Spectrum of pulmonary fungal pathogens, associated risk factors, and anti-fungal susceptibility pattern among persons with presumptive tuberculosis at Gombe, Nigeria
Bibliographic record
Abstract
Background: Pulmonary mycosis (PM) poses a great diagnostic challenge due to the lack of pathognomonic and radiological features, especially in the absence of mycology laboratory tests. This study was aimed to isolate, phenotypically identify, determine the prevalence of pulmonary fungal pathogens and antifungal susceptibility pattern of isolates of presumptive tuberculosis (PTB) patients attending Federal Teaching Hospital (FTH) Gombe, Nigeria. Methods: nested polymerase chain reaction. Results: Of the 216 participants, 19.9% had PTB and 73.6% had pulmonary fungal pathogens. Among the isolated pulmonary fungal pathogens, Aspergillus fumigatus made the highest occurrence, while 6.5% had PTB-fungal co-infection. No significant association existed between the prevalence of PM with age and sex of participants (P < 0.05). Cigarette smoking (adjusted odds ratio [aOR] = 15.9 [95% confidence interval (CI): 0.9-268.8]), prolong antibiotic use (aOR = 77.9 [95% CI: 4.7-1283]) and possession of domestic pet (aOR = 77.9 [95% CI: 4.7-1283]) were significant risk factors of PM (P < 0.05). Penicillium citrinum, Mucor spp. and Aspergillus flavus are more susceptible to voriconazole, and Candida albicans was found to be more susceptible to Nystatin. Of the 159 fungal isolates, 92.5% were resistant to fluconazole. Conclusion: Findings from this study revealed high level pulmonary fungal pathogens, especially among PTB patients. A majority of fungal isolates were resistant to fluconazole. It's recommended that persons should do away with or minimize risk factors for pulmonary fungal pathogens identified in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".