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Choubey U, Bansal V, Shah P, Anamika FNU, Gupta V, Sahu S, Rezhan M, Jain R. Atrial fibrillation and dementia: not just a coincidence. J Geriatr Cardiol 2023; 20:697-701. [PMID: 37840632 PMCID: PMC10568548 DOI: 10.26599/1671-5411.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2023] Open
Affiliation(s)
| | - Vasu Bansal
- Dayanand Medical College and Hospital, Ludhiana, Punjab, India
| | | | - FNU Anamika
- University College of Medical Sciences, New Delhi, India
| | - Vasu Gupta
- Dayanand Medical College and Hospital, Ludhiana, Punjab, India
| | - Sweta Sahu
- J.J.M. Medical College, Davangere, Karnataka, India
| | - Miran Rezhan
- Pennsylvania State University, State College, Pennsylvania, USA
| | - Rohit Jain
- Penn State Milton S Hershey Medical Center, Hershey, Pennsylvania, USA
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Yamin M, Salim S, Setiati S, Pudianto AP, Zulmiyusrini P, Nasution SA, Wijaya IP, Rusdi L, Karim B, Santoso RFH, Silitonga FAH. Validity and reliability studies of the Indonesian version of Atrial Fibrillation Severity Scale (AFSS). BMC Cardiovasc Disord 2023; 23:216. [PMID: 37118699 PMCID: PMC10148504 DOI: 10.1186/s12872-023-03240-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/12/2023] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND In the atrial fibrillation (AF) population, worsened quality of life (QOL) has been reported even before complications occur. Symptom-based questionnaires can be used to evaluate AF treatment. The Atrial Fibrillation Severity Scale (AFSS) was first developed in Canada in English, which is not the main language in Indonesia. This study aims to test the reliability and validity of the Indonesian version of the Atrial Fibrillation Severity Scale (AFSS). METHODS Translation of the AFSS from English to Indonesian was done using forward and backward translation. The final version was then validated with the Short Form-36 (SF-36) questionnaire, and a test-retest reliability study was done in a 7-14-day interval. RESULTS An Indonesian version of AFSS was achieved and deemed acceptable by a panel of researchers. This version is reliable and valid, with Cronbach's α of 0.819, Intraclass Correlation Coefficient (ICC) ranging from 0.803 to 0.975, and total score correlation ranging from 0.333 to 0.895. Pearson's analysis of AFSS and SF-36 revealed that the total AF burden domain was poorly correlated with role limitations due to emotional problems (r:0.427; p < 0.01) and pain (r:0.495; p < 0.01). The symptom severity domain was poorly correlated with physical functioning (r:-0.335; p < 0.01), role limitations due to emotional problems (r:0.499; p < 0.01), pain (r:0.458; p < 0.01), and total SF-36 score (r:-0.361; p < 0.01). Total AFSS score was moderately correlated with role limitations due to emotional problems (r:0.516; p < 0.01) and pain (r:0.538; p < 0.01). The total AFSS score was poorly correlated with the European Heart Rhythm Association (EHRA) score (r:0.315; p < 0.01). CONCLUSION The Indonesian version of AFSS has good internal and external validity with good reliability.
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Affiliation(s)
- Muhammad Yamin
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Simon Salim
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia.
