Prediction of Rehospitalization and Death in Severe Heart Failure by Physicians and Nurses of the ESCAPE Trial

Do patients at high risk of nonsudden cardiac death benefit from prophylactic ICD therapy?

PURPOSE OF REVIEW

Randomized controlled trials have established that prophylactic implantable cardioverter defibrillator (ICD) therapy improves survival in patients with reduced left ventricular ejection fraction (LVEF). However, mortality reduction is not uniform across the implanted population and recent data have highlighted the importance of nonsudden cardiac death (non-SCD) risk in predicting benefit from ICD therapy. This review explores the importance of non-SCD risk in patient selection for prophylactic ICD therapy, as well as the proposed approaches to identify potential ICD recipients at high risk of non-SCD.

RECENT FINDINGS

Data from randomized controlled trials have demonstrated that patients at high risk of non-SCD do not gain significant survival benefit from prophylactic ICD therapy irrespective of their risk of SCD. A variety of strategies to identify low LVEF patients at high risk of non-SCD have been proposed. These include the use of individual risk markers, such as advanced age and renal dysfunction, the presence of cardiac and noncardiac comorbidities, and the use of more complex risk scores.

SUMMARY

Non-SCD risk is an important issue in patient selection for prophylactic ICD therapy. However, the optimal strategy to identify patients at high non-SCD risk is unclear and further research is needed.

Predictors of re-hospitalization in patients with chronic heart failure

Heart failure (HF) is a chronic, progressive illness that is highly prevalent in the United States and worldwide. This morbid illness carries a very poor prognosis, and leads to frequent hospitalizations. Repeat hospitalization in HF is both largely burdensome to the patient and the healthcare system, as it is one of the most costly medical diagnoses among Medicare recipients. For years, investigators have strived to determine methods to reduce hospitalization rates of HF patients. Despite such efforts, recent reports indicate that re-hospitalization rates remain persistently high, without any improvement over the past several years and thus, this topic clearly needs aggressive attention. We performed a key-word search of the literature for relevant citations. Published articles, limited to English abstracts indexed primarily in the PubMed database through the year 2011, were reviewed. This article discusses various clinical parameters, serum biomarkers, hemodynamic parameters, and psychosocial factors that have been reviewed in the literature as predictors of re-hospitalization of HF patients. With this information, our hope is that the future holds better risk-stratification models that will allow providers to identify high-risk patients, and better customize effective interventions according to the needs of each individual HF patient.

The relationship between hospital admission rates and rehospitalizations

BACKGROUND

Efforts to reduce hospital readmissions have focused primarily on improving transitional care. Yet variation in readmission rates may more closely reflect variation in the underlying hospitalization rates than differences in the quality of care during and after discharge.

METHODS

We used national Medicare data to calculate, for each local hospital referral region (HRR), the 30-day, 60-day, and 90-day readmission rates among patients discharged with congestive heart failure or pneumonia. We also calculated population-based all-cause admission rates among Medicare enrollees in each HRR. We examined the variation in HRR readmission rates that was explained by overall hospitalization rates versus differences in patients' coexisting conditions, quality of discharge planning, physician supply, and bed supply.

RESULTS

HRR readmission rates ranged from 11 to 32% for congestive heart failure and from 8 to 27% for pneumonia. In univariate analyses, all-cause admission rates accounted for the highest proportion of regional variation in readmission rates for congestive heart failure (28%, 34%, and 37% at 30, 60, and 90 days, respectively); the next highest proportions were explained by case mix (11%, 15%, and 18%) and the number of cardiologists per capita (12%, 14%, and 15%). Results for pneumonia were similar, except that the number of pulmonologists per capita accounted for a lower proportion of the variation (6%, 8%, and 7%, respectively). In multivariate analyses, admission rates accounted for 16 to 24% of the variation for congestive heart failure and 11 to 20% for pneumonia; no other factor accounted for more than 6%.

CONCLUSIONS

We found a substantial association between regional rates of rehospitalization and overall admission rates. Programs directed at shared savings from lower utilization of hospital services might be more successful in reducing readmissions than programs initiated to date. (Funded by the Commonwealth Fund.).

Linking electronic health record-extracted psychosocial data in real-time to risk of readmission for heart failure

BACKGROUND

Knowledge of psychosocial characteristics that helps to identify patients at increased risk for readmission for heart failure (HF) may facilitate timely and targeted care.

