Thirty-day rehospitalizations after acute myocardial infarction: a cohort study

Randomized Trial of Remote Assessment of Patients After an Acute Coronary Syndrome

BACKGROUND

Telemedicine programs can provide remote diagnostic information to aid clinical decisions that could optimize care and reduce unplanned readmissions post-acute coronary syndrome (ACS).

OBJECTIVES

TELE-ACS (Remote Acute Assessment of Patients With High Cardiovascular Risk Post-Acute Coronary Syndrome) is a randomized controlled trial that aims to compare a telemedicine-based approach vs standard care in patients following ACS.

METHODS

Patients were suitable for inclusion with at least 1 cardiovascular risk factor and presenting with ACS and were randomized (1:1) before discharge. The primary outcome was time to first readmission at 6 months. Secondary outcomes included emergency department (ED) visits, major adverse cardiovascular events, and patient-reported symptoms. The primary analysis was performed according to intention to treat.

RESULTS

A total of 337 patients were randomized from January 2022 to April 2023, with a 3.6% drop-out rate. The mean age was 58.1 years. There was a reduced rate of readmission over 6 months (HR: 0.24; 95% CI: 0.13-0.44; P < 0.001) and ED attendance (HR: 0.59; 95% CI: 0.40-0.89) in the telemedicine arm, and fewer unplanned coronary revascularizations (3% in telemedicine arm vs 9% in standard therapy arm). The occurrence of chest pain (9% vs 24%), breathlessness (21% vs 39%), and dizziness (6% vs 18%) at 6 months was lower in the telemedicine group.

CONCLUSIONS

The TELE-ACS study has shown that a telemedicine-based approach for the management of patients following ACS was associated with a reduction in hospital readmission, ED visits, unplanned coronary revascularization, and patient-reported symptoms. (Telemedicine in High-Risk Cardiovascular Patients Post-ACS [TELE-ACS]; NCT05015634).

β-Blocker Use and Clinical Outcomes in Patients With COPD Following Acute Myocardial Infarction

Importance

While β-blockers are associated with decreased mortality in cardiovascular disease (CVD), exacerbation-prone patients with chronic obstructive pulmonary disease (COPD) who received metoprolol in the Beta-Blockers for the Prevention of Acute Exacerbations of Chronic Obstructive Pulmonary Disease (BLOCK-COPD) trial experienced increased risk of exacerbations requiring hospitalization. However, the study excluded individuals with established indications for the drug, raising questions about the overall risk and benefit in patients with COPD following acute myocardial infarction (AMI).

Objective

To investigate whether β-blocker prescription at hospital discharge is associated with increased risk of mortality or adverse cardiopulmonary outcomes in patients with COPD and AMI.

Design, Setting, and Participants

This prospective, longitudinal cohort study with 6 months of follow-up enrolled patients aged 35 years or older with COPD who underwent cardiac catheterization for AMI at 18 BLOCK-COPD network hospitals in the US from June 2020 through May 2022.

Exposure

Prescription for any β-blocker at hospital discharge.

Main Outcomes and Measures

The primary outcome was time to the composite outcome of death or all-cause hospitalization or revascularization. Secondary outcomes included death, hospitalization, or revascularization for CVD events, death or hospitalization for COPD or respiratory events, and treatment for COPD exacerbations.

Results

Among 3531 patients who underwent cardiac catheterization for AMI, prevalence of COPD was 17.1% (95% CI, 15.8%-18.4%). Of 579 total patients with COPD and AMI, 502 (86.7%) were prescribed a β-blocker at discharge. Among the 562 patients with COPD included in the final analysis, median age was 70.0 years (range, 38.0-94.0 years) and 329 (58.5%) were male; 553 of the 579 patients (95.5%) had follow-up information. Among those discharged with β-blockers, there was no increased risk of the primary end point of all-cause mortality, revascularization, or hospitalization (hazard ratio [HR], 1.01; 95% CI, 0.66-1.54; P = .96) or of cardiovascular events (HR, 1.11; 95% CI, 0.65-1.92; P = .69), COPD-related or respiratory events (HR, 0.75; 95% CI, 0.34-1.66; P = .48), or treatment for COPD exacerbations (rate ratio, 1.01; 95% CI, 0.53-1.91; P = .98).

Conclusions and Relevance

In this cohort study, β-blocker prescription at hospital discharge was not associated with increased risk of adverse outcomes in patients with COPD and AMI. These findings support use of β-blockers in patients with COPD and recent AMI.

Enhancing Behavioural Changes: A Narrative Review on the Effectiveness of a Multifactorial APP-Based Intervention Integrating Physical Activity

The rapid evolution of technologies is a key innovation in the organisation and management of physical activities (PA) and sports. The increase in benefits and opportunities related to the adoption of technologies for both the promotion of a healthy lifestyle and the management of chronic diseases is evident. In the field of telehealth, these devices provide personalised recommendations, workout monitoring and injury prevention. The study aimed to provide an overview of the landscape of technology application to PA organised to promote active lifestyles and improve chronic disease management. This review identified specific areas of focus for the selection of articles: the utilisation of mobile APPs and technological devices for enhancing weight loss, improving cardiovascular health, managing diabetes and cancer and preventing osteoporosis and cognitive decline. A multifactorial intervention delivered via mobile APPs, which integrates PA while managing diet or promoting social interaction, is unquestionably more effective than a singular intervention. The main finding related to promoting PA and a healthy lifestyle through app usage is associated with "behaviour change techniques". Even when individuals stop using the APP, they often maintain the structured or suggested lifestyle habits initially provided by the APP. Various concerns regarding the excessive use of APPs need to be addressed.

Unplanned readmissions after Impella mechanical circulatory support

BACKGROUND

Early readmissions significantly impact on patient-wellbeing, burden the health-care system, and are important quality metrics. Data on 30-day readmission following Impella mechanical circulatory support (MCS) are unknown. We aimed to assess the rates, causes and clinical outcomes associated with 30-day unplanned readmissions after Impella mechanical circulatory support (MCS).

METHODS

Discharged patients who underwent Impella MCS between 2016 and 2019 in the U.S. Nationwide Readmission Database were analyzed. Incidence, causes, and outcomes associated with 30-day unplanned readmissions were assessed.

RESULTS

Of 22,055 patients who received Impella MCS, 2685 (12.2%) experienced 30-day readmissions. Cardiac readmissions accounted for 51.7% compared to 48.3% of non-cardiac readmissions, and most (70%) patients were readmitted back to the index hospital. Heart failure was the leading cause of cardiac readmissions accounting for 25% of them, whereas infections were the most common cause among non-cardiac readmissions. Patients who were readmitted were significantly older (median age 71 versus 68 years), more likely to be female (31% versus 26%) and had a shorter length-of-stay (index hospitalization, median 8 versus 9 days) compared to those who were not readmitted. Factors independently associated with 30-day readmissions were chronic renal (aOR: 1.46, 95% CI: 1.35-1.57), pulmonary (aOR: 1.23, 95% CI: 1.15-1.33), and liver disease (aOR: 1.38, 95% CI: 1.17-1.63), anemia (aOR: 1.35, 95% CI: 1.26-1.46), female sex (aOR: 1.21, 95% CI: 1.12-1.30), index admission on weekends (aOR: 1.23, 95% CI: 1.13-1.34), STEMI diagnosis (aOR: 1.16, 95% CI: 1.02-1.31), major adverse event during index hospitalization (aOR: 1.11, 95% CI: 1.00-1.24), prolonged length-of-stay (median 9 vs. 8 days, P < 0.001), and discharge against medical advice (aOR: 2.06, 95% CI: 1.37-3.09). Significantly higher mortality rates were overserved during readmissions to a hospital different than the MCS implanting hospital (12% versus 5.9%, P < 0.001).

CONCLUSION

Thirty-day readmissions after Impella MCS are relatively common and relate to sex, baseline comorbidities, presentation, expected primary payer, discharge destination and initial length of hospital stay. Heart failure was the leading cause of cardiac readmissions, whereas infections were the most common cause among non-cardiac readmissions. Most patients were readmitted to the same hospital as their index admission for MCS. Higher mortality rates were observed when patients were readmitted to a different hospital.

Common procedures and conditions leading to inpatient hospital admissions in adults with and without diabetes from 2015 to 2019 in Germany : A comparison of frequency, length of hospital stay and complications

OBJECTIVE

To evaluate common surgical procedures and admission causes in inpatient cases with diabetes in Germany between 2015 and 2019 and compare them to inpatient cases without diabetes.

METHODS

Based on the German diagnosis-related groups (G-DRG) statistics, regression models stratified by age groups and gender were used to calculate hospital admissions/100,000 individuals, hospital days as well as the proportion of complications and mortality in inpatient cases ≥ 40 years with or without a documented diagnosis of diabetes (type 1 or type 2).

RESULTS

A total of 14,222,326 (21%) of all inpatient cases aged ≥ 40 years had a diagnosis of diabetes. More middle-aged females with vs. without diabetes/100,000 individuals [95% CI] were observed, most pronounced in cases aged 40-< 50 years with myocardial infarction (305 [293-319] vs. 36 [36-37], p < 0.001). Higher proportions of complications and longer hospital stays were found for all procedures and morbidities in cases with diabetes.

CONCLUSION

Earlier hospitalizations, longer hospital stays and more complications in inpatient cases with diabetes together with the predicted future increase in diabetes prevalence depict huge challenges for the German healthcare system. There is an urgent need for developing strategies to adequately care for patients with diabetes in hospital.

