Effect of C-reactive protein and serum amyloid A point-of-care testing on antibiotic prescribing for acute respiratory-tract infections at village clinics in China: A study protocol for a cluster randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance is a globally recognised public health threat. In rural China, antibiotic use is common for acute respiratory infections (ARIs), which include symptoms such as coughing and fever that are most likely viral infections but with a small proportion as bacterial infections. This study aims to evaluate the effectiveness of a comprehensive intervention based on C-reactive protein and serum amyloid A point-of-care testing (CRP&SAA POCT) in reducing the inappropriate use of antibiotics for ARIs in Chinese village clinics. METHODS: This is a pragmatic, parallel-group, controlled, cluster-randomised, superiority trial featuring blinded outcome evaluation and data analysis, along with unblinded treatment. This study will be conducted over a period of six months across 40 village clinics in Hubei, China. CRP&SAA POCT will be implemented in 20 village clinics within the intervention arm. This will include additional training for village doctors on the operations of CRP&SAA POCT, which encompasses centralised training, the distribution of training manuals, and desk reminders. Patient education materials will be provided to assist patients in understanding how CRP&SAA POCT can aid in their diagnosis and treatment. The control arm will not receive any intervention except the usual care. The primary outcome is the proportion of patients of all age groups who are diagnosed with ARIs and prescribed antibiotics during their initial visit in both study arms. All analyses will be conducted using the intention-to-treat approach. DISCUSSION: Our study is one of the first trials utilizing CRP&SAA POCT to address the inappropriate prescription of antibiotics for ARIs in village clinics in China. We will also evaluate the implementation process to inform future scale-up in similar resource constrained settings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier - NCT06568432.
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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 | 0.036 | 0.024 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.005 |
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".