Package: syrona 0.2.2

Maarja Pajusalu

syrona: Stratified Prevalence Comparison Across OMOP CDM Datasets

Derives stratified prevalence tables from the condition, procedure, and drug records in OMOP CDM (Observational Medical Outcomes Partnership Common Data Model) databases, computes log2 prevalence ratios between paired datasets, and synthesizes them via random-effects meta-analysis at multiple aggregation levels (year, age group, and sex). Between-study variance is estimated with the Paule-Mandel method, as described in Paule and Mandel (1982) <doi:10.6028/jres.087.022>.

Authors:Maarja Pajusalu [aut, cre]

syrona_0.2.2.tar.gz
syrona_0.2.2.zip(r-4.7-any)syrona_0.2.2.zip(r-4.6-any)syrona_0.2.2.zip(r-4.5-any)
syrona_0.2.2.tgz(r-4.6-any)syrona_0.2.2.tgz(r-4.5-any)
syrona_0.2.2.tar.gz(r-4.7-any)syrona_0.2.2.tar.gz(r-4.6-any)
syrona_0.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
syrona/json (API)

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

Bug tracker:https://github.com/healthinformaticsut/syrona/issues

On CRAN:

Conda:

5.00 score 158 downloads 33 exports 116 dependencies

Last updated from:1e1d32a980. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK156
source / vignettesOK232
linux-releaseOK204
macos-releaseOK165
macos-oldrelOK285
windows-develOK80
windows-releaseOK95
windows-oldrelOK87
wasm-releaseOK158

Exports:apply_cohort_filterbuild_forest_detailbuild_forest_overviewbuild_forest_summarybuild_heatmapbuild_point_diffbuild_pr_distributionbuild_pr_distribution_chaptersbuild_pyramidcohort_summarycompare_allcompare_meta_agegroupscompare_meta_by_sexcompare_meta_summarycompare_yearlycreate_caresite_cohortdelete_cohortextract_allformat_foldformat_pvalinsert_cohortlist_care_siteslist_comparisonslist_datasetsload_comparisonload_datasetload_syrona_themerun_appsyrona_connectsyrona_connect_pgsyrona_disconnecttruncate_nameweight_color

Dependencies:askpassbackportsbase64encbitbit64blobbootbslibcachemCDMConnectorcheckmateclicliprcommonmarkCompQuadFormcpp11crayoncurlDBIdbplyrdigestdplyrevaluatefarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverfsgdtoolsgenericsggiraphggplot2ggtextgluegridtextgtablehighrhmshtmltoolshtmlwidgetshttpuvhttr2isobandjpegjquerylibjsonliteknitrlabelinglaterlatticelifecyclelitedownlme4magrittrmarkdownMASSmathjaxrMatrixmemoisemetametabookmetadatmetaformimeminqanlmenloptrnumDerivomopgenericsopensslotelpbapplypillarpkgconfigpngprettyunitsprogresspromisespurrrR6rappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackreadrreformulasrlangrmarkdownS7sassscalesshinysnakecasesourcetoolsstringistringrsyssystemfontstibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevroomwithrxfunxml2xtableyaml

Introduction
What is Syrona? | How it differs from other OHDSI tools | Installation | Dependencies | Quick start | 1. Connect to a database | 2. Extract a dataset | 3. Compare two datasets | 4. Disconnect | Output structure | Next steps
Rendered froma00_introduction.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-04-07

Extraction
Overview | Connecting to a database | PostgreSQL database | DuckDB (local files) | Running extraction | All domains (default) | Single domain | Shorthand: pass a DuckDB path directly | What each extractor does | Denominators (ACHILLES-116) | Condition prevalence (ACHILLES-404) | Condition chapters | Drug prevalence | Drug chapters | Procedure chapters | k-Anonymity | Loading and listing datasets | Disconnect
Rendered froma01_extraction.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-04-07

OHDSI Cohort Workflows
Overview | Defining a cohort | Care-site cohorts | Create cohorts | Extract by cohort | Verify a cohort | Delete a cohort | Cohorts from data frames | Care-site cohort options | Collapse strategy | Observation period clipping | How cohort filtering works | Compatibility with other OHDSI tools
Rendered froma03_cohorts.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-04-07

End-to-End Walkthrough
Step 0 - Prerequisites | Finding your schemas | Step 1 - Open the SSH tunnel and connect | Verify | For local DuckDB users | Step 2 - Explore care sites | Step 3 - Create two cohorts | Step 4 - Extract the first cohort | Step 5 - Extract the second cohort | Step 6 - Compare | Step 7 - Launch the dashboard | Step 8 - Cleanup and disconnect | Troubleshooting | install_github() fails with "HTTP error 401 / Bad credentials" | "Could not connect" / "Connection refused" | "Permission denied for schema ..." | dbListTables() returns empty | "Cohort 1: 0 rows inserted" | extract_all() is very slow | Dashboard launches but dropdowns are empty | What to read next
Rendered froma04_walkthrough.Rmdusingknitr::rmarkdown

Last update: 2026-09-21
Started: 2026-07-03

Comparison & Meta-Analysis
Overview | Running a comparison | All domains | Single domain | Step-by-step usage | Prevalence ratio formula | Output columns | Meta-analysis strategy | Heterogeneity metrics | Loading and listing comparisons
Rendered froma02_comparison.Rmdusingknitr::rmarkdown

Last update: 2026-07-03
Started: 2026-04-07

Readme and manuals

Help Manual

Help pageTopics
Apply OHDSI cohort filtering to CDM table references.apply_cohort_filter
Build a per-year forest plot for a single conceptbuild_forest_detail
Build an overview forest plot paired with the heatmapbuild_forest_overview
Build a compact F/M/Both forest plot for a single conceptbuild_forest_summary
Build an interactive heatmap of prevalence ratiosbuild_heatmap
Build a dumbbell chart showing absolute prevalence valuesbuild_point_diff
Build a PR distribution histogram from meta_summary databuild_pr_distribution
Build a faceted PR distribution - one small histogram per chapterbuild_pr_distribution_chapters
Build an interactive population pyramidbuild_pyramid
Get summary statistics for a cohort.cohort_summary
Run the full comparison pipeline for two datasets across available domains.compare_all
Meta-analysis across years: one row per concept_id x sex x age_group.compare_meta_agegroups
Meta-analysis across age groups: one row per concept_id x sex.compare_meta_by_sex
Meta-analysis across sexes: one row per concept_id (sex = "Both").compare_meta_summary
Compare two datasets at the per-year stratum level.compare_yearly
Create an OHDSI cohort from a care site.create_caresite_cohort
Delete a cohort from the cohort table.delete_cohort
Run the full source data extraction pipeline.extract_all
Format a log2 prevalence ratio as a fold difference stringformat_fold
Format p-values in Nature styleformat_pval
Insert a cohort from a local data frame.insert_cohort
List care sites with patient counts.list_care_sites
List available comparisons.list_comparisons
List all available datasets.list_datasets
Load a previously saved comparison from CSV.load_comparison
Load a previously saved dataset from CSV.load_dataset
Load all Syrona design tokens into the calling environmentload_syrona_theme
Run the Syrona dashboardrun_app
Connect to a DuckDB OMOP CDM.syrona_connect
Connect to a PostgreSQL OMOP CDM.syrona_connect_pg
Disconnect from an OMOP CDM database.syrona_disconnect
Truncate a concept name to a maximum number of characterstruncate_name
Map population weight (%) to a hex color on a log-scale gradientweight_color