MétaCan
Menu
← Back to cohort
Record W4391886372 · doi:10.1093/jcag/gwad061.121

A121 CROSS-SECTIONAL STUDY OF RESIDENT PHYSICIAN KNOWLEDGE AND PERCEPTIONS REGARDING NON-ALCOHOLIC FATTY LIVER DISEASE IN CANADA

2024· article· en· W4391886372 on OpenAlexaffabout
Keying Zhu, Manisha Jogendran, Yanchun Zhang, Trana Hussaini, Daljeet Chahal, Eric M. Yoshida

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsFatty liverAlcoholic liver diseaseCross-sectional studyMedicinePerceptionDiseaseEnvironmental healthFamily medicinePsychologyGastroenterologyInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Background Non-alcoholic Fatty Liver Disease (NAFLD) is a prevalent condition affecting approximately 25% of the Canadian population and is projected to continue increasing. Given the increasing prevalence and complications of NAFLD, it is imperative for future primary care physicians to possess a thorough understanding of NAFLD to enhance patient care. Aims To assess the knowledge and perceptions of primary care resident physicians in Canada concerning NAFLD. Methods We conducted a nationwide cross-sectional survey of resident physicians in primary care specialties to assess their knowledge of NAFLD. Additionally, we evaluated resident perceptions regarding the importance of NAFLD and their exposure and familiarity with the condition. "Reasonable knowledge" was defined as correctly answering more than 50% of the questions. We assessed associations using χ2 testing and multiple logistic regression analysis. Results We received 413 responses, with 252 (61%) from family medicine residents and 161 (39%) from internal medicine residents. Among the respondents, 90% considered NAFLD an important public health issue, but only 7% felt they had adequate exposure to the condition, and 94% expressed a need for more teaching. 59% indicated that they were only slightly familiar or unfamiliar with NAFLD. The majority of respondents correctly identified diabetes (90%), dyslipidemia (96%), and obesity (97%) as risk factors for NAFLD, while fewer recognized obstructive sleep apnea (53%), hypothyroidism (27%) and hypopituitarism (14%) as risk factors. Cardiovascular disease and cirrhosis were reported as the most common causes of mortality from NAFLD by 37% and 35% of respondents, respectively. Up to 59% of respondents reported that non-alcoholic steatohepatitis can be diagnosed through imaging or a blood test. Respondents demonstrated a strong understanding of nonpharmacologic therapies, but only 11% recognized that there are no approved medications for NAFLD. Overall, 35% of the respondents displayed a reasonable knowledge of NAFLD. In univariate analysis, factors associated with greater NAFLD knowledge included internal medicine residency (P=0.001), higher post-graduate year (P=0.003), prior GI or hepatology rotations (P=0.003), and subjective familiarity with NAFLD (Pampersand:003C0.001). However, only higher post-graduate year (P=0.048) and subjective familiarity (P=0.003) remained statistically significant in multivariate analysis. Conclusions Resident physicians perceive NAFLD as an important health issue but significantly lack exposure and knowledge about the condition. Further emphasis and education are needed to bridge these knowledge gaps and improve patient outcomes. Funding Agencies None Endoscopy, Technology & Imaging

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)0.001
metaresearch head score (Gemma)0.003
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.269
Teacher spread0.258 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of Gastroenterology→Same topicLiver Disease Diagnosis and Treatment→French-language works237,207→