OBJECTIVE

We hypothesized that certain psychosocial characteristics extracted from the electronic health record (EHR) would be associated with an increased risk for hospital readmission within the next 30 days.

METHODS

We identified 15 psychosocial predictors of readmission. Eleven of these were extracted from the EHR (six from structured data sources and five from unstructured clinical notes). We then analyzed their association with the likelihood of hospital readmission within the next 30 days among 729 patients admitted for HF. Finally, we developed a multivariable predictive model to recognize individuals at high risk for readmission.

RESULTS

We found five characteristics-dementia, depression, adherence, declining/refusal of services, and missed clinical appointments-that were associated with an increased risk for hospital readmission: the first four features were captured from unstructured clinical notes, while the last item was captured from a structured data source.

CONCLUSIONS

Unstructured clinical notes contain important knowledge on the relationship between psychosocial risk factors and an increased risk of readmission for HF that would otherwise have been missed if only structured data were considered. Gathering this EHR-based knowledge can be automated, thus enabling timely and targeted care.

Assessing the impact of screening colonoscopy on mortality in the medicare population

BACKGROUND

Some have recommended against routine screening for colorectal cancer (CRC) among patients ≥75 years of age, while others have suggested that screening colonoscopy (SC) is less beneficial for women than men. We estimated the expected benefits (decreased mortality from CRC) and harms (SC-related mortality) of SC based on sex, age, and comorbidity.

OBJECTIVE

To stratify older patients according to expected benefits and harms of SC based on sex, age, and comorbidity.

DESIGN

Retrospective study using Medicare claims data.

PARTICIPANTS

Medicare beneficiaries 67-94 years old with and without CRC.

MAIN MEASURES

Life expectancy, CRC- and colonoscopy-attributable mortality rates across strata of sex, age, and comorbidity, pay-off time (i.e. the minimum time until benefits from SC exceeded harms), and life-years saved for every 100,000 SC.

KEY RESULTS

Increasing age and comorbidity were associated with lower CRC-attributable mortality. Due to shorter life expectancy and CRC-attributable mortality, the benefits associated with SC were substantially lower among patients with greater comorbidity. Among men aged 75-79 years with no comorbidity, the number of life-years saved was 459 per 100,000 SC, while men aged 67-69 with ≥3 comorbidities had 81 life-years saved per 100,000 SC. There was no evidence that SC was less effective in women. Among men and women 75-79 with no comorbidity, number of life-years saved was 459 and 509 per 100,000 SC, respectively; among patients with ≥3 comorbidities, there was no benefit for either men or women.

CONCLUSIONS

Although the effectiveness of SC was equivalent for men and women, there was substantial variation in SC effectiveness within age groups, arguing against screening recommendations based solely on age.

Prediction of emergent heart failure death by semi-quantitative triage risk stratification

OBJECTIVES

Generic triage risk assessments are widely used in the emergency department (ED), but have not been validated for prediction of short-term risk among patients with acute heart failure (HF). Our objective was to evaluate the Canadian Triage Acuity Scale (CTAS) for prediction of early death among HF patients.

METHODS

We included patients presenting with HF to an ED in Ontario from Apr 2003 to Mar 2007. We used the National Ambulatory Care Reporting System and vital statistics databases to examine care and outcomes.

RESULTS

Among 68,380 patients (76±12 years, 49.4% men), early mortality was stratified with death rates of 9.9%, 1.9%, 0.9%, and 0.5% at 1-day, and 17.2%, 5.9%, 3.8%, and 2.5% at 7-days, for CTAS 1, 2, 3, and 4-5, respectively. Compared to lower acuity (CTAS 4-5) patients, adjusted odds ratios (aOR) for 1-day death were 1.32 (95%CI; 0.93-1.88; p = 0.12) for CTAS 3, 2.41 (95%CI; 1.71-3.40; p<0.001) for CTAS 2, and highest for CTAS 1: 9.06 (95%CI; 6.28-13.06; p<0.001). Predictors of triage-critical (CTAS 1) status included oxygen saturation <90% (aOR 5.92, 95%CI; 3.09-11.81; p<0.001), respiratory rate >24 breaths/minute (aOR 1.96, 95%CI; 1.05-3.67; p = 0.034), and arrival by paramedic (aOR 3.52, 95%CI; 1.70-8.02; p = 0.001). While age/sex-adjusted CTAS score provided good discrimination for ED (c-statistic = 0.817) and 1-day (c-statistic = 0.724) death, mortality prediction was improved further after accounting for cardiac and non-cardiac co-morbidities (c-statistics 0.882 and 0.810, respectively; both p<0.001).

