Incidence and predictors of 30-day hospital readmission rate following percutaneous coronary intervention (from the National Heart, Lung, and Blood Institute Dynamic Registry)

The association between metabolic syndrome and major adverse cardiac and cerebrovascular events in patients with acute coronary syndrome undergoing percutaneous coronary intervention

Metabolic syndrome (MetS) poses an additional risk for the development of coronary artery disease and major adverse cardiac and cerebrovascular events (MACCE). In this study, we investigated the association between MetS and its components and MACCE after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS). The presence of MetS was calculated at baseline using the NCEP-ATP III criteria. The primary outcome was MACCE and its components were secondary outcomes. Unadjusted and adjusted Cox Regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CI) of the association between MetS or its components and MACCE and its components. A total of 13,459 ACS patients who underwent PCI (MetS: 7939 and non-MetS: 5520) with a mean age of 62.7 ± 11.0 years (male: 72.5%) were included and median follow-up time was 378 days. Patients with MetS had significantly higher MACCE risk (adjusted HR [aHR] 1.22, 95% CI 1.08-1.39). The only component of MACCE that exhibited a significantly higher incidence in MetS patients was myocardial infarction (aHR 1.43, 95% CI 1.15-1.76). MetS components that were significantly associated with a higher incidence of MACCE were hypertension and impaired fasting glucose. Having three MetS components did not increase MACCE (aHR 1.12, 95% CI 0.96-1.30) while having four (aHR 1.32, 95% CI 1.13-1.55) or five (aHR 1.42, 95% CI 1.15-1.75) MetS components was associated with a higher incidence of MACCE. MetS was associated with a higher risk of MACCE in ACS patients undergoing PCI. Among MACCE components, myocardial infarction was significantly higher in patients with MetS. Impaired fasting glucose and hypertension were associated with a higher risk of MACCE. Identifying these patterns can guide clinicians in choosing appropriate preventive measures.

Effect of Rivaroxaban vs Enoxaparin on Major Cardiac Adverse Events and Bleeding Risk in the Acute Phase of Acute Coronary Syndrome: The H-REPLACE Randomized Equivalence and Noninferiority Trial

IMPORTANCE

Parenteral enoxaparin is a preferred anticoagulant used in the acute phase for patients with acute coronary syndrome (ACS). The safety and efficacy of short-term low-dose rivaroxaban in this clinical setting remain unknown.

OBJECTIVE

To compare the safety and efficacy of rivaroxaban vs enoxaparin in the acute phase of ACS.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter, prospective, open-label, active-controlled, equivalence and noninferiority trial was conducted from January 2017 through May 2021 with a 6-month follow-up at 21 hospitals in China. Participants included patients with ACS missing the primary reperfusion window or before selective revascularization. Data were analyzed from November 2021 to November 2022.

INTERVENTIONS

Participants were randomized 1:1:1 to oral rivaroxaban 2.5 mg or 5 mg or 1 mg/kg subcutaneous enoxaparin twice daily in addition to dual antiplatelet therapy (DAPT; aspirin 100 mg and clopidogrel 75 mg once daily) for a mean of 3.7 days.

MAIN OUTCOMES AND MEASURES

The primary safety end point was bleeding events, as defined by the International Society on Thrombosis and Haemostasis, and the primary efficacy end point was major adverse cardiovascular events (MACEs), including cardiac death, myocardial infarction, rerevascularization, or stroke during the 6-month follow-up.

RESULTS

Of 2055 enrolled patients, 2046 (99.6%) completed the trial (mean [SD] age 65.8 [8.2] years, 1443 [70.5%] male) and were randomized to enoxaparin (680 patients), rivaroxaban 2.5 mg (683 patients), or rivaroxaban 5 mg (683 patients). Bleeding rates were 46 patients (6.8%) in the enoxaparin group, 32 patients (4.7%) in the rivaroxaban 2.5 mg group, and 36 patients (5.3%)in the rivaroxaban 5 mg group (rivaroxaban 2.5 mg vs enoxaparin: noninferiority hazard ratio [HR], 0.68; 95% CI, 0.43 to 1.07; P = .005; rivaroxaban 5 mg vs enoxaparin: noninferiority HR, 0.88; 95% CI, 0.70 to 1.09; P = .001). The incidence of MACEs was similar among groups, and noninferiority was reached in the rivaroxaban 5 mg group (HR, 0.60; 95% CI, 0.31 to 1.16, P = .02) but not in the rivaroxaban 2.5 mg group (HR, 0.68; 95% CI, 0.36 to 1.30; P = .05) compared with the enoxaparin group.

