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Record W4406020717 · doi:10.14740/gr1765

Think With Your Gut: A Retrospective Analysis on the Effects of Chronic Gastrointestinal Illness and Psychiatric Comorbidities

2024· article· en· W4406020717 on OpenAlexvenueno aff
Rakahn Haddadin, Danny Aboujamra, Zachary I. Merhavy, George Trad, John Ryan

Bibliographic record

VenueGastroenterology Research · 2024
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsnot available
FundersHCA Healthcare
KeywordsMedicinePsychiatryRetrospective cohort studyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Background: As mental health awareness increases, healthcare professionals must understand the interplay between chronic gastrointestinal (GI) conditions and psychological well-being, particularly regarding healthcare utilization. This study uniquely aggregates various chronic GI disorders, such as inflammatory bowel disease, celiac disease, and eosinophilic esophagitis, to examine their impact on depression and anxiety. Methods: Utilizing a retrospective observational design, we analyzed data from 34,876 patients admitted to HCA national hospitals from January 2016 to December 2022. Results: We found that patients with GI conditions and comorbid psychiatric disorders had significantly higher readmission rates and longer hospital stays compared to those without mental health diagnoses. Results indicated that patients with GI disorders and depression or anxiety were 1.29 times more likely to be readmitted within 90 days and had 1.50 times longer hospital stay. Conclusion: These findings underscore the importance of integrated care approaches addressing physical and mental health in managing chronic GI conditions. Future research should focus on targeted interventions to enhance mental health management and improve outcomes in this vulnerable patient population.

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)0.001
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 score0.015
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.327
Teacher spread0.306 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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