Risk stratification of patients with nonalcoholic fatty liver disease using a case identification pathway in primary care: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Identification of patients with nonalcoholic fatty liver disease (NAFLD) with advanced liver fibrosis in primary care remains an unmet need. Our primary objective was to implement a pathway driven by shear wave elastography (SWE) to facilitate risk stratification of patients with NAFLD within primary care and evaluate whether SWE assessment can reduce referrals of patients with NAFLD at low risk for fibrosis to hepatology. METHODS: A multidisciplinary NAFLD clinical care pathway was codeveloped by hepatologists, radiologists and primary care physicians in Calgary to provide access to SWE-based screening of patients with NAFLD risk factors in primary care. The study outcome measures were estimated NAFLD-related referrals to the hepatology service in Calgary after implementation of the NAFLD pathway and characteristics of patients with NAFLD at risk for advanced fibrosis. The NAFLD pathway was implemented in January 2018 and was made available to all primary care physicians in the Calgary Health Zone. Patients with NAFLD who had liver stiffness (SWE value ≥ 8.0 kPa) or an inconclusive assessment were referred to hepatology. A serum liver fibrosis score was also measured with the fibrosis-4 (FIB-4) index, and performance of an FIB-4 index score of 1.30 or greater to risk stratify patients with NAFLD was evaluated. Demographic, clinical and laboratory characteristics of study groups were compared. RESULTS: Between March and October 2018, 2084 patients with suspected NAFLD were evaluated. Nonalcoholic fatty liver disease was confirmed by ultrasonography in 1958 (94.1%). A majority of the cohort had elevated liver enzyme values (1028 [52.5%]) and obesity (body mass index ≥ 30) (1063/1764 [60.3%]). Most patients with NAFLD (1791 [91.5%]) had an SWE value less than 8.0 kPa and were not referred to hepatology. Sixty-seven patients (3.4%) had an SWE value of 8.0 kPa or more, and 100 (5.1%) had an inconclusive SWE; these patients were referred to hepatology. Using an FIB-4 index score cut-off of 1.30 would have led to hepatology referral of 396/1251 patients (31.6%). INTERPRETATION: Implementation of a primary care-accessible SWE pathway for patients with NAFLD facilitated fibrosis risk stratification and greatly reduced hepatology referrals. Using the FIB-4 index score alone would led to higher rates of referral of patients with NAFLD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".