CONCLUSIONS

A semi-quantitative triage acuity scale assigned at ED presentation and based largely on respiratory factors predicted emergent death among HF patients.

Multivariate risk scores and patient outcomes in advanced heart failure

Significant improvements in survival have occurred for patients with advanced heart failure, with an increasing array of therapeutic options sharing quite varied properties of cost, invasiveness, and impact on life expectancy. Risk models allow patients and providers to achieve a better understanding of prognosis than is possible through unstructured holistic assessment. This article reviews scoring systems for heart failure prognostication in the general sense and in the setting of providing answers to specific clinical queries. Topics addressed include outpatient survival, risk of inpatient and post-discharge mortality, potential changes to clinician decision-making through better understanding of prognosis, and mortality after having a left ventricular assist device placed or receiving an implantable cardiac-defibrillator.

Inability of providers to predict unplanned readmissions

BACKGROUND

Readmissions cause significant distress to patients and considerable financial costs. Identifying hospitalized patients at high risk for readmission is an important strategy in reducing readmissions. We aimed to evaluate how well physicians, case managers, and nurses can predict whether their older patients will be readmitted and to compare their predictions to a standardized risk tool (Probability of Repeat Admission, or P(ra)).

METHODS

Patients aged ≥ 65 discharged from the general medical service at University of California, San Francisco Medical Center, a 550-bed tertiary care academic medical center, were eligible for enrollment over a 5-week period. At the time of discharge, the inpatient team members caring for each patient estimated the chance of unscheduled readmission within 30 days and predicted the reason for potential readmission. We also calculated the P(ra) for each patient. We identified readmissions through electronic medical record (EMR) review and phone calls with patients/caregivers. Discrimination was determined by creating ROC curves for each provider group and the P(ra).

RESULTS

One hundred sixty-four patients were eligible for enrollment. Of these patients, five died during the 30-day period post-discharge. Of the remaining 159 patients, 52 patients (32.7%) were readmitted. Mean readmission predictions for the physician providers were closest to the actual readmission rate, while case managers, nurses, and the P(ra) all overestimated readmissions. The ability to discriminate between readmissions and non-readmissions was poor for all provider groups and the P(ra) (AUC from 0.50 for case managers to 0.59 for interns, 0.56 for P(ra)). None of the provider groups predicted the reason for readmission with accuracy.

CONCLUSIONS

This study found (1) overall readmission rates were higher than previously reported, possibly because we employed a more thorough follow-up methodology, and (2) neither providers nor a published algorithm were able to accurately predict which patients were at highest risk of readmission. Amid increasing pressure to reduce readmission rates, hospitals do not have accurate predictive tools to guide their efforts.

Six-minute walk distance predicts 30-day readmission in hospitalized heart failure patients

BACKGROUND AND AIMS

Identification of patients with heart failure (HF) at high risk of hospital readmission is critical to refine processes for reducing readmission rates. We hypothesized that patients with higher 6-min walk (6MW) distance at the time of hospital discharge are at low risk for early readmission.

METHODS

We prospectively enrolled 265 patients admitted with HF and left ventricular systolic dysfunction. 6MW testing was administered prior to discharge. Multivariate logistic regression analysis was performed to determine the relationship between 6MW distance and 30-day readmission, stratifying by ≤400 m and >400 m.

RESULTS

Two hundred ten patients underwent 6MW testing prior to discharge. Patients with 6MW >400 m had a 30-day readmission rate of 15.9%, whereas patients with 6MW ≤400 m had a 30-day readmission rate of 30.3% (p = 0.016). Patients requiring readmission within 30 days had a median 6MW of 30 m, whereas patients not requiring readmission at 30 days walked 338 m (p = 0.012). 6MW distance predicted freedom from readmission at 30 days (OR: 0.435, 95% CI 0.21-0.9, p = 0.025). Other independent predictors of 30-day readmission included history of gout (0.117, 0.021-0.637, p = 0.013), use of angiotensin-converting enzyme inhibitor or accepted alternative (0.372, 0.169-0.820, p = 0.014) and blood urea nitrogen level (1.019, 1.003-1.035, p = 0.020).

CONCLUSIONS

Low 6MW distance predicts early hospital readmission in patients with HF. Programs seeking to produce systems that are effective in reducing early hospital readmission may desire to incorporate 6MW testing during HF hospital care.

