scholarly journals Obesity paradox in Japanese patients after percutaneous coronary intervention: An observation cohort study

2013 ◽  
Vol 62 (1) ◽  
pp. 18-24 ◽  
Author(s):  
Hidehiro Kaneko ◽  
Junji Yajima ◽  
Yuji Oikawa ◽  
Shingo Tanaka ◽  
Daisuke Fukamachi ◽  
...  
Keyword(s):  
Percutaneous Coronary Intervention ◽  
Cohort Study ◽  
Japanese Patients ◽  
Coronary Intervention ◽  
Obesity Paradox ◽  
Percutaneous Coronary

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

BMJ Open ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. e026683 ◽  
Author(s):  
Taku Inohara ◽  
Shun Kohsaka ◽  
Kyohei Yamaji ◽  
Hideki Ishii ◽  
Tetsuya Amano ◽  
...  
Keyword(s):  
Percutaneous Coronary Intervention ◽  
Cohort Study ◽  
Risk Stratification ◽  
Hospital Mortality ◽  
Retrospective Cohort ◽  
Validation Cohort ◽  
Coronary Intervention ◽  
Hospital Death ◽  
Risk Models ◽  
Percutaneous Coronary

ObjectivesTo 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).DesignA retrospective cohort study was conducted.SettingThe 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.ParticipantsOverall, 669 181 patients who underwent PCI between January 2014 and December 2016 in 1018 institutes.Main outcome measuresIn-hospital death.ResultsThe 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.ConclusionsThese 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.

scholarly journals Obesity Paradox—Does It Exist in the Contemporary South Indian Post-Percutaneous Coronary Intervention Population?

2020 ◽  
Vol 5 (01) ◽  
pp. 38-47
Author(s):  
Aramalla Sunitha ◽  
Shabbir Ali Shaik ◽  
Indrani Garre
Keyword(s):  
Percutaneous Coronary Intervention ◽  
Cardiovascular Events ◽  
Coronary Intervention ◽  
Obesity Paradox ◽  
Arterial Disease ◽  
Major Adverse Cardiovascular Events ◽  
Predisposing Factor ◽  
Coronary Arterial Disease ◽  
South Indian ◽  
Percutaneous Coronary

Abstract Background Obesity is a predisposing factor for atherosclerotic coronary arterial disease. Many studies have shown a protective effect of obesity for major adverse cardiovascular events after percutaneous coronary intervention (PCI). Aim The main purpose of this article is to assess the clinical characteristics, invasive angiographic features, and in-hospital cardiovascular events in obese patients compared with normal and underweight patients. We wanted to know the relationship between body mass index (BMI) and outcomes after PCI. Methods We conducted a prospective study among patients undergoing PCI. Between 2017 and 2019, we included 1,669 participants. Multiple logistic regression was performed to determine the effect of BMI on in-hospital adverse events. Results The patients were classified into four groups: obese (BMI ≥30 kg/m2), overweight (BMI 25 to <29.9 kg/m2), normal BMI (BMI 18.51 to <24.9 kg/m2), and underweight (BMI <18.5 kg/m2). Of 1,669 enrolled patients, 1,233 were men, and 436 were women. Among the women, 19 (35.8%) were underweight, 214(25.4%) were normal having normal BMI, 137 (23.5%) were overweight, and 66 (34%) were obese. Among the men, 34 (2.7%) were underweight, 626 (51%) has normal BMI, 445(36%) were overweight, and 128 (10.3%) were obese. Among 840 patients with normal BMI, 797 (95.4%) had no in-hospital events, 39 (4.6%) had in-hospital events. Among 582 patients who were overweight, 30 (5%) had in-hospital events, and 551 (95%) had no in-hospital events. Among 194 patients who were obese, 9 (4.6%) had in-hospital events and 181 (95.4%) had no in-hospital events.There were no in-hospital events in the underweight group. When in-hospital events were compared with different subgroups depending on the weight, it was not statistically significant (for obesity, p = 0.72, and underweight, p = 0.162). When the events in patients with higher than normal BMI (overweight and obese) were compared with events in underweight, it was statistically significant (p = 0.03). It means that a higher BMI was associated with a higher in-hospital event rate. Conclusion A paradox regarding the association of higher BMI with decreased in-hospital events after PCI is not seen in contemporary south Indian post PCI patients.

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