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      Validity of heart failure diagnoses, treatments, and readmissions in the Danish National Patient Registry

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          Abstract

          Background

          The Danish National Patient Registry (DNPR) is a valuable resource for population-based research, but the validity of routine registration of advanced heart failure (HF) treatments within the registry is unknown. We, therefore, investigated the validity of HF, advanced HF treatments, and HF readmissions in the DNPR.

          Methods

          We randomly sampled patients registered at a Danish University Hospital during 2017–2021 from the DNPR. We identified 200 patients with first-time HF, 390 patients with one of eight advanced HF treatments, and 133 patients with HF admission after implantable cardioverter-defibrillator (ICD) or cardiac resynchronisation therapy (CRT). Compared with medical record reviews, we calculated positive predictive values (PPVs) with 95% confidence intervals (CIs).

          Results

          The PPV for first-time HF was 81% (95% CI: 74–86%). For advanced HF treatments, the PPV was 97% (95% CI: 91–99%) for ICD, 96% (95% CI: 86–100%) for CRT-pacemaker, 88% (95% CI: 76–95%) for CRT-defibrillator, 100% (95% CI: 83–100%) for left ventricular assist device, 43% (95% CI: 18–71%) for intra-aortic balloon pump, 38% (95% CI: 25–35%) for impella, 100% (95% CI: 93–100%) for cardiopulmonary support, and 100% (95% CI: 94–100%) for heart transplantation. The PPV for HF admission after ICD was 25% (95% CI: 16–37%) and 18% (95% CI: 9.2–30%) after CRT.

          Conclusions

          The PPV of routine registrations in the DNPR was moderate for first-time HF, high for most advanced HF treatments, and low for HF admissions after ICD or CRT. Thus, the DNPR is a valuable data source for population-based research on first-time HF and many advanced HF treatments.

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          Most cited references25

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          Interrater reliability: the kappa statistic

          The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.
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            2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure

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              The Danish National Patient Registry: a review of content, data quality, and research potential

              Background The Danish National Patient Registry (DNPR) is one of the world’s oldest nationwide hospital registries and is used extensively for research. Many studies have validated algorithms for identifying health events in the DNPR, but the reports are fragmented and no overview exists. Objectives To review the content, data quality, and research potential of the DNPR. Methods We examined the setting, history, aims, content, and classification systems of the DNPR. We searched PubMed and the Danish Medical Journal to create a bibliography of validation studies. We included also studies that were referenced in retrieved papers or known to us beforehand. Methodological considerations related to DNPR data were reviewed. Results During 1977–2012, the DNPR registered 8,085,603 persons, accounting for 7,268,857 inpatient, 5,953,405 outpatient, and 5,097,300 emergency department contacts. The DNPR provides nationwide longitudinal registration of detailed administrative and clinical data. It has recorded information on all patients discharged from Danish nonpsychiatric hospitals since 1977 and on psychiatric inpatients and emergency department and outpatient specialty clinic contacts since 1995. For each patient contact, one primary and optional secondary diagnoses are recorded according to the International Classification of Diseases. The DNPR provides a data source to identify diseases, examinations, certain in-hospital medical treatments, and surgical procedures. Long-term temporal trends in hospitalization and treatment rates can be studied. The positive predictive values of diseases and treatments vary widely (<15%–100%). The DNPR data are linkable at the patient level with data from other Danish administrative registries, clinical registries, randomized controlled trials, population surveys, and epidemiologic field studies – enabling researchers to reconstruct individual life and health trajectories for an entire population. Conclusion The DNPR is a valuable tool for epidemiological research. However, both its strengths and limitations must be considered when interpreting research results, and continuous validation of its clinical data is essential.
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                Author and article information

                Journal
                Int J Popul Data Sci
                Int J Popul Data Sci
                IJPDS
                International Journal of Population Data Science
                Swansea University
                2399-4908
                21 October 2024
                2024
                : 9
                : 1
                : 2394
                Affiliations
                [1 ] Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
                [2 ] Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
                [3 ] Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark
                [4 ] Department of Cardiology, Gødstrup Regional Hospital, Herning, Denmark
                Author notes
                [*] [* ]Corresponding author: Kasper Bonnesen bonnesen@ 123456clin.au.dk

                Conflict of interests: The authors declare that they have no competing interests.

                Article
                9:1:26
                10.23889/ijpds.v6i1.2394
                11636635
                39669906
                d2fd9b1a-1434-4790-8953-4713a45987a6

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

                History
                Categories
                Population Data Science

                cardiac surgical procedures,epidemiology,heart failure,predictive value of tests,validation study

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