Prediction of cardiac and noncardiac mortality after percutaneous coronary intervention

Daniel B. Spoon, Ryan J. Lennon, Peter J. Psaltis, Abhiram Prasad, David Holmes, Amir Lerman, Charanjit Rihal, Bernard J. Gersh, Henry H. Ting, Mandeep Singh, Rajiv Gulati

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Background-Current risk models for predicting long-term mortality after percutaneous coronary intervention are restricted to all-cause mortality. We sought to develop novel risk models for the prediction of cardiac and noncardiac mortality after percutaneous coronary intervention. Methods and Results-We retrospectively evaluated patients who underwent index percutaneous coronary intervention at Mayo Clinic from 2003 to 2008. Long-term deaths were ascertained through scheduled prospective surveillance. Cause of death was determined via telephone interviews, medical records, and autopsy reports. Fine and Gray extension of Cox proportional hazards models was used to model cause-specific cumulative incidence. Candidate variables and interactions were chosen a priori, without variable selection methods. Resulting models were mapped to an integer-based risk score. The study comprised 6636 patients followed up over a median of 62 months (25th, 75th percentiles: 45, 77 months). There were 1488 deaths, 518 (35%) cardiac, 938 (63%) noncardiac, and 32 (2%) unknown. The 5-year predicted cardiac mortality ranged from 0.6% to 97%, with a corrected c-statistic of 0.82. Risk factors for cardiac death included age, body mass index, ejection fraction, and history of congestive heart failure. The integer score for noncardiac death included age, medicine index, body mass index, current smoker, noncardiac Charlson index and cardiac Charlson index, and accommodated significant age-based interactions for smoking and the 2 Charlson indices. Predicted noncardiac mortality at 5 years ranged from 0.2% to 81%, with a corrected c-statistic of 0.77. Conclusions-We report novel risk models to predict cardiac and noncardiac long-term mortality after percutaneous coronary intervention.

Original languageEnglish (US)
Article numbere002121
JournalCirculation: Cardiovascular Interventions
Volume8
Issue number9
DOIs
StatePublished - Sep 1 2015

Fingerprint

Percutaneous Coronary Intervention
Mortality
Body Mass Index
Proportional Hazards Models
Medical Records
Cause of Death
Autopsy
Heart Failure
Smoking
Medicine
Interviews
Incidence

Keywords

  • Cause of Death
  • Mortality
  • Percutaneous coronary intervention
  • Proportional hazards models
  • Risk factors

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Prediction of cardiac and noncardiac mortality after percutaneous coronary intervention. / Spoon, Daniel B.; Lennon, Ryan J.; Psaltis, Peter J.; Prasad, Abhiram; Holmes, David; Lerman, Amir; Rihal, Charanjit; Gersh, Bernard J.; Ting, Henry H.; Singh, Mandeep; Gulati, Rajiv.

In: Circulation: Cardiovascular Interventions, Vol. 8, No. 9, e002121, 01.09.2015.

Research output: Contribution to journalArticle

Spoon, Daniel B. ; Lennon, Ryan J. ; Psaltis, Peter J. ; Prasad, Abhiram ; Holmes, David ; Lerman, Amir ; Rihal, Charanjit ; Gersh, Bernard J. ; Ting, Henry H. ; Singh, Mandeep ; Gulati, Rajiv. / Prediction of cardiac and noncardiac mortality after percutaneous coronary intervention. In: Circulation: Cardiovascular Interventions. 2015 ; Vol. 8, No. 9.
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abstract = "Background-Current risk models for predicting long-term mortality after percutaneous coronary intervention are restricted to all-cause mortality. We sought to develop novel risk models for the prediction of cardiac and noncardiac mortality after percutaneous coronary intervention. Methods and Results-We retrospectively evaluated patients who underwent index percutaneous coronary intervention at Mayo Clinic from 2003 to 2008. Long-term deaths were ascertained through scheduled prospective surveillance. Cause of death was determined via telephone interviews, medical records, and autopsy reports. Fine and Gray extension of Cox proportional hazards models was used to model cause-specific cumulative incidence. Candidate variables and interactions were chosen a priori, without variable selection methods. Resulting models were mapped to an integer-based risk score. The study comprised 6636 patients followed up over a median of 62 months (25th, 75th percentiles: 45, 77 months). There were 1488 deaths, 518 (35{\%}) cardiac, 938 (63{\%}) noncardiac, and 32 (2{\%}) unknown. The 5-year predicted cardiac mortality ranged from 0.6{\%} to 97{\%}, with a corrected c-statistic of 0.82. Risk factors for cardiac death included age, body mass index, ejection fraction, and history of congestive heart failure. The integer score for noncardiac death included age, medicine index, body mass index, current smoker, noncardiac Charlson index and cardiac Charlson index, and accommodated significant age-based interactions for smoking and the 2 Charlson indices. Predicted noncardiac mortality at 5 years ranged from 0.2{\%} to 81{\%}, with a corrected c-statistic of 0.77. Conclusions-We report novel risk models to predict cardiac and noncardiac long-term mortality after percutaneous coronary intervention.",
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AU - Psaltis, Peter J.

