend <0.001). Meanwhile, the 1-year mortality rates decreased from 29.5 to 20.2 % (adjusted p = 0.004) in the tertiary and from 32.4 to 23.1 % (adjusted p = 0.006) in the secondary care. The decrease in the 30-day mortality rates was statistically significant only in the secondary care hospitals.

CONCLUSIONS

The use of evidence-based treatments in Estonian AMI patients improved between 2001 and 2011. At the same time, we observed a significant reduction in the long-term mortality rates, both for patients primarily hospitalized into secondary as well as into tertiary care hospitals.

Development, Validation and Deployment of a Real Time 30 Day Hospital Readmission Risk Assessment Tool in the Maine Healthcare Information Exchange

Objectives

Identifying patients at risk of a 30-day readmission can help providers design interventions, and provide targeted care to improve clinical effectiveness. This study developed a risk model to predict a 30-day inpatient hospital readmission for patients in Maine, across all payers, all diseases and all demographic groups.

Methods

Our objective was to develop a model to determine the risk for inpatient hospital readmission within 30 days post discharge. All patients within the Maine Health Information Exchange (HIE) system were included. The model was retrospectively developed on inpatient encounters between January 1, 2012 to December 31, 2012 from 24 randomly chosen hospitals, and then prospectively validated on inpatient encounters from January 1, 2013 to December 31, 2013 using all HIE patients.

Results

A risk assessment tool partitioned the entire HIE population into subgroups that corresponded to probability of hospital readmission as determined by a corresponding positive predictive value (PPV). An overall model c-statistic of 0.72 was achieved. The total 30-day readmission rates in low (score of 0–30), intermediate (score of 30–70) and high (score of 70–100) risk groupings were 8.67%, 24.10% and 74.10%, respectively. A time to event analysis revealed the higher risk groups readmitted to a hospital earlier than the lower risk groups. Six high-risk patient subgroup patterns were revealed through unsupervised clustering. Our model was successfully integrated into the statewide HIE to identify patient readmission risk upon admission and daily during hospitalization or for 30 days subsequently, providing daily risk score updates.

Conclusions

The risk model was validated as an effective tool for predicting 30-day readmissions for patients across all payer, disease and demographic groups within the Maine HIE. Exposing the key clinical, demographic and utilization profiles driving each patient’s risk of readmission score may be useful to providers in developing individualized post discharge care plans.