Evidence map›Paper›PMID 30885191›Full record

ArticleBMC medical informatics and decision making2019

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

Rabah M Al Abdi, Hussam Alshraideh, Heba H Hijazi, Mohamad Jarrah, Mohammad S Alyahya

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Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Rabah M Al AbdiBiomedical Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, Irbid, Jordan. rmalabdi@just.edu.jo.ORCID 0000-0002-5927-7341
Hussam AlshraidehIndustrial Engineering Department, Faculty of Engineering, Jordan University of Science and Technology, Irbid, Jordan.
Heba H HijaziDepartment of Health Management and Policy, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
Mohamad JarrahDivision of Cardiology, Internal Medicine Department, King Abdullah University Hospital, Jordan University of Science and Technology, Irbid, Jordan.
Mohammad S AlyahyaDepartment of Health Management and Policy, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary 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.

methodsThis 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.

resultsThe 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.

conclusionThe 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.

Indexed as

Clinical Decision-MakingQuality of LifeAdultAgedCoronary Artery DiseaseEchocardiographyFemaleHumansMaleMiddle AgedOutcome Assessment, Health CarePatient AdmissionPercutaneous Coronary InterventionProspective StudiesDecision makingElective percutaneous coronary interventionPercutaneous coronary interventionQuality of lifeRisk factors

Identifiers

PMID30885191
PMCPMC6421658

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