Long-Term Predictors of Hospitalized Reinfarction after an Incident Acute Myocardial Infarction

The aim of this study was to compare characteristics of incident acute myocardial infarction (AMI) and first and second time reinfarctions in terms of sociodemographic characteristics, comorbidities, symptoms, treatment, clinical characteristics, medication and outcome. A further aim was to identify predictors for an increased risk of hospitalized reinfarction. Between 2000 and 2017, a total of 13,276 AMI cases were recorded by a population-based registry in the area of Augsburg, Germany, and were included in this study (11,871 incident events, 1217 cases of first-time reinfarction and 202 cases of second-time reinfarction). Median follow-up time was 5.3 years. For differences in baseline characteristics, Chi-square tests and analysis of variance (ANOVA) were calculated. To determine factors that are associated with an increased risk of hospitalized reinfarction COX regression models were fitted. Myocardial reinfarctions differ from incident events in some major characteristics such as the frequency of comorbidities, laboratory values, ECG presentation and therapy, but not regarding 28-day mortality. Moreover, typical comorbidities and risk factors (diabetes, hypertension, hyperlipidemia, smoking, impaired renal function) are associated with an increased risk of hospitalized reinfarction. Conversely, STEMI ECG, being married, German nationality and bypass surgery are predictors for a lower risk of hospitalized reinfarction. Incident AMI and reinfarction are distinctly different in many characteristics, which physicians should have in mind when treating patients with prior AMI. Typical comorbidities are risk factors for hospitalized reinfarction. This underlines the importance of comprehensive treatment of these comorbidities including education of patients and encouragement towards lifestyle adjustments.

Readmission After ACS: Burden, Epidemiology, and Mitigation

PURPOSE OF REVIEW

The past decade has brought increased efforts to better understand causes for ACS readmissions and strategies to minimize them. This review seeks to provide a critical appraisal of this rapidly growing body of literature.

RECENT FINDINGS

Prior to 2010, readmission rates for patients suffering from ACS remained relatively constant. More recently, several strategies have been implemented to mitigate this including improved risk assessment models, transition care bundles, and development of targeted programs by federal organizations and professional societies. These strategies have been associated with a significant reduction in ACS readmission rates in more recent years. With this, improvements in 30-day post-discharge mortality rates are also being appreciated. As we continue to expand our knowledge on independent risk factors for ACS readmissions, further strategies targeting at-risk populations may further decrease the rate of readmissions. Efforts to understand and reduce 30-day ACS readmission rates have resulted in overall improved quality of care for patients.

Treatment gaps, 1-year readmission and mortality following myocardial infarction by diabetes status, sex and socioeconomic disadvantage

AIMS

We evaluated variation in treatment for, and outcomes following, myocardial infarction (MI) by diabetes status, sex and socioeconomic disadvantage.

METHODS

We included all people aged ≥30 years who were discharged alive from hospital following MI between 1 July 2012 and 30 June 2017 in Victoria, Australia (n=43 272). We assessed receipt of inpatient procedures and discharge dispensing of cardioprotective medications for each admission, as well as 1-year all-cause, cardiovascular, and MI readmission rates and 1-year all-cause mortality.

RESULTS

Risk of all-cause (HR: 1.22 (1.19-1.26)), cardiovascular (1.29 (1.25-1.34)), MI (1.52 (1.43-1.62)) and heart failure readmission (1.62 (1.50-1.75)) and mortality (1.18 (1.11-1.26)) were higher in people with diabetes. Males and people in more disadvantaged areas were at increased risk of readmission and mortality following MI. People with diabetes (vs without) were more likely to receive coronary artery bypass grafting (CABG) but less likely to receive percutaneous coronary intervention (PCI) during, or within 30 days of, their index admission. Females were less likely to receive either (eg, 87% of males with a STEMI received PCI or CABG vs 70% of females), and people in more disadvantaged areas were less likely to receive PCI. People with diabetes, males and people in more disadvantaged areas were more likely to be dispensed cardioprotective medications at or within 90 days of discharge.

CONCLUSIONS

Following an MI, people with diabetes and males had poorer outcomes but received more intensive cardiovascular treatments. However, socioeconomic disadvantage was associated with both less intensive inpatient treatment and poorer outcomes.

Risk factors for major adverse cardiovascular events after the first acute coronary syndrome

AIMS

To evaluate risk factors for major adverse cardiac event (MACE) after the first acute coronary syndrome (ACS) and to examine the prevalence of risk factors in post-ACS patients.

METHODS

We used Finnish population-based myocardial infarction register, FINAMI, data from years 1993-2011 to identify survivors of first ACS (n = 12686), who were then followed up for recurrent events and all-cause mortality for three years. Finnish FINRISK risk factor surveys were used to determine the prevalence of risk factors (smoking, hyperlipidaemia, diabetes and blood pressure) in post-ACS patients (n = 199).

RESULTS

Of the first ACS survivors, 48.4% had MACE within three years of their primary event, 17.0% were fatal. Diabetes (p = 4.4 × 10-7), heart failure (HF) during the first ACS attack hospitalization (p = 6.8 × 10-15), higher Charlson index (p = 1.56 × 10-19) and older age (p = .026) were associated with elevated risk for MACE in the three-year follow-up, and revascularization (p = .0036) was associated with reduced risk. Risk factor analyses showed that 23% of ACS survivors continued smoking and cholesterol levels were still high (>5mmol/l) in 24% although 86% of the patients were taking lipid lowering medication.

CONCLUSION

Diabetes, higher Charlson index and HF are the most important risk factors of MACE after the first ACS. Cardiovascular risk factor levels were still high among survivors of first ACS.

Factors affecting hospital readmission rates following an acute coronary syndrome: A systematic review

Aim

To synthesise quantitative evidence on factors that impact hospital readmission rates following ACS with comorbidities.

Design

Systematic review and narrative synthesis.

Data sources

A search of eight electronic databases, including Embase, Medline, PsycINFO, Web of Science, CINAHL, Cochrane Library, Scopus and the Joanna Briggs Institute (JBI).

Review methods

The search strategy included keywords and MeSH terms to identify English language studies published between 2001 and 2020. The quality of included studies was assessed by two independent reviewers, using Joanna Briggs Institute (JBI) critical appraisal tools.

Results

Twenty‐four articles were included in the review. All cause 30‐day readmission rate was most frequently reported and ranged from 4.2% to 81%. Reported factors that were associated with readmission varied across studies from socio‐demographic, behavioural factors, comorbidity factors and cardiac factors. Findings from some of the studies were limited by data source, study designs and small sample size.

Conclusion

Strategies that integrate comprehensive discharge planning and individualised care planning to enhance behavioural support are related to a reduction in readmission rates. It is recommended that nurses are supported to influence discharge planning and lead the development of nurse‐led interventions to ensure discharge planning is both coordinated and person‐centred.

Temporal Trends and Patient Characteristics Associated with 30-Day Hospital Readmission Rates after a First Acute Myocardial Infarction

BACKGROUND

Limited data exist about relatively recent trends in the magnitude and characteristics of patients who are re-hospitalized after hospital admission for an acute myocardial infarction. This study examined trends in the frequency and sociodemographic and clinical characteristics of patients readmitted to the hospital within 30 days after an initial acute myocardial infarction.

METHODS

We reviewed the medical records of 3116 individuals who were hospitalized for a validated first acute myocardial infarction in 6 study periods between 2003 and 2015 at the 3 major medical centers in central Massachusetts.

RESULTS

The median age of our population was 67 years, and 42% were women. The risk of being readmitted to the hospital within 30 days after an initial acute myocardial infarction increased slightly during the most recent study years after controlling for potentially confounding factors. Overall, older adults and patients with previously diagnosed atrial fibrillation, heart failure, diabetes, chronic kidney disease, stroke, and peripheral vascular disease were at higher risk for being readmitted to the hospital than respective comparison groups. For those hospitalized in the most recent study years of 2011/2015, a higher risk of rehospitalization was associated with a previous diagnosis of chronic kidney disease, peripheral vascular disease, the presence of 3 or more chronic conditions, and having developed atrial fibrillation or heart failure during the patient's hospitalization for a first acute myocardial infarction.

CONCLUSIONS

We identified several groups at higher risk for hospital readmission in whom enhanced surveillance efforts as well as tailored educational and treatment approaches remain needed.

Characteristics and Outcomes of Early Recurrent Myocardial Infarction After Acute Myocardial Infarction

Background We aimed to understand the characteristics and outcomes of patients readmitted with a recurrent myocardial infarction (RMI) within 90 days of discharge after an acute myocardial infarction (early RMI). Methods and Results We analyzed the timing of reinfarction, etiology, and outcome for all patients admitted with an early RMI within 90 days of discharge after an acute myocardial infarction between January 1, 2010 and January 1, 2017. We identified 6626 admissions for acute myocardial infarction (index myocardial infarction) which led to 168 cases of RMI within 90 days of discharge. The mean patient age was 65.1±13.1 years, and 37% were women. The 90-day probability of readmission with an early RMI was 2.5%. Black race, medical management, higher troponin T, and shorter length of stay were independent predictors of early RMI. Medically managed group had a higher risk for early RMI compared with percutaneous coronary intervention (P=0.04) or coronary artery bypass grafting (P=0.2). Predominant mechanisms for reinfarction were stent thrombosis (17%), disease progression (12%), and unchanged coronary artery disease (11%). At 5 years, the all-cause mortality rate for patients with an early RMI was 49% (95% CI, 40%-57%) compared with 22% (95% CI, 21%-23%) for patients without an early RMI (P<0.0001). Conclusions Early RMI is a life-threatening condition with nearly 50% mortality within 5 years. Stent-related events and progression in coronary artery disease account for most early RMI. Medication compliance, aggressive risk factor management, and care transitions should be the cornerstone in preventing early RMI.

