Pharmacotherapy of Systemic Vasculitis Combined with Cryoglobulinemic Syndrome Using Pharmacoeconomic Approaches
Bibliographic record
Abstract
BACKGROUND: It was substantiated the relevance and necessity of the chosen research topic as a result of a review of the scientific literature on the epidemiology and pharmacotherapy of patients with systemic vasculitis associated with cryoglobulinemic syndrome. OBJECTIVE: In this study were selected drugs that have the diagnostic ATC-code J05 Antiviral agents for systemic use; J05A Antivirals of direct action; J05AB01 antiviral agents for systemic use according to INN Aciclovir. METHODS: This study is based on pharmacoeconomic, organizational and legal, forensic and pharmaceutical approaches to pharmacotherapy with using literature review. Experimental data were processed on the basis of the Department of Internal Medicine of the Lviv Medical Institute and the Department of Medical and Pharmaceutical Law, General and Clinical Pharmacy of the Kharkiv Medical Academy of Postgraduate Education. RESULTS: Clinical and pharmacological analysis of basic therapy of systemic vasculitis was performed. Pharmacoeconomic studies have been conducted. According to the results of ABC analysis, drugs according to INN Aciclovir ATC-code J05AB01 for pharmacotherapy of patients with systemic vasculitis combined with cryoglobulinemic syndrome were distributed in descending order of value. According to the results of VEN-analysis, it is estimated that category V drugs accounted for the largest number of prescriptions and the cost of therapy (100%). CONCLUSION: This study provide an opportunity to make administrative and managerial decisions in determining the pharmacotherapy of patients with systemic vasculitis combined with cryoglobulinemic syndrome to improve the use of drugs in hospitals.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".