CONCLUSIONS AND RELEVANCE

In this equivalence and noninferiority trial, oral rivaroxaban 5 mg showed noninferiority to subcutaneous enoxaparin (1 mg/kg) for patients with ACS treated with DAPT during the acute phase. Results of this feasibility study provide useful information for designing future randomized clinical trials with sufficient sample sizes.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03363035.

Incidence and prognosis of late readmission after percutaneous coronary intervention

BACKGROUND

Early readmission (< 30 days) after percutaneous coronary intervention (PCI) is associated with a worse prognosis, but little is known regarding the causes and consequences of late readmission. The aim of the present study was to determine the incidence, causes, and prognosis of patients readmitted > 1 < 12-months after PCI (late readmission).

METHODS

Single-center retrospective cohort study of 743 consecutive post-PCI patients. Patient characteristics and follow-up data were collected by reviewing their electronic medical records and from standardized telephone interviews performed at 1 year and at the end of follow-up.

RESULTS

Of the 743 patients, 224 (30.14%) were readmitted 1-12 months after PCI, 109 due to chest pain (48.66%), and 115 for other reasons (51.34%). Hospital readmission was associated with lower survival rates of 77.6% vs. 98.3% at 24 months and 73.5% vs. 97.6% at 36 months (p < 0.001). Univariate predictors for late readmission were hypertension, older age, chronic kidney disease, lower left ventricular ejection fraction, and lower baseline hemoglobin concentration. Only baseline hemoglobin concentration was an independent predictor of late readmission (odds ratio: 0.867, 95% confidence interval: 0.778-0.966, p = 0.01). Readmission for chest pain portrayed a lower mortality rate compared to other causes, with survival rates of 90.2% vs. 50% at 36 months (p < 0.001).

CONCLUSIONS

Late hospital readmission after PCI is associated with a worse prognosis and is related to patient comorbidities. Readmission for chest pain is common and portrayed a more favorable prognosis, similar to patients not readmitted. A readily available parameter, baseline anemia, was the main predictor of late readmission.

Perkütan Koroner Girişim Sonrası Periyodik Muayene Zaman Aralığı ve Sıklığının İkinci "Akut Koroner Sendrom" Yaşanmasına Etkisi

Objective: The aim of this study was to evaluate the effect of follow-ups of patients who underwent percutaneous coronary intervention (PCI) at short (

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.

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.

Causes and predictors of early readmission after percutaneous coronary intervention among patients discharged on oral anticoagulant therapy

Patients discharged on oral anticoagulant (OAC) therapy after percutaneous coronary intervention (PCI) represent a complex population and are at higher risk of early readmission. The reasons and predictors of early readmission in this group have not been well characterized. We identified patients in an integrated health care system who underwent PCI between 2009 and 2014 and were readmitted within 30 days within this health care system. Of the 9,357 patients surviving to discharge after the index PCI, 692 were readmitted within 30 days (7.4%). At the time of readmission, 143 had been discharged from the index PCI hospitalization on OACs (96.5% on warfarin) and 549 had not been discharged on OACs, with readmission rates of 12.9% and 6.7%, respectively (p<0.01). The most common reason for readmission among all patients was chest pain syndromes (21.7% on OACs, 34.4% not on OACs). However, bleeding represented the next most frequent cause of readmission among patients on OACs (14.0% on OACs vs 6.0% not on OACs, p<0.01). Among patients on OAC therapy, peripheral arterial disease (odds ratio [OR] 1.66, 95% confidence interval [CI] 1.07-2.57, p = 0.02) and nonelective PCI (OR 1.91, 95% CI 1.17-3.12, p<0.01) were found to be independent predictors of 30-day readmission. During rehospitalization, compared to patients not on OACs, patients on OACs suffered a higher unadjusted rate of mortality (6.3% vs 1.8%, p<0.01) and a longer length of stay (6.4 ± 7.1 days vs 4.9 ± 6.8 days, p = 0.02). In conclusion, patients discharged on OAC therapy after PCI are commonly readmitted, with bleeding representing a major reason. These readmissions are associated with high mortality and longer lengths of stay. Interventions targeted towards optimizing discharge planning for these complex patients are needed to potentially reduce readmissions.