An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure

BACKGROUND

Readmission soon after hospital discharge is an expensive and often preventable event for patients with heart failure. We present a model approved by the National Quality Forum for the purpose of public reporting of hospital-level readmission rates by the Centers for Medicare & Medicaid Services.

METHODS AND RESULTS

We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with heart failure. The model was derived with the use of Medicare claims data for a 2004 cohort and validated with the use of claims and medical record data. The unadjusted readmission rate was 23.6%. The final model included 37 variables, had discrimination ranging from 15% observed 30-day readmission rate in the lowest predictive decile to 37% in the upper decile, and had a c statistic of 0.60. The 25th and 75th percentiles of the risk-standardized readmission rates across 4669 hospitals were 23.1% and 24.0%, with 5th and 95th percentiles of 22.2% and 25.1%, respectively. The odds of all-cause readmission for a hospital 1 standard deviation above average was 1.30 times that of a hospital 1 standard deviation below average. State-level adjusted readmission rates developed with the use of the claims model are similar to rates produced for the same cohort with the use of a medical record model (correlation, 0.97; median difference, 0.06 percentage points).

CONCLUSIONS

This claims-based model of hospital risk-standardized readmission rates for heart failure patients produces estimates that may serve as surrogates for those derived from a medical record model.

Hospitalization as an opportunity to integrate palliative care in heart failure management

PURPOSE OF REVIEW

Hospitalization for heart failure is a critical event associated with high rates of readmissions, morbidity, and mortality. This review examines the role of hospitalization for heart failure as an opportunity to assess comprehensive patient needs including palliative care needs.

RECENT FINDINGS

Recent evidence demonstrates that institution of a comprehensive care plan at discharge reduces the high rates of readmissions and death seen in patients with heart failure. The chronic progressive nature of heart failure, with its concomitant limitations in functioning, significant psychosocial distress, and risk of death at all stages of illness creates a need for palliative care services that span the disease trajectory. These services include symptom management, psychosocial care, advance care planning, assistance in defining goals of care, and family/caregiver support and should be provided simultaneously with optimal medical management. Hospice is also underutilized.

SUMMARY

Hospitalization for heart failure should serve as an opportunity to assess, introduce, and provide comprehensive care that includes palliative care alongside optimal medical management. Palliative care services have the potential to positively impact the health and quality of life of patients with heart failure and should be integrated as an ongoing key component of their care.

Are scores useful in advanced heart failure?

Advanced heart failure (HF) is becoming an increasingly challenging problem as more patients with this disease are living longer, yet experiencing its inexorable progression. Adding to this complex matter, there are different views on how to define advanced HF, whereby an acute decompensation episode does not necessarily indicate advanced disease. Several scores have been described aiming at a better prognostic performance across the HF spectrum. These include the Heart Failure Survival Score, the Seattle Heart Failure Model, the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure predictive schemes, the Acute Decompensated Heart Failure National Registry regression tree discrimination, among others. Most scoring systems have been built based on outpatient populations or recently hospitalized HF subjects. The setting of advanced HF has not gained much attention as far as prognostication is concerned, and yet there lies potentially challenging decision-making situations where issues, such as heart transplantation, use of costly devices and end-of-life questions, are raised.

Hospitalizations after heart failure diagnosis a community perspective

OBJECTIVES

The purpose of this study was to determine the lifetime burden and risk factors for hospitalization after heart failure (HF) diagnosis in the community.

BACKGROUND

Hospitalizations in patients with HF represent a major public health problem; however, the cumulative burden of hospitalizations after HF diagnosis is unknown, and no consistent risk factors for hospitalization have been identified.

METHODS

We validated a random sample of all incident HF cases in Olmsted County, Minnesota, from 1987 to 2006 and evaluated all hospitalizations after HF diagnosis through 2007. International Classification of Diseases-9th Revision codes were used to determine the primary reason for hospitalization. To account for repeated events, Andersen-Gill models were used to determine the predictors of hospitalization after HF diagnosis. Patients were censored at death or last follow-up.

