Diagnosis of Visceral Leishmaniasis Using Peripheral Blood Microscopy in Ethiopia: A Prospective Phase-III Study of the Diagnostic Performance of Different Concentration Techniques Compared to Tissue Aspiration
Bibliographic record
Abstract
Visceral leishmaniasis (VL) is a fatal parasitic disease. Unfortunately, diagnosis of VL in east Africa currently relies on aspiration of tissue from the spleen or bone marrow, which is painful and potentially dangerous. We sought to determine whether peripheral blood could be used instead of invasive tissue aspirates to diagnose VL, using three parasite concentration techniques. Three hundred and one consecutive people suspected of having VL were recruited. Compared with microscopy of tissue aspirates, the diagnostic accuracy of peripheral blood microscopy was as follows: whole blood thin smear sensitivity 1.5% (95% confidence interval [CI] 0.0-8.3) and specificity 100% (95% CI 76.8-100); buffy-coat smear sensitivity 19.5% (95% CI 14.3-25.6) and specificity 98.9% (95% CI 94.1-100); peripheral blood mononuclear cell (PBMC) smear sensitivity 33.7% (95% CI 27.3-40.5) and specificity 95.7% (95% CI 89.6-98.6). Sensitivity of PBMC smears was significantly higher in human immunodeficiency virus (HIV)-coinfected patients (N = 48/301); two-sample test of proportions, P = 0.0097; sensitivity 55.9% (95% CI 37.9-72.8) and specificity 92.9% (95% CI 66.1-99.8), and correlated with the degree of parasite load in the tissue. Combining the results from smears of both PBMC and buffy coat yielded a sensitivity and specificity of 67.6% (95% CI 49.1-82.6) and 92.9% (95% CI 66.1-99.8), respectively, in HIV-coinfected patients. In this setting, VL could be ruled-in with peripheral blood microscopy in a substantial number of VL suspects and may reduce the number of tissue aspirations performed, particularly in HIV-coinfected patients. More sensitive and logistically feasible methods than light microscopy are needed to detect Leishmania donovani parasites present in blood.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".