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Predicting mortality among a community-based sample of older people with heart failure.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

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Predicting mortality among a community-based sample of older people with heart failure. / Barnes, Sarah; Gott, Merryn; Payne, Sheila et al.
In: Chronic Illness, Vol. 4, No. 1, 2008, p. 5-12.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Barnes, S, Gott, M, Payne, S, Parker, C, Seamark, D, Gariballa, S & Small, N 2008, 'Predicting mortality among a community-based sample of older people with heart failure.', Chronic Illness, vol. 4, no. 1, pp. 5-12. https://doi.org/10.1177/1742395307083783

APA

Barnes, S., Gott, M., Payne, S., Parker, C., Seamark, D., Gariballa, S., & Small, N. (2008). Predicting mortality among a community-based sample of older people with heart failure. Chronic Illness, 4(1), 5-12. https://doi.org/10.1177/1742395307083783

Vancouver

Barnes S, Gott M, Payne S, Parker C, Seamark D, Gariballa S et al. Predicting mortality among a community-based sample of older people with heart failure. Chronic Illness. 2008;4(1):5-12. doi: 10.1177/1742395307083783

Author

Barnes, Sarah ; Gott, Merryn ; Payne, Sheila et al. / Predicting mortality among a community-based sample of older people with heart failure. In: Chronic Illness. 2008 ; Vol. 4, No. 1. pp. 5-12.

Bibtex

@article{1b9314cff62948d8a5677693915b01bd,
title = "Predicting mortality among a community-based sample of older people with heart failure.",
abstract = "Objective: To identify factors available to general practitioners (GPs) that are predictive of mortality within a general practice-based population of heart failure patients, and to report the sensitivity and specificity of prognostic information from GPs. Methods: Five hundred and forty-two heart failure patients aged >60 years were recruited from 16 UK GP surgeries. Patients completed quality-of-life and services use questionnaires every 3 months for 24 months or until death. Factors with independent significant association with survival were identified using Cox proportional hazards regression analysis. Results: Women had a 58% lower risk of death. Patients self-reporting New York Heart Association Classification III or IV had an 81% higher risk of death. Patients aged 85+ years had over a five-fold risk of death as compared with those aged <65 years. Patients with a co-morbidity of cancer had a 78% higher risk of death. Of the 14 patients who died in a 12-month period, the GPs identified 11 (sensitivity 79%). They identified 133 of the 217 who did not die (specificity 61%). Discussion: Predictors readily available to GPs, such as patient characteristics, are easy to adapt to use in general practice, where most heart failure patients are diagnosed and treated. Identifying factors likely to influence death is useful in primary care, as this can initiate discussion about end-of-life care.",
keywords = "General practice • Heart failure • Mortality • Older people",
author = "Sarah Barnes and Merryn Gott and Sheila Payne and Chris Parker and David Seamark and Salah Gariballa and Neil Small",
year = "2008",
doi = "10.1177/1742395307083783",
language = "English",
volume = "4",
pages = "5--12",
journal = "Chronic Illness",
issn = "1745-9206",
publisher = "SAGE Publications Ltd",
number = "1",

}

RIS

TY - JOUR

T1 - Predicting mortality among a community-based sample of older people with heart failure.

AU - Barnes, Sarah

AU - Gott, Merryn

AU - Payne, Sheila

AU - Parker, Chris

AU - Seamark, David

AU - Gariballa, Salah

AU - Small, Neil

PY - 2008

Y1 - 2008

N2 - Objective: To identify factors available to general practitioners (GPs) that are predictive of mortality within a general practice-based population of heart failure patients, and to report the sensitivity and specificity of prognostic information from GPs. Methods: Five hundred and forty-two heart failure patients aged >60 years were recruited from 16 UK GP surgeries. Patients completed quality-of-life and services use questionnaires every 3 months for 24 months or until death. Factors with independent significant association with survival were identified using Cox proportional hazards regression analysis. Results: Women had a 58% lower risk of death. Patients self-reporting New York Heart Association Classification III or IV had an 81% higher risk of death. Patients aged 85+ years had over a five-fold risk of death as compared with those aged <65 years. Patients with a co-morbidity of cancer had a 78% higher risk of death. Of the 14 patients who died in a 12-month period, the GPs identified 11 (sensitivity 79%). They identified 133 of the 217 who did not die (specificity 61%). Discussion: Predictors readily available to GPs, such as patient characteristics, are easy to adapt to use in general practice, where most heart failure patients are diagnosed and treated. Identifying factors likely to influence death is useful in primary care, as this can initiate discussion about end-of-life care.

AB - Objective: To identify factors available to general practitioners (GPs) that are predictive of mortality within a general practice-based population of heart failure patients, and to report the sensitivity and specificity of prognostic information from GPs. Methods: Five hundred and forty-two heart failure patients aged >60 years were recruited from 16 UK GP surgeries. Patients completed quality-of-life and services use questionnaires every 3 months for 24 months or until death. Factors with independent significant association with survival were identified using Cox proportional hazards regression analysis. Results: Women had a 58% lower risk of death. Patients self-reporting New York Heart Association Classification III or IV had an 81% higher risk of death. Patients aged 85+ years had over a five-fold risk of death as compared with those aged <65 years. Patients with a co-morbidity of cancer had a 78% higher risk of death. Of the 14 patients who died in a 12-month period, the GPs identified 11 (sensitivity 79%). They identified 133 of the 217 who did not die (specificity 61%). Discussion: Predictors readily available to GPs, such as patient characteristics, are easy to adapt to use in general practice, where most heart failure patients are diagnosed and treated. Identifying factors likely to influence death is useful in primary care, as this can initiate discussion about end-of-life care.

KW - General practice • Heart failure • Mortality • Older people

U2 - 10.1177/1742395307083783

DO - 10.1177/1742395307083783

M3 - Journal article

VL - 4

SP - 5

EP - 12

JO - Chronic Illness

JF - Chronic Illness

SN - 1745-9206

IS - 1

ER -