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Page 1: Influence of Predictive Modeling in Implementing Optimal Heart Failure Therapy in Inpatient Setting

Table (309).

Explanatory factorfor readmission

% of Patientsidentifyingfactor as acause of

readmission(n5105)

% of ReadmittingProvidersidentifyingfactor as acause of

readmission(n5100)

% of DischargingProvidersidentifyingfactor asa cause ofreadmission(n597)

Patient vs.ReadmittingProvider(McNemarp-value,

Kappa statistic,Kappa p-value)

Patient vs.Discharging

Provider (McNemarp-value, Kappastatistic, Kappa

p-value)

DischaringProvider vs.ReadmittingProvider(McNemar

p-value, Kappastatistic,

Kappa p-value)

Distressing symptoms 78.6 48.5 49.0 !0.01, 0.13, 0.12 !0.01, 0.16, 0.09 1.00, 0.18, 0.12Unavoidable progression

of illness44.3 27.8 29.0 0.04, 0.06, 0.58 !0.01, 0.06, 0.55 0.31, 0.32, !0.01

Psychosocial and accessto care factors

51.0 30.9 40.0 0.01, 0.11, 0.30 0.31, 0.36, !0.01 0.41, 0.40, !0.01

Self-care adherence 46.7 29.9 42.0 !0.01, 0.12, 0.22 0.36, 0.20, 0.07 0.04, 0.59, !0.01Health systems failure 43.3 22.7 25.0 !0.01, 0.14, 0.12 0.03, 0.10, 0.34 1.00, 0.21, 0.06Side effect of care 21.7 25.8 20.0 0.54, -0.02, 0.98 0.66, 0.11, 0.36 0.21, 0.45, !0.01Cardiovascular

co-morbidity20.2 9.3 5.0 0.04, 0.03, 0.72 0.01, -0.05, 0.52 0.63, 0.31, !0.01

Non-cardiovascularco-morbidity

37.9 36.1 25.0 0.23, 0.28, 0.02 0.03, 0.27, 0.02 1.00, 0.52, !0.01

S120 Journal of Cardiac Failure Vol. 20 No. 8S August 2014

those of their care teams. Effective transitional care processes may need to morefully incorporate patients’ beliefs about their illness and root causes forrehospitalization.

310Influence of Predictive Modeling in Implementing Optimal Heart FailureTherapy in Inpatient SettingHari Prasad1, Gujan Chowdhary2, Fahad Ali2, Dwight Stapleton1; 1Guthrie Clinic/Robert Packer Hospital, Sayre, PA; 2Guthrie Clinic/Robert Packer Hospital, Sayre,PA

Background: A gap remains between evidence-based guidelines in the treatment ofheart failure and current pharmacologic and device therapy. The Seattle Heart FailureModel is an accurate predictive tool that allows the clinician to quantitatively assessthe influence of pharmacologic and device therapy on heart failure that has been vali-dated in outpatient setting. We attempt to use the Seattle Heart Failure Model in opti-mizing the heart failure therapy. Methods: We examined 405 patients’ charts whowere admitted with a diagnosis of acute systolic heart failure or acute on chronic sys-tolic heart failure with a left ventricular ejection fraction # 40%. Twenty-one dataelements were entered into the Seattle Heart Failure Model to create a survival esti-mate before and after implementation of interventions known to be beneficial, bothpharmacologic (addition of ACE/ARB, statin, b-blocker, aldosterone blocker) anddevice-based (consideration for AICD, BiV pacer, BiV ICD). Results: The meanage of the population examined was 77 6 9 years. The cohort was comprised of72 % males, mean weight 89 6 22.5kg, with NYHA class 2.4 6 0.6 symptoms.Ischemic etiology was identified in 86% with a mean left ventricular EF of 29.8 69 %. Laboratory data included mean Hgb 10.1 6 1.5g/dL with 15 6 8% lympho-cytes, mean total cholesterol of 176 6 42mg/dL and mean sodium of 133 63.5mmol/L. The one year all-cause mortality rates were 19.5 % reflecting advancedheart failure population. In the 405 patients examined, we were able to alter therapy(medical or device) in 86%. This included advancement of medical therapy in 56%,consideration for device referral in 11%, or both (medical therapy and devicereferral) in 19 %. This augmentation of therapy resulted in an increase in estimatedmean life expectancy from 6.6 years to 9.6 years (p ! 0.001). Conclusion: Use ofthe Seattle Heart Failure Model significantly helps in intensification of heart failuretherapy when applied at time of discharge or in first follow up visit post discharge.

