Assessing response bias from missing quality of life data: The Heckman method

BACKGROUND: The objective of this study was to demonstrate the use of the Heckman two-step method to assess and correct for bias due to missing health related quality of life (HRQL) surveys in a clinical study of acute coronary syndrome (ACS) patients. METHODS: We analyzed data from 2,733 veterans with a confirmed diagnosis of acute coronary syndromes (ACS), including either acute myocardial infarction or unstable angina. HRQL outcomes were assessed by the Short-Form 36 (SF-36) health status survey which was mailed to all patients who were alive 7 months following ACS discharge. We created multivariable models of 7-month post-ACS physical and mental health status using data only from the 1,660 survey respondents. Then, using the Heckman method, we modeled survey non-response and incorporated this into our initial models to assess and correct for potential bias. We used logistic and ordinary least squares regression to estimate the multivariable selection models. RESULTS: We found that our model of 7-month mental health status was biased due to survey non-response, while the model for physical health status was not. A history of alcohol or substance abuse was no longer significantly associated with mental health status after controlling for bias due to non-response. Furthermore, the magnitude of the parameter estimates for several of the other predictor variables in the MCS model changed after accounting for bias due to survey non-response. CONCLUSION: Recognition and correction of bias due to survey non-response changed the factors that we concluded were associated with HRQL seven months following hospital admission for ACS as well as the magnitude of some associations. We conclude that the Heckman two-step method may be a valuable tool in the assessment and correction of selection bias in clinical studies of HRQL

Atrial fibrillation and outcomes in heart failure with preserved versus reduced left ventricular ejection fraction

BACKGROUND: Atrial fibrillation (AF) and heart failure (HF) are 2 of the most common cardiovascular conditions nationally and AF frequently complicates HF. We examined how AF has impacts on adverse outcomes in HF-PEF versus HF-REF within a large, contemporary cohort. METHODS AND RESULTS: We identified all adults diagnosed with HF-PEF or HF-REF based on hospital discharge and ambulatory visit diagnoses and relevant imaging results for 2005-2008 from 4 health plans in the Cardiovascular Research Network. Data on demographic features, diagnoses, procedures, outpatient pharmacy use, and laboratory results were ascertained from health plan databases. Hospitalizations for HF, stroke, and any reason were identified from hospital discharge and billing claims databases. Deaths were ascertained from health plan and state death files. Among 23 644 patients with HF, 11 429 (48.3%) had documented AF (9081 preexisting, 2348 incident). Compared with patients who did not have AF, patients with AF had higher adjusted rates of ischemic stroke (hazard ratio [HR] 2.47 for incident AF; HR 1.57 for preexisting AF), hospitalization for HF (HR 2.00 for incident AF; HR 1.22 for preexisting AF), all-cause hospitalization (HR 1.45 for incident AF; HR 1.15 for preexisting AF), and death (incident AF HR 1.67; preexisting AF HR 1.13). The associations of AF with these outcomes were similar for HF-PEF and HF-REF, with the exception of ischemic stroke. CONCLUSIONS: AF is a potent risk factor for adverse outcomes in patients with HF-PEF or HF-REF. Effective interventions are needed to improve the prognosis of these high-risk patients

