Relationship of Family Caregivers’ Perception of Patients’ Health Status and Time to...
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day cognitive function measured by Spatial Span backward (d5.23) and Everyday Cognition Battery (d5.39) and HF self-care (d50.28) relative to control. Conclu- sion: Despite small sample size, ACT showed potential for improved speed of pro- cessing and memory, thus improved HF outcome; thus warrants full evaluation of ACT for its benefit on cognitive, functional, and HF specific outcomes. 130 Pre-Discharge BNP Predicts 30 and 60 Day Re-admissions in Patients with Decompensated Heart Failure Sangita Sudharshan 1 , Eric Novak 2 , Maximillian Rosario 3 , Mitchell G. Scott 3 , Edward M. Geltman 2 ; 1 Washington University in St. Louis School of Medicine, St. Louis, MO; 2 Washington University in St. Louis School of Medicine, St. Louis, MO; 3 Washington University in St. Louis School of Medicine, St. Louis, MO Introduction: Identifying patients at risk for re-admission after hospitalization for acute decompensated heart failure (ADHF) is critical so that preventative interventions can be implemented. Potentially predictive biomarkers include BNP, troponin I (HsTn- I), and galectin-3 (Gal-3). BNP is a marker of myocardial stretch which is increased in ADHF. Gal-3 is thought to be associated with cardiac macrophage activation of fibro- blasts and ventricular remodeling. Their ability to predict 30 day re-admission is not well defined. Hypothesis: The aim of our study is to identify clinical variables and bio- markers which predict 30 day re-admission. Methods: We enrolled 124 participants admitted to our facility between 4/2013 and 1/2014 with a diagnosis of ADHF. Re- admission data was available for 107 and 91 patients at 30 and 60 days, respectively. We evaluated 30 clinical variables (including age, gender, race, electrolytes, physical examination, ejection fraction, and kidney function). Biomarkers were obtained within 48 hrs prior to hospital discharge. Gal-3 was assessed with two commercially available assays. We compared subjects who were and were not re-admitted (Re-ad). Results: Following index hospitalization, 20% and 36% of patients were re-admitted within 30 and 60 days, respectively. Among the thirty clinical variables, only sodium was significantly different–lower in those re-admitted (137 6 5 vs. 140 6 4). The table shows the median values of the biomarkers. Figure 1 depicts the ROC curves of these biomarkers for prediction of 30 and 60 day re-admission. Discharge BNP was found to be a significant predictor of 30 and 60 day re-admission [AUC 0.69 (p50.046), AUC 0.70 (p50.005) respectively]. Gal-3, BNP change from admission to discharge, and HsTnI were not significant predictors of 30 or 60 day re-admission. Conclusion: Our study demonstrates that BNP assessed at hospital discharge is a significant predic- tor of 30 and 60 day hospital re-admissions. Obtaining this data should help to identify those at-risk and aid in directing resources to reduce hospital re-admissions. 131 Relationship of Family Caregivers’ Perception of Patients’ Health Status and Time to Hospitalization for Decompensating Heart Failure Jill R. Quinn 1 , Maureen Friedman 2 , Rebecca Tucker 1 , Leway Chen 3 , Mary G. Carey 1 ; 1 University of Rochester, Rochester, NY; 2 Nazareth College, Rochester, NY; 3 University of Rochester, Rochester, NY Introduction/Purpose: Little is known about family caregivers’ (FC) perceptions of the health status of chronic heart failure (HF) patients and the relationship of these perceptions with care seeking for decompensating HF. The purpose of this study was to compare the FC’s perceptions of the patient’s health status prior to hospitalization and the time to hospitalization for decompensating HF. Methods: A cross sectional sample of FCs was recruited during patients’ hospitalization for HF to complete the Kansas City Cardiomyopathy Question- naire (KCCQ), which was modified to measure the FCs’ perceptions of the pa- tients’ health status 2 weeks before hospitalization. The KCCQ is a validated questionnaire that quantifies patients’ health status to the degree of physical limitation, symptoms (stability, frequency, and burden), social limitation, self-efficacy, and QOL for patients with HF. The questionnaire with modified wording was used for FCs to respond about their perceptions of the patients’ health status, physical limitations, symptoms, social