Pentraxin 3 is more accurate than C-reactive protein for Takayasu arteritis activity assessment: A systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Whether the circulating levels of pentraxin 3 (PTX3), an acute phase reactant (APR), are higher in active Takayasu arteritis (TAK), and if so, whether PTX3 is more accurate than C-reactive protein (CRP) in TAK activity assessment has been investigated in this study. STUDY DESIGN: Research works such as PubMed, Embase, ScienceDirect, Cochrane Library, and two Chinese literature databases (CNKI and WanFang) were searched for studies conducted till August 30th, 2019. Two investigators searched the studies independently, who evaluated the quality of the study using the Newcastle-Ottawa scale (NOS) and extracted data. Pooled standard mean difference (SMD) and diagnostic indexes, with a 95% confidence interval (CI), were calculated using a random-effect model. RESULTS: Totally, 8 studies involving 473 TAK (208 active and 265 inactive TAK) patients and 252 healthy controls were eventually included in the meta-analysis. PTX3 level in the blood in active TAK patients were found to be higher than that in dormant TAK with pooled SMD of 0.761 (95% CI = 0.38-1.14, p<0.0001; I2 = 68%, p of Q test = 0.003). And there was no publication bias. Among the 8 studies, 5 studies identified active TAK with both PTX3 and CRP. The pooled sensitivity, specificity, and AUC values of PTX3 in active TAK diagnosis were higher than those of CRP (0.78 [95% CI = 0.65-0.87] vs. 0.66 [95% CI = 0.53-0.77], p = 0.012; 0.85 [95% CI = 0.77-0.90] vs. 0.77 [95% CI = 0.56-0.90], p = 0.033; 0.88 [95% CI = 0.85-0.90] vs. 0.75 [95% CI = 0.71-0.79], p < 0.0001). It showed potential publication bias using Egger's test (p of PTX3 = 0.031 and p of CRP = 0.047). CONCLUSIONS: PTX3 might be better than CRP in the assessment of TAK activity. Yet, it should be cautious before clinical use for moderate heterogeneity and potential publication bias of the meta-analysis.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.052 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".