Co-infection Pulmonary Tuberculosis and Severe COVID-19 in a Pregnant Woman at the University Hospital of Kinshasa: A Case Report
Bibliographic record
Abstract
Background: To date, world widely, only a couple of papers have reported the association between pulmonary tuberculosis, Coronavirus disease 2019 (COVID-19) and pregnancy, and none of these reports was from sub-Saharan Africa where tuberculosis is endemic. Objective: the main objective of this study is to describe the co-infection Pulmonary Tuberculosis and Severe COVID-19 in pregnant young Woman at the University Hospital of Kinshasa. Method: The report case is of a pregnant woman aged 19 (Pare 2, Gesture 2, Abortion 0) with no known significant medical history, at 32 weeks of gestation based last menstrual period She has benefited from clinic examination, biological examinations (Ziehl’s on sputum), a chest CT scan and a morphological ultrasound. Result: On admission, COVID-19 was the only working diagnosis. However, the persistent coughing prompted clinicians to request a Ziehl-Neelsen staining of sputum that revealed the diagnosis of pulmonary TB. The reverse-transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19 infection and HIV serology negative. A contrast-enhanced chest computed tomography (CT) showed airspace disease involving the right upper lobar, right medial basal segment and left upper lobe in the background of diffuse micro-nodular opacities favored to represent military pulmonary tuberculosis. There were associated cystic bronchiectasis in bilateral upper lobe and bilateral small amount of pleural effusion. Aforementioned findings were favored to represent a secondary or reactivation tuberculosis. The obstetrical ultrasound showed a single live intrauterine pregnancy in breech presentation, estimated at 34 weeks 3 days of gestation without usual features including detectable congenital malformation. Conclusion: The outcome of a pregnant woman with simultaneous COVID-19 and pulmonary tuberculosis is improved when the diagnosis is made early and management is promptly initiated. This attitude also improves the fetal prognosis. In the context of the COVID-19, the association of COVID-19 and pulmonary tuberculosis, especially in immunocompromised patients should be considered.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".