Drug-Resistant TB, HIV and COVID-19 Co-Infection: Case Reviews from Kwa-Zulu Natal, South Africa
Bibliographic record
Abstract
Razia Hassan-Moosa,1,2 Kegaugetswe Wilhemina Motsomi,1 Radhamoney Narasimmulu,1 Aida Sivro,1,3– 5 Kevindra K Naidu,1 Ayesha BM Kharsany,1,3 Natasha Samsunder,1 Rubeshan Perumal,1,2 Kogieleum Naidoo1,2 1Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa; 2MRC-CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa; 3Department of Medical Microbiology, University of KwaZulu-Natal, Durban, South Africa; 4JC Wilt Infectious Disease Research Centre, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada; 5Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, CanadaCorrespondence: Kegaugetswe Wilhemina Motsomi, Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal Nelson R Mandela School of Medicine, Private Bag X7, Congella, Durban, 4013, South Africa, Email pinky.motsomi@caprisa.orgBackground: Coronavirus disease (COVID-19) potentially exacerbates drug-resistant tuberculosis (DR-TB). We describe the clinical presentation and outcomes of three patients with human immunodeficiency virus (HIV), DR-TB and COVID-19.Case One: A virologically suppressed 31-year-old man on antiretroviral therapy (ART) and multidrug-resistant (MDR)-TB treatment presented with mild COVID-19 and was hospitalised for 10 days of clinical monitoring, despite being clinically stable with normal baseline inflammatory markers. Severe acute respiratory syndrome coronavirus polymerase chain reaction (SARS-CoV-2 PCR) positivity persisted at Day 28.Case Two: A virologically suppressed 37-year-old woman on ART and MDR-TB treatment presented with moderate COVID-19. Baseline inflammatory markers were raised, and dexamethasone and azithromycin were initiated with good clinical improvement. SARS-CoV-2 PCR positivity persisted at Day 28.Case Three: A viraemic 24-year-old woman on second-line ART and MDR-TB treatment, presented with mild COVID-19 disease, normal oxygenation and normal inflammatory markers, and remained clinically stable with negative SARS-CoV-2 PCR at Days 14 and 28.Conclusion: Screening for SARS-CoV-2 infection is advised for DR-TB patients with new or worsening respiratory symptoms.Keywords: HIV, DR-TB, COVID-19, case reviews, screening, transmission
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".