| | - Siti Setiati
- Division of Geriatrics, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Angga Pramudita Pudianto
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Putri Zulmiyusrini
- Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jakarta, Indonesia
| | - Sally Aman Nasution
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Ika Prasetya Wijaya
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Lusiani Rusdi
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Birry Karim
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Raden Fidiaji Hiltono Santoso
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
| | - Friska Anggraini Helena Silitonga
- Division of Cardiology, Department of Internal Medicine, Faculty of Medicine, Universitas Indonesia - Cipto Mangunkusumo Hospital, Jl. Pangeran Diponegoro No.71, Central Jakarta, Jakarta, Indonesia
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Jones JL, Lumsden NG, Simons K, Ta'eed A, de Courten MP, Wijeratne T, Cox N, Neil CJA, Manski-Nankervis JA, Hamblin PS, Janus ED, Nelson CL. Using electronic medical record data to assess chronic kidney disease, type 2 diabetes and cardiovascular disease testing, recognition and management as documented in Australian general practice: a cross-sectional analysis. Fam Med Community Health 2022; 10:fmch-2021-001006. [PMID: 35177470 PMCID: PMC8860071 DOI: 10.1136/fmch-2021-001006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Objectives To evaluate the capacity of general practice (GP) electronic medical record (EMR) data to assess risk factor detection, disease diagnostic testing, diagnosis, monitoring and pharmacotherapy for the interrelated chronic vascular diseases—chronic kidney disease (CKD), type 2 diabetes (T2D) and cardiovascular disease. Design Cross-sectional analysis of data extracted on a single date for each practice between 12 April 2017 and 18 April 2017 incorporating data from any time on or before data extraction, using baseline data from the Chronic Disease early detection and Improved Management in PrimAry Care ProjecT. Deidentified data were extracted from GP EMRs using the Pen Computer Systems Clinical Audit Tool and descriptive statistics used to describe the study population. Setting Eight GPs in Victoria, Australia. Participants Patients were ≥18 years and attended GP ≥3 times within 24 months. 37 946 patients were included. Results Risk factor and disease testing/monitoring/treatment were assessed as per Australian guidelines (or US guidelines if none available), with guidelines simplified due to limitations in data availability where required. Risk factor assessment in those requiring it: 30% of patients had body mass index and 46% blood pressure within guideline recommended timeframes. Diagnostic testing in at-risk population: 17% had diagnostic testing as per recommendations for CKD and 37% for T2D. Possible undiagnosed disease: Pathology tests indicating possible disease with no diagnosis already coded were present in 6.7% for CKD, 1.6% for T2D and 0.33% familial hypercholesterolaemia. Overall prevalence: Coded diagnoses were recorded in 3.8% for CKD, 6.6% for T2D, 4.2% for ischaemic heart disease, 1% for heart failure, 1.7% for ischaemic stroke, 0.46% for peripheral vascular disease, 0.06% for familial hypercholesterolaemia and 2% for atrial fibrillation. Pharmaceutical prescriptions: the proportion of patients prescribed guideline-recommended medications ranged from 44% (beta blockers for patients with ischaemic heart disease) to 78% (antiplatelets or anticoagulants for patients with ischaemic stroke). Conclusions Using GP EMR data, this study identified recorded diagnoses of chronic vascular diseases generally similar to, or higher than, reported national prevalence. It suggested low levels of extractable documented risk factor assessments, diagnostic testing in those at risk and prescription of guideline-recommended pharmacotherapy for some conditions. These baseline data highlight the utility of GP EMR data for potential use in epidemiological studies and by individual practices to guide targeted quality improvement. It also highlighted some of the challenges of using GP EMR data.
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Affiliation(s)
- Julia L Jones
- Nephrology, Western Health, Melbourne, Victoria, Australia .,Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia
| | - Natalie G Lumsden
- Nephrology, Western Health, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,General Practice, University of Melbourne, Melbourne, Victoria, Australia
| | - Koen Simons
- Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
| | - Anis Ta'eed
- Nephrology, Western Health, Melbourne, Victoria, Australia
| | - Maximilian P de Courten
- Mitchell Institute for Education and Health Policy, Melbourne, Victoria, Australia.,Chronic Disease Prevention and Management, Victoria University, Melbourne, Victoria, 3011
| | - Tissa Wijeratne
- Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,La Trobe University, Melbourne, Victoria, Australia.,Neurology, Western Health, Melbourne, Victoria, Australia
| | - Nicholas Cox
- Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,Cardiology, Western Health, Melbourne, Victoria, Australia
| | - Christopher J A Neil
- Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,Cardiology, Western Health, Melbourne, Victoria, Australia
| | | | - Peter Shane Hamblin
- Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,Endocrinology and Diabetes, Western Health, Melbourne, Victoria, Australia
| | - Edward D Janus
- Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia.,Medicine, Western Health, Melbourne, Victoria, Australia
| | - Craig L Nelson
- Nephrology, Western Health, Melbourne, Victoria, Australia.,Medicine, University of Melbourne, Melbourne, Victoria, Australia.,Western Health Chronic Disease Alliance, Melbourne, Victoria, Australia
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