311Giant Cell Myocarditis; Not Necessarily the Harbinger of DeathMuhammad Chaudhry, Luanda Grazette, Michael Fong; University of SouthernCalifornia, Los Angeles, CA

Introduction: Giant cell myocarditis is a rare disease with likely fatal outcome inmajority of cases. Here we present an interesting case of giant cell myocarditis ina 22 year old lady with favorable clinical outcome and discuss the etiology, pathogen-esis and management and prognosis of this challenging disease entity. Case Report:22 year old woman was was initially admitted at an outside hospital about a monthago with worsening shortness of breath on exertion (NYHA III), two pilloworthopnea and mild lower extremity swelling. In addition, she had frequent , brief,self- resolving episodes of palpitations not associated with presyncope or syncopeand dull left upper chest pain lasting 2- 20 min about two to three times daily. Trans-thoracic echocardiogram showed LVEF of 35% and coronary angiogram didnot show any evidence of coronary artery disease. She was diuresed and discharged

to be readmitted again in 4 days with worsening fatigue and shortness of breath. Atthis point, she was transferred to our hospital for higher level of care. On physicalexam she was afebrile, tachycardic with heart rate of 120-130/min, blood pressure95/64 mm of Hg, respiratory rate of 20/min and oxygen saturation 97% on roomair. JVP was 6cm with no sustained hepatojugular reflex. There were no crackleson chest auscultation mild RV lift and a short 2/6 systolic murmur at right upperster-nal border. There was no lower extremity edema. EKG shows ST elevation in inferiorleads, poor R wave progression and Q waves in anterolateral leads. There was mildtroponin elevation of 0.28. Cardiac MRI showed left ventricular ejection fraction of26% and moderate left ventricular enlargement with aneurysmal formation of the midto apical anterior and inferolateral walls. There was extensive late gadoliniumenhancement of the anterior, lateral, and inferolateral walls with correspondingmyocardial edema, compatible with myocarditis. Due to unexplained rapidly wors-ening heart failure, urgent right catheterization with right ventricular biopy wasdone which showed reasonable filling .pressures and low cardiac output and index( Mean RA -14, Mean PA -19, Mean PCWP 14, Thermodilution CO 3.33 and Cardiacindex 1.73). RV biopsy showed giant cells with scattered eosinophils.Immunochem-istry for C4D was negative. She was initiated on low dose milrinone and pulse steroidtherapy was initiated alongwith antithymocyte globulin for five days. Steroid oraltransition was done and Tacrolimus and Mycophenolate Mofetil were added to theregimen. Repeat biopsy at one month revealed complete resolution and her clinicalstatus showed dramatic improvement with continued therapy. Conclusion: Giantcell myocarditis has a 60-90% fatality rate within first year of diagnosis. Though clin-ical outcomes have generally been poor, prompt diagnosis and quick initiation oftherapy is the only possible way towards a better outcome as in this case. We empha-sise on aggressive treatment with multiple high dose immunosuppression as a reason-able approach to management which can be unexpectedly life saving.

312Predisposition to Thrombus Formation in Patients with Left Ventricular AssistDevices: The Minnesota Experience (Don’t Cha Know?)Vincent Pureza1, Hirad Yarmohammadi2, Fateh Bazerbachi1, Chadi Alraies2, SirtazAdatya2; 1University of Minnesota, Minneapolis, MN; 2University of Minnesota,Minneapolis, MN

Introduction: The continuous-flow left ventricular assist device (LVAD) hasbecome a mainstay of therapy for many patients with advanced heart failure.LVAD therapy has been shown to improve quality of life and prolong survival.However, a major concern is the morbidity and mortality brought upon by devicethrombosis. There exists a great need to better understand the presentation andprogression of device thrombosis in patients undergoing LVAD therapy. Ourgoal is to describe clinical features that may predispose patients to device throm-bosis, and to analyze the association between these features and the risk of futurethrombotic events. Hypothesis: We hypothesize that certain clinical features,including markedly elevated lactate dehydrogenase (LDH) levels and subthera-peutic international normalized ratios (INR) predispose LVAD patients to thrombi.Method: We reviewed medical records of 53 LVAD patients who were hospital-ized for suspected LVAD thrombosis. The presence of acute heart failure, changein urine color and LVAD parameters were examined. LDH and INR levels weremonitored over time. Finally, inpatient interventions, changes in outpatient treat-ment, as well as 30-day hospital readmissions were also investigated. Results:This cohort was predominantly male (74%), with an average age of 55 years(range: 15-78 years). The average interval between initial LVAD placement tothrombotic event was 15 months (range: 0.13-64 months). On admission,

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