An Evaluation of the Cost-effectiveness of Comprehensive MTM Integrated with Point-of-Care Phenotypic and Genetic Testing for U.S. Elderly Patients After Percutaneous Coronary Intervention

BACKGROUND

Poor health outcomes after percutaneous coronary intervention (PCI) in elderly patients is an area of concern among policymakers and administrators. In an effort to determine the best strategy to improve outcomes among elderly patients who underwent PCI, several studies have evaluated the cost-effectiveness of genotype-guided antiplatelet therapy compared with universal use of any one of the antiplatelet drugs indicated for patients with acute coronary syndrome (ACS) who underwent PCI. The results have either been in favor of genotype-guided antiplatelet therapy or universal use of ticagrelor. However, no study has yet evaluated the cost-effectiveness of pharmacist-provided face-to-face medication therapy management (MTM) combined with point-of-care genotype-guided antiplatelet therapy (POCP) when compared with universal use of ticagrelor or clopidogrel for the elderly after PCI.

OBJECTIVE

To evaluate the cost-effectiveness of a pharmacist integration of MTM with POCP (MTM-POCP) when compared with universal use of ticagrelor or clopidogrel combined with MTM (MTM-ticagrelor or MTM-clopidogrel).

METHODS

We conducted a cost-effectiveness analysis from the perspective of the U.S. health care system. A hybrid model, consisting of a 1-year decision tree and a 20-year Markov model, was used to simulate a cohort of elderly patients (aged at least 65 years) with ACS who underwent PCI. Treatment strategies available to patients were POCP, POCP-MTM, MTM-clopidogrel, or MTM-ticagrelor. Data used to populate the model were obtained from the PLATO trial and other published studies. Outcome measures were costs, quality-adjusted life-years (QALYs) and incremental cost per QALY gained. A deterministic and probabilistic sensitivity analysis was conducted to account for the joint uncertainty around the key parameters of the model. Finally, a benchmark willingness to pay of $50,000-200,000 was considered.

RESULTS

The use of PCOP (with dual antiplatelet therapy) resulted in 5.29 QALYs, at a cost of $50,207. MTM-clopidogrel resulted in 5.34 QALYs, at a cost of $50,011. The use of POCP-MTM resulted in 5.36 QALYs, at a cost of $50,270. Finally, MTM-ticagrelor resulted in 5.42 QALYs, at a cost of $53,346. MTM-ticagrelor was found to be cost-effective compared with MTM-clopidogrel or MTM-POCP, irrespective of the willingness to pay. The deterministic and probabilistic sensitivity analyses confirmed the robustness of the base-case analysis.

CONCLUSIONS

The combination of MTM-ticagrelor was cost-effective when compared with MTM-POCP or MTM-clopidogrel. The transitional probabilities, however, were mostly based on published studies. Analysis based on a prospective randomized clinical study, comparing all the treatment strategies included in this study, is warranted to confirm our findings.

DISCLOSURES

No outside funding supported this study. The authors have no conflicts of interest to declare. Study concept and design were contributed by Okere and Diaby. Ezendu took the lead in data collection, along with Okere. Data interpretation was performed by all the authors. The manuscript was written by Okere, Diaby, and Berthe and revised by Okere and Diaby.

Survival outcomes post percutaneous coronary intervention: Why the hype about stent type? Lessons from a healthcare system in India

