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Record W2565204976 · doi:10.14740/jocmr2847w

Symptomatic Gallstones in the Young: Changing Trends of the Gallstone Disease-Related Hospitalization in the State of New York: 1996 - 2010

2016· article· en· W2565204976 on OpenAlexvenueno aff
Sridhar Chilimuri, Vinaya Gaduputi, Hassan Tariq, Suresh Kumar Nayudu, Trupti Vakde, Mariela Glandt, Harish Patel

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typearticle
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGallstonesObesityDiabetes mellitusDiseasePediatricsPopulationDemographyEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of the study was to evaluate if the gallstone-related hospitalizations in the young (< 20 years of age) have increased over time in both the Bronx County and New York State as a whole. METHODS: We retrospectively reviewed 15 years (1996 - 2010) of Statewide Planning and Research Cooperative System (SPARCS) data of New York State Department of Health. Patients with ICD-9 code diagnosis of 574 (cholelithiasis) among the first three discharge diagnoses were reviewed. RESULTS: Total number of all cause admissions to hospitals had increased from 2.44 million to 2.77 million (1996 - 2010). However, gallstone-related hospitalizations had decreased from 1.7% to 1.2%. It was noted that there was a 30% increment in the proportion of those below 20 years of age with gallstone disease requiring hospitalization over the same period. This young patient population contributed only 2.04% to all gallstone-related hospitalizations in 1996, whereas it had increased to 2.96% in 2010. This trend was more pronounced in women, Hispanics and in those who were residing in the Bronx County as compared to all other New York counties combined. CONCLUSION: The gallstone-related hospitalizations in the young (< 20 years of age) have increased over time in both the Bronx County and New York State as a whole. This could be due to increasing prevalence of risk factors such as obesity, physical inactivity, diabetes and early pregnancy.

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)0.016
metaresearch head score (Gemma)0.006
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 score0.111
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.123
GPT teacher head0.451
Teacher spread0.328 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

Explore more

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