Time-trends and predictors of interhospital transfers and 30-day rehospitalizations after acute coronary syndrome from 2000-2015

Aims

Assess trends and factors associated with interhospital transfers (IHT) and 30-day acute coronary syndrome (ACS) rehospitalizations in a national administrative database of patients admitted with an ACS between 2000–2015.

Methods and results

Cohort study of patients hospitalized with ACS from 2000 to 2015, using a validated linkage algorithm to identify and link patient-level sequential hospitalizations occurring within 30 days from first admission (considering all hospitalizations within the 30-day timeframe as belonging to the same ACS episode of care-ACS-EC). From 212,481 ACS-EC, 42,670 (20.1%) had more than one hospitalization. ACS-EC hospitalization rates decreased throughout the study period (2000: 207.7/100.000 person-years to 2015: 185,8/100,000 person-years, p for trend <0.05). Proportion of IHT increased from 10.5% in 2000 to 20.1% in 2015 compared to a reduction in both planned and unplanned 30-day ACS rehospitalization from 9.0% in 2000 to 2.7% in 2015. After adjusting for patient and first admission hospital’s characteristics, compared to 2000–2003, in 2012–2015 the odds of IHT increased by 3.81 (95%CI: 3.65–3.98); the odds of unplanned and planned 30-day ACS rehospitalization decreased by 0.36 (95%CI: 0.33; 0.39) and 0.47 (95%CI: 0.43; 0.53), respectively. Female sex, older age and the presence and severity of comorbidities were associated with lower likelihood of being transferred or having a planned 30-day ACS rehospitalization. Unplanned 30-day ACS rehospitalization was more likely in patients with higher comorbidity burden.

Conclusion

IHT and 30-day ACS rehospitalization reflect coronary referral network efficiency and access to specialized treatment. Identifying factors associated with higher likelihood of IHT and 30-day ACS rehospitalization may allow heightened surveillance and interventions to reduce rehospitalizations and inequities in access to specialized treatment.

Predictive Model Based on Health Data Analysis for Risk of Readmission in Disease-Specific Cohorts

BACKGROUND

Intervention planning to reduce 30-day readmission post-acute myocardial infarction (AMI) in an environment of resource scarcity can be improved by readmission prediction score. The aim of study is to derive and validate a prediction model based on routinely collected hospital data for identification of risk factors for all-cause readmission within zero to 30 days post discharge from AMI.

METHODS

Our study includes 2,849 AMI patient records (January 2005 to December 2014) from a tertiary care facility in India. EMR with ICD-10 diagnosis, admission, pathological, procedural and medication data is used for model building. Model performance is analyzed for different combination of feature groups and diabetes sub-cohort. The derived models are evaluated to identify risk factors for readmissions.

RESULTS

The derived model using all features has the highest discrimination in predicting readmission, with AUC as 0.62; (95 percent confidence interval) in internal validation with 70/30 split for derivation and validation. For the sub-cohort of diabetes patients (1359) the discrimination is slightly better with AUC 0.66; (95 percent CI;). Some of the positively associated predictive variables, include age group 80-90, medicine class administered during index admission (Anti-ischemic drugs, Alpha 1 blocker, Xanthine oxidase inhibitors), additional procedure in index admission (Dialysis). While some of the negatively associated predictive variables, include patient demography (Male gender), medicine class administered during index admission (Betablocker, Anticoagulant, Platelet inhibitors, Anti-arrhythmic).

CONCLUSIONS

Routinely collected data in the hospital's clinical and administrative data repository can identify patients at high risk of readmission following AMI, potentially improving AMI readmission rate.

Factors influencing readmission among Thais with myocardial infarction

Background

Readmission among patients with myocardial infarction is costly, and it has become a marker of quality of care. Therefore, factors related to readmission warrant examination.

Objective

This study aimed at examining factors influencing readmission in Thai with myocardial infarction.

Methods

This was a cross-sectional study with 200 participants randomly selected from five regional hospitals in Thailand. All research tools used indicated acceptable validity and reliability. Linear Structural Relationship version 8.72 was used for the data analysis.

Results

The findings showed that the hypothesized model with social support, depression, symptom severity, comorbidity, and quality of life could explain 4% (R² = 0.04) of the variance in readmission (χ² = 1.39, df = 2, p < 0.50, χ²/df = 0.69, GIF = 1.00, RMSEA = 0.00, SRMR = 0.01, and AGFI = 0.98). Symptom severity was the most influential factor that had a positive and direct effect on the readmission rate (0.06, p < 0.05).

Conclusion

These findings serve as an input to decrease readmission in patients with myocardial infarction by reducing the symptom severity and comorbidity and promoting a better quality of life.

Assessing whether ad hoc clinician-generated patient questionnaires provide psychometrically valid information

Background

The provision of psychometrically valid patient reported outcomes (PROs) improves patient outcomes and reflects their quality of life. Consequently, ad hoc clinician-generated questionnaires of the past are being replaced by more rigorous instruments. This change, while beneficial, risks the loss/orphaning of decades-long information on difficult to capture/chronically ill populations. The goal of this study was to assess to the quality of data retrieved from these legacy questionnaires.

Methods

Participants included 8563 patients who generated a total of 12,626 hospital admissions over the 2004–2014 study period. Items used to screen for issues related to function, mood, symptoms, and social support among patients with chronic disease were identified in our medical center’s patient information questionnaire. Cluster and exploratory factor analyses (EFA) followed by multidimensional item response theory (MIRT) analyses were used to select items that defined factors. Scores were derived with summation and MIRT approaches; inter-factor relationships and relationships of factor scores to assigned diagnostic codes were assessed. Rasch analyses assessed the constructs’ measurement properties.

Results

Literature review and clinician interviews yielded four hypothesized constructs: psychological distress/wellbeing, symptom burden, social support, and physical function. Rasch analyses showed that, while all had good measurement properties, only one, function, separated individuals well. In exploratory factor analyses (EFA), 11 factors representing depression, respiratory symptoms, musculoskeletal pain, family support, mobility, activities of daily living, alcohol consumption, weight loss, fatigue, neurological disorders, and fear at home were identified. Based on the agreement between EFA and cluster analyses as well as Cronbach’s alpha, six domains were retained for analyses. Correlations were strong between activities of daily living and mobility (.84), and moderate between pain and mobility (.37) and psychological distress (.59) Known-group validity was supported from the relationships between factor scores and the relevant diagnostic code assignments (.12 to .20).

Conclusions and discussion

Items from ad hoc clinician-generated patient information questionnaires can be aggregated into valid factors that assess supportive care domains among chronically ill patients. However, the binary response options offered by many screening items limit their information content and consequently, as highlighted by Rasch analyses, their ability to meaningfully discriminate trait levels in these populations.

Autologous CXCR4+ Hematopoietic Stem Cells Injected into the Scar Tissue of Chronic Myocardial Infarction Patients Normalizes Tissue Contractility and Perfusion

BACKGROUND

Chronic myocardial infarction (CMI), represents a public health and a financial burden. Since stem cell transplant is used to regenerate cardiac tissue after acute myocardial infarction.

AIM OF THE STUDY

To determine if autologous CXCR4 stem cells could restore damaged myocardial tissue in patients with CMI lesions.

METHODS

20 NYHA grade III male patients with CMI defined by clinical, biochemical, ECG and echocardiographic parameters were included. Patients were treated with G-CSF for 6 d before isolating their autologous stem cells from PBMCs. Cell phenotyping was done by cytofluorometry using monoclonal antibodies (anti-CXCR4, -CD34, -48, -117, -133, -Ki67, -SDF1 and CXCR4); CXCR4 cell subpopulations isolated by sorting were adjusted to 1 × 10⁸ cells by subpopulation and injected in a circular pattern into the cicatrix previously defined by echocardiography.

RESULTS

Patients were followed for 6 and 12 months. Six months after cell implant improvements in left ventricle ejection fraction (from 33-50%), stress rate values (from -3/-9% to -18/-22%), stress tests (from 4-12 METS), and the quantity of left ventricle affected segments (3-9) disappeared according to the G-SPECT images. 12 months evaluations did not show significant differences. Interestingly, 3 months after cell implant the ECG showed normal electrical activity in 9 patients whereas after 6 months it was normal in all the patients.

CONCLUSIONS

These results ratify that locally injected autologous CXCR4+ bone marrow-derived stem cells have a physiological and a clinical impact in patients with CMI.

Temporal trends in healthcare resource utilization and costs following acute myocardial infarction

BACKGROUND

Acute myocardial infarction (AMI) is associated with greater utilization of healthcare resources and financial expenditure.

OBJECTIVES

To evaluate temporal trends in healthcare resource utilization and costs following AMI throughout 2003-2015.

METHODS

AMI patients who survived the first year following hospitalization in a tertiary medical center (Soroka University Medical Center) throughout 2002-2012 were included and followed until 2015. Length of the in-hospital stay (LOS), emergency department (ED), primary care, outpatient consulting clinic visits and other ambulatory services, and their costs, were evaluated and compared annually over time.

