The role of serum cytokeratin 18 and platelet count as non-invasive markers in the diagnosis of nonalcoholic fatty liver disease in children with type 1 diabetes mellitus
Bibliographic record
Abstract
Introduction Nonalcoholic fatty liver disease (NAFLD) is the commonest chronic hepatopathy in children and adults. Aim of the study To evaluate the role of cytokeratin 18 (CK-18) and platelet count as non-invasive markers in the diagnosis of nonalcoholic fatty liver disease in children with type 1 diabetes mellitus (T1DM). Material and methods The study included 71 T1DM patients with age range 6–18 years old and 48 healthy age- and sex-matched volunteers. The T1DM patients were divided into NAFLD(+) (n = 12) and NAFLD(–) (n = 40) groups. Blood samples were collected for assessment of complete blood count, complete lipid profile, glycosylated haemoglobin, liver enzymes, and serum CK-18. Ultrasonography distinctively quantifies visceral fat and subcutaneous fat, ultrasound evaluation of hepatic steatosis, and liver size. Acoustic radiation force impulse elastography was used to evaluate liver fibrosis. Results The mean serum cholesterol, triglyceride, and LDL-cholesterol were statistically significantly higher in cases with NAFLD compared to cases without NAFLD and controls (p = 0.033, p = 0.001, p = 0.023, respectively). Comparing with the controls, cases exhibited significantly higher values for platelets count (p < 0.005). Regarding the mean level of serum CK-18, it was 168.88 ±96.462 mIU/ml in patients without NAFLD vs. 173.29 ±101.95 mIU/ml in patients with NAFLD and 140.75 ±79.97 mIU/ml in controls. Interestingly, the observed positive correlation between serum CK-18 and platelets counts in diabetic patients was statistically significant (r = 0.230, p = 0.046). Platelets count and visceral fat thickness were statistically significantly predictors of NAFLD. Significantly higher serum CK-18 in cases with NAFLD and liver fibrosis compared with those without liver fibrosis evaluated by acoustic radiation force impulse elastography. Conclusions CK-18 and platelet count may be useful markers for predicting liver fibrosis and help in the follow-up regimen of NAFLD in cases with T1DM.
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 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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".