Patterns of Complex Comorbidity in Older Patients with Heart Failure

Background Heart failure (HF) carries a high burden of comorbidity with approximately one half of patients with HF having at least one additional comorbid condition present. Rates of comorbidity in patients with HF have steadily increased over the past 2 decades. Objective To examine patterns of comorbidity among older patients with HF in the Cardiovascular Research Network PRESERVE cohort. Methods PRESERVE Cohort Data are from the CVRN PRESERVE cohort which is a multicenter cohort of 37,054 patients [mean age = 74 years (SD = 12.4 yrs); 46% female] with HF diagnosed between 2005 and 2008 currently being conducted at 4 CVRN sites: KPNC, KPCO, KPNW, and FCHP. The primary data source for the PRESERVE cohort was the HMO Research Network Virtual Data Warehouse. Identification of Coexisting Diseases Coexisiting illnesses at the time of HF diagnosis were based on diagnoses and procedures mapped to relevant International Classification of Diseases, Ninth Edition (ICD-9) codes. For the purposes of characterizing clusters of comorbidities, we focused on coexisting conditions with a prevalence rate of ≥3%. Statistical Analysis We used the Agglomerative Clustering technique to characterize patterns of comorbidity. Over multiple iterations, each condition is clustered with the condition with which it has the highest squared correlation. This process is repeated to determine whether assigning a condition to a different cluster increases the amount of explained variance [ranging from 1.0 (all variance explained) to 0.0 (no variance explained)]. The conditions in each cluster are as correlated as possible among themselves and as uncorrelated as possible with conditions in other clusters. Results Burden of Comorbidity There was a high degree of comorbidity and multi-morbidity among patients with HF. (Table 1) Hypertension and arrhythmias were the comorbidities of HF that occurred most often in the absence of other chronic conditions (4.8% and 4.7%, respectively). The average number of comorbid conditions varied from 3.5 to 5.2. Patients with HF and unstable angina or other thromboembolic disorders had the highest multi-morbidity (mean = 5.2 conditions), whereas those with HF and hypertension had the lowest (mean = 3.5). Clustering of Comorbiditites A five-cluster structure was derived. Cluster 1: Dyslipidemia, Hypertension, Diabetes Mellitus, Visual Impairment Cluster 2: Acute Myocardial Infarction, Unstable Angina, Thromboembolic Disorder, Dementia Cluster 3: Aortic Valvular Disease, Cancer, Hearing Impairment, Arrthythmia Cluster 4: Peripheral Arterial Disease, Stroke Cluster 5: Lung Disease, Liver Disease, Depression Discussion and Conclusions Cluster analysis is an innovative approach to examining the co-occurrence of diseases and allows for identification of broad patterns of multi-morbidity beyond the pairings of diseases or disease counts. Patients with HF have a high rate of multi-morbidity, with an average of 4 co-occurring conditions. Intuitive and unintuitive patterns of clustering were identified. Randomized clinical trials in HF will need to include more diverse patient populations in order to adapt to the increasingly complex patient population. A cluster analysis approach to characterizing patterns of comorbidity may help indentify important patient subgroups

The association between care co-ordination and emergency department use in older managed care enrollees

OBJECTIVE: To investigate the association between care co-ordination and use of the Emergency Department (ED) in older managed care enrollees. DESIGN: Nested case-control with 103 cases (used the ED) and 194 controls (did not use the ED). PATIENTS AND METHODS: Older patients with multiple chronic illnesses enrolled in a care management programme of a large group-model health maintenance organisation with more than 50,000 members over the age of 64. Better care co-ordination was defined as timely follow-up after a change in treatment; fewer decision-makers involved with the care plan; and a higher patient-perceived rating of overall care co-ordination. Logistic regression was used to assess the relationship between ED use (the outcome variable) and measures of care co-ordination (the predictor variables). RESULTS: Self-reported care co-ordination was not significantly different between cases and controls for any of the four classifications of inappropriate ED use. Similarly, no differences were found in the number of different physicians or medication prescribers involved in the patients' care. Four-week follow-up after potentially high-risk events for subsequent ED use, including changes in chronic disease medications, missed encounters, and same day encounters, did not differ between subjects with inappropriate ED use and controls. CONCLUSION: Existing measures of care co-ordination were not associated with inappropriate ED use in this study of older adults with complex care needs. The absence of an association may, in part, be attributable to the paucity of validated measures to assess care co-ordination, as well as the methodological complexity inherent in studying this topic. Future research should focus on the development of new measures and on approaches that better isolate the role of care co-ordination from other potential variables that influence utilisation

Comparison of Inappropriate Shocks and Other Health Outcomes Between Single- and Dual-Chamber Implantable Cardioverter-Defibrillators for Primary Prevention of Sudden Cardiac Death: Results from the Cardiovascular Research Network Longitudinal Study of Implantable Cardioverter-Defibrillators