A prospective, multicenter study was initiated by the Government of Maharashtra, India, to determine predictors of long-term outcomes of percutaneous coronary intervention (PCI) for coronary artery disease, and to compare the effectiveness of drug-eluting stents (DESs) and bare-metal stents (BMSs) in patients undergoing PCI under government-funded insurance. The present analysis included 4595 patients managed between August 2012 and November 2016 at any of 110 participating centers. Using the classical multivariable regression and propensity-matching approach, we found age to be the most important predictor of 1-year mortality and target lesion revascularization at 1 year post-PCI. However, using machine learning methods to account for unmeasured confounders and bias in this large observational study, we determined total stent length and number of stents deployed as the most important predictors of 1-year survival, followed by age and employment status. The unadjusted death rates were 5.0% and 3.8% for the BMS and DES groups, respectively (p = 0.185, log-rank test). The rate of re-hospitalization (p<0.001) and recurrence of unstable angina (p = 0.08) was significantly lower for DESs than for BMSs. Increased use of DES after 2015 (following establishment of a price cap on DESs) was associated with a sharp decrease in adjusted hazard ratios of DESs versus BMSs (from 0.94 in 2013 to 0.58 in 2016), suggesting that high price was limiting DES use in some high-risk patients. Since stented length and stent number were the most important predictors of survival outcomes, adopting an ischemia-guided revascularization strategy is expected to help improve outcomes and reduce procedural costs. In the elderly, PCI should be reserved for cases where the benefits outweigh the higher risk of the procedure. As unemployed patients had poorer long-term outcomes, we expect that implementation of a post-PCI cardiovascular rehabilitation program may improve long-term outcomes.

Clinical predictors and outcome implications of early readmission in lung transplant recipients

BACKGROUND

The purpose of this study was to identify risk factors and outcome implications for 30-day hospital readmission in lung transplant recipients.

METHODS

We conducted a retrospective cohort study of lung transplant cases from a single, high-volume lung transplant program between January 2000 and March 2012. Demographic and health data were reviewed for all patients. Risk factors for 30-day readmission (defined as readmission within 30 days of discharge from index lung transplant hospitalization) were modeled using logistic regression, with selection of parameters by backward elimination.

RESULTS

The sample comprised 795 patients after excluding scheduled readmissions and in-hospital deaths. Overall 30-day readmission rate was 45.4% (n = 361). Readmission rates were similar across different diagnosis categories and procedure types. By univariate analysis, post-operative complications that predisposed to 30-day readmission included pneumonia, any infection, and atrial fibrillation (all p < 0.05). In the final multivariate model, occurrence of any post-transplant complication was the most significant risk factor for 30-day readmission (odds ratio = 1.764; 95% confidence interval, 1.259-2.470). Even for patients with no documented perioperative complication, readmission rates were still >35%. Kaplan-Meier analysis and multi-variate regression modeling to assess readmission as a predictor of long-term outcomes showed that 30-day readmission was not a significant predictor of worse survival in lung recipients.

CONCLUSIONS

Occurrence of at least 1 post-transplant complication increases risk for 30-day readmission in lung transplant recipients. In this patient population, 30-day readmission does not predispose to adverse long-term survival. Quality indicators other than 30-day readmission may be needed to assess hospitals that perform lung transplantation.

Readmission after inpatient percutaneous coronary intervention in the Medicare population from 2000 to 2012

BACKGROUND

Since year 2000, reducing hospital readmissions has become a public health priority. In addition, there have been major changes in percutaneous coronary intervention (PCI) during this period.

METHODS

The cohort consisted of 3,250,194 patients admitted for PCI from January 2000 through November 2012.

RESULTS

Overall, 30-day readmission was 15.8%. Readmission rates declined from 16.1% in 2000 to 15.4% in 2012 (adjusted odds ratio for readmission 1.33 in 2000 compared with 2012). Of all readmissions after PCI, the majority were for cardiovascular-related conditions (>60%); however, only a small percentage (<8%) of total readmissions were for acute myocardial infarction, unstable angina, or cardiac arrest/cardiogenic shock. A much larger percentage of patients were readmitted with chest pain/angina (7.9%), chronic ischemic heart disease (26.6%), and heart failure (12%). A small proportion was due to procedural complications and gastrointestinal (GI) bleeding. The use of PCI with stenting during readmissions was variable, increasing from 14.2% in 2000 to 23.7% in 2006 and then declining to 12.1% in 2012. Hospital mortality during readmission was 2.5% overall and varied over time (2.8% in 2000, decreasing to 2.2% in 2006 and then rising again to 3.1% in 2012). Patients who were readmitted had >4× higher 30-day mortality than those who were not.

CONCLUSIONS

Among Medicare beneficiaries, readmission after PCI declined over time despite patients having more comorbidities. This translated into a 33% lower likelihood of readmission in 2012 compared with 2000. A small proportion of readmissions were for acute coronary syndromes.

