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Record W4411306241 · doi:10.1111/epi.18503

A multihospital, single health system validation of International Classification of Diseases, 10th Revision, Clinical Modification coding for status epilepticus in the United States

2025· article· en· W4411306241 on OpenAlexaff
Megan MacKenzie, Nathalie Jetté, Brian Johnson, Parul Agarwal, Cristina Schreckinger, Carolina Ferreira‐Atuesta, S. Townes, Brian Mathew, Ariella Cohen, Sharon Nirenberg, Leah J. Blank

Bibliographic record

VenueEpilepsia · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsUniversity of Calgary
FundersNational Center for Advancing Translational SciencesNational Institute on Aging
KeywordsStatus epilepticusCoding (social sciences)MedicinePsychologyEpilepsyPsychiatryStatisticsMathematics

Abstract

fetched live from OpenAlex

Status epilepticus (SE) is a common, life-threatening neurologic emergency. Understanding population-level outcomes after SE requires a validated case definition, yet International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes of SE have not been well-validated in US populations since adoption in 2015. We aimed to determine whether the ICD-10-CM code-based definitions accurately identify SE in the in-hospital setting. The population included all ages (excluding neonates) admitted to a Mount Sinai Health System (MSHS) intensive care unit (ICU) in 2019. A data collection form was developed, tested, and used by trained reviewers. Every admission in a random month (November) was reviewed to determine whether all SE cases had at least one code for epilepsy, seizure, or convulsion followed by all charts with an ICD-10-CM diagnosis code for seizure/epilepsy/convulsion in 2019. Chart review data were linked to MSHS electronic medical record data. Sensitivity (Sn), specificity (Sp), negative predictive value (NPV), and positive predictive value (PPV) with 95% confidence intervals (CIs) and Youden index were calculated for ICD-10 coding of SE (G40.xx1 or G40.xx3, as G41 was not adopted in the United States). MSHS had 13 694 ICU admissions in 2019, for which 1851 charts were reviewed and of which 173 were admissions with definite SE. The ICD-10-CM case definition (G40.xx1) has an Sn of 68.7% (95% CI = 61.5-75.8) and Sp of 92.6% (95% CI = 91.4-93.8). PPV was 47.4% (95% CI = 41-53.8), and NPV was 96.8% (95% CI = 95.9-97.6). Youden index was 61.3%. ICD-10-CM coding for SE has high specificity but limited sensitivity. These findings align with SE prevalence studies showing a decrease in prevalence with the change from ICD-9-CM to ICD-10-CM, which may be related to the United States' unique adoption of ICD-10-CM, which did not include the standalone SE code (G41). Our findings emphasize the importance of revision and improvement of coding practices to best represent the prevalence of SE, and of consideration when planning for the next iteration of ICD coding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.037
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.354
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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