Background In US clinical practice, many patients who undergo placement of an implantable cardioverter‐defibrillator (ICD) for primary prevention of sudden cardiac death receive dual‐chamber devices. The superiority of dual‐chamber over single‐chamber devices in reducing the risk of inappropriate ICD shocks in clinical practice has not been established. The objective of this study was to compare risk of adverse outcomes, including inappropriate shocks, between single‐ and dual‐chamber ICDs for primary prevention. Methods and Results We identified patients receiving a single‐ or dual‐chamber ICD for primary prevention who did not have an indication for pacing from 15 hospitals within 7 integrated health delivery systems in the Longitudinal Study of Implantable Cardioverter‐Defibrillators from 2006 to 2009. The primary outcome was time to first inappropriate shock. ICD shocks were adjudicated for appropriateness. Other outcomes included all‐cause hospitalization, heart failure hospitalization, and death. Patient, clinician, and hospital‐level factors were accounted for using propensity score weighting methods. Among 1042 patients without pacing indications, 54.0% (n=563) received a single‐chamber device and 46.0% (n=479) received a dual‐chamber device. In a propensity‐weighted analysis, device type was not significantly associated with inappropriate shock (hazard ratio, 0.91; 95% confidence interval, 0.59–1.38 [P=0.65]), all‐cause hospitalization (hazard ratio, 1.03; 95% confidence interval, 0.87–1.21 [P=0.76]), heart failure hospitalization (hazard ratio, 0.93; 95% confidence interval, 0.72–1.21 [P=0.59]), or death (hazard ratio, 1.19; 95% confidence interval, 0.93–1.53 [P=0.17]). Conclusions Among patients who received an ICD for primary prevention without indications for pacing, dual‐chamber devices were not associated with lower risk of inappropriate shock or differences in hospitalization or death compared with single‐chamber devices. This study does not justify the use of dual‐chamber devices to minimize inappropriate shocks

Use of Risk Models to Predict Death in the Next Year Among Individual Ambulatory Patients With Heart Failure

Importance: The clinical practice guidelines for heart failure recommend the use of validated risk models to estimate prognosis. Understanding how well models identify individuals who will die in the next year informs decision making for advanced treatments and hospice. Objective: To quantify how risk models calculated in routine practice estimate more than 50% 1-year mortality among ambulatory patients with heart failure who die in the subsequent year. Design, Setting, and Participants: Ambulatory adults with heart failure from 3 integrated health systems were enrolled between 2005 and 2008. The probability of death was estimated using the Seattle Heart Failure Model (SHFM) and the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk calculator. Baseline covariates were collected from electronic health records. Missing covariates were imputed. Estimated mortality was compared with actual mortality at both population and individual levels. Main Outcomes and Measures: One-year mortality. Results: Among 10930 patients with heart failure, the median age was 77 years, and 48.0% of these patients were female. In the year after study enrollment, 1661 patients died (15.9% by life-table analysis). At the population level, 1-year predicted mortality among the cohort was 9.7% for the SHFM (C statistic of 0.66) and 17.5% for the MAGGIC risk calculator (C statistic of 0.69). At the individual level, the SHFM predicted a more than 50% probability of dying in the next year for 8 of the 1661 patients who died (sensitivity for 1-year death was 0.5%) and for 5 patients who lived at least a year (positive predictive value, 61.5%). The MAGGIC risk calculator predicted a more than 50% probability of dying in the next year for 52 of the 1661 patients who died (sensitivity, 3.1%) and for 63 patients who lived at least a year (positive predictive value, 45.2%). Conversely, the SHFM estimated that 8496 patients (77.8%) had a less than 15% probability of dying at 1 year, yet this lower-risk end of the score range captured nearly two-thirds of deaths (n = 997); similarly, the MAGGIC risk calculator estimated a probability of dying of less than 25% for the majority of patients who died at 1 year (n = 914). Conclusions and Relevance: Although heart failure risk models perform reasonably well at the population level, they do not reliably predict which individual patients will die in the next year

Evidence and recommendations on the use of telemedicine for the management of arterial hypertension:an international expert position paper

Telemedicine allows the remote exchange of medical data between patients and healthcare professionals. It is used to increase patients’ access to care and provide effective healthcare services at a distance. During the recent coronavirus disease 2019 (COVID-19) pandemic, telemedicine has thrived and emerged worldwide as an indispensable resource to improve the management of isolated patients due to lockdown or shielding, including those with hypertension. The best proposed healthcare model for telemedicine in hypertension management should include remote monitoring and transmission of vital signs (notably blood pressure) and medication adherence plus education on lifestyle and risk factors, with video consultation as an option. The use of mixed automated feedback services with supervision of a multidisciplinary clinical team (physician, nurse, or pharmacist) is the ideal approach. The indications include screening for suspected hypertension, management of older adults, medically underserved people, high-risk hypertensive patients, patients with multiple diseases, and those isolated due to pandemics or national emergencies

