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Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan

OBJECTIVES: To provide an accurate adjustment for mortality in a benchmark, developing a risk prediction model from its own dataset is mandatory. We aimed to develop and validate a risk model predicting in-hospital mortality in a broad spectrum of Japanese patients after percutaneous coronary interv...

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Autores principales: Inohara, Taku, Kohsaka, Shun, Yamaji, Kyohei, Ishii, Hideki, Amano, Tetsuya, Uemura, Shiro, Kadota, Kazushige, Kumamaru, Hiraku, Miyata, Hiroaki, Nakamura, Masato
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538054/
https://www.ncbi.nlm.nih.gov/pubmed/31122979
http://dx.doi.org/10.1136/bmjopen-2018-026683
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author Inohara, Taku
Kohsaka, Shun
Yamaji, Kyohei
Ishii, Hideki
Amano, Tetsuya
Uemura, Shiro
Kadota, Kazushige
Kumamaru, Hiraku
Miyata, Hiroaki
Nakamura, Masato
author_facet Inohara, Taku
Kohsaka, Shun
Yamaji, Kyohei
Ishii, Hideki
Amano, Tetsuya
Uemura, Shiro
Kadota, Kazushige
Kumamaru, Hiraku
Miyata, Hiroaki
Nakamura, Masato
author_sort Inohara, Taku
collection PubMed
description OBJECTIVES: To provide an accurate adjustment for mortality in a benchmark, developing a risk prediction model from its own dataset is mandatory. We aimed to develop and validate a risk model predicting in-hospital mortality in a broad spectrum of Japanese patients after percutaneous coronary intervention (PCI). DESIGN: A retrospective cohort study was conducted. SETTING: The Japanese-PCI (J-PCI) registry includes a nationally representative retrospective sample of patients who underwent PCI and covers approximately 88% of all PCIs in Japan. PARTICIPANTS: Overall, 669 181 patients who underwent PCI between January 2014 and December 2016 in 1018 institutes. MAIN OUTCOME MEASURES: In-hospital death. RESULTS: The study population (n=669 181; mean (SD) age, 70.1(11.0) years; women, 24.0%) was divided into two groups: 50% of the sample was used for model derivation (n=334 591), while the remaining 50% was used for model validation (n=334 590). Using the derivation cohort, both ‘full’ and ‘preprocedure’ risk models were developed using logistic regression analysis. Using the validation cohort, the developed risk models were internally validated. The in-hospital mortality rate was 0.7%. The preprocedure model included age, sex, clinical presentation, previous PCI, previous coronary artery bypass grafting, hypertension, dyslipidaemia, smoking, renal dysfunction, dialysis, peripheral vascular disease, previous heart failure and cardiogenic shock. Angiographic information, such as the number of diseased vessel and location of the target lesion, was also included in the full model. Both models performed well in the entire validation cohort (C-indexes: 0.929 and 0.926 for full and preprocedure models, respectively) and among prespecified subgroups with good calibration, although both models underestimated the risk of mortality in high-risk patients with the elective procedure. CONCLUSIONS: These simple models from a nationwide J-PCI registry, which is easily applicable in clinical practice and readily available directly at the patients’ presentation, are valid tools for preprocedural risk stratification of patients undergoing PCI in contemporary Japanese practice.
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spelling pubmed-65380542019-06-12 Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan Inohara, Taku Kohsaka, Shun Yamaji, Kyohei Ishii, Hideki Amano, Tetsuya Uemura, Shiro Kadota, Kazushige Kumamaru, Hiraku Miyata, Hiroaki Nakamura, Masato BMJ Open Cardiovascular Medicine OBJECTIVES: To provide an accurate adjustment for mortality in a benchmark, developing a risk prediction model from its own dataset is mandatory. We aimed to develop and validate a risk model predicting in-hospital mortality in a broad spectrum of Japanese patients after percutaneous coronary intervention (PCI). DESIGN: A retrospective cohort study was conducted. SETTING: The Japanese-PCI (J-PCI) registry includes a nationally representative retrospective sample of patients who underwent PCI and covers approximately 88% of all PCIs in Japan. PARTICIPANTS: Overall, 669 181 patients who underwent PCI between January 2014 and December 2016 in 1018 institutes. MAIN OUTCOME MEASURES: In-hospital death. RESULTS: The study population (n=669 181; mean (SD) age, 70.1(11.0) years; women, 24.0%) was divided into two groups: 50% of the sample was used for model derivation (n=334 591), while the remaining 50% was used for model validation (n=334 590). Using the derivation cohort, both ‘full’ and ‘preprocedure’ risk models were developed using logistic regression analysis. Using the validation cohort, the developed risk models were internally validated. The in-hospital mortality rate was 0.7%. The preprocedure model included age, sex, clinical presentation, previous PCI, previous coronary artery bypass grafting, hypertension, dyslipidaemia, smoking, renal dysfunction, dialysis, peripheral vascular disease, previous heart failure and cardiogenic shock. Angiographic information, such as the number of diseased vessel and location of the target lesion, was also included in the full model. Both models performed well in the entire validation cohort (C-indexes: 0.929 and 0.926 for full and preprocedure models, respectively) and among prespecified subgroups with good calibration, although both models underestimated the risk of mortality in high-risk patients with the elective procedure. CONCLUSIONS: These simple models from a nationwide J-PCI registry, which is easily applicable in clinical practice and readily available directly at the patients’ presentation, are valid tools for preprocedural risk stratification of patients undergoing PCI in contemporary Japanese practice. BMJ Publishing Group 2019-05-22 /pmc/articles/PMC6538054/ /pubmed/31122979 http://dx.doi.org/10.1136/bmjopen-2018-026683 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Cardiovascular Medicine
Inohara, Taku
Kohsaka, Shun
Yamaji, Kyohei
Ishii, Hideki
Amano, Tetsuya
Uemura, Shiro
Kadota, Kazushige
Kumamaru, Hiraku
Miyata, Hiroaki
Nakamura, Masato
Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan
title Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan
title_full Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan
title_fullStr Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan
title_full_unstemmed Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan
title_short Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan
title_sort risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in japan
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6538054/
https://www.ncbi.nlm.nih.gov/pubmed/31122979
http://dx.doi.org/10.1136/bmjopen-2018-026683
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