RESULTS

Overall 8047 patients qualified for the current study; mean age 65.0 (SD = 13.6) years, 30.3% women. During follow-up, LOS and the number of primary care visits has decreased significantly. However, ED and consultant visits as well as ambulatory-services utilization has increased. Total costs have decreased throughout this period. Multivariate analysis, adjusted for potential confounders, showed as significant trend of decrease in LOS and ambulatory-services utilization, yet an increase in ED visits with no change in total costs.

CONCLUSIONS

Despite a decline in utilization of most healthcare services throughout the investigated decade, healthcare expenditure has not changed. Further evaluation of the cost-effectiveness of long-term resource allocation following AMI is warranted. Nevertheless, we believe more intense ambulatory follow-up focusing on secondary prevention and early detection, as well as high-quality outpatient chest pain unit are warranted.

Effects of the patient education strategy 'Learning and Coping' in cardiac rehabilitation on readmissions and mortality: a randomized controlled trial (LC-REHAB)

We assessed the effects of the patient education strategy 'Learning and Coping' (LC) in cardiac rehabilitation (CR) on mortality and readmissions by exploring results from the LC-REHAB trial. In all, 825 patients with ischaemic heart disease or heart failure were randomized to the intervention arm (LC-CR) or the control arm (standard CR) at three hospitals in Denmark. LC-CR was situational and inductive, with experienced patients as co-educators supplemented with two individual interviews. Group-based training and education hours were the same in both arms. Outcomes were time to death or readmission, length of stay and absolute number of deaths or readmissions. No between-arm differences were found in time to death, first readmission, or length of stay. Within 30 days after completion of CR, the absolute number of all-cause readmissions was 117 in the LC arm and 146 in the control arm, adjusted odds ratio 78 (95% CI: 0.61-1.01), P = 0.06. This trend diminished over time. Adding LC strategies to standard CR showed a short term but no significant long-term effect on mortality or readmissions. However, the study was not powered to detect differences in mortality and morbidity. Thus, a risk of overseeing a true effect was present.

Sociodemographic, labour market marginalisation and medical characteristics as risk factors for reinfarction and mortality within 1 year after a first acute myocardial infarction: a register-based cohort study of a working age population in Sweden

OBJECTIVES

Research covering a wide range of risk factors related to the prognosis during the first year after an acute myocardial infarction (AMI) is insufficient. This study aimed to investigate whether sociodemographic, labour market marginalisation and medical characteristics before/at AMI were associated with subsequent reinfarction and all-cause mortality.

DESIGN

Population-based cohort study.

PARTICIPANTS

The cohort included 15 069 individuals aged 25-64 years who had a first AMI during 2008-2010.

PRIMARY AND SECONDARY OUTCOME MEASURES

The outcome measures consisted of reinfarction and all-cause mortality within 1 year following an AMI, which were estimated by univariate and multivariable HRs and 95% CIs by Cox regression.

RESULTS

Sociodemographic characteristics such as lower education showed a 1.1-fold and 1.3-fold higher risk for reinfarction and mortality, respectively. Older age was associated with a higher risk of mortality while being born in non-European countries showed a lower risk of mortality. Labour market marginalisation such as previous long-term work disability was associated with a twofold higher risk of mortality. Regarding medical characteristics, ST-elevation myocardial infarction was predictive for reinfarction (HR: 1.14, 95% CI: 1.07 to 1.21) and all-cause mortality (HR: 3.80, 95% CI: 3.08 to 4.68). Moreover, diabetes mellitus, renal insufficiency, stroke, cancer and mental disorders were associated with a higher risk of mortality (range of HRs: 1.24-2.59).

CONCLUSIONS

Sociodemographic and medical risk factors were identified as risk factors for mortality and reinfarction after AMI, including older age, immigration status, somatic and mental comorbidities. Previous long-term work disability and infarction type provide useful information for predicting adverse outcomes after AMI during the first year, particularly for mortality.

Long-Term Time-Varying Risk of Readmission After Acute Myocardial Infarction

Background

Readmission after myocardial infarction (MI) is a publicly reported quality metric with hospital reimbursement linked to readmission rates. We describe the timing and pattern of readmission by cause within the first year after MI in consecutive patients, regardless of revascularization strategy, payer status, or age.

Methods and Results

We identified patients discharged after an MI from April 2008 to June 2012. Readmission within 12 months was the primary end point. Readmissions were classified into 4 groups: MI related, other cardiovascular, noncardiovascular, and planned. A total of 3069 patients were discharged after an MI (average age, 65±13 years; and 1941 [63%] men). A total of 655 patients (21.3%) were readmitted at least once (897 total readmissions). A total of 147 patients (4.8%) were readmitted ≥2 times, accounting for 389 readmissions (43%). The instantaneous risk of all‐cause readmission was highest (15 readmissions/100 patients per month; 95% confidence interval, 12–19 readmissions/100 patients per month) immediately after discharge, decreased by almost half (8.1 readmissions/100 patients per month; 95% confidence interval, 7.2–9.0 readmissions/100 patients per month) within 15 days, and was substantially lower and relatively constant (1.4 readmissions/100 patients per month; 95% confidence interval, 1.2–1.6 readmissions/100 patients per month) out to 1 year. Cardiovascular causes of readmission were more common early after discharge.

Conclusions

Most patients with MI are never readmitted, whereas a small minority (≈5%) account for nearly half of 1‐year readmissions. The readmission pattern after MI is characterized by an early peak (first 15 days) of cardiovascular readmissions, followed by a middle period (months 1–4) of noncardiovascular readmissions, and ending with a low‐risk period (>4 months) during which the risk appears independent of cause.

See Editorial by Levy and Allen

Thirty-day readmission, length of stay and self-management behaviour among patients with acute coronary syndrome and type 2 diabetes mellitus: A scoping review

AIMS AND OBJECTIVES

To summarise the current evidence on comorbid type 2 diabetes mellitus (T2DM) related to 30-day readmission and hospital length of stay (LOS) among patients with acute coronary syndrome (ACS) and evidence on the effectiveness of self-management programmes for patients with both conditions.

BACKGROUND

Acute coronary syndrome and T2DM remain two major diseases leading to serious consequences. Thirty-day readmission and LOS were considered indicators of the quality of care, with the understanding that the potential significant effects of these outcomes could be varied.

DESIGN

This scoping review followed the methodology described by Arksey and O'Malley.

METHODS

Five databases including PubMed, Embase, Cochrane Library, Web of Science and CINAHL were searched, and a total of 20 articles involving 913,807 patients were included. Results were reported in accordance with PRISMA-ScR guidelines.

RESULTS

The results indicated that patients with both ACS and T2DM have prolonged LOS and increased 30-day readmission rates. The findings supported that improvements in patient self-management behaviour for optimal health outcomes were partially successful by effective self-management programmes; however, few articles on intervention programmes specifically designed for patients with two conditions were found.

CONCLUSION

Prolonged LOS and increased 30-day readmission rates are found among patients with ACS and T2DM. Based on few pilot studies building on each other, the effectiveness of self-management programmes in promoting self-care behaviour, self-efficacy and knowledge for patients with ACS and T2DM cannot be concluded.

RELEVANCE TO CLINICAL PRACTICE

Findings from this review provide valuable information on and a better understanding of readmissions and LOS among patients with ACS and T2DM for healthcare providers. Future developments and implementations of effective self-management programmes should target patients with dual diagnoses to improve health behaviour and reduce readmission and LOS.

Understanding Readmissions in Medicare Beneficiaries During the 90-Day Follow-Up Period of an Acute Myocardial Infarction Admission

Background

Medicare has a voluntary episodic payment model for Medicare beneficiaries that bundles payment for the index acute myocardial infarction (AMI) hospitalization and all post‐discharge services for a 90‐day follow‐up period. The purpose of this study is to report on the types and frequency of readmissions and identify demographic and clinical factors associated with readmission of Medicare beneficiaries that survived their AMI hospitalization.

Methods and Results

This retrospective study used the Inpatient Standard Analytical File for 2014. There were 143 286 Medicare beneficiaries with AMI who were discharged alive from 3619 hospitals. All readmissions occurring in any hospital within 90 days of the index AMI discharge date were identified. Of 143 286 Medicare beneficiaries discharged alive from their index AMI hospitalization, 28% (40 145) experienced at least 1 readmission within 90 days and 8% (11 477) had >1 readmission. Readmission rates were higher among Medicare beneficiaries who did not undergo a percutaneous coronary intervention in their index AMI admission (34%) compared with those that underwent a percutaneous coronary intervention (20.2%). Using all Medicare beneficiary's index AMI, 27 comorbid conditions were significantly associated with the likelihood of a Medicare beneficiary having a readmission during the follow‐up period. The strongest clinical characteristics associated with readmissions were dialysis dependence, type 1 diabetes mellitus, and heart failure.

Conclusions

This study provides benchmark information on the types of hospital readmissions Medicare beneficiaries experience during a 90‐day AMI bundle. This paper also suggests that interventions are needed to alleviate the need for readmissions in high‐risk populations, such as, those managed medically and those at risk of heart failure.