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AU - Holmes, David

AU - Lerman, Amir

AU - Rihal, Charanjit

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AU - Gulati, Rajiv

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N2 - Background-Current risk models for predicting long-term mortality after percutaneous coronary intervention are restricted to all-cause mortality. We sought to develop novel risk models for the prediction of cardiac and noncardiac mortality after percutaneous coronary intervention. Methods and Results-We retrospectively evaluated patients who underwent index percutaneous coronary intervention at Mayo Clinic from 2003 to 2008. Long-term deaths were ascertained through scheduled prospective surveillance. Cause of death was determined via telephone interviews, medical records, and autopsy reports. Fine and Gray extension of Cox proportional hazards models was used to model cause-specific cumulative incidence. Candidate variables and interactions were chosen a priori, without variable selection methods. Resulting models were mapped to an integer-based risk score. The study comprised 6636 patients followed up over a median of 62 months (25th, 75th percentiles: 45, 77 months). There were 1488 deaths, 518 (35%) cardiac, 938 (63%) noncardiac, and 32 (2%) unknown. The 5-year predicted cardiac mortality ranged from 0.6% to 97%, with a corrected c-statistic of 0.82. Risk factors for cardiac death included age, body mass index, ejection fraction, and history of congestive heart failure. The integer score for noncardiac death included age, medicine index, body mass index, current smoker, noncardiac Charlson index and cardiac Charlson index, and accommodated significant age-based interactions for smoking and the 2 Charlson indices. Predicted noncardiac mortality at 5 years ranged from 0.2% to 81%, with a corrected c-statistic of 0.77. Conclusions-We report novel risk models to predict cardiac and noncardiac long-term mortality after percutaneous coronary intervention.

AB - Background-Current risk models for predicting long-term mortality after percutaneous coronary intervention are restricted to all-cause mortality. We sought to develop novel risk models for the prediction of cardiac and noncardiac mortality after percutaneous coronary intervention. Methods and Results-We retrospectively evaluated patients who underwent index percutaneous coronary intervention at Mayo Clinic from 2003 to 2008. Long-term deaths were ascertained through scheduled prospective surveillance. Cause of death was determined via telephone interviews, medical records, and autopsy reports. Fine and Gray extension of Cox proportional hazards models was used to model cause-specific cumulative incidence. Candidate variables and interactions were chosen a priori, without variable selection methods. Resulting models were mapped to an integer-based risk score. The study comprised 6636 patients followed up over a median of 62 months (25th, 75th percentiles: 45, 77 months). There were 1488 deaths, 518 (35%) cardiac, 938 (63%) noncardiac, and 32 (2%) unknown. The 5-year predicted cardiac mortality ranged from 0.6% to 97%, with a corrected c-statistic of 0.82. Risk factors for cardiac death included age, body mass index, ejection fraction, and history of congestive heart failure. The integer score for noncardiac death included age, medicine index, body mass index, current smoker, noncardiac Charlson index and cardiac Charlson index, and accommodated significant age-based interactions for smoking and the 2 Charlson indices. Predicted noncardiac mortality at 5 years ranged from 0.2% to 81%, with a corrected c-statistic of 0.77. Conclusions-We report novel risk models to predict cardiac and noncardiac long-term mortality after percutaneous coronary intervention.

KW - Cause of Death

KW - Mortality

KW - Percutaneous coronary intervention

KW - Proportional hazards models

KW - Risk factors

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