Factors Influencing the Serological Response in Hepatic Echinococcus granulosus Infection
Bibliographic record
Abstract
Knowledge of variables influencing serology is crucial to evaluate serology results for the diagnosis and clinical management of cystic echinococcosis (CE). We analyzed retrospectively a cohort of patients with hepatic CE followed in our clinic in 2000-2012 to evaluate the influence of several variables on the results of commercial enzyme-linked immunosorbent assay (ELISA) and indirect hemagglutination (IHA) tests. Sera from 171 patients with ≥ 1 hepatic CE cyst, and 90 patients with nonparasitic cysts were analyzed. CE cysts were staged according to the WHO-IWGE classification and grouped by activity. A significant difference in ELISA optical density (OD) values and percentage of positivity was found among CE activity groups and with controls (P < 0.001). The serological response was also influenced by age (P < 0.001) and cyst number (P = 0.003). OD values and cyst size were positively correlated in active cysts (P = 0.001). IHA test showed comparable results. When we analyzed the results of 151 patients followed over time, we found that serology results were significantly influenced by cyst activity, size, number, and treatment ≤ 12 months before serum collection. In conclusion, serological responses as assessed by commercial tests depend on CE cyst activity, size and number, and time from treatment. Clinical studies and clinicians in their practice should take this into account.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".