The impact of diabetes on one-year health status outcomes following acute coronary syndromes

Abstract Background Diabetes is an important predictor of mortality patients with ACS. However, little is known about the association between diabetes and health status after ACS. The objective of this study was to examine the association between diabetes and patients' health status outcomes one year after an acute coronary syndrome (ACS). Methods This was a prospective cohort study of patients hospitalized with ACS. Patients were evaluated at baseline and one year with the Seattle Angina Questionnaire (SAQ). Socio-demographic and clinical characteristics were ascertained during index ACS hospitalization. One year SAQ Angina Frequency, Physical Limitation, and Health-Related Quality of Life (HRQoL) scales were the primary outcomes of the study. Results Of 1199 patients, 326 (37%) had diabetes. Patients with diabetes were more likely to present with unstable angina (52% vs. 40%; p < 0.001), less likely to present with STEMI (20% vs. 31%; p < 0.001), and less likely to undergo coronary angiography (68% vs. 82%; p < 0.001). In multivariable analyses, the presence of diabetes was associated with significantly more angina (OR 1.36; 95% CI 1.01–1.38), cardiac-related physical limitation (OR 1.94; 95% CI 1.57–3.24) and HRQoL deficits (OR 1.43; 95% CI 1.01–2.04) at one year. Conclusion Diabetes is associated with more angina, worse physical limitation, and worse HRQoL one year after an ACS. Future studies should assess whether health status outcomes of patients with diabetes could be improved through more aggressive ACS treatment or post-discharge surveillance and angina management.Peer Reviewe

Risk of Heart Failure in Breast Cancer Patients After Anthracycline and Trastuzumab Treatment: A Retrospective Cohort Study

Background: Clinical trials demonstrated that women treated for breast cancer with anthracycline or trastuzumab are at increased risk for heart failure and/or cardiomyopathy (HF/CM), but the generalizability of these findings is unknown. We estimated real-world adjuvant anthracycline and trastuzumab use and their associations with incident HF/CM. Methods We conducted a population-based, retrospective cohort study of 12 500 women diagnosed with incident, invasive breast cancer from January 1, 1999 through December 31, 2007, at eight integrated Cancer Research Network health systems. Using administrative procedure and pharmacy codes, we identified anthracycline, trastuzumab, and other chemotherapy use. We identified incident HF/CM following chemotherapy initiation and assessed risk of HF/CM with time-varying chemotherapy exposures vs no chemotherapy. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age at diagnosis, stage, Cancer Research Network site, year of diagnosis, radiation therapy, and comorbidities. Results: Among 12 500 women (mean age = 60 years, range = 22–99 years), 29.6% received anthracycline alone, 0.9% received trastuzumab alone, 3.5% received anthracycline plus trastuzumab, 19.5% received other chemotherapy, and 46.5% received no chemotherapy. Anthracycline and trastuzumab recipients were younger, with fewer comorbidities than recipients of other chemotherapy or none. Compared with no chemotherapy, the risk of HF/CM was higher in patients treated with anthracycline alone (adjusted HR = 1.40, 95% CI = 1.11 to 1.76), although the increased risk was similar to other chemotherapy (adjusted HR = 1.49, 95% CI = 1.25 to 1.77); the risk was highly increased in patients treated with trastuzumab alone (adjusted HR = 4.12, 95% CI = 2.30 to 7.42) or anthracycline plus trastuzumab (adjusted HR = 7.19, 95% CI = 5.00 to 10.35). Conclusions: Anthracycline and trastuzumab were primarily used in younger, healthier women and associated with increased HF/CM risk compared with no chemotherapy. This population-based observational study complements findings from clinical trials on cancer treatment safety

Device Therapies Among Patients Receiving Primary Prevention Implantable Cardioverterâ Defibrillators in the Cardiovascular Research Network

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143721/1/jah33061_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143721/2/jah33061.pd