Validity of dried blood spot testing for sexually transmitted and blood-borne infections: A narrative systematic review
Bibliographic record
Abstract
Testing for human immunodeficiency virus (HIV) and hepatitis C virus (HCV) using dried blood spot (DBS) specimens has been an integral part of bio-behavioural surveillance in Canada for almost two decades, though less is known regarding the use of DBS in surveillance of other sexually transmitted and blood-borne infections (STBBI). A systematic review was conducted using a peer-reviewed search strategy to assess the current evidence regarding the validity of STBBI testing using DBS specimens. Eligibility criteria included studies reporting use of DBS specimens for STBBI testing with either commercially available or "in-house" tests in populations 15 years of age or older. Studies reporting a measure of validity such as sensitivity, specificity, positive and negative predictive values were eligible for inclusion. Quality of studies and risk of bias were assessed using the QUADAS-2 tool. A total of 7,132 records were identified. Of these, 174 met the criteria for inclusion. Among the studies that reported validity measures, a substantial proportion demonstrated high sensitivity (≥90%) in 62.5% of cases (N = 334/534 sensitivity measurements), and high specificity (≥90%) was observed in 84.9% of instances (N = 383/451 specificity measurements). However, the quality of the studies varied greatly. Our findings support the validity of the use of DBS specimens in STBBI testing where sufficient evidence was available, but validity is highly dependent on thorough method development and validation.
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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 | 0.019 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".