Characteristics, Management, and Short-Term Outcomes of Adults ≥65 Years Hospitalized With Acute Myocardial Infarction With Prior Anemia and Heart Failure

Our study objectives were to examine the impact of anemia and heart failure (HF) on in-hospital complications, and postdischarge outcomes (7 and 30-day rehospitalizations and mortality) in adults ≥65 years hospitalized with acute myocardial infarction (AMI). We used multivariable-adjusted logistic regression models to examine the association between the presence of anemia and/or HF, and the examined outcomes. The study population consisted of 3,863 patients ≥65 years hospitalized with AMI at the 3 major medical centers in Worcester, MA, during 6 annual periods between 2001 and 2011. Individuals were categorized into 4 groups based on the presence of previously diagnosed anemia (hemoglobin ≤10 mg/dl) and/or HF: Those without these conditions (n = 2,300), those with anemia only (n = 382), those with HF only (n = 837), and those with both conditions (n = 344). The median age of the study population was 79 years and 49% were men. Individuals who had been previously diagnosed with anemia and HF had the highest proportion of older adults (≥85 years) and the lowest proportion of those who had received any cardiac interventional procedure during hospitalization. After multivariable adjustment, individuals who presented with both previously diagnosed conditions were at the greatest risk for experiencing adverse events. Patients who presented with HF only were at higher risk for developing several clinical complications during hospitalization, whereas those with anemia only were at slightly higher risk of being rehospitalized within 7-days of their index hospitalization. In conclusion, anemia and HF are prevalent chronic conditions that increased the risk of adverse events in older adults hospitalized with AMI.

Racial and Ethnic Differences in 30-Day Hospital Readmissions Among US Adults With Diabetes

IMPORTANCE

Differences in readmission rates among racial and ethnic minorities have been reported, but data among people with diabetes are lacking despite the high burden of diabetes and its complications in these populations.

OBJECTIVES

To examine racial/ethnic differences in all-cause readmission among US adults with diabetes and categorize patient- and system-level factors associated with these differences.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study includes 272 758 adult patients with diabetes, discharged alive from the hospital between January 1, 2009, and December 31, 2014, and stratified by race/ethnicity. An administrative claims data set of commercially insured and Medicare Advantage beneficiaries across the United States was used. Data analysis took place between October 2016 and February 2019.

MAIN OUTCOMES AND MEASURES

Unplanned all-cause readmission within 30 days of discharge and individual-, clinical-, economic-, index hospitalization-, and hospital-level risk factors for readmission.

RESULTS

A total of 467 324 index hospitalizations among 272 758 adults with diabetes (mean [SD] age, 67.7 [12.7]; 143 498 [52.6%] women) were examined. The rates of 30-day all-cause readmission were 10.2% (33 683 of 329 264) among white individuals, 12.2% (11 014 of 89 989) among black individuals, 10.9% (4151 of 38 137) among Hispanic individuals, and 9.9% (980 of 9934) among Asian individuals (P < .001). After adjustment for all factors, only black patients had a higher risk of readmission compared with white patients (odds ratio, 1.05; 95% CI, 1.02-1.08). This increased readmission risk among black patients was sequentially attenuated, but not entirely explained, by other demographic factors, comorbidities, income, reason for index hospitalization, or place of hospitalization. Compared with white patients, both black and Hispanic patients had the highest observed-to-expected (OE) readmission rate ratio when their income was low (annual household income <$40 000 among black patients: OE ratio, 1.11; 95% CI, 1.09-1.14; among Hispanic patients: OE ratio, 1.11; 95% CI, 1.07-1.16) and when they were hospitalized in nonprofit hospitals (black patients: OE ratio, 1.10; 95% CI, 1.08-1.12; among Hispanic patients: OE ratio, 1.08; 95% CI, 1.05-1.12), academic hospitals (black patients: OE ratio, 1.16; 95% CI, 1.13-1.20; Hispanic patients: OE ratio, 1.12; 95% CI, 1.06-1.19), or large hospitals (ie, with ≥400 beds; black patients: OE ratio, 1.11; 95% CI, 1.09-1.14; Hispanic patients: OE ratio, 1.09; 95% CI, 1.04-1.14).

CONCLUSIONS AND RELEVANCE

In this study, black patients with diabetes had a significantly higher risk of readmission than members of other racial/ethnic groups. This increased risk was most pronounced among lower-income patients hospitalized in nonprofit, academic, or large hospitals. These findings reinforce the importance of identifying and addressing the many reasons for persistent racial/ethnic differences in health care quality and outcomes.

Readmissions After Acute Myocardial Infarction: How Often Do Patients Return to the Discharging Hospital?

Background

When patients require readmission after a recent myocardial infarction (MI), returning to the discharging (index) hospital may be associated with better outcomes as a result of greater continuity in care. However, little evidence exists to answer this frequent patient question.

Methods and Results

Among Medicare patients aged ≥65 years discharged home alive post‐MI from 491 US hospitals in the ACTION (Acute Coronary Treatment Intervention Outcomes Network) Registry, we compared reason for readmission, duration of rehospitalization, and 30‐day mortality between patients readmitted to the index versus nonindex hospital within 30 days of index MI discharge. Among 53 471 MI patients, 7715 (14%) were readmitted within 30 days, and most readmitted patients (73%) returned to the discharging hospital. Reason for readmission was not significantly associated with location of readmission. In multivariable modeling, the strongest factors associated with readmission to a nonindex hospital were distance from the discharging hospital, transfer‐in during the index MI hospitalization, and frequency of nonindex hospital admissions in the year preceding to the index MI. Duration of rehospitalization did not differ significantly between patients readmitted to the index versus nonindex hospital (median, 4 versus 3 days; P=0.17). Mortality risk was also not significantly different between patients readmitted to the index versus nonindex hospital overall (7.4 versus 7.7%; adjusted odds ratio, 0.89; 95% CI, 0.73–1.10) and when stratified by reason for readmission (P for interaction=0.61).

Conclusions

Post‐MI readmissions did not differ in reason for readmission, duration of rehospitalization, or associated mortality when compared between patients who returned to the discharging hospital and those who sought care elsewhere.

Left ventricular ejection fraction and adjudicated, cause-specific hospitalizations after myocardial infarction complicated by heart failure or left ventricular dysfunction

BACKGROUND

Reduced left ventricular ejection fraction (LVEF) after acute myocardial infarction (MI) increases risk of cardiovascular (CV) hospitalizations, but evidence regarding its association with non-CV outcome is scarce. We investigated the association between LVEF and adjudicated cause-specific hospitalizations following MI complicated with low LVEF or overt heart failure (HF).

METHODS

In an individual patient data meta-analysis of 19,740 patients from 3 large randomized trials, Fine and Gray competing risk modeling was performed to study the association between LVEF and hospitalization types.

RESULTS

The most common cause of hospitalization was non-CV (n = 2,368 for HF, n = 1,554 for MI, and n = 3,703 for non-CV). All types of hospitalizations significantly increased with decreasing LVEF. The absolute risk increase associated with LVEF ≪25% (vs LVEF ≫35%) was 15.5% (95% CI 13.4-17.5) for HF, 4.7% (95% CI 3.0-6.4) for MI, and 10.4% (95% CI 8.0-12.8) for non-CV hospitalization. On a relative scale, after adjusting for confounders, each 5-point decrease in LVEF was associated with an increased risk of HF (hazard ratio [HR] 1.15, 95% CI 1.12-1.18), MI (HR 1.06, 95% CI 1.03-1.10), and non-CV hospitalization (HR 1.03, 95% CI 1.01-1.05).

CONCLUSIONS

In a high-risk population with complicated acute MI, the absolute risk increase in non-CV hospitalizations associated with LVEF ≪25% was two thirds of the absolute risk increase in HF hospitalizations and twice the absolute risk increase in MI hospitalizations. LVEF was an independent predictor of all types of hospitalization and appears as an integrative marker of sicker patient status.

Fall Risk and Outcomes Among Patients Hospitalized With Cardiovascular Disease in the Community

Background As the population with cardiovascular disease ages, geriatric conditions are of increasing relevance. A possible geriatric prognostic indicator may be a fall risk score, which is mandated by The Joint Commission to be measured on all hospitalized patients. The prognostic value of a fall risk score on outcomes after dismissal is not well known. Thus, we aimed to determine whether a fall risk score is associated with death and hospital readmissions in patients with a recent incident cardiovascular disease event. Methods and Results In this retrospective cohort study, Olmsted County, MN patients with incident heart failure, myocardial infarction, or atrial fibrillation between August 1, 2005, and December 31, 2011, who were hospitalized within 180 days after the event were studied. Fall risk was measured by the Hendrich II fall risk model. Patients were followed for death or readmission within 30 days or 1 year. Among 2456 hospitalized patients with recent incident cardiovascular disease (549 heart failure, 784 myocardial infarction, 1123 atrial fibrillation; mean [SD] age, 71 [15] years; 55% men), the fall risk score was high in 22% of patients and moderate in 38%. The risk of death was increased if the fall risk score was increased, independent of age and comorbidities (moderate hazard ratio, 1.51; 95% CI, 1.09-2.08; high hazard ratio, 3.49; 95% CI, 2.52-4.85). Similarly, the risk of 30-day readmissions was substantially increased with a greater fall risk score (moderate hazard ratio, 1.29; 95% CI, 1.03-1.62; high hazard ratio, 1.63; 95% CI, 1.23-2.15). Results were similar for readmissions within 1 year. Conclusions More than half of hospitalized patients with recent incident cardiovascular disease have an elevated fall risk score, which is associated with an increased risk in readmissions and death. These results delineate an approach for risk stratification and management that may prevent readmissions and improve survival.

Readmission and processes of care across weekend and weekday hospitalisation for acute myocardial infarction, heart failure or stroke: an observational study of the National Readmission Database

OBJECTIVES

Variation in hospital resource allocations across weekdays and weekends have led to studies of the 'weekend effect' for ST elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI), heart failure (HF) and stroke. However, few studies have explored the 'weekend effect' on unplanned readmission. We aimed to investigate 30-day unplanned readmissions and processes of care across weekend and weekday hospitalisations for STEMI, NSTEMI, HF and stroke.