RESULTS

Among 1,077 HF patients (mean age 76.8 years, 582 [54.0%] female), 4,359 hospitalizations occurred over a mean follow-up of 4.7 years. Hospitalizations were common after HF diagnosis, with 895 (83.1%) patients hospitalized at least once, and 721 (66.9%), 577 (53.6%), and 459 (42.6%) hospitalized > or =2, > or =3, and > or =4 times, respectively. The reason for hospitalization was HF in 713 (16.5%) hospitalizations and other cardiovascular in 936 (21.6%), whereas over one-half (n = 2,679, 61.9%) were noncardiovascular. Male sex, diabetes mellitus, chronic obstructive pulmonary disease, anemia, and creatinine clearance <30 ml/min were independent predictors of hospitalization (p < 0.05 for each).

CONCLUSIONS

Multiple hospitalizations are common after HF diagnosis, though less than one-half are due to cardiovascular causes. Comorbid conditions are strongly associated with hospitalizations, and this information could be used to define effective interventions to prevent hospitalizations in HF patients.

Palliative care in congestive heart failure

Symptoms and compromised quality of life prevail throughout the course of heart failure (HF) and thus should be specifically addressed with palliative measures. Palliative care for HF should be integrated into comprehensive HF care, just as evidence-based HF care should be included in end-of-life care for HF patients. The neurohormonal and catabolic derangements in HF are at the base of HF symptoms. A complex set of abnormalities can be addressed with a variety of interventions, including evidence-based HF care, specific exercise, opioids, treatment of sleep-disordered breathing, and interventions to address patient and family perceptions of control over their illness. Both potential sudden cardiac death and generally shortened length of life by HF should be acknowledged and planned for. Strategies to negotiate communication about prognosis with HF patients and their families can be integrated into care. Additional evidence is needed to direct care at the end of life, including use of HF medications, and to define management of multiple sources of distress for HF patients and their families.

End-of-life care in heart failure

The clinical syndrome of heart failure is increasing in prevalence, as is the number of elderly persons with heart failure. Increasing frailty and progression of heart failure in large numbers of patients means clinicians are increasingly challenged to provide end-of-life care for heart failure patients. End-of-life care has been little studied, but management can be understood from early clinical trials of advanced heart failure. Evidence-based heart failure medications, including angiotensin-converting enzyme inhibitors and beta blockers, improve symptoms in patients with advanced heart failure and depressed ejection fraction and should usually be continued in end-stage disease. Patients also should have ongoing meticulous management of fluid status to maximize quality of life. End-of-life care should be planned with the patient and family and should incorporate comprehensive symptom management, bereavement support, and spiritual support. Ongoing communication with patients and families about prognosis can ease the planning of care when the end of life nears.

The nature of heart failure as a challenge to the integration of palliative care services

PURPOSE OF REVIEW

Despite its increasing prevalence and high mortality risk, heart failure is widely regarded as 'treatable'. Aggressive measures are employed even in its end stages. This review explores the clinical characteristics of heart failure, patterns of clinician response, and new data that may help to surmount current barriers to palliative approaches.

RECENT FINDINGS

The 'treatment imperative' that has helped to reduce overall cardiovascular mortality marginalizes palliative approaches in heart failure. The possibility of dying remains unacknowledged, and communication about palliative options tends not to occur. Both the apparently benign nature of heart failure and its inherent unpredictability discourage end-of-life considerations. Recent studies, however, provide evidence that these barriers may be surmountable, and also furnish tools to help with prognosis. A true heart failure continuum including palliative care would be desirable, although structural barriers exist.

SUMMARY

Therapeutic successes have encouraged clinicians to pursue heart failure treatment through the end stages of disease. These very successes, however, have made the course of advanced heart failure easier to predict. What is needed now is courage among clinicians to open early dialog about disease process, prognosis and palliative options with the growing number of patients with advanced disease.

High mortality without ESCAPE: the registry of heart failure patients receiving pulmonary artery catheters without randomization

BACKGROUND

In the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE), there was no difference in days alive and out of the hospital for patients with decompensated heart failure randomly assigned to therapy guided by pulmonary artery catheter (PAC) plus clinical assessment versus clinical assessment alone. The external validity of these findings is debated.

METHODS AND RESULTS

ESCAPE sites enrolled 439 patients receiving PAC without randomization in a prospective registry. Baseline characteristics, pertinent trial exclusion criteria, reasons for PAC use, hemodynamics, and complications were collected. Survival was determined from the National Death Index and the Alberta Registry. On average, registry patients had lower blood pressure, worse renal function, less neurohormonal antagonist therapy, and higher use of intravenous inotropes compared with trial patients. Although clinical assessment anticipated less volume overload and greater hypoperfusion among the registry population, measured filling pressures were similarly elevated in the registry and trial patients, whereas measured perfusion was slightly higher among registry patients. Registry patients had longer hospitalization (13 vs 6 days, P < .001) and higher 6-month mortality (34% vs 20%, P < .001) than trial patients.

