Lotte Sahin Levison, Peter Jepsen, Henning Andersen
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引用次数: 0
Abstract
Purpose: Health care databases are a valuable source for epidemiological research on amyotrophic lateral sclerosis (ALS) if diagnosis codes are valid. We evaluated the validity of the diagnostic codes for ALS in the Danish National Patient Registry (DNPR).
Patients and methods: We obtained data from the DNPR for all adult (>17 years) patients registered with ALS in Denmark between 1987 and 2022 (median population of 4.2 million during the study period). We randomly selected adult patients living in the North Denmark Region and Central Denmark Region (median population 1.4 million), with a primary discharge diagnosis code of ALS, diagnosed at three departments of neurology. We retrieved and reviewed medical records and estimated the positive predictive value (PPV) of the ALS diagnosis.
Results: Over 36 years, we identified 5679 patients. From the validation cohort of 300 patients, we were able to retrieve 240 (80%) medical records, and 215 ALS diagnoses were confirmed. The overall positive predictive value was 89.6% (95% confidence interval (CI): 85.1-92.8). The highest PPV was achieved for diagnoses registered for patients aged ≥70 years (93.8; 95% CI: 86.2-97.3) compared to patients <60 years (83.4; 95% CI: 73.3-90.7).
Conclusion: We found a high PPV of primary diagnostic codes for ALS from Danish departments of neurology, demonstrating high validity. Thus, the DNPR is a well-suited data source for large-scale epidemiological research on ALS.
期刊介绍:
Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment.
Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews.
Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews.
When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes.
The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.