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Record W2551584921 · doi:10.1371/journal.pone.0165161

Incidence of Appendicitis over Time: A Comparative Analysis of an Administrative Healthcare Database and a Pathology-Proven Appendicitis Registry

2016· article· en· W2551584921 on OpenAlexafffund
Stephanie Coward, Hashim Kareemi, Fiona Clement, Scott Zimmer, Elijah Dixon, Chad G. Ball, Steven J. Heitman, Mark G. Swain, Subrata Ghosh, Gilaad G. Kaplan

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsAlberta Health ServicesUniversity of Calgary
FundersGovernment of AlbertaUniversity of Calgary
KeywordsAppendicitisMedicineIncidence (geometry)PopulationCancer registryDiagnosis codeCohortEpidemiologyGeneral surgeryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

IMPORTANCE: At the turn of the 21st century, studies evaluating the change in incidence of appendicitis over time have reported inconsistent findings. OBJECTIVES: We compared the differences in the incidence of appendicitis derived from a pathology registry versus an administrative database in order to validate coding in administrative databases and establish temporal trends in the incidence of appendicitis. DESIGN: We conducted a population-based comparative cohort study to identify all individuals with appendicitis from 2000 to2008. SETTING & PARTICIPANTS: Two population-based data sources were used to identify cases of appendicitis: 1) a pathology registry (n = 8,822); and 2) a hospital discharge abstract database (n = 10,453). INTERVENTION & MAIN OUTCOME: The administrative database was compared to the pathology registry for the following a priori analyses: 1) to calculate the positive predictive value (PPV) of administrative codes; 2) to compare the annual incidence of appendicitis; and 3) to assess differences in temporal trends. Temporal trends were assessed using a generalized linear model that assumed a Poisson distribution and reported as an annual percent change (APC) with 95% confidence intervals (CI). Analyses were stratified by perforated and non-perforated appendicitis. RESULTS: The administrative database (PPV = 83.0%) overestimated the incidence of appendicitis (100.3 per 100,000) when compared to the pathology registry (84.2 per 100,000). Codes for perforated appendicitis were not reliable (PPV = 52.4%) leading to overestimation in the incidence of perforated appendicitis in the administrative database (34.8 per 100,000) as compared to the pathology registry (19.4 per 100,000). The incidence of appendicitis significantly increased over time in both the administrative database (APC = 2.1%; 95% CI: 1.3, 2.8) and pathology registry (APC = 4.1; 95% CI: 3.1, 5.0). CONCLUSION & RELEVANCE: The administrative database overestimated the incidence of appendicitis, particularly among perforated appendicitis. Therefore, studies utilizing administrative data to analyze perforated appendicitis should be interpreted cautiously.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.312
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.342
Teacher spread0.257 · 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 teacher head, 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

Citations67
Published2016
Admission routes2
Has abstractyes

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