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Record W2605610706 · doi:10.14740/gr723w

Changing Trends in Age, Gender, Racial Distribution and Inpatient Burden of Achalasia

2017· article· en· W2605610706 on OpenAlexvenueno aff
Vaibhav Wadhwa, Prashanthi N. Thota, Malav P. Parikh, Rocío López, Madhusudhan R. Sanaka

Bibliographic record

VenueGastroenterology Research · 2017
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAchalasiaMedicineDysphagiaMyotomyDemographicsPediatricsInternal medicineDemographySurgeryEsophagus

Abstract

fetched live from OpenAlex

BACKGROUND: Achalasia is an idiopathic esophageal motility disorder characterized by dysphagia, regurgitation, chest discomfort and weight loss. The aim of this study was to evaluate the temporal trends in demographic variables, interventions, and inpatient burden in achalasia-related hospitalizations. METHODS: We evaluated the National Inpatient Sample Database (NIS) for all patients in whom achalasia (ICD-9 code: 530.0) was the principal discharge diagnosis from 1997 to 2013. Data regarding the patient demographics, number of hospitalizations, length of stay, associated hospital costs and temporal trends over the study period were obtained. RESULTS: In 1997, there were 2,493 admissions with a principal discharge diagnosis of achalasia as compared to 5,195 in 2013 with an average increase of 4% per year (P < 0.001). In 1997, the proportion of patients under 65 years of age was 53.8% versus 60.1% in 2013. Increasing prevalence in African Americans was noted (11.1% to 17.1%). Inflation-adjusted hospital charges related to achalasia showed a mean increase of $2,521 per year (P < 0.001). There was an increase in Heller myotomy procedures over the study period (P < 0.001). CONCLUSIONS: The number of hospitalizations for achalasia and associated costs has significantly increased significantly over the last 16 years in the United States with disproportionate increase in patients under 65 years of age and racial minorities. Further research on cost-effective evaluation and management of achalasia is required.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.093
GPT teacher head0.415
Teacher spread0.322 · 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

Citations50
Published2017
Admission routes1
Has abstractyes

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