Application of the Seattle Heart Failure Model in Patients on Cardiac Resynchronization Therapy

Perrotta, Laura; Ricciardi, Giuseppe; Pieragnoli, Paolo; Chiostri, Marco; Pontecorboli, Giulia; Santo, Tiziana De; Bellocci, Fulvio; Vitulano, Nicola; Emdin, Michele; Mascioli, Giosuè; Ricceri, Ilaria; Porciani, Maria Cristina; Michelucci, Antonio; Padeletti, Luigi

doi:10.1111/j.1540-8159.2011.03258.x

Cited by 12 publications

(10 citation statements)

References 33 publications

(41 reference statements)

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“…Perrota et al 27 Validation SHFM n/a n/a n/a n/a H-L test: P>0.2 at 1, 2, and 3 y At 1 y=0.70 (0.61-0.79)…”

Section: Seattle Heart Failure Modelmentioning

confidence: 99%

“…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%

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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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“…Perrota et al 27 Validation SHFM n/a n/a n/a n/a H-L test: P>0.2 at 1, 2, and 3 y At 1 y=0.70 (0.61-0.79)…”

Section: Seattle Heart Failure Modelmentioning

confidence: 99%

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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“…A net underestimation of absolute risk calculated with the SHFM was observed among patients with an implanted device. More recently, Perrotta et al . reported that, in a mixed CRT population (CRT‐D, 263 patients; CRT‐P, 79 patients) with moderate to severe HF, the performance of the SHFM was good in predicting short‐, intermediate and long‐term survival, with Harrell c‐statistics ranging between 0.69 (1 year) and 0.70 (2 and 5 years).…”

Section: Discussionmentioning

confidence: 99%

“…The performance of the SHFM in advanced HF patients referred for cardiac transplantation who were racially diverse and receiving optimal contemporary therapy has been recently tested; in this cohort, it was shown that in terms of absolute risk, SHFM systematically overestimated survival and underestimated risk, an effect more pronounced among patients with implanted devices. Little is known about the performance of the SHFM in CRT patients, particularly considering device type and more recent CRT recommendations.…”

Section: Introductionmentioning

confidence: 99%

Validation of Seattle Heart Failure Model for mortality risk prediction in patients treated with cardiac resynchronization therapy

Regoli

Scopigni

Leyva

et al. 2013

European J of Heart Fail

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AimsSurvival prediction by the Seattle Heart Failure Model (SHFM) of patients treated with cardiac resynchronization therapy (CRT) remains ill defined. The performance of the SHFM in this clinical setting was therefore evaluated. Methods and resultsData from 1309 consecutive CRT patients (five centres) were collected retrospectively; 1139 of these patients were considered for analysis. Three-hundred and seven deaths occurred over 40.1 months (interquartile range 25.2-60.0 months; mean event rate 9.7%/year; survival of 89, 81, and 64% at 1, 2, and 5 years). Kaplan-Meier event-free survival analysis stratified according to tertile of SHFM score was significant (log rank test P , 0.001). High-risk tertile (T1) survival was 82, 67, and 46% at 1, 2, and 5 years, respectively. Observed compared with SHFM-predicted survival was 0.11 vs. 0.08, 0.19 vs. 0.16, and 0.36 vs. 0.36, at 1, 2, and 5 years. Model discrimination by c-statistic was 0.64; the logistic models' area under the receiver operating characteristic curve (AUC-ROC) of risk tertiles was 0.66, 0.68, and 0.67, at 1, 2, and 5 years. Compared with the other two groups, T1 was globally more compromised. Within the T1 group, independent predictors of death were male gender, ischaemic heart failure aetiology, lower body weight, and CRT pacemaker. ConclusionsSHFM performance was found to be modest, tending to overestimate survival. However, SHFM identified a high-risk, globally more compromised patient subgroup, hence supporting a comprehensive approach, which should include nutritional, metabolic, and immunological aspects, as well as defibrillator

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“…age and cause of heart failure), disease severity and duration of follow-up. [14][15][16][17][18][19][20] However, as the accuracy of the prediction degrades from the sample in which the system was first developed to subsequent application, 21 it requires to be validated before application in new patients.…”

Section: Introductionmentioning

confidence: 99%

Validity of the Seattle Heart Failure Model for prognosis in a population at low coronary heart disease risk

Laszczyńska

Severo

Friões

et al. 2016

Journal of Cardiovascular Medicine

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Application of the Seattle Heart Failure Model in Patients on Cardiac Resynchronization Therapy

Abstract: The SHFM successfully stratifies HF patients on CRT/CRT-D and can be reliably applied to help clinicians in predicting survival in this clinical setting.

Cited by 12 publications

References 33 publications

Risk Prediction Models for Mortality in Ambulatory Patients With Heart Failure

Risk Prediction Models for Mortality in Ambulatory Patients With Heart Failure

Validation of Seattle Heart Failure Model for mortality risk prediction in patients treated with cardiac resynchronization therapy

Validity of the Seattle Heart Failure Model for prognosis in a population at low coronary heart disease risk

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