Systematic Review and Meta-Analysis of a Urine-Based Pneumococcal Antigen Test for Diagnosis of Community-Acquired Pneumonia Caused by Streptococcus pneumoniae
Bibliographic record
Abstract
Standard culture methods for diagnosis of Streptococcus pneumoniae pneumonia take at least 24 h. The BinaxNOW urine-based test for S. pneumoniae (BinaxNOW-SP) takes only 15 min to conduct, potentially enabling earlier diagnosis and targeted treatment. This study was conducted to assess whether the use of BinaxNOW-SP at the time of hospital admission would provide adequate sensitivity and specificity for diagnosis of community-acquired pneumonia (CAP) in adult patients. We searched PubMed, EMBASE/OVID, Cochrane Collaboration, Centre for Reviews and Dissemination, INAHTA, and CADTH for diagnostic or etiologic studies of hospitalized predominately adult patients with clinically defined CAP that reported the diagnostic performance of BinaxNOW-SP versus cultures. Two authors independently extracted study details and diagnostic two-by-two tables. We found that 27 studies met our inclusion criteria, and three different reference standards were used between them. A bivariate meta-analysis of 12 studies using a composite of culture tests as the reference standard estimated the sensitivity of BinaxNOW-SP as 68.5% (95% credibility interval [CrI], 62.6% to 74.2%) and specificity as 84.2% (95% CrI, 77.5% to 89.3%). A meta-analysis of all 27 studies, adjusting for the imperfect and variable nature of the reference standard, gave a higher sensitivity of 74.0% (CrI, 66.6% to 82·3%) and specificity of 97.2% (CrI, 92.7% to 99.8%). The analysis showed substantial heterogeneity across studies, which did not decrease with adjustment for covariates. We concluded that the higher pooled sensitivity (compared to culture) and high specificity of BinaxNOW-SP suggest it would be a useful addition to the diagnostic workup for community-acquired pneumonia. More research is needed regarding the impact of BinaxNOW-SP on clinical practice.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".