RETRACTED: Non-tuberculous mycobacterial infections among patients with suspected or confirmed pulmonary tuberculosis in Ethiopia: A systematic review and meta-analysis
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Objectives: This study reviews and analyzes non-tuberculous mycobacteria (NTM) isolation from Ethiopian sputum samples, estimating prevalence, identifying common species, and analyzing regional and temporal variations. Methods: This systematic review and meta-analysis aimed to determine NTM prevalence among diseased individuals in Ethiopia. Using PubMed, Scopus, Web of Science, Google Scholar, and African Journals Online, we conducted a comprehensive literature search. Data extraction and quality assessment were conducted using the Newcastle-Ottawa scale. Meta-analysis was performed using STATA-18 software with a random-effects model and included subgroup analysis. The protocol of this study was registered with PROSPERO (CRD420251000131). Results: In this review, a total of 5415 participants were involved, and 53.8% were patients with suspected tuberculosis (TB), 37.6% were patients with pulmonary TB, 4.0% were patients with multidrug-resistant TB, and 4.6% were HIV-positive patients. The NTM prevalence was 3.8%, showing high heterogeneity and regional species variability. The meta-analysis highlighted differences in NTM prevalence across age groups and diagnostic tools, emphasizing the need for enhanced diagnostics and continuous surveillance to improve patient outcomes and inform public health strategies. Conclusions: The review summarizes the epidemiology and geographical distribution of NTM infections and common NTM species isolated from patients with suspected pulmonary TB in Ethiopia, revealing regional variations and clinical implications. Despite limited data, Ethiopia has a lower prevalence of NTM compared with other African regions and the worldwide average.
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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 | 0.031 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.015 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".