CONCLUSIONS

The decision to use PAC without randomization identified a population with higher disease severity and risk of mortality. This prospective registry highlights the complex context of patient selection for randomized trials.

Discordance between patient-predicted and model-predicted life expectancy among ambulatory patients with heart failure

CONTEXT

Patients with chronic heart failure have impaired long-term survival, but their own expectations regarding prognosis have not been well studied.

OBJECTIVES

To quantify expectations for survival in patients with heart failure, to compare patient expectations to model predictions, and to identify factors associated with discrepancies between patient-predicted and model-predicted prognosis.

DESIGN, SETTING, AND PARTICIPANTS

Prospective face-to-face survey of patients from the single-center Duke Heart Failure Disease Management Program between July and December 2004, with follow-up through February 2008. Patient-predicted life expectancy was obtained using a visual analog scale. Model-predicted life expectancy was calculated using the Seattle Heart Failure Model. Actuarial-predicted life expectancy, based on age and sex alone, was calculated using life tables. Observed survival was determined from review of medical records and search of the Social Security Death Index.

MAIN OUTCOME MEASURE

Life expectancy ratio (LER), defined as the ratio of patient-predicted to model-predicted life expectancy.

RESULTS

The cohort consisted of 122 patients (mean age, 62 years; 47% African American, 42% New York Heart Association [NYHA] class III or IV). On average, patients overestimated their life expectancy relative to model-predicted life expectancy (median patient-predicted life expectancy, 13.0 years; model-predicted expectancy, 10.0 years). Median LER was 1.4 (interquartile range, 0.8-2.5). Younger age, increased NYHA class, lower ejection fraction, and less depression were the most significant predictors of higher LER. During a median follow-up of 3.1 years, 29% of the original cohort died. There was no association between higher LER and improved survival (adjusted hazard ratio for overestimated compared with concordant LER, 1.05; 95% confidence interval, 0.46-2.42).

CONCLUSIONS

Ambulatory patients with heart failure tended to substantially overestimate their life expectancy compared with model-based predictions for survival. Because differences in perceived survival could affect decision making regarding advanced therapies and end-of-life planning, the causes of these discordant predictions warrant further study.

Effects of a Rho kinase inhibitor on pressure overload induced cardiac hypertrophy and associated diastolic dysfunction

The RhoA-Rho kinase (ROCK) signaling pathway has an important role in cardiovascular diseases. However, the effect of Rho kinase inhibition on pressure overload-induced cardiac hypertrophy (POH) and associated diastolic dysfunction has not been evaluated. This study examined the effect of a selective ROCK inhibitor (GSK-576371) in a POH model, induced by suprarenal abdominal aortic constriction. POH rats were divided into the following four groups: 1 (GSK 1, n = 9) or 3 (GSK 3, n = 10) mg/kg bid GSK-576371, 1 mg.kg(-1).day(-1) ramipril (n = 10) or vehicle (n = 11) treatment for 4 wk. Sham animals (n = 11) underwent surgery without banding. Echocardiograms were performed before surgery and posttreatment, and hemodynamic data were obtained at completion of the study. Echocardiography showed an increase in relative wall thickness of the left ventricle (LV) following POH + vehicle treatment compared with sham animals. This was attenuated by both doses of GSK-576371 and ramipril. Vehicle treatment demonstrated abnormal diastolic parameters, including mitral valve (MV) inflow E wave deceleration time, isovolumic relaxation time, and MV annular velocity, which were dose dependently restored toward sham values by GSK-576371. LV end diastolic pressure was increased following POH + vehicle treatment compared with sham (6.9 +/- 0.7 vs. 3.2 +/- 0.7 mmHg, P = 0.008) and was reduced with GSK 3 and ramipril treatment (1.7 +/- 0.7, P < 0.01 and 2.9 +/- 0.6 mmHg, P < 0.01, respectively). Collagen I deposition in the LV was increased following POH + vehicle treatment (32.2%; P < 0.01) compared with sham animals and was significantly attenuated with GSK 1 (21.7%; P < 0.05), GSK 3 (23.8%; P < 0.01), and ramipril (35.5%; P < 0.01) treatment. These results suggest that ROCK inhibition improves LV geometry and reduces collagen deposition accompanied by improved diastolic function in POH.