DESIGN

We grouped hospitalisations for STEMI, NSTEMI, HF or stroke into weekday or weekend admissions. Multivariable adjusted ORs for binary outcomes across weekend versus weekday (reference) groups were estimated using logistic regression.

SETTING

We included all non-elective hospitalisations for STEMI, NSTEMI, HF or stroke, which were recorded in the US Nationwide Readmissions Database between 2010 and 2014.

PARTICIPANTS

The analysis sample included 659 906 hospitalisations for STEMI, 1 420 600 hospitalisations for NSTEMI, 3 027 699 hospitalisations for HF, and 2 574 168 hospitalisations for stroke.

MAIN OUTCOME MEASURES

The primary outcome was unplanned 30-day readmission. As secondary outcomes, we considered length of stay and the following processes of care: coronary angiography, primary percutaneous coronary intervention, coronary artery bypass graft, thrombolysis, brain scan/imaging, thrombectomy, echocardiography and cardiac resynchronisation therapy/implantable cardioverter-defibrillator.

RESULTS

Unplanned 30-day readmission rates were 11.0%, 15.1%, 23.0% and 10.9% for STEMI, NSTEMI, HF and stroke, respectively. Weekend hospitalisations for HF were associated with a statistically significant but modest increase in 30-day readmissions (OR of 1.045, 95% CI 1.033 to 1.058). Weekend hospitalisation for STEMI, NSTEMI or stroke was not associated with increased risk of 30-day readmission.

CONCLUSION

There was no clinically meaningful evidence against the supposition that weekend and weekday hospitalisations have the same 30-day unplanned readmissions. Thirty-day readmission rates were high, especially for HF, which has implications for service provision. Strategies to reduce readmission rates should be explored, regardless of day of hospitalisation.

The prevalence of 30-day readmission after acute myocardial infarction: A systematic review and meta-analysis

Objective

The 30‐day readmission is associated with increased medical costs, which has become an important quality metric in several medical institutions. This current study is aimed at clarifying the prevalence, the underlying risk factors, and reasons of the 30‐day readmission after acute myocardial infarction (AMI).

Methods

PubMed, Cochrane Library, and EMBASE were systematically searched to identify eligible studies. Random‐effect models were employed to perform pooled analyses. Means and 95% confidence intervals (CIs) were used to estimate prevalence and reasons for 30‐day readmission. We also used Odds ratios (ORs) to explore the potential significant predictors of risk factors of 30‐day readmission after AMI. Potential publication bias was assessed using funnel plot and Begg'test.

Results

A total of 14 relevant studies were included in this systematic review and meta‐analysis. The pooled 30‐day readmission rate of AMI was 12% (95% CI 0.11‐0.14). Acute coronary syndrome (ACS), angina and acute ischemic heart disease, and heart failure (HF) were the principal cardiovascular reasons of 30‐day readmission. Meanwhile, non‐specific chest pain was regarded as the significant cause among non‐cardiovascular reasons. The common co‐morbidities kidney disease, HF and diabetes mellitus were significant risk factors for 30‐day readmission. No significant publication bias was found by funnel plot and statistical tests.

Conclusions

The 30‐day readmission rate of post‐AMI ranged from 11% to 14% and can be mainly attributed to cardiovascular and non‐cardiovascular events. The common co‐morbidities, such as kidney disease, HF, and diabetes mellitus were significant risk factors for 30‐day readmission.

Post-hospital syndrome predicts poor postoperative outcomes and increased cost following transvaginal midurethral sling placement

INTRODUCTION AND HYPOTHESIS

Post-hospital syndrome (PHS), a 90-day period of health vulnerability related to physiologic stressors following recent inpatient admission, has been observed in surgical and non-surgical patients. We aim to explore its effects on readmission and complication rates in patients undergoing elective female mid-urethral sling placement for the treatment of stress urinary incontinence.

METHODS

The Healthcare Cost and Utilization Project State Inpatient Database, State Emergency Department Database, and State Ambulatory Surgery Database for Florida between 2009 and 2014 were linked and utilized. Patients were identified as having undergone an outpatient mid-urethral sling placement with or without cystoscopy by CPT code. The primary exposure was PHS, defined as any inpatient admission within 90 days of mid-urethral sling placement. Patients with inpatient hospitalizations within 1 year of sling procedure were categorized based on timing of prior admission and analyzed. The primary outcomes were 30-day hospital readmission, rates of postoperative ED visits, minor/major complications rates, and overall 30-day cost. A multivariable logistic regression model was fit to assess independent predictors of adverse surgical outcomes.

RESULTS

A total of 17,081 female patients who underwent mid-urethral sling procedures were identified. Patients with PHS were at higher risk for 30-day readmission [OR: 5.36 (IQR: 3.61-7.93); p < 0.005], 30-day ED visits [OR: 2.38 (IQR: 1.75-3.25); p < 0.005], major complications [OR: 6.22 (IQR: 4.67-8.29); p < 0.005], and minor complications [OR: 4.62 (IQR: 3.77-5.67); p < 0.005]. This risk was time dependent in nature with a decreasing risk profile the further surgery was from index hospitalization. Furthermore, PHS patients were more likely to incur an increased cost burden with an average 30-day increased cost of $705.80.

CONCLUSIONS

Hospitalization within 90 days prior to mid-urethral sling placement is a risk-adjusted, independent predictor of increased rates of 30-day readmission rates, 30-day ED visits, 30-day minor/major complications, and increased hospital-related cost. Clinical and surgical outcomes may be improved with consideration of prior hospitalizations in determining the timing of mid-urethral sling placement for stress urinary incontinence.

Trends and predictors of recurrent acute coronary syndrome hospitalizations and unplanned revascularization after index acute myocardial infarction treated with percutaneous coronary intervention

BACKGROUND

Repeat hospitalizations for recurrent acute coronary syndrome (ACS) or unplanned revascularization after acute myocardial infarction (MI) are common, costly and potentially preventable. We aim to describe 10-year trends and identify independent risk factors of these repeat hospitalizations.

METHODS

We analyzed data from 9615 patients from the Melbourne Interventional Group registry (2005-2014) who underwent percutaneous coronary intervention (PCI) for their index MI and survived to discharge. Patients with ≥1 hospitalization for recurrent ACS events and/or unplanned revascularization in the year after discharge were included in the recurrent coronary hospitalization group. We assessed yearly trends of recurrent coronary events and identified independent predictors using multivariate analysis.

RESULTS

Recurrent coronary hospitalization occurred in 1175 (12.2%) patients. There was a significant decrease in the rate of recurrent ACS hospitalization (15.3%-7.6%, P for trend <.001) and unplanned revascularization (4.2%-2.1%, P for trend = .01), but not in all-cause re-hospitalizations (P for trend = .28). On multivariate analysis, female gender, diabetes mellitus, previous coronary bypass surgery, previous PCI, reduced ejection fraction, heart failure, multi-vessel coronary disease and obstructive sleep apnea were independent predictors of recurrent coronary hospitalizations (all P < .05).

CONCLUSIONS

Recurrent hospitalization for ACS or unplanned revascularization has decreased significantly over the past decade. Risk factors for such events are numerous and largely non-modifiable, however they identify a cohort of patients in whom non-culprit vessel PCI in multi-vessel disease, optimization of left ventricular dysfunction and diabetes management may improve outcomes.

Impact of cardiac- and noncardiac-related conditions on adverse outcomes in patients hospitalized with acute myocardial infarction

Background

To examine the impact of cardiac- and noncardiac-related conditions on the risk of hospital complications and 7- and 30-day rehospitalizations in older adult patients with an acute myocardial infarction (AMI).

Methods and Results

The study population consisted of 3863 adults aged 65 years and older hospitalized with AMI in Worcester, Massachusetts, during six annual periods between 2001 and 2011. Individuals were categorized into four groups based on the presence of 11 previously diagnosed cardiac and noncardiac conditions. The median age of the study population was 79 years and 49% were men. Twenty-eight percent of patients had two or less cardiac- and no noncardiac-related conditions, 21% had two or less cardiac and one or more noncardiac conditions, 20% had three or more cardiac and no noncardiac conditions, and 31% had three or more cardiac and one or more noncardiac conditions. Individuals who presented with one or more noncardiac-related conditions were less likely to have been prescribed evidence-based medications and/or to have undergone coronary revascularization procedures than patients without any noncardiac condition. After multivariable adjustment, individuals with three or more cardiac and one or more noncardiac conditions were at greatest risk for all adverse outcomes.

Conclusions

Older patients hospitalized with AMI carry a significant burden of cardiac- and noncardiac-related conditions. Older adults who presented with multiple cardiac and noncardiac conditions experienced the worse short-term outcomes and treatment strategies should be developed to improve their in-hospital and post-discharge care and outcomes.

Unplanned Readmissions After Acute Myocardial Infarction: 1-Year Trajectory Following Discharge From a Safety Net Hospital

BACKGROUND

Financial penalties rendered by the Centers for Medicare and Medicaid Services have brought about new challenges for safety net hospitals that serve a vulnerable patient population with risk factors associated with high readmission rates. Our goal was to determine the 1-year trajectory of unplanned readmissions in post-myocardial infarction (MI) patients, and to identify factors associated with readmission.

METHODS

A total of 261 acute MI patients admitted from April 2015 to April 2016 were evaluated in a multidisciplinary cardiology clinic within 10 days of hospital discharge and baseline characteristics and medical comorbidities were collected. Readmission and mortality data were obtained at 1 year through chart review and telephone follow-up.

