Package: osdc 0.11.3

Luke William Johnston

osdc: Open Source Diabetes Classifier for Danish Registers

The algorithm first identifies a population of individuals from Danish register data with any type of diabetes as individuals with two or more inclusion events. Then, it splits this population into individuals with either type 1 diabetes or type 2 diabetes by identifying individuals with type 1 diabetes and classifying the remainder of the diabetes population as having type 2 diabetes.

Authors:Signe Kirk Brødbæk [aut], Anders Aasted Isaksen [aut], Luke William Johnston [aut, cre], Steno Diabetes Center Aarhus [cph], Aarhus University [cph]

osdc_0.11.3.tar.gz
osdc_0.11.3.zip(r-4.7)osdc_0.11.3.zip(r-4.6)osdc_0.11.3.zip(r-4.5)
osdc_0.11.3.tgz(r-4.6-any)osdc_0.11.3.tgz(r-4.5-any)
osdc_0.11.3.tar.gz(r-4.7-any)osdc_0.11.3.tar.gz(r-4.6-any)
osdc_0.11.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
osdc/json (API)

# Install 'osdc' in R:
install.packages('osdc', repos = c('https://steno-aarhus.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/steno-aarhus/osdc/issues

Pkgdown/docs site:https://steno-aarhus.github.io

On CRAN:

Conda:

diabetes-classificationopen-sourcesoftwarewebsitequarto

7.40 score 4 stars 1 packages 7 scripts 603 downloads 11 exports 51 dependencies

Last updated from:c3310db98a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK167
source / vignettesOK201
linux-release-x86_64OK169
macos-release-arm64OK161
macos-oldrel-arm64OK136
windows-develOK135
windows-releaseOK141
windows-oldrelOK142
wasm-releaseOK150

Exports:algorithmclassify_diabetesedge_casesjoin_registersnon_casesnon_cases_metadataprepare_lpr2prepare_lpr3aprepare_lpr3fregisterssimulate_registers

Dependencies:backportsblobcachemcheckmateclicmprskcodeCollectioncollectionscpp11data.tableDBIdbplyrdplyrduckdbduckplyrEpietmfabricatrfastmapgenericsgluejsonlitelatticelifecyclelubridatemagrittrMASSMatrixmemoisemgcvnlmenumDerivpillarpkgconfigplyrpurrrR6RcppRcppArmadillorlangstringistringrsurvivaltibbletidyrtidyselecttimechangeutf8vctrswithrzoo

Design
Principles | Use cases | Core functionality | Function conventions | Naming | Input | Output | Interface | prepare_lpr*() | classify_diabetes()
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Last update: 2026-06-04
Started: 2025-08-22

Algorithm
General description | High-level flowchart | Classifying type 1 diabetes | Classifying type 2 diabetes | Detailed and technical description | lpr_diag | lpr_adm | diagnoser | kontakter | lab_forsker | lmdb | Across register logic | References
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Last update: 2026-05-22
Started: 2025-08-22

Getting started
What does this package do? | Step-by-step usage | Step 1: Install and load the package | Step 2: Check which registers are needed | Step 3: Prepare the data | Step 4: Run the classification | Step 5 (optional): Collect the results into R | Understanding the output | About stable_inclusion_date vs raw_inclusion_date | Step 6: Saving the results | Working with real register data | Getting help
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Last update: 2026-04-27
Started: 2025-08-22

Changes from original
Specific changes since the original validation (version from the paper) | Version 1.0 | Validity | Validity in 2019 | Stratified by diabetes type and age at onset | Bootstrapped metrics | Validity in 2025 | Potential future changes | References
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Last update: 2026-04-14
Started: 2025-08-22

Data sources
Data required from registers | Expected data structure | Getting access to data
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Last update: 2026-04-14
Started: 2025-08-22

Internal function flow
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Last update: 2026-04-14
Started: 2025-08-22

Rationale
Identifying type 1 and 2 diabetes cases in Danish healthcare registers | Danish register data infrastructure | Current Danish register-based diabetes classifiers | Challenges in current classifiers | Diabetes classification algorithms | References
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Last update: 2026-04-14
Started: 2025-08-22