The use of echocardiographic and clinical data recorded on admission to simplify decision making for elective percutaneous coronary intervention: a prospective cohort study

• Published in: BMC medical informatics and decision making 2019-03, Vol.19 (1), p.46-46, Article 46
• Main Authors: Al Abdi, Rabah M, Alshraideh, Hussam, Hijazi, Heba H, Jarrah, Mohamad, Alyahya, Mohammad S
• Format: Article
• Language: English
• Subjects: Adult; Aged; Analysis; Angioplasty; Aorta; Balloon angioplasty; Cardiovascular disease; Clinical Decision-Making; Cohort analysis; Complications; Coronary artery; Coronary artery disease; Coronary Artery Disease - diagnosis; Coronary Artery Disease - therapy; Correlation analysis; Data acquisition; Decision making; Diabetes mellitus; Diabetics; Domains; Echocardiography - statistics & numerical data; Elective percutaneous coronary intervention; Emotions; Female; Females; Health; Health aspects; Health risk assessment; Heart diseases; Hospital admission and discharge; Humans; Hypertension; Information management; Male; Males; Mathematical models; Medical personnel; Medical research; Men; Middle Aged; Mortality; Outcome and process assessment (Medical care); Outcome Assessment, Health Care - statistics & numerical data; Patient Admission - statistics & numerical data; Patients; Percutaneous coronary intervention; Percutaneous Coronary Intervention - statistics & numerical data; Percutaneous endoscopic gastrostomy; Physicians; Prospective Studies; Quality of Life; Regression analysis; Risk factors
• ISSN: 1472-6947; 1472-6947
• DOI: 10.1186/s12911-019-0797-9

Coronary artery disease (CAD), a leading cause of mortality, affects patient health-related quality of life (HRQoL). Elective percutaneous coronary interventions (ePCIs) are usually performed to improve HRQoL of CAD patients. The aim of this study was to design models using admission data to predict the outcomes of the ePCI treatments on the patients' HRQoL. This prospective cohort study was conducted with CAD patients who underwent ePCIs at the King Abdullah University Hospital in Jordan from January 2014 through May 2015. Six months after their ePCI procedures, the participants completed the improved MacNew (QLMI-2) questionnaire, which was used for evaluating three domains (physical, emotional and social) of HRQoL. Multivariate linear regression was used to design models to predict the three domains of HRQoL from echocardiographic findings and clinical data that are routinely measured on admission. The study included 239 patients who underwent ePCIs and responded to the QLMI-2 questionnaire. The mean age (± standard deviation) of the participants was 55.74 ± 11.84 years, 54.58 ± 11.37 years for males (n = 174) and 59.11 ± 12.49 years for females (n = 65). The average scores for physical, emotional and social HRQoL were 4.38 ± 1.27, 4.4 ± 1.11, and 4.37 ± 1.32, respectively. Out of the 42 factors inputted to the models to predict HRQoL scores, 10, 9, and 9 factors were found to be significant determinants for physical, emotional and social domains, respectively, with adjusted coefficients of determination of 0.630, 0.604 and 0.534, respectively. Basophil levels on admission showed a significant positive correlation with the three domains of HRQoL, while aortic root diameter showed a negative correlation. Scores for the three domains were significantly lower in women than in men. Hypertensive and diabetic patients had significantly lower HRQoL scores than patients without hypertension and diabetes. The prediction of HRQoL scores 6 months after an ePCI is possible based on data acquired on admission. The models developed here can be used as decision-making tools to guide physicians in identifying the efficacy of ePCIs for individual patients, hence decreasing the rate of inappropriate ePCIs and reducing costs and complications.