RESULTS

At 1 year, there were 90 (34%) unplanned readmissions of which half were for noncardiac diagnoses. Of these, 69 patients (77%) were readmitted once, 16 (18%) were readmitted twice, 2 (2%) were readmitted 3 times, and 3 (3%) were readmitted 4 times over the subsequent year. Cardiac causes of 1-year readmission included recurrent MI in 23 (9%) and decompensated heart failure in 18 (7%) patients. Depressed left ventricular systolic function (hazard ratio, 2.23; 95% confidence interval, 2.00-2.44; P = 0.0003) and diabetes mellitus (hazard ratio, 1.60; 95% confidence interval, 1.38-1.82; P = 0.029) were associated with a significantly higher risk of readmission at 1 year.

CONCLUSION

Following acute MI, patients are readmitted for cardiac and noncardiac diagnoses well beyond the 30-day mark. This is likely a function of the vulnerability of the patient population rather than a reflection of the medical care provided. More frequent surveillance may attenuate this problem.

All-cause mortality, cardiovascular events, and health care costs after 12 months of dual platelet aggregation inhibition after acute myocardial infarction in real-world patients: findings from the Platelet-aggregation Inhibition: Persistence with treatment and cardiovascular Events in Real world (PIPER) study

Objectives

The aim of the study was to assess all-cause mortality and cardiovascular (CV) events in patients after a period of 12 months of treatment with dual antiplatelet therapy (DAPT) after hospitalization for acute myocardial infarction (AMI) in a real-world setting. Health care costs for the management of patients post-AMI was also assessed.

Methods

A retrospective analysis using data from the administrative databases of six local health units (LHUs) was performed. All beneficiaries of these LHUs hospitalized with AMI between January 01, 2010, and December 31, 2011, and exposed to a treatment period with DAPT up to 12 months after AMI discharge were included. All-cause mortality, CV hospitalizations, and health care costs occurring during the 36-month follow-up period from end of treatment with DAPT were considered. For the cost analysis, only patients still alive at the end of the follow-up period were included.

Results

A total of 2,721 patients were included (mean ± SD age 63.6±17.3 years, 67.8% males). About 17% and 18% of all patients had CV events and died during the follow-up period, respectively. The annual mean cost per patient was €3,523.27. During the follow-up period, 63 patients had a second AMI event; for whom, the mean health care cost per patient was €19,570.70.

Conclusion

In a real-world setting in Italy, considering a 36-month follow-up period, all-cause mortality, CV events, and related health care cost of patients hospitalized with an AMI undergoing a 12-month treatment period with DAPT remained relevant. This study suggests that increased efforts aimed at the prevention of recurrent AMI are warranted, as well as an accurate risk stratification in order to improve long-term outcome.

Gender Differences in the Rate of 30-Day Readmissions after Percutaneous Coronary Intervention for Acute Coronary Syndrome

BACKGROUND

It has been reported that women have higher 30-day readmission rates than men after acute coronary syndrome (ACS). However, readmission after percutaneous coronary intervention (PCI) for ACS is a distinct subset of patients in whom gender differences have not been adequately studied.

METHODS

Hawaii statewide hospitalization data from 2010 to 2015 were assessed to compare gender differences in 30-day readmission rates among patients hospitalized with ACS who underwent PCI during the index hospitalization. Readmission diagnoses were categorized using an aggregated version of the Centers for Medicare and Medicaid Services Condition Categories. Multivariable logistic regression was applied to evaluate the effect of gender on the 30-day readmission rate.

RESULTS

A total of 5,354 patients (29.4% women) who were hospitalized with a diagnosis of ACS and underwent PCI were studied. Overall, women were older, with more identified as Native Hawaiian, and had a higher prevalence of cardiovascular risk factors compared with men. The 30-day readmission rate was 13.9% in women and 9.6% in men (p < .0001). In the multivariable model, female gender (odds ratio [OR], 1.32; 95% confidence interval [CI], 1.09-1.60), Medicaid (OR, 1.48; 95% CI, 1.07-2.06), Medicare (1.72; 95% CI, 1.35-2.19), heart failure (1.88; 95% CI, 1.53-2.33), atrial fibrillation (OR, 1.54; 95% CI-1.21-1.95), substance use (OR, 1.88; 95% CI, 1.27-2.77), history of gastrointestinal bleeding (OR, 2.43; 95% CI, 1.29-4.58), and chronic kidney disease (OR, 1.78; 95% CI, 1.42-2.22) were independent predictors of 30-day readmissions. Readmission rates were highest during days 1 through 6 (peak, day 3) after discharge. The top three cardiac causes of readmissions were heart failure, recurrent angina, and recurrent ACS.

CONCLUSIONS

Female gender is an independent predictor of 30-day readmission after ACS that requires PCI. Our finding suggests women are at a higher risk of post-ACS cardiac events such as heart failure and recurrent ACS, and further gender-specific intervention is needed to reduce 30-day readmission rate in women after ACS.

Etiologies, predictors, and economic impact of readmission within 1 month among patients with takotsubo cardiomyopathy

BACKGROUND

Limited data exist on readmission among patients with takotsubo cardiomyopathy (TC), a commonly reversible cause of heart failure.

HYPOTHESIS

We sought to identify etiologies and predictors for readmission among TC patients.

METHODS

We queried the National Readmissions Database for 2013-2014 to identify patients with primary admission for TC using ICD-9-CM code 429.83. Patients readmitted to hospital within 1 month after discharge were further evaluated to identify etiologies, predictors, and resultant economic burden of readmission. Additionally, we analyzed readmission for TC at 6 months.

RESULTS

We studied 5997 patients admitted with TC, of whom 1.2% experienced in-hospital mortality. Median age was 67 years, with 91.5% being female. Among survivors, 10.3% were readmitted within 1 month; 25% of the initial 1-month readmissions occurred within 4 days, 50% within 10 days, and 75% within 20 days from discharge. The most common etiologies for readmission were cardiac (26%), respiratory (16%), and gastrointestinal (11%) causes. Heart failure was the most common cardiac etiology. Significant predictors of increased 1-month readmission included systemic thromboembolic events, length of stay ≥3 days, and underlying psychoses. Obesity and private insurance predicted lower 1-month readmission. The annual national cost impact for index admission and 1-month readmissions was ≈$112 million. Recurrent TC was seen among 1.9% of patients readmitted within 6 months.

CONCLUSIONS

Though the overall rate of 1-month readmission following TC is low, associated economic burden from readmission is still significant. Patients are readmitted mostly for noncardiac causes. Readmission for another episode of TC within 6 months was uncommon.

Food as Medicine for Secondary Prevention of Cardiovascular Events Following an Acute Coronary Syndrome

Cardiovascular disease is the leading cause of death in men and women in the USA. Once a patient experiences an acute coronary syndrome (ACS), they are at increased risk for hospital readmission within 30 days and 6 months after discharge and more importantly, they have worse survival. Hospital readmissions lead to poor clinical outcomes for the patient and also significantly increase healthcare costs due to repeat diagnostic evaluation, imaging, and coronary interventions. The goal after hospital discharge is to modify cardiovascular (CV) risk factors including hypertension, hyperlipidemia, and diabetes to prevent repeat coronary events; however, drug therapy is only one aspect. Several diets have been shown to decrease weight and reduce these risk factors over short durations; however, most people typically cannot sustain their diet and regain the weight. The Intelligent Quisine (IQ) diet is a prepared meal plan that was designed to meet the American Heart Association and American Diabetes Association nutritional guidelines and simplify the daily consumption of a nutritionally complete, calorie conscious meal. The IQ diet has been shown to significantly reduce blood pressure, cholesterol levels, glucose levels, and weight over a 10-week period. Additional studies have shown that patients are able to remain compliant on the diet for a year and maintain the reduction of their CV risk factors. If patients are consistent with a healthy calorie conscious and nutritionally complete diet modifying CV risk factors long term, then food could be as powerful in reducing CV events as evidence-based drug therapy. There is a need to begin conceptualizing food as medicine. To this end, it is time for a randomized control trial implementing the IQ diet versus current standard dietary recommendations in a large number of patients and measuring hard CV endpoints. Many readmissions can be avoided with proper patient education and support emphasizing lifestyle modifications such as eating healthy and smoking cessation on a foundation of optimal medical therapy.

Characteristics and outcomes associated with 30-day readmissions following acute coronary syndrome 2000-2013: the Acute Coronary Syndrome Israeli Survey

BACKGROUND

Readmissions following acute myocardial infarction are associated with poor outcomes and a heavy economic burden. There are few evidence-based data on the characteristics and outcomes of patients readmitted following acute coronary syndrome. We explored the incidence and outcomes of patients readmitted after an acute coronary syndrome in the past decade.

METHODS

The study population comprised all acute coronary syndrome patients who were enrolled and prospectively followed up in the biennial Acute Coronary Syndrome Israeli Survey from 2000 to 2013. Multivariate analysis identified factors independently associated with readmission and long-term mortality.