Development and validation of a simple risk score to predict 30-day readmission after percutaneous coronary intervention in a cohort of medicare patients

OBJECTIVES

To develop a risk model that can be used to identify PCI patients at higher risk of readmission who may benefit from additional resources at the time of discharge.

BACKGROUND

A high proportion of patients undergoing PCI are readmitted within 30 days of discharge.

METHODS

The sample comprised patients aged ≥65 years who underwent PCI at a CathPCI Registry®-participating hospital and could be linked with 100% Medicare fee-for-service claims between 01/2007 and 12/2009. The sample (n = 388,078) was randomly divided into risk score development (n = 193,899) and validation (n = 194,179) cohorts. We did not count as readmissions those associated with staged revascularization procedures. Multivariable logistic regression models using stepwise selection models were estimated to identify variables independently associated with all-cause 30-day readmission.

RESULTS

The mean 30-day readmission rates for the development (11.36%) and validation (11.35%) cohorts were similar. In total, 19 variables were significantly associated with risk of 30-day readmission (P < 0.05), and model c-statistics were similar in the development (0.67) and validation (0.66) cohorts. The simple risk score based on 14 variables identified patients at high and low risk of readmission. Patients with a score of ≥13 (15.4% of sample) had more than an 18.5% risk of readmission, while patients with a score ≤6 (41.9% of sample) had less than an 8% risk of readmission.

CONCLUSION

Among PCI patients, risk of readmission can be estimated using clinical factors present at the time of the procedure. This risk score may guide clinical decision-making and resource allocation for PCI patients at the time of hospital discharge. © 2016 Wiley Periodicals, Inc.

Thirty-day Hospital Readmissions in Patients with Non-ST-segment Elevation Acute Myocardial Infarction

BACKGROUND

Limited data exist about relatively recent trends in the magnitude and characteristics of patients who are rehospitalized shortly after admission for a non-ST-segment elevation acute myocardial infarction (NSTEMI). This observational study describes decade-long trends (1999-2009) in the magnitude and characteristics of patients readmitted to the hospital within 30 days of hospitalization for an incident (initial) episode of NSTEMI.

METHODS

We reviewed the medical records of 2249 residents of the Worcester (Mass) metropolitan area who were hospitalized for an initial NSTEMI in 6 biennial periods between 1999 and 2009 at 3 central Massachusetts medical centers.

RESULTS

The average age of our study population was 72 years, 90% were white, and 46% were women. The proportion of patients who were readmitted to the hospital for any cause within 30 days after discharge for an NSTEMI remained unchanged between 1999 and 2009 (approximately 15%) in both crude and multivariable adjusted analyses. Slight declines were observed for cardiovascular disease-related 30-day readmissions over the 10-year study period. Women, elderly patients, those with multiple chronic comorbidities or a prolonged index hospitalization, and patients who developed heart failure during their index hospitalization were at higher risk for being readmitted within 30 days than respective comparison groups.

CONCLUSION

Thirty-day hospital readmission rates after hospital discharge for a first NSTEMI remained stable between 1999 and 2009. We identified several groups at higher risk for hospital readmission; further surveillance efforts and/or tailored educational and treatment approaches remain needed for these groups.

Is the readmission rate a valid quality indicator? A review of the evidence

INTRODUCTION

Hospital readmission rates are increasingly used for both quality improvement and cost control. However, the validity of readmission rates as a measure of quality of hospital care is not evident. We aimed to give an overview of the different methodological aspects in the definition and measurement of readmission rates that need to be considered when interpreting readmission rates as a reflection of quality of care.

METHODS

We conducted a systematic literature review, using the bibliographic databases Embase, Medline OvidSP, Web-of-Science, Cochrane central and PubMed for the period of January 2001 to May 2013.

RESULTS

The search resulted in 102 included papers. We found that definition of the context in which readmissions are used as a quality indicator is crucial. This context includes the patient group and the specific aspects of care of which the quality is aimed to be assessed. Methodological flaws like unreliable data and insufficient case-mix correction may confound the comparison of readmission rates between hospitals. Another problem occurs when the basic distinction between planned and unplanned readmissions cannot be made. Finally, the multi-faceted nature of quality of care and the correlation between readmissions and other outcomes limit the indicator's validity.