limitations, self-efficacy and QOL. Instrument reliability was evaluated. Time-to-hospitalization was measured from date of patient reported symptom onset to date of hospitalization. Results: Among the 144 FCs, most were primarily spouses with the majority being white females and a mean age of 58.2 years (SD514.3). Mean time-to- hospitalization was 25 days (SD555.3) with a median time of 6.5 days. Statisti- cally significant correlations with time-to-hospitalization were specifically found with FCs’ perceived physical limitations (r5 -0.17), symptom frequency (r5 -0.20), and social limitations (r5 -0.18) for the patient. Higher correlations with time-to-hospitalization were found with FCs’ perceived symptom burden (r5 -0.23) and quality of life (r5 -0.24). FCs’ overall perceived health summary score for the patient was negatively correlated with time-to-hospitalization and hierarchical regression showed that FC’s overall summary score was a significant predictor (b5 -0.22, p! .05) and uniquely predicted 3% of the variance in time-to-hospitalization. Cronbach’s alpha for the KCCQ was 0.90. Conclusions: FCs’ perception of the patients’ overall health status as poor and quality of life as low predicted longer time to hospitalization after onset of worsening symptoms. However, FCs’ perception of greater patient physical and social limitations as well as higher symptom frequency and burden were uniquely associated with shorter time to hospitalization. Further research is needed to understand the factors that influence the FC perceptions of their significant other’s health status, physical and social limitations, and symptoms and their involvement in the decision to seek care for their significant other’s decompen- sating HF. 132 Severe Pre-Transplant Pulmonary Hypertension Is Not Associated with Detrimental Long-Term Survival after Heart Transplantation: Analyses from the UNOS Registry Kairav Vakil, Alok Sharma, Sue Duval, Selcuk Adabag, Kashan Syed Abidi, Ziad Taimeh, Monica Colvin-Adams; University of Minnesota, Minneapolis, MN Background: Severe pre-transplant pulmonary hypertension (PH) has been associ- ated with adverse short-term outcomes after heart transplantation (HT) in small single-center studies. The impact of pre-transplant PH on survival after HT has not been examined in a large, multi-center cohort. Methods: Adults ($ 18 years) who underwent first time HT in the US between 1987 and 2012 were retrospec- tively identified from the UNOS registry. Pulmonary vascular resistance (PVR) was used to classify PH as mild (2.5-3.4 WU), moderate (3.5-4.9 WU), or severe (O5.0 WU) based on the patients’ most recent pre-transplant hemodynamic assess- ment. Secondary analyses were performed using trans-pulmonary gradient (TPG) and mean pulmonary artery pressure (mPAP) to classify PH severity. Primary outcome was all-cause mortality. Results: Data on 26,649 HT recipients (mean age 52612 years; 76% male; 76% Caucasian) were analyzed. During a mean follow-up of 5.764.8 years, there were 10,334 (39%) deaths. On multivariate Cox regression analysis (adjusted for age, sex, race, BMI, ischemic etiology, life support and ischemic time), pre-transplant PH (PVR $2.5 WU) was a significant predictor (HR 1.11, 95% CI 1.06-1.15) of all-cause mortality. However, adjusted survival at 6-month, 1-, 5-, & 10-years after HT did not differ between patients with mild, moderate, and severe PH (pO0.05) (Figure/Table). Similar results were obtained when TPG or mPAP were used to classify PH. To assess the impact of PH reversibility on our findings, sub-group analyses were performed in patients with left ventricular assist device or total artificial heart prior to HT, that yielded similar results when comparing mild, moderate, and severe PH (log-rank pO0.05). Conclusion: Severe pre-transplant PH as assessed by PVR, TPG, or Table (130). Biomarker values as predictors of hospital re-admission–Kruskal-Wallis test Biomarker (units) Overall-median Not Re-ad 30d-median Re-ad 30d-median P value Gal-3 Abbott (ng/mL) 26.8 26.4 34.5 0.14 Gal-3 BG Medicine (ng/mL) 21.8 21.6 24.6 0.38 Discharge BNP (pg/mL) 417.4 401.5 1079.2 0.039 BNP change-difference between discharge and admit BNP (pg/mL) -126.5 -126.5 -131.4 0.81 HsTn-I (pg/mL) 26.8 27.9 24.6 0.75 Figure 1. Composite ROC curves of biomarkers at 30 days and 60 days The 18 th Annual Scientific Meeting HFSA S53
Transcript of Relationship of Family Caregivers’ Perception of Patients’ Health Status and Time to...