RESULTS

There were 13,010 study patients, of whom 556 (4.2%) had an unplanned readmission within 30 days of the index event. Stent thrombosis during the index hospitalisation (odds ratio (OR) 8.43; 95% confidence interval (CI) 4.11-16.07; P<0.001), female sex (OR 1.34; 95% CI 1.1-1.63; P=0.003), older age (>65 years; OR 1.28; 95% CI 1.06-1.55; P=0.011), and lack of dual-antiplatelet therapy (OR 1.52; 95% CI 1.25-1.86; P<0.001) were independently associated with readmission. Readmitted patients were less likely to have been treated with guideline-directed medical therapy during hospitalisation and at discharge, and were less likely to have undergone coronary angiography. A strong trend towards decline in readmission rates following acute coronary syndrome was observed between 2000 and 2013 (P<0.001). However, the association between readmission and poor long-term outcome was more pronounced among patients readmitted during more recent years (2008-2013).

CONCLUSIONS

Patients readmitted to hospital following acute coronary syndrome comprise an undertreated, high-risk cohort. Our findings indicate that despite a significant decline in readmission rates following acute coronary syndrome over the past decade, readmission within 30 days following acute coronary syndrome still portends a grave outcome.

HIV and early hospital readmission: evaluation of a tertiary medical facility in Lilongwe, Malawi

BACKGROUND

Delivery of quality healthcare in resource-limited settings is an important, understudied public health priority. Thirty-day (early) hospital readmission is often avoidable and an important indicator of healthcare quality.

METHODS

We investigated the prevalence of all-cause early readmission and its associated factors using age and sex adjusted risk ratios (RR) and 95% confidence intervals (CI). A retrospective review of the medical ward database at Kamuzu Central Hospital in Lilongwe, Malawi was conducted between February and December 2013.

RESULTS

There were 3547 patients with an index admission of which 2776 (74.4%) survived and were eligible for readmission. Among these patients: 49.7% were male, mean age was 39.7 years, 36.1% were HIV-positive, 34.6% were HIV-negative, and 29.3% were HIV-unknown. The prevalence of early hospital readmission was 5.5%. Diagnoses associated with 30-day readmission were HIV-positive status (RR = 2.41; 95% CI: 1.64-3.53) and malaria (RR = 0.45; 95% CI: 0.22-0.91). Other factors associated with readmission were multiple diagnoses (excluding HIV) (RR = 1.52; 95% CI: 1.11-2.06), and prolonged length of stay (≥ 16 days) at the index hospitalization (RR = 3.63; 95% CI: 1.72-7.67).

CONCLUSION

Targeting HIV-infected inpatients with multiple diagnoses and longer index hospitalizations may prevent early readmission and improve quality of care.

Effectiveness of discharge education on outcomes in acute coronary syndrome patients: a systematic review protocol

REVIEW QUESTION

The question of this review is what is the effectiveness of discharge education on outcomes in acute coronary syndrome patients?

Factors associated with 30-day readmission after hospitalisation for community-acquired pneumonia in older patients: a cross-sectional study in seven Spanish regions

OBJECTIVE

Hospital readmission in patients admitted for community-acquired pneumonia (CAP) is frequent in the elderly and patients with multiple comorbidities, resulting in a clinical and economic burden. The aim of this study was to determine factors associated with 30-day readmission in patients with CAP.

DESIGN

A cross-sectional study.

SETTING

The study was conducted in patients admitted to 20 hospitals in seven Spanish regions during two influenza seasons (2013-2014 and 2014-2015).

PARTICIPANTS

We included patients aged ≥65 years admitted through the emergency department with a diagnosis compatible with CAP. Patients who died during the initial hospitalisation and those hospitalised more than 30 days were excluded. Finally, 1756 CAP cases were included and of these, 200 (11.39%) were readmitted.

MAIN OUTCOME MEASURES

30-day readmission.

RESULTS

Factors associated with 30-day readmission were living with a person aged <15 years (adjusted OR (aOR) 2.10, 95% CI 1.01 to 4.41), >3 hospital visits during the 90 previous days (aOR 1.53, 95% CI 1.01 to 2.34), chronic respiratory failure (aOR 1.74, 95% CI 1.24 to 2.45), heart failure (aOR 1.69, 95% CI 1.21 to 2.35), chronic liver disease (aOR 2.27, 95% CI 1.20 to 4.31) and discharge to home with home healthcare (aOR 5.61, 95% CI 1.70 to 18.50). No associations were found with pneumococcal or seasonal influenza vaccination in any of the three previous seasons.

CONCLUSIONS

This study shows that 11.39% of patients aged ≥65 years initially hospitalised for CAP were readmitted within 30 days after discharge. Rehospitalisation was associated with preventable and non-preventable factors.

Prevalence, Causes, and Predictors of 30-Day Readmissions Following Hospitalization With Acute Myocardial Infarction Complicated By Cardiogenic Shock: Findings From the 2013-2014 National Readmissions Database

Background

Prior studies have shown that survivors of acute myocardial infarction (AMI) complicated by cardiogenic shock are likely to have increased risk of readmissions in the early post‐discharge period. However, the contemporary prevalence, reasons, and predictors of 30‐day readmissions are not well known.

Methods and Results

Hospitalizations for a primary diagnosis of AMI complicated by cardiogenic shock, and discharged alive, were identified in the 2013 and 2014 Nationwide Readmissions Databases. Prevalence and reasons for 30‐day unplanned readmissions were investigated. A hierarchical logistic regression model was used to identify independent predictors of 30‐day readmissions. Among 1 116 933 patient hospitalizations with AMI, 39 807 (3.6%) had cardiogenic shock and were discharged alive. Their 30‐day readmission rate was 18.6%, with a median time for readmission 10 days post discharge. Predictors of readmission included: non–ST‐segment elevation myocardial infarction, female sex, low‐income status, nonprivate insurance, chronic renal failure, long‐term ventricular assist device or intra‐aortic balloon placement, and tachyarrhythmia. The majority of readmissions were attributable to cardiac‐related causes (52%); heart failure being the most frequent cardiac cause (39% of all cardiac causes). Noncardiac‐related readmissions included infections (14.9%), bleeding (5.3%), and respiratory causes (4.9%). The median cost per readmission was $9473 US dollars ($5037–20 199).

Conclusions

Among survivors of AMI complicated by cardiogenic shock who were discharged from hospital, almost 1 in 5 are readmitted at 30 days, mainly because of cardiac reasons such as heart failure and new AMI. The risk of readmission was associated with certain baseline patient/hospital characteristics.

Correction to: Hospital Readmission of Patients with Diabetes

This article was originally published with errors that were introduced during the editing process. The corrected version of this article appears below.

Thirty-Day Readmissions After Left Ventricular Assist Device Implantation in the United States

Background:

Early readmissions contribute significantly to heart failure–related morbidity and negatively affect quality of life. Data on left ventricular assist device (LVAD)–related 30-day readmissions are scarce and limited to small studies.

Methods and Results:

Patients undergoing LVAD implantation between January 2013 and November 2014 who survived the index hospitalization were identified in the Nationwide Readmissions Database. We analyzed the incidence, predictors, causes, and costs of 30-day readmissions. Of 2510 LVAD recipients, 788 (31%) were readmitted within 30 days. Length of index hospitalization ≥31 days (hazard ratio [HR], 1.26; 95% confidence interval [CI], 1.07–1.50) and female sex (HR, 1.19; 95% CI, 1.01–1.42) were associated with a higher risk of 30-day readmission, whereas private insurance (HR, 0.83; 95% CI, 0.70–0.99), pre-LVAD use of short-term mechanical circulatory support (HR, 0.53; 95% CI, 0.29–0.98), and discharge to a short-term hospital facility (HR, 0.41; CI, 0.21–0.78) were associated with a lower risk. Cardiac causes accounted for 23.8% of readmissions: heart failure (13.4%) and arrhythmias (8.1%). Noncardiovascular causes accounted for 76.2% of readmissions: infection (30.2%), bleeding (17.6%), and device-related causes (8.2%). Mean length of stay for readmission was 10.7 days (median, 6 days), and average hospital cost per readmission was $34 948±2457.

Conclusions:

Early readmissions are frequent after LVAD implantation even in contemporary times. Preimplant identification of high-risk patients, and a protocol-driven follow-up using a multidisciplinary approach will be needed to reduce readmissions and improve outcomes.

Exploring the effects of transfers and readmissions on trends in population counts of hospital admissions for coronary heart disease: a Western Australian data linkage study

OBJECTIVES

To develop a method for categorising coronary heart disease (CHD) subtype in linked data accounting for different CHD diagnoses across records, and to compare hospital admission numbers and ratios of unlinked versus linked data for each CHD subtype over time, and across age groups and sex.

DESIGN

Cohort study.

DATA SOURCE

Person-linked hospital administrative data covering all admissions for CHD in Western Australia from 1988 to 2013.

MAIN OUTCOME

Ratios of (1) unlinked admission counts to contiguous admission (CA) counts (accounting for transfers), and (2) 28-day episode counts (accounting for transfers and readmissions) to CA counts stratified by CHD subtype, sex and age group.

RESULTS

In all CHD subtypes, the ratios changed in a linear or quadratic fashion over time and the coefficients of the trend term differed across CHD subtypes. Furthermore, for many CHD subtypes the ratios also differed by age group and sex. For example, in women aged 35-54 years, the ratio of unlinked to CA counts for non-ST elevation myocardial infarction admissions in 2000 was 1.10, and this increased in a linear fashion to 1.30 in 2013, representing an annual increase of 0.0148.

CONCLUSION

The use of unlinked counts in epidemiological estimates of CHD hospitalisations overestimates CHD counts. The CA and 28-day episode counts are more aligned with epidemiological studies of CHD. The degree of overestimation of counts using only unlinked counts varies in a complex manner with CHD subtype, time, sex and age group, and it is not possible to apply a simple correction factor to counts obtained from unlinked data.