The Sensitivity and Specificity of Loop-Mediated Isothermal Amplification (LAMP) Assay for Tuberculosis Diagnosis in Adults with Chronic Cough in Malawi
Bibliographic record
Abstract
Current tuberculosis diagnostics lack sensitivity, and are expensive. Highly accurate, rapid and cheaper diagnostic tests are required for point of care use in low resource settings with high HIV prevalence.To investigate the sensitivity and specificity, and cost of loop-mediated isothermal amplification (LAMP) assay for tuberculosis diagnosis in adults with chronic cough compared to Xpert® MTB/RIF, fluorescence smear microscopy.Between October 2013 and March 2014, consecutive adults at a primary care clinic were screened for cough, offered HIV testing and assessed for tuberculosis using LAMP, Xpert® MTB/RIF and fluorescence smear microscopy. Sensitivity and specificity (with culture as reference standard), and costs were estimated.Of 273 adults recruited, 44.3% (121/273) were HIV-positive and 19.4% (53/273) had bacteriogically confirmed tuberculosis. The sensitivity of LAMP compared to culture was 65.0% (95% CI: 48.3% to 79.4%) with 100% (95% CI: 98.0% to 100%) specificity. The sensitivity of Xpert® MTB/RIF (77.5%, 95% CI: 61.5% to 89.2%) was similar to that of LAMP, p = 0.132. The sensitivity of concentrated fluorescence smear microscopy with routine double reading (87.5%, 95% CI: 73.2% to 95.8%) was higher than that of LAMP, p = 0.020. All three tests had high specificity. The lowest cost per test of LAMP was at batch size of 14 samples (US$ 9.98); this was lower than Xpert® MTB/RIF (US$ 13.38) but higher than fluorescence smear microscopy (US$ 0.65).The sensitivity of LAMP was similar to Xpert® MTB/RIF but lower than fluorescence smear microscopy; all three tests had high specificity. These findings support the Malawi policy that recommends a combination of fluorescence smear microscopy and Xpert® MTB/RIF prioritised for people living with HIV, already found to be smear-negative, or being considered for retreatment of tuberculosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".