Identifying community based chronic heart failure patients in the last year of life: a comparison of the Gold Standards Framework Prognostic Indicator Guide and the Seattle Heart Failure Model

Haga, Kristin; Murray, Scott A; Reid, John H.; Ness, Andrea; O'Donnell, Maureen; Yellowlees, Diane; Denvir, Martin A.

doi:10.1136/heartjnl-2011-301021

Cited by 73 publications

(62 citation statements)

References 22 publications

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“…73 In a another example of how such risk modeling can break down in practical application, when the widely used Seattle Heart Failure Model was applied to a cohort of 138 heart failure patients with NYHA class III and IV symptoms, the model identified 6 patients (4.3%) with a predicted life expectancy of ≤1 year; at the 12 month follow-up, 43 patients (31%) had died. 74 Thus, applying population estimates to individual patients can be highly problematic, and guidelines citing specific survival cutoffs are difficult to operationalize. Furthermore, almost no models include estimates for nonsurvival end points such as healthrelated quality of life.…”

Section: Unknown Cardiac Prognosismentioning

confidence: 99%

Wearable Cardioverter-Defibrillator Therapy for the Prevention of Sudden Cardiac Death

Piccini¹,

Allen²,

Kudenchuk³

et al. 2016

Circulation

117

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Section: Unknown Cardiac Prognosismentioning

confidence: 99%

Wearable Cardioverter-Defibrillator Therapy for the Prevention of Sudden Cardiac Death

Piccini¹,

Allen²,

Kudenchuk³

et al. 2016

Circulation

117

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“…The SHFM has been validated in 14 independent cohorts including 16 057 patients with HF (4 cohorts including 8983 patients with HF were selected from randomized controlled trials [ Table II in the online-only Data Supplement]). 11,18,[22][23][24][25][26][27][28] The validation cohorts involve diverse populations with a mean age from 52 to 77 years, a higher proportion of males (61%-82%), and mean LVEF between 17% and 45%. In 4 cohorts, the used of β-blockers was 20% to 35%, and in the remaining cohorts was >60% (maximum of 92%).…”

Section: Seattle Heart Failure Modelmentioning

confidence: 99%

Risk Prediction Models for Mortality in Ambulatory Patients With Heart Failure

Alba

Agoritsas

Jankowski

et al. 2013

Circ: Heart Failure

162

106

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Background— Optimal management of heart failure requires accurate assessment of prognosis. Many prognostic models are available. Our objective was to identify studies that evaluate the use of risk prediction models for mortality in ambulatory patients with heart failure and describe their performance and clinical applicability. Methods and Results— We searched for studies in Medline, Embase, and CINAHL in May 2012. Two reviewers selected citations including patients with heart failure and reporting on model performance in derivation or validation cohorts. We abstracted data related to population, outcomes, study quality, model discrimination, and calibration. Of the 9952 studies reviewed, we included 34 studies testing 20 models. Only 5 models were validated in independent cohorts: the Heart Failure Survival Score, the Seattle Heart Failure Model, the PACE (incorporating peripheral vascular disease, age, creatinine, and ejection fraction) risk score, a model by Frankenstein et al, and the SHOCKED predictors. The Heart Failure Survival Score was validated in 8 cohorts (2240 patients), showing poor-to-modest discrimination ( c -statistic, 0.56–0.79), being lower in more recent cohorts. The Seattle Heart Failure Model was validated in 14 cohorts (16 057 patients), describing poor-to-acceptable discrimination (0.63–0.81), remaining relatively stable over time. Both models reported adequate calibration, although overestimating survival in specific populations. The other 3 models were validated in a cohort each, reporting poor-to-modest discrimination (0.66–0.74). Among the remaining 15 models, 6 were validated by bootstrapping ( c -statistic, 0.74–0.85); the rest were not validated. Conclusions— Externally validated heart failure models showed inconsistent performance. The Heart Failure Survival Score and Seattle Heart Failure Model demonstrated modest discrimination and questionable calibration. A new model derived from contemporary patient cohorts may be required for improved prognostic performance.

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“…Although the model performed well in a US-based cohort of 4077 non-clinical trial patients, 24 a small European study found very poor correlation between the SHFM and observed mortalities of 138 community-based patients with HF. 25 Notably, more than 75% of the cohort had stage 3 or worse chronic kidney disease, and the SHFM does not account for kidney disease.…”

Section: Ambulatory Settingmentioning

confidence: 99%

End-of-life Heart Failure Care in the United States

Buggey

Mentz

Galanos

2015

Heart Failure Clinics

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Identifying community based chronic heart failure patients in the last year of life: a comparison of the Gold Standards Framework Prognostic Indicator Guide and the Seattle Heart Failure Model

Abstract: Neither the GSF nor the SHF accurately predicted which patients were in the last year of life. The poor prognostic ability of these models highlights one of the barriers to providing timely palliative care in CHF.

Cited by 73 publications

References 22 publications

Wearable Cardioverter-Defibrillator Therapy for the Prevention of Sudden Cardiac Death

Wearable Cardioverter-Defibrillator Therapy for the Prevention of Sudden Cardiac Death

Risk Prediction Models for Mortality in Ambulatory Patients With Heart Failure

End-of-life Heart Failure Care in the United States

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