Diagnostic and Predictive value of Serum Anti C1q Antibody in a sample of Patients with Systemic Lupus Erythematous
Bibliographic record
Abstract
Background: Anti C1q antibody is the most studied between antibodies directed against a component of the complement system. AntiC1q antibodies are present in patients with lupus, who often have high clinical disease activity. The aim is to assess Diagnostic and predictive value of serum anti C1q antibody in patients with SLE, to evaluate the correlation between serum anti C1q antibody with sociodemographic and clinical characteristic of SLE patients.Materials and methods: A total of 35 SLE patients and 35 apparently healthy individuals were selected as control group in the current study. Serum level of anti C1q antibody was detected by ELISA technique. This case control study was conducted at the Rheumatology Consultation Clinic of Baghdad Teaching Hospital, kidney Diseases and Transplant Center/ Medical City from January 2020 to September 2020.Results: There was a significant association between Anti C1q antibody and Systemic Lupus Erythematous Disease Activity Index Score. There was no significant association between Anti C1q antibody among patients or controls. There was no significant association between sociodemographic characteristics and anti C1q antibody. For laboratory investigations, there was no significant association with anti C1q antibody. There was no significant association between organ involvement and anti C1q antibody.Conclusion: As associated with SLE disease activity score suggesting its potential usefulness in assessment of disease activity, but not as accurate diagnostic marker, which is still need further elucidation and interpretation.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".