The 18th Annual Scientific Meeting � HFSA S53
day cognitive function measured by Spatial Span backward (d5.23) and EverydayCognition Battery (d5.39) and HF self-care (d50.28) relative to control. Conclu-sion: Despite small sample size, ACT showed potential for improved speed of pro-cessing and memory, thus improved HF outcome; thus warrants full evaluation ofACT for its benefit on cognitive, functional, and HF specific outcomes.
130Pre-Discharge BNP Predicts 30 and 60 Day Re-admissions in Patients withDecompensated Heart FailureSangita Sudharshan1, Eric Novak2, Maximillian Rosario3, Mitchell G. Scott3, EdwardM. Geltman2; 1Washington University in St. Louis School of Medicine, St. Louis,MO; 2Washington University in St. Louis School of Medicine, St. Louis, MO;3Washington University in St. Louis School of Medicine, St. Louis, MO
Introduction: Identifying patients at risk for re-admission after hospitalization foracute decompensated heart failure (ADHF) is critical so that preventative interventionscan be implemented. Potentially predictive biomarkers include BNP, troponin I (HsTn-I), and galectin-3 (Gal-3). BNP is a marker of myocardial stretch which is increased inADHF. Gal-3 is thought to be associated with cardiac macrophage activation of fibro-
Table (130). Biomarker values as predictors of hospital re-admission–Kruskal-Wallis test
Biomarker (units) Overall-median Not Re-ad 30d-median Re-ad 30d-median P value
Gal-3 Abbott (ng/mL) 26.8 26.4 34.5 0.14Gal-3 BG Medicine (ng/mL) 21.8 21.6 24.6 0.38Discharge BNP (pg/mL) 417.4 401.5 1079.2 0.039BNP change-difference between discharge and admit BNP (pg/mL) -126.5 -126.5 -131.4 0.81HsTn-I (pg/mL) 26.8 27.9 24.6 0.75
Figure 1. Composite ROC curves of biomarkers at 30 days and 60 days
blasts and ventricular remodeling. Their ability to predict 30 day re-admission is notwell defined.Hypothesis: The aim of our study is to identify clinical variables and bio-markers which predict 30 day re-admission. Methods: We enrolled 124 participantsadmitted to our facility between 4/2013 and 1/2014 with a diagnosis of ADHF. Re-admission data was available for 107 and 91 patients at 30 and 60 days, respectively.We evaluated 30 clinical variables (including age, gender, race, electrolytes, physicalexamination, ejection fraction, and kidney function). Biomarkers were obtained within48 hrs prior to hospital discharge. Gal-3 was assessed with two commercially availableassays. We compared subjects who were and were not re-admitted (Re-ad). Results:Following index hospitalization, 20% and 36% of patients were re-admitted within30 and 60 days, respectively. Among the thirty clinical variables, only sodium wassignificantly different–lower in those re-admitted (137 6 5 vs. 140 6 4). The tableshows the median values of the biomarkers. Figure 1 depicts the ROC curves of thesebiomarkers for prediction of 30 and 60 day re-admission. Discharge BNP was found tobe a significant predictor of 30 and 60 day re-admission [AUC 0.69 (p50.046), AUC0.70 (p50.005) respectively]. Gal-3, BNP change from admission to discharge, andHsTnI were not significant predictors of 30 or 60 day re-admission. Conclusion:Our study demonstrates that BNP assessed at hospital discharge is a significant predic-tor of 30 and 60 day hospital re-admissions. Obtaining this data should help to identifythose at-risk and aid in directing resources to reduce hospital re-admissions.
131Relationship of Family Caregivers’ Perception of Patients’ Health Status andTime to Hospitalization for Decompensating Heart FailureJill R. Quinn1, Maureen Friedman2, Rebecca Tucker1, Leway Chen3, Mary G.Carey1; 1University of Rochester, Rochester, NY; 2Nazareth College, Rochester,NY; 3University of Rochester, Rochester, NY
Introduction/Purpose: Little is known about family caregivers’ (FC) perceptionsof the health status of chronic heart failure (HF) patients and the relationship of
these perceptions with care seeking for decompensating HF. The purpose ofthis study was to compare the FC’s perceptions of the patient’s health status priorto hospitalization and the time to hospitalization for decompensating HF.Methods: A cross sectional sample of FCs was recruited during patients’hospitalization for HF to complete the Kansas City Cardiomyopathy Question-naire (KCCQ), which was modified to measure the FCs’ perceptions of the pa-tients’ health status 2 weeks before hospitalization. The KCCQ is a validatedquestionnaire that quantifies patients’ health status to the degree of physicallimitation, symptoms (stability, frequency, and burden), social limitation,self-efficacy, and QOL for patients with HF. The questionnaire with modifiedwording was used for FCs to respond about their perceptions of the patients’health status, physical limitations, symptoms, social limitations, self-efficacyand QOL. Instrument reliability was evaluated. Time-to-hospitalization wasmeasured from date of patient reported symptom onset to date of hospitalization.Results: Among the 144 FCs, most were primarily spouses with the majoritybeing white females and a mean age of 58.2 years (SD514.3). Mean time-to-hospitalization was 25 days (SD555.3) with a median time of 6.5 days. Statisti-cally significant correlations with time-to-hospitalization were specifically foundwith FCs’ perceived physical limitations (r5 -0.17), symptom frequency(r5 -0.20), and social limitations (r5 -0.18) for the patient. Higher correlationswith time-to-hospitalization were found with FCs’ perceived symptom burden(r5 -0.23) and quality of life (r5 -0.24). FCs’ overall perceived health summaryscore for the patient was negatively correlated with time-to-hospitalization andhierarchical regression showed that FC’s overall summary score was a significantpredictor (b5 -0.22, p! .05) and uniquely predicted 3% of the variance intime-to-hospitalization. Cronbach’s alpha for the KCCQ was 0.90. Conclusions:FCs’ perception of the patients’ overall health status as poor and quality oflife as low predicted longer time to hospitalization after onset of worseningsymptoms. However, FCs’ perception of greater patient physical and sociallimitations as well as higher symptom frequency and burden were uniquelyassociated with shorter time to hospitalization. Further research is needed tounderstand the factors that influence the FC perceptions of their significantother’s health status, physical and social limitations, and symptoms and theirinvolvement in the decision to seek care for their significant other’s decompen-sating HF.
132Severe Pre-Transplant Pulmonary Hypertension Is Not Associated withDetrimental Long-Term Survival after Heart Transplantation: Analyses fromthe UNOS RegistryKairav Vakil, Alok Sharma, Sue Duval, Selcuk Adabag, Kashan Syed Abidi, ZiadTaimeh, Monica Colvin-Adams; University of Minnesota, Minneapolis, MN
Background: Severe pre-transplant pulmonary hypertension (PH) has been associ-ated with adverse short-term outcomes after heart transplantation (HT) in smallsingle-center studies. The impact of pre-transplant PH on survival after HT hasnot been examined in a large, multi-center cohort. Methods: Adults ($ 18 years)who underwent first time HT in the US between 1987 and 2012 were retrospec-tively identified from the UNOS registry. Pulmonary vascular resistance (PVR)was used to classify PH as mild (2.5-3.4 WU), moderate (3.5-4.9 WU), or severe(O5.0 WU) based on the patients’ most recent pre-transplant hemodynamic assess-ment. Secondary analyses were performed using trans-pulmonary gradient (TPG)and mean pulmonary artery pressure (mPAP) to classify PH severity. Primaryoutcome was all-cause mortality. Results: Data on 26,649 HT recipients (meanage 52612 years; 76% male; 76% Caucasian) were analyzed. During a meanfollow-up of 5.764.8 years, there were 10,334 (39%) deaths. On multivariateCox regression analysis (adjusted for age, sex, race, BMI, ischemic etiology, lifesupport and ischemic time), pre-transplant PH (PVR $2.5 WU) was a significantpredictor (HR 1.11, 95% CI 1.06-1.15) of all-cause mortality. However, adjustedsurvival at 6-month, 1-, 5-, & 10-years after HT did not differ between patientswith mild, moderate, and severe PH (pO0.05) (Figure/Table). Similar resultswere obtained when TPG or mPAP were used to classify PH. To assess the impactof PH reversibility on our findings, sub-group analyses were performed in patientswith left ventricular assist device or total artificial heart prior to HT, that yieldedsimilar results when comparing mild, moderate, and severe PH (log-rankpO0.05). Conclusion: Severe pre-transplant PH as assessed by PVR, TPG, or