CONCLUSIONS

Although readmission rates are a promising quality indicator, several methodological concerns identified in this study need to be addressed, especially when the indicator is intended for accountability or pay for performance. We recommend investing resources in accurate data registration, improved indicator description, and bundling outcome measures to provide a more complete picture of hospital care.

A meta-analysis of complications following deceased donor liver transplant

BACKGROUND

Liver transplantation is a complex surgery associated with high rates of postoperative complications. While national outcomes data are available, national rates of most complications are unknown.

DATA SOURCES

A systematic review of the literature reporting rates of postoperative complications between 2002 and 2012 was performed. A cohort of 29,227 deceased donor liver transplant recipients from 74 studies was used to calculate pooled incidences for 17 major postoperative complications.

CONCLUSIONS

This is the first comprehensive review of postoperative complications after liver transplantation and can serve as a guide for transplant and nontransplant clinicians. Efforts to collect national data on complications, such as through the National Surgical Quality Improvement Program, would improve the ability to provide patients with informed consent, serve as a tool for individual center performance monitoring, and provide a central source against which to measure interventions aimed at improving patient care.

Causes of short-term readmission after percutaneous coronary intervention

BACKGROUND

Rehospitalization within 30 days after an admission for percutaneous coronary intervention (PCI) is common, costly, and a future target for Medicare penalties. Causes of readmission after PCI are largely unknown.

METHODS AND RESULTS

To illuminate the causes of PCI readmissions, patients with PCI readmitted within 30 days of discharge between 2007 and 2011 at 2 hospitals were identified, and their medical records were reviewed. Of 9288 PCIs, 9081 (97.8%) were alive at the end of the index hospitalization. Of these, 893 patients (9.8%) were readmitted within 30 days of discharge and included in the analysis. Among readmitted patients, 341 patients (38.1%) were readmitted for evaluation of recurrent chest pain or other symptoms concerning for angina, whereas 59 patients (6.6%) were readmitted for staged PCI without new symptoms. Complications of PCI accounted for 60 readmissions (6.7%). For cases in which chest pain or other symptoms concerning for angina prompted the readmission, 21 patients (6.2%) met criteria for myocardial infarction, and repeat PCI was performed in 54 patients (15.8%). The majority of chest pain patients (288; 84.4%) underwent ≥1 diagnostic imaging test, most commonly coronary angiography, and only 9 (2.6%) underwent target lesion revascularization.

CONCLUSIONS

After PCI, readmissions within 30 days were seldom related to PCI complications but often for recurrent chest pain. Readmissions with recurrent chest pain infrequently met criteria for myocardial infarction but were associated with high rates of diagnostic testing.

A prediction model to identify patients at high risk for 30-day readmission after percutaneous coronary intervention

BACKGROUND

The Affordable Care Act creates financial incentives for hospitals to minimize readmissions shortly after discharge for several conditions, with percutaneous coronary intervention (PCI) to be a target in 2015. We aimed to develop and validate prediction models to assist clinicians and hospitals in identifying patients at highest risk for 30-day readmission after PCI.

METHODS AND RESULTS

We identified all readmissions within 30 days of discharge after PCI in nonfederal hospitals in Massachusetts between October 1, 2005, and September 30, 2008. Within a two-thirds random sample (Developmental cohort), we developed 2 parsimonious multivariable models to predict all-cause 30-day readmission, the first incorporating only variables known before cardiac catheterization (pre-PCI model), and the second incorporating variables known at discharge (Discharge model). Models were validated within the remaining one-third sample (Validation cohort), and model discrimination and calibration were assessed. Of 36,060 PCI patients surviving to discharge, 3760 (10.4%) patients were readmitted within 30 days. Significant pre-PCI predictors of readmission included age, female sex, Medicare or State insurance, congestive heart failure, and chronic kidney disease. Post-PCI predictors of readmission included lack of β-blocker prescription at discharge, post-PCI vascular or bleeding complications, and extended length of stay. Discrimination of the pre-PCI model (C-statistic=0.68) was modestly improved by the addition of post-PCI variables in the Discharge model (C-statistic=0.69; integrated discrimination improvement, 0.009; P<0.001).

CONCLUSIONS

These prediction models can be used to identify patients at high risk for readmission after PCI and to target high-risk patients for interventions to prevent readmission.