ArticleJMIR medical informatics2026
Developing Country-Specific Charlson Comorbidity Index Mappings for Use With German Administrative Data: Methodological Comparative Study.
Article in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Charlson Comorbidity Index (CCI) is widely used to quantify comorbidity burden in observational research. Applying it to real-world data requires accurate International Classification of Diseases-based mappings. The commonly used mapping does not reflect current German coding standards.
objectiveThis study aimed to develop year-specific mappings (2004 to 2026) based on the German modification of the International Classification of Diseases, 10th Revision (ICD-10-GM), for the CCI with an open-source implementation and compare them with the commonly used mapping.
methodsFor each year, mappings were curated via independent dual review with consensus. In 515,827 inpatient cases from a German tertiary center (2010-2024), year-appropriate mappings and the commonly used mapping were applied, and the results were pooled into 2 corresponding datasets that were subsequently compared. Agreement was assessed using the intraclass correlation coefficient (2-way mixed-effects model for absolute agreement based on single measurement), and the significance of the discordances was measured using the McNemar test.
resultsAgreement was very high; 3.1% (16,136/515,827) of cases differed. A single code was present in 48.9% (7896/16,136) of the discordant cases and was intentionally excluded in the new mappings as it was not diagnostic for the category it was assigned to. Discordant results were found in 58.8% (10/17) of the categories ("peripheral vascular disease," "mild liver disease," and "severe liver disease") being present in, respectively, 51.7% (8339/16,136), 17.4% (2813/16,136), and 16.4% (2657/16,136) of the discordant cases. After filtering the dataset to only include observations with any diagnosis of a malignant disease, 6.9% (9377/136,607) of cases differed, and 79.3% (7434/9377) of those differences were caused by the "peripheral vascular disease" category, suggesting significant discrepancies for specific research questions.
conclusionsWe provide transparent, year-specific ICD-10-GM (2004-2026) mappings and an open-source tool for CCI calculation. The mappings align with current German coding practice and enable reproducible, year-appropriate comorbidity adjustment using administrative data.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.