Liver diseases in the general population – the importance of active screening
Bibliographic record
Abstract
F -literature search, G -Funds CollectionBackground.Chronic liver diseases are the 5 th most common cause of death in Slovakia overall, and in the case of productive age, they are in 3 rd place after cardiovascular and oncological diseases.The most common liver diseases in Slovakia include: alcoholic liver disease with its various stages (alcoholic hepatitis to liver cirrhosis), viral liver diseases and non-alcoholic fatty liver disease.Objectives.To determine the incidence of liver diseases in a sample of general population from the Bardejov district and, based on the findings, to draw recommendations for general practitioners regarding the need for liver disease screening in their clinics. Material and methods.During the "Week of Healthy liver" event, we examined a total of 179 people (126 women and 73 men).The average age of the examined patients was 52.6 years (± 13.3 years).The participants had an opportunity to have their blood pressure, pulse, waist circumference and hip circumference measured.they could also be measured on a tanita scale, have capillary blood samples for antibodies against hepatitis B, C and venous blood for a biochemical spectrum (15 indicators) taken, undergo a transient elastography examination and percentage measurement of fat in the liver. Results.The average BMi of the participants was 27.8 (± standard deviation 6.35).66% of the participants were overweight and obese.via transient elastography, we found the presence of fibrosis in 20.5% of the participants; up to 59% of the patients had fatty liver (S1-S3). in the group of patients without detected liver fibrosis (135/170), we detected steatosis of grade 1-3 (S1-S3) in 73/135 patients (54%) of the group.We analysed the connections between the occurrence of fibrosis and steatosis of the liver and other examined laboratory parameters (including laboratory ones).We processed the results statistically.Conclusions.NaFlD provides a large field of action for interventions by general practitioners. in overweight and obese patients, NaFlD screening should be performed with a focus on measuring blood pressure, weighing the patient, measuring the waist and hips circumference, determining the level of cholesterol, liver function tests, blood glucose levels and the patients should be sent for an ultrasonographic examination of the abdominal cavity.These examinations can also be carried out during the patient's preventive examination, which is reimbursed by health insurance companies once every 2 years.The position of general practitioners in the screening and